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Right For Me: Protocol for a cluster randomised trial of two interventions for facilitating shared decision-making about
contraceptive methods
Journal: BMJ Open
Manuscript ID bmjopen-2017-017830
Article Type: Protocol
Date Submitted by the Author: 18-May-2017
Complete List of Authors: Thompson, Rachel; Dartmouth College, The Dartmouth Institute for Health Policy and Clinical Practice Manski, Ruth; Dartmouth College, The Dartmouth Institute for Health
Policy and Clinical Practice Donnelly, Kyla; Dartmouth College, The Dartmouth Institute for Health Policy and Clinical Practice Stevens, Gabrielle; Dartmouth College, The Dartmouth Institute for Health Policy and Clinical Practice Agusti, Daniela; Dartmouth College, The Dartmouth Institute for Health Policy and Clinical Practice Banach, Michelle; Patient Partner Boardman, Maureen; Dartmouth College, Geisel School of Medicine Brady, Pearl; Patient Partner Colon Bradt, Christina; Patient Partner Foster, Tina; Dartmouth College, The Dartmouth Institute for Health Policy
and Clinical Practice Johnson, Deborah; Dartmouth College, Geisel School of Medicine Li, Zhongze; Dartmouth College Norsigian, Judy; Stakeholder Partner Nothnagle, Melissa; Brown University Warren Alpert Medical School, Department of Family Medicine Olson, Ardis; Dartmouth College, Geisel School of Medicine Shepherd, Heather; The University of Sydney, Psycho-Oncology Cooperative Research Group Stern, Lisa; Planned Parenthood Northern California, Tosteson, Tor; Dartmouth College, The Dartmouth Institute for Health
Policy and Clinical Practice Trevena, Lyndal; University of Sydney, School of Public Health Upadhya, Krishna; Johns Hopkins School of Medicine Elwyn, Glyn; Dartmouth College,
<b>Primary Subject Heading</b>:
Patient-centred medicine
Secondary Subject Heading: Reproductive medicine, Obstetrics and gynaecology, Public health, Health services research
Keywords: GYNAECOLOGY, PRIMARY CARE, PUBLIC HEALTH
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Right For Me: Protocol for a cluster randomised
trial of two interventions for facilitating shared
decision-making about contraceptive methods
Rachel Thompson, Ruth Manski, Kyla Z Donnelly, Gabrielle Stevens, Daniela Agusti, Michelle Banach, Maureen B
Boardman, Pearl Brady, Christina Colón Bradt, Tina Foster, Deborah J Johnson, Zhongze Li, Judy Norsigian, Melissa
Nothnagle, Ardis L Olson, Heather L Shepherd, Lisa F Stern, Tor D Tosteson, Lyndal Trevena, Krishna K Upadhya,
Glyn Elwyn
Correspondence: Rachel Thompson, [email protected], +1 603 653 0860
Funding: Research reported in this protocol was funded through a Patient-Centered Outcomes Research Institute
(PCORI) Award (CDR-1403-12221). Apart from requiring adherence to Methodology Standards that specify best
practices in the design and conduct of patient-centred outcomes research, the funder has had no role in study
design; writing of the protocol; or the decision to submit the report for publication. The views presented in this
protocol are solely the responsibility of the author(s) and do not necessarily represent the views of the Patient-
Centered Outcomes Research Institute (PCORI), its Board of Governors or Methodology Committee. The Patient-
Centered Outcomes Research Institute can be contacted at [email protected].
Acknowledgements: We thank Amina Hetu and Nitzy Bustamante for their contribution to the development of
study materials. We thank Shama Alam and Elizabeth Harman for participating in the production of study
interventions. We also thank those who provided valuable feedback on early drafts of the Right For Me Decision
Aids and other materials, including Amanda Beery, Ann Davis, Rachel Darche, Amanda Dennis, Candace Gibson,
Christina Lachance, Lindsay Smith, Michele Stranger-Hunter, Lawrence Swiader, Christina Warner, Jacki Witt,
Elisabeth Woodhams, and Lauren Zapata.
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ABSTRACT
Introduction: Despite the observed and theoretical advantages of shared decision-making in a range of clinical
contexts, including contraceptive care, there remains a paucity of evidence on how to facilitate its adoption. This
paper describes the protocol for a study to assess the comparative effectiveness of patient- and provider-targeted
interventions for facilitating shared decision-making about contraceptive methods.
Methods and analysis: We will conduct a 2x2 factorial cluster randomised controlled trial with four arms: (1) video
+ prompt card, (2) decision aids + training, (3) video + prompt card and decision aids + training, and (4) usual care.
The clusters will be clinics in the United States that deliver contraceptive care. The participants will be people who
have completed a health care visit at a participating clinic, were assigned female sex at birth, are aged 15 to 49
years, are able to read and write English or Spanish, and have not previously participated in the study. The primary
outcome will be shared decision-making about contraceptive methods. Secondary outcomes will be the
occurrence of a conversation about contraception in the health care visit, satisfaction with the conversation about
contraception, intended contraceptive method(s), intention to use a highly effective method, values concordance
of the intended method(s), decision regret, contraceptive method(s) used, use of a highly effective method, use of
the intended method(s), adherence, satisfaction with the method(s) used, unintended pregnancy, and unwelcome
pregnancy. We will collect study data via longitudinal patient surveys administered immediately after the health
care visit, 4 weeks later, and 6 months later.
Ethics and dissemination: We will disseminate results via presentations at scientific and professional conferences,
papers published in peer-reviewed, open-access journals, and scientific and lay reports. We will also make an
anonymised copy of the final participant-level data set available to others for research purposes.
Registration: ClinicalTrials.gov Identifier NCT02759939
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INTRODUCTION
Background and Rationale
Shared decision-making is the process of health care providers and patients making health decisions together.
While a number of conceptual definitions have been offered (1), the most common considers shared decision-
making a process in which providers and patients exchange information, deliberate about available options
together, and come to agreement on the option to implement (2). Shared decision-making is conceptually distinct
from paternalistic decision-making, which assumes that the patient’s preferences have no place in the decision-
making process, and from informed decision-making, which assumes that the provider’s only legitimate role in the
decision-making process is information provision (2,3).
Proponents of shared decision-making have described it as an ethical imperative (4) and the pinnacle of patient-
centered care (5). There is also a growing body of evidence of its generally positive impact on patient affective-
cognitive, behavioural, and health outcomes in a range of clinical contexts (6). In contraceptive care, shared
decision-making may represent a strategy for promoting health and wellbeing while safeguarding patient
autonomy, the importance of which is emphasised in key practice guidelines (7,8). For example, shared decision-
making about contraceptive methods may facilitate the prevention of unintended or unwelcome pregnancies by
increasing the likelihood that people choose methods aligned with their individual preferences and values, are
satisfied with the methods they adopt, and use them in a way that takes full advantage of their potential
contraceptive and other benefits. The anticipated gains from shared decision-making about contraceptive methods
may be particularly pronounced for members of minority racial and ethnic groups and people of low
socioeconomic status, who experience significant disparities in contraceptive care and outcomes (9).
Despite the numerous observed and theoretical advantages of shared decision-making, there remains a paucity of
evidence on how to facilitate its adoption. A recent systematic review of interventions for improving the adoption
of shared decision-making by health care providers found that, while interventions targeting patients alone (e.g.,
question prompt lists) or providers alone (e.g., audit and feedback) had some – if modest – positive effects on the
adoption of shared decision-making, effects were generally greater when interventions targeted both groups (10).
However, based on the small number and poor quality of available studies, reviewers were tentative in their
conclusions and advocated for further research to respond to this important knowledge gap. Answering this call,
this paper describes the protocol for a study that will assess the comparative effectiveness of patient- and
provider-targeted interventions for facilitating shared decision-making about contraceptive methods in the health
care visit.
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Objectives
The first objective of this study is to evaluate the effect of a patient-targeted intervention (a video + prompt card
that encourages patients to ask three specific questions in the health care visit) and a provider-targeted
intervention (decision aids + training in their use; see Interventions), on shared decision-making about
contraceptive methods in the health care visit. The second objective is to evaluate the effect of these interventions
on the occurrence of a conversation about contraception in the health care visit, satisfaction with the conversation
about contraception, intended contraceptive method(s), intention to use a highly effective method, values
concordance of the intended method(s), decision regret, contraceptive method(s) used, use of a highly effective
method, use of the intended method(s), adherence, satisfaction with the method(s) used, unintended pregnancy,
and unwelcome pregnancy (see Outcomes and Measures). The third objective is to evaluate the feasibility of the
interventions (operationalised as rates of patient exposure to the interventions) and their acceptability to
patients1.
Research Questions
There are four research questions pertaining to the first study objective: (1) Does implementing the video +
prompt card increase the rate of shared decision-making about contraceptive methods compared to usual care?
(2) Does implementing the decision aids + training increase the rate of shared decision-making about contraceptive
methods compared to usual care? (3) Does implementing the video + prompt card and the decision aids + training
result in greater increases in the rate of shared decision-making about contraceptive methods compared to usual
care than implementing either of the interventions alone? and (4) What patient characteristics and other factors
modify the effect of implementing the interventions on the rate of shared decision-making about contraceptive
methods? Research questions pertaining to the second and third study objectives, as well as study hypotheses, are
available in a supplementary file.
METHODS
Trial Design
We will conduct a 2x2 factorial cluster randomised controlled trial with four arms: (1) video + prompt card, (2)
decision aids + training, (3) video + prompt card and decision aids + training, and (4) usual care. This design will
enable us to assess the effect of the two interventions, both alone and together, as compared to usual care. The
clusters will be clinics (see Study Setting) and participants will be a subset of patients attending these clinics (see
Participants). While a cluster randomised controlled trial requires more participants than would a trial with a
1
We intend to evaluate the feasibility and acceptability of the interventions from the perspectives of health care providers and
other clinic staff in a separate, qualitative study.
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different approach to randomisation, we consider a cluster design most robust to prevent the contamination
possible if the unit of randomisation were to be patients or providers (11).
Study Setting
The trial will take place in 16 clinics in the Northeast United States, permitting the recommended minimum of four
clusters per trial arm to minimise potential confounding from cluster effects (11). Participating clinics may be
primary care and/or reproductive health care clinics but must deliver contraceptive care, which we define as
providing contraceptive methods on site, prescribing or referring people for contraceptive methods, and/or
counselling people about contraceptive methods. Participating clinics must also have sufficient patient flow that
staff are confident to be able to facilitate ten eligible patients, on average, completing a post-visit survey each
week. Within each clinic, contraceptive care may be provided by any person with relevant training (e.g., a
physician, nurse, physician assistant, nurse practitioner, midwife, non-medically-licensed counsellor). Participating
clinics may operate in hospital or community settings, be located in rural or urban areas, be publicly or privately
funded, and be for-profit or not-for-profit. Participating clinics may deliver services in more than one geographic
location but, to minimise contamination, may not employ someone who delivers contraceptive care in another
participating clinic and may not employ a study investigator. Participating clinics will receive monetary
compensation for the time expended by clinic staff on data collection and other administrative activities related to
their role in the study. A list of participating clinics may be requested.
Interventions
Video + Prompt Card (Patient-Targeted Intervention)
We developed a brief video intended to be viewed by patients in the clinic immediately before the health care
visit. The video was designed to enhance patients’ motivation, skills, and self-efficacy to ask their providers three
questions in the health care visit: (1) What are my options? (2) What are the possible pros and cons of those
options? and (3) How likely are each of those pros and cons to happen to me? Earlier iterations of these questions2
increased shared decision-making when used by unannounced standardised patients in a primary care setting in
Australia (12) and were the focus of the AskShareKnow program, a multi-pronged intervention that was feasible to
implement in a reproductive and sexual health care setting in Australia and acceptable to patients (13). The video
was adapted from a four-minute video that comprised one component of the AskShareKnow program (13). Our
adaptation features a patient sharing a personal account of her experiences of health care, communicating the
2
The first iteration was: (1) What are my options? (2) What are the possible benefits and harms of those options? and (3) How
likely are the benefits and harms of each option to occur? (12). The second iteration was: (1) What are my options? (2) What are
the possible benefits and harms of those options? and (3) How likely are each of those benefits and harms to happen to me?
(13).
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benefits of asking questions, normalising challenges associated with asking questions, and encouraging people to
ask the three target questions. The format and content of the adaptation responded to patient and stakeholder
perspectives solicited via discussions among the research team (which includes patient partners and stakeholder
representatives), focus groups with patients, and consultation with the patient featured in the adaptation, who has
since joined our research team. We developed versions of the video in English and Spanish, each with and without
on-screen captions. We will supply clinics with tablet computers programmed to view the videos and headphones.
We also developed a small prompt card intended to be distributed to patients who view the video. The card was
designed to remind patients of the three questions presented in the video. The prompt card was adapted from a
refrigerator magnet that comprised another component of the AskShareKnow program (13). Again, we developed
versions of the prompt card in English and Spanish. We will supply clinics with the prompt cards and display stands.
Decision Aids + Training (Provider-Targeted Intervention)
We developed seven one-page decision aids on contraceptive methods intended to be used by providers with
patients during the health care encounter. There are decision aids on long-acting reversible contraceptive
methods, short-acting reversible methods, barrier methods, natural methods, permanent methods, and
emergency methods, as well a decision aid that provides an overview of these six categories of contraceptive
methods. The decision aids were designed to help providers facilitate shared decision-making about contraceptive
methods in the health care visit. The format of the decision aids was adapted from that used in Option GridTM
decision aids for clinical encounters, which have been found to increase shared decision-making in osteoarthritis
care (14) and to be acceptable to physicians (15). We engaged patients and stakeholders in developing the decision
aids, including via a survey of patients and contraceptive care providers (16), patient focus groups, and review of
decision aid iterations by patient partners and stakeholder representatives. We developed versions of the
decisions aids in English and Spanish. We will supply clinics with tear-pads of the decision aids and display stands.
We also developed a five-minute training video and accompanying written guidance intended to be viewed by
providers before beginning to use the decision aids (and as frequently as desired thereafter). The training video
and frequently asked questions were designed to enhance providers’ motivation, skills, and self-efficacy to use the
decision aids to facilitate shared decision-making in the health care visit. The content of the training video was
informed by the Theoretical Domains Framework (17,18), which was devised to guide implementation research
that involves health care provider behaviour change. The video features an Obstetrician-Gynaecologist, Nurse
Practitioner, and patient representative explaining how decision aids can support the delivery of quality health
care and providing guidance on using the decision aids with patients. The written guidance reinforces and
elaborates on training video content. We will host the training video and frequently asked questions on the study
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website. One or more clinic representatives will be charged with encouraging and enabling relevant health care
providers in the clinic to review the training video and written guidance.
Implementation of Interventions
The strategies we developed to support adoption of the interventions purposefully omitted elements difficult to
scale (e.g., face-to-face training by intervention developers, periodic feedback on rates of patient exposure to the
interventions) to maximise the ecological validity of study findings. For the video and prompt card, we developed a
set of presentation slides for clinic staff that provides guidance on their objectives and implementation. The slide
deck will be hosted on the study website, along with a preview of the video and prompt card. One or more clinic
representatives will be charged with encouraging and enabling others in the clinic to review the slide deck. For the
decision aids and training, we also developed a set of presentation slides for clinic staff that provides guidance on
their objectives and implementation. The slide deck will be hosted on the study website. Again, one or more clinic
representatives will be charged with encouraging and enabling others in the clinic to review the slide deck. To
further approximate real-world conditions, we will not prevent clinics from implementing concomitant
interventions or care during the study.
Data Collection
We will collect study data via longitudinal patient surveys administered immediately after the index health care
visit (T1), 4 weeks (i.e., 28 days) after the index health care visit (T2), and 6 months (i.e., 182 days) after the index
health care visit (T3) (see Figure 1). Participants may elect to complete surveys in English or Spanish. The T1 survey
will be administered in clinics using tablet computers and the Qualtrics online survey platform (19). At the end of
the T1 survey, we will invite a subset of participants (see Participants) to give permission to be re-contacted for the
T2 and T3 surveys. Participants aged 20 years and older may elect to complete these surveys online (with email
communication) or on paper (with postal mail communication). Participants aged under 20 years may only elect to
complete these surveys online (with email communication) to safeguard their privacy. A unique password will be
used to link participant responses across surveys. Copies of the surveys may be requested.
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Figure 1. Data collection schematic
We have devised several strategies to maximise data quality. We chose to collect data via surveys rather than
interviews given the vulnerability of the topic area to social desirability bias (20). For the T1 survey, which will be
administered in clinics and collect data on participants’ care experiences and evaluations, we elected to use an
online survey completed via tablet computer to ensure no handling of surveys by clinic staff and thus reinforce the
confidentiality of responses. The study Information Sheet also reassures participants that no health care providers
from participating clinics will have access to identified participant-level data. For all surveys, we used programmed
or instructional skips to ensure that participants will be asked only relevant questions, thereby minimising survey
fatigue. In the online surveys, we also implemented additional data quality strategies, such as pop-up messages
that notify participants of missed questions and invite them to respond prior to proceeding to the next page.
We will also administer the T1, T2, and T3 surveys to a group of patients who attend participating clinics before we
begin the trial. This ‘pilot’ data collection will replicate the trial data collection and thus, allow clinic staff time to
become proficient in data collection processes. A further advantage of this pilot data collection is that we can
assess equivalence between clinics in the usual rate of shared decision-making about contraceptive methods,
adopt stratified assignment of clinics to trial arms if warranted (see Assignment), and statistically adjust for the
usual rate of shared decision-making in relevant data analyses.
Assignment
Each clinic will be assigned to one of the four trial arms using permuted-block randomisation with an equal
allocation ratio to achieve balance in the number of clinics per trial arm. Should we observe non-equivalence
between clinics in the rate of shared decision-making about contraceptive methods during the pilot data collection
period, we will adopt stratified permuted-block randomisation. Specifically, we will rank clinics according to the
rate of shared decision-making and construct four strata based on this ranking, with one clinic assigned to each
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trial arm in each stratum. The study statistician (TT) and statistical analyst will generate the allocation sequence
and assign clinics to trial arms. Due to the study design, it is not feasible to blind clinic staff, study participants, or
researchers to the trial arm to which each clinic has been assigned.
Participants
People who have completed a health care visit at a participating clinic, were assigned female sex at birth, are aged
15 to 49 years, are able to read and write English or Spanish, and have not previously participated in the study will
be eligible for the T1 survey. People who have not completed a visit at a participating clinic during the study period
(including a patient's parent or a person acting as a patient’s legal proxy), were not assigned female sex at birth,
are aged under 15 or over 49 years, are unable to read and write English or Spanish, or have previously
participated in the study will be ineligible for the T1 survey. To enable us to answer study research questions
without unnecessary participant burden, additional eligibility criteria will be imposed for the T2 and T3 surveys.
People who completed the T1 survey, experienced a contraceptive conversation in the health care visit, and
intended to use one or more contraceptive methods following the visit (see Outcomes and Measures) will be
eligible for the T2 and T3 surveys. People are not required to have completed the T2 survey to be eligible for the T3
survey.
Outcomes and Measures
We consulted with patients and other stakeholders in the process of selecting study outcomes. We prioritised the
inclusion of patient-centred outcomes, including participants’ perceptions of the values concordance of their
intended contraceptive method(s), decision regret pertaining to their intended contraceptive method(s), and
satisfaction with the contraceptive method(s) used. To maximise the utility of study results for different audiences
and purposes, we also elected to include a small number of more conventional, public health-oriented outcomes,
such as use of a highly effective contraceptive method (21). All primary and secondary study outcomes are
presented in Table 1 and elaborated below.
To maximise data quality, we selected measures for the primary and secondary outcomes based on their brevity,
readability, availability in English and Spanish, psychometric properties, prior use in other studies or population-
level surveys, and use of patient-centred language and tone. Where we identified a suitable measure in English
that was not available in Spanish, we arranged for it to be translated. Where we could not identify a suitable
measure, we developed or adapted one in English and arranged for it to be translated.
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Table 1. Outcomes and Timing of Measurement
T1 Survey T2 Survey T3 Survey
Conversation about contraception ●
Shared decision-making about contraceptive methods ●
Satisfaction with conversation about contraception ●
Intended contraceptive method(s) ●
Intention to use a highly effective contraceptive method ●
Values concordance of intended contraceptive method(s) ● ● ●
Decision regret about intended contraceptive method(s) ● ●
Contraceptive method(s) used ● ●
Use of a highly effective contraceptive method ● ●
Use of intended contraceptive method(s) ● ●
Adherence to contraceptive method(s) used ● ●
Satisfaction with contraceptive method(s) used ● ●
Unintended pregnancy (pregnancy timing preferences) ●
Unintended pregnancy (pregnancy seeking) ●
Unwelcome pregnancy ●
Primary Outcome
Shared decision-making about contraceptive methods We will measure shared decision-making
about contraceptive methods in the health care visit using the three-item CollaboRATE (22,23). CollaboRATE was
developed in consultation with end users (23) and assesses people’s perceptions of the extent to which their
health care provider(s) shared information, elicited their preferences, and ensured their preferences were
integrated as decisions were made. We will use the version of CollaboRATE with a five-point response scale and
adopt the binary scoring approach (22). When used in this way in an experimental validation study, CollaboRATE
demonstrated concurrent validity via a strong, positive correlation with the 9-Item Shared Decision Making
Questionnaire (SDM-Q-9; (24)) and a moderate, positive correlation with the five-item Doctor Facilitation subscale
of the Perceived Involvement in Care Scale (PICS; (25)) (22). CollaboRATE also demonstrated discriminative validity,
intra-rater reliability, and sensitivity to change (22). Because the CollaboRATE items are not condition-specific, we
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will use a customised opening statement to orientate participants to the conversation about contraception they
experienced in the health care visit.3
Secondary Outcomes
Conversation about contraception We will measure whether participants experienced a conversation
about contraception in the health care visit using a self-developed item. Due to divergent perspectives on the
circumstances under which a contraceptive conversation is indicated, we will report this outcome among (a) all
participants, (b) all participants except those not at risk of unintended pregnancy (see Other Data for definition
and measurement), and (c) all participants except those not at risk of unintended pregnancy and those who
reported that they did not want or need to talk about contraception.
Satisfaction with conversation about contraception We will measure participants' satisfaction with
the conversation about contraception in the health care visit using an item adapted from Weisman et al. (26).
Intended contraceptive method(s) We will measure what, if any, contraceptive method(s)
participants intend to use in the next four weeks using a self-developed checklist of 20 methods. The checklist
specifies common and brand names for some methods, encourages participants to review explanatory information
about the methods if unsure, and allows participants to select multiple methods or select “none of these”. We will
report this outcome among (a) all participants, (b) all participants except those not at risk of unintended pregnancy
(see Other Data for definition and measurement), and (c) all participants except those not at risk of unintended
pregnancy and those who reported that they did not want or need to use a birth control method.
Intention to use a highly effective contraceptive method We will use data on participants’ intended
contraceptive method(s) to derive a variable that represents whether they intend to use at least one highly
effective contraceptive method in the next four weeks. We consider highly effective contraceptive methods to
comprise the copper intrauterine device (IUD), the hormonal IUD, the contraceptive implant, female sterilisation,
and male sterilisation, all of which have a typical-use unintended pregnancy rate of <1% in the first year of use
(27). We will report this outcome among (a) all participants, (b) all participants except those not at risk of
unintended pregnancy (see Other Data for definition and measurement), and (c) all participants except those not
at risk of unintended pregnancy and those who reported that they did not want or need to use a birth control
method.
3
To enhance the usefulness of data for future research, participants who did not experience a contraceptive conversation will
be asked to complete CollaboRATE with reference to the health care visit in general.
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Values concordance of intended contraceptive method(s) We will measure participants' perceptions
of the values concordance of their intended contraceptive method(s) (i.e., the degree of alignment between the
method(s) and their individual values and preferences) using the self-developed, single-item Measure of Alignment
of Choices (MATCH). MATCH contains an opening statement that orients the participant to the contraceptive
method(s) of interest and then asks either “How confident are you that this method is right for you?” or “How
confident are you that these methods are right for you?”. When we administer this measure at T2 and T3, we will
remind participants of their nominated intended contraceptive method(s).
Decision regret about intended contraceptive method(s) We will measure participants' feelings of
decision regret about the contraceptive method(s) they intended to use using an adaptation of the five-item
Decision Regret Scale (28,29). When we administer this measure at T2 and T3, we will remind participants of their
nominated intended contraceptive method(s).
Contraceptive method(s) used We will measure what, if any, contraceptive method(s) participants
used in the last four weeks using an adaptation of the checklist used to assess intended contraceptive method(s).
Use of a highly effective contraceptive method We will use data on the contraceptive method(s)
participants used to derive a variable that represents whether they used at least one highly effective contraceptive
method in the last four weeks.
Use of intended contraceptive method(s) We will use data on participants’ intended contraceptive
method(s) and the contraceptive method(s) they used to derive a variable that represents whether participants
used their intended contraceptive method(s) in the last four weeks.4
Adherence to contraceptive method(s) used We will measure participants' adherence to the
contraceptive method(s) they used in the last four weeks using the self-developed, 21-item Adherence to Birth
Control (ABC) measure.
Satisfaction with contraceptive method(s) used We will measure participants' satisfaction with the
contraceptive method(s) they used in the last four weeks using a self-developed item. We will use a slightly
modified version of this item to measure satisfaction among participants who reported that they used none of the
listed contraceptive methods in the last four weeks.
4
For participants who complete the T2 survey on the target completion date, the four-week recall period adopted for the
assessment of contraceptive method(s) used in this survey will align with the four-week timeframe adopted in the assessment
of intended contraceptive method(s) in the T1 survey.
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Unintended pregnancy (pregnancy timing preferences) We will measure participants’ experience of
one or more unintended pregnancies, as defined by their pregnancy timing preferences, after the health care visit.
For each pregnancy experienced after the health care visit, we will measure the pregnancy timing preferences
participants’ held immediately before conception using an item adapted from the Pregnancy Risk Assessment
Monitoring System (PRAMS) Phase 7 questionnaire (30). We will classify participants either as having experienced
unintended pregnancy or not having experienced unintended pregnancy based on their responses.
Unintended pregnancy (pregnancy seeking) We will measure participants’ experience of one or more
unintended pregnancies, as defined by their pregnancy seeking, after the health care visit. For each pregnancy
experienced after the health care visit, we will measure participants’ pregnancy seeking immediately before
conception using an item adapted from Kavanaugh and Schwarz (31). We will classify participants either as having
experienced unintended pregnancy or not having experienced unintended pregnancy based on their responses.
Unwelcome pregnancy We will measure participants’ experience of one or more unwelcome
pregnancies after the health care visit. For each pregnancy experienced after the health care visit, we will measure
participants’ feelings on learning about the pregnancy using an item adapted from the PRAMS Phase 7
questionnaire (30). We will classify participants either as having experience unwelcome pregnancy or not having
experienced unwelcome pregnancy based on their responses.
Process Outcomes
Intervention exposure and question asking We will measure participants’ exposure to the video,
receipt of the prompt card, and use of the three questions in the health care visit using five items adapted from
Shepherd et al. (13), administered at T1. We will measure participants’ exposure to one or more of the decision
aids (including nature and timing of exposure) using a self-developed item administered at T1.
Acceptability of interventions We will measure the acceptability of the video, prompt card, and
decision aid(s) to participants using three self-developed items administered at T1.
Exposure to concomitant interventions We will measure exposure to other information on
contraception on the day of the health care visit using a self-developed item administered at T1.
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Other Data
Visit date The T1 survey will automatically record the date and time of survey completion (and thus,
date of the health care visit) for each participant. We will use these data to distinguish between pilot and trial
participants.
Clinic We will measure the clinic in which each participant had their health care visit (and thus, trial
arm) using a self-developed item measure administered at T1. The T1 survey will also automatically record the
Internet Protocol (IP) address of the tablet computer on which the T1 survey is completed. We will use these data
to review the accuracy of patient-reported data on clinic, managing inconsistencies on a case-by-case basis.
Previous contraceptive method(s) We will measure what, if any, contraceptive method(s) participants
used in the four weeks before the health care visit using an adaptation of the checklist used to assess intended
contraceptive method(s).
Pregnancies We will measure the number of pregnancies participants experienced after the health
care visit using a self-developed item administered at T3. When we administer this item, we will remind
participants of the date of their health care visit.
Explanatory questions and risk of unintended pregnancy At T1, we will ask participants who did not
experience a conversation about contraception to report one or more reasons for this from a self-developed list.
At T1, we will also ask participants who do not intend to use any of the contraceptive methods in the checklist to
report one or more reasons for this from a self-developed list. We will use the self-reported data participants
provide in response to these questions to identify those not at risk of unintended pregnancy at the time of the
health care visit. We will consider participants to be not at risk of unintended pregnancy if they report that they
are pregnant, are trying to get pregnant, do not have ovaries or a uterus, have entered menopause, are infertile, or
do not plan to have vaginal sex with a person that produces sperm.
At T2 and T3, we will ask participants who had not used their intended contraceptive method(s) in the last
four weeks to report the reason(s) for this in an open-ended question. When administering the ABC measure at T2
and T3, we will provide a free text box after the adherence question(s) for each method to enable participants to
elaborate on their response(s). We will also provide a free text box at the end of the T2 and T3 surveys to enable
participants to share any other information they choose.
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Participant and visit characteristics We will measure several participant and visit characteristics at T1.
We will measure participants’ age, ability to read and write English or Spanish, sex assigned at birth (32), visit
completion, previous study participation, and clinic (see above) to confirm study eligibility. We will also measure
participants’ current gender identity (32), race, ethnicity, and educational attainment (33), health insurance
coverage (34), and health literacy (35–39). We will measure participants’ reproductive history using four self-
developed items. We will also document the language in which each participant completed the survey.
Recruitment and Retention
Prospective participants will be made aware of the opportunity to take part in the study on the day of their health
care visit via study posters and Information Sheets displayed in participating clinics and/or through communication
with clinic staff. We have adopted several strategies for achieving adequate participant enrolment and maximising
participant retention, informed by both reviews of empirical evidence (40,41) and patient and stakeholder
perspectives. To help achieve adequate participant enrolment, we developed engaging recruitment materials that
use a study name and branding designed with patient input. We adopted inclusive eligibility criteria (see
Participants) and elected to allow participation without a commitment to complete all three surveys. We will also
compensate participants with a $10 gift card for completing the T1 survey.
To maximise retention of participants enrolled in the study and minimise nonresponse error, we adopted both
online and paper completion modes for the T2 and T3 surveys for participants aged 20 years and older (see Data
Collection). We will provide people who elect to complete the surveys on paper with an addressed, reply-paid
envelope to facilitate survey return. We elected to administer the sending and receiving of T2 and T3 surveys from
the research institution, thereby removing the responsibility from clinic staff. We have also developed survey
invitation and reminder schedules customised to the survey mode. For the online completion mode, we will send
two daily email reminders to participants who have not completed the T2 or T3 survey and will also send an email
prompt one week in advance of the T2 survey invitation to encourage completion on the target date (see Figure 2).
For the paper completion mode, we will send a similar mail prompt one week in advance of the T2 and T3 survey
invitations, but will not send daily mail reminders due to anticipated variation in mail delivery times and the
potential for such reminders to arrive simultaneously or overlap (see Figure 2). Again, we will compensate
participants with a $10 gift card for completing each of the T2 and T3 surveys.
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Figure 2. Survey invitation and reminder schedule
Sample Size and Power
Sample Size
Each of the 16 participating clinics will be expected to facilitate ten eligible patients completing the T1 survey per
week on average. Thus, we estimate that 1,040 participants per trial arm will complete the T1 survey during the
trial period. We estimate that 728 participants per trial arm (70%) will experience a conversation about
contraception and thus comprise the sample for the primary outcome analysis. We estimate that 70% of the
participants who experience a contraceptive conversation will be eligible for and agree to be invited to complete
the T2 and T3 surveys. Of these, we estimate that 80% will complete the T2 survey and that 70% will complete the
T3 survey (see Figure 3).
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Figure 3. Estimated sample sizes per trial arm
*Estimates of the total number of patients eligible for the study will be provided by clinics based on routinely collected data
^Sample for primary outcome analyses
Additionally, we estimate that, in each clinic, 130 pilot participants will complete the T1 survey, 91 pilot
participants will experience a conversation about contraception, and 51 and 45 pilot participants will complete the
T2 and T3 surveys, respectively.
Power
The study was powered to answer Research Questions 1, 2, and 3 (see Research Questions). As outlined above, we
estimate a sample size of 728 participants per trial arm for the primary outcome analysis (see Figure 3). We base
our detectable difference calculations on tests comparing the proportion of participants who experience shared
decision-making about contraceptive methods (the primary outcome) between trial arms, assuming a proportion
of 66% in the usual care arm (42). Given the fixed number of clusters per trial arm and the estimated sample size,
we determine a detectable increase of 16% (from 66% to 82%) in the proportion of participants who experience
shared decision-making, based on a z-test test comparing two proportions with clustered data, with an estimated
intra-cluster correlation coefficient (ICC) of 0.03 (43), a two-sided significance level of 5%, and a power of 80%. If
we apply a Bonferroni correction for the three possible comparisons versus the usual care arm to retain a nominal
family-wise significance level of 5%, we can detect an increase of 18.1% in the proportion of participants who
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experience shared decision-making. These calculations show that we will have a sufficient sample size to detect
meaningful changes in shared decision-making. All calculations were done using the PASS 2008 sample size
package (44) based on standard methods (45).
Data Management and Analysis
Data Management
The surveys will collect direct and indirect participant identifiers. To minimise risks to participant privacy, only
three people from the study team (the principal investigator, the project manager, and the data manager) will be
allowed to access highly identifying participant-level data and files. The people in these roles will be responsible for
sending and receiving T2 and T3 surveys and associated correspondence; entering, cleaning, and recoding data;
and securely storing and transferring identified participant-level data and files. They will also be responsible for
deleting or destroying highly identifying information (i.e., participant names, email addresses, and mailing
addresses) from all documents and files upon the completion of the study and otherwise anonymising data prior to
sharing it. Our anonymisation process will take into account 28 direct and indirect patient identifiers (46). To
maximise the utility of study data, we will store both identified data (excluding highly identifying information) and
anonymised data indefinitely. A comprehensive data management plan may be requested.
Data Analysis
Analysis Plan A data analysis plan is available in a supplementary file.
Protocol Nonadherence While we will report rates of protocol nonadherence (derived from patient
reports of exposure to the intended intervention(s)), the analyses for Research Questions 1, 2, and 3 will be
conducted by intention to treat. Patient exposure to the interventions may comprise one factor included in the
analyses for Research Question 4.
Treatment of Missing Data We will report rates of and reasons for missing data, whether due to
unanswered questions or participant attrition. In the treatment of missing data, we will assess (and report)
whether participants with missing data differ systematically from others on background or other characteristics,
clinic, or trial arm, and consider this in the interpretation of findings. Depending on the findings of this assessment,
we will adopt listwise deletion of missing cases with adjustments for covariates associated with missingness,
multiple imputation, or equivalent methods (e.g., maximum likelihood estimates in mixed models).
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Study Limitations
Three potential limitations warrant discussion. First, we chose to implement the trial in 16 clinics in reasonable
proximity to our research institution. This minimised costs and thus enabled us to enrol the recommended
minimum number of clusters per trial arm (11). However, potential confounding from cluster effects may have
been further minimised by a greater number of clinics and the racial, ethnic, and linguistic diversity of participants
enhanced by greater geographical diversity in clinics. Second, we chose to collect minimal contact information for
participants eligible for the T2 and T3 surveys. Given the sensitivity of the topic, we considered this important for
preventing both barriers to recruitment and risks to participants’ privacy. However, this simultaneously limited
opportunities for participant contact and may compromise retention. Third, while clinic estimates of the total
number of eligible patients during the study period will enable calculation of the participation rate, a lack of
information on the characteristics of all eligible patients will preclude conclusions about sample
representativeness.
ETHICS AND DISSEMINATION
Research Ethics Approval
Institutional Review Board approval for the study was granted by the Committee for the Protection of Human
Subjects (CPHS) at Dartmouth College (Study #00028721), as well as by an external Institutional Review Board
affiliated with one participating clinic.
Consent
When adopting a cluster randomised study design, it is not usually feasible to obtain participants’ consent to
randomisation (11,47,48). Instead, consent to randomisation is typically provided by a surrogate decision-maker at
the cluster level (47,48). We will obtain agreement to randomisation from a representative from each clinic and
will seek eligible patients’ informed consent to participate in data collection for the study.
To eliminate barriers to participation and minimise risks to participants, we were granted Institutional Review
Board approval for a waiver of documented informed consent and for a waiver of parental consent for participants
aged 15-17 years. In our modified consent process, clinic staff will provide potentially eligible patients with a tablet
computer (proactively and/or upon request) that displays an electronic version of the study Information Sheet.
This Information Sheet enables patients to self-assess their eligibility for the study, become informed about the
study purposes, processes, benefits, and risks, and elect whether to participate in the study. Patients who select
‘Yes’ in response to the question ‘Now that you have read this information, do you agree to participate in this
study?’ that follows this electronic Information Sheet will be taken as having given informed consent and will
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proceed to the T1 survey immediately. Paper copies of the Information Sheet will also be available in participating
clinics.
Privacy and Confidentiality
We have adopted several strategies to protect the privacy of participants. We were granted Institutional Review
Board approval for a waiver of documented informed consent (see Consent) and will administer the provision of
participant compensation from the research institution so that no information on participants will be stored in any
clinic. The waver of documented informed consent also means that patients can participate in the study without
ever providing their name or contact details if they are willing to forego compensation. Participants aged under 20
years may only elect to complete the T2 and T3 surveys online (with email communication) to safeguard their
privacy. Participants aged 20 years and older who elect to complete the T2 and T3 surveys on paper will receive
(and send) all associated correspondence in unbranded envelopes. We will use an otherwise meaningless random
code generated during T1 survey completion to link participant surveys across the three time points. Finally, we
have restricted access to identified participant-level data and files (see Data Management).
Monitoring
Following internal institutional consultation, we determined that a formal Data and Safety Monitoring Board
(DSMB) was unnecessary due to the minimal risks associated with study participation and the focus of the study on
outcomes other than mortality or morbidity (49). We anticipate no harms arising from implementation of the
interventions. If we become aware of any harms or other adverse events, either through study data or other
avenues, we will review and address these according to standard institutional processes in consultation with the
relevant Institutional Review Board(s). We will also file regular reports on trial progress and any adverse events
with the Institutional Review Boards. Although we intend to conduct some analyses of pilot data collected before
assigning clinics to trial arms, we do not anticipate undertaking any interim analyses of trial outcome data and
have not devised any stopping guidelines.
Dissemination Policy
Full Protocol
Members of the scientific community and the public can access the full study protocol via this open access
publication. Substantive modifications to this protocol will be communicated to the relevant staff at participating
clinics during regular communications. Substantive modifications to this protocol will also be communicated to
others via study meetings, written summaries, published modifications to the trial profile at clinicaltrials.gov,
and/or via statements in scientific papers or reports arising from the study.
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Study Findings
We will disseminate study findings through various channels. We will deliver presentations at scientific
conferences and professional meetings and publish papers in peer-reviewed, open-access journals. We will adhere
to International Committee of Medical Journal Editors (ICMJE) recommendations pertaining to authorship roles
and responsibilities in papers arising from this study (50). We will also prepare a final report of study findings and
accompanying summary for lay audiences. We will disseminate these documents to participants and participating
clinics, health care providers, policy makers, the public, and other relevant groups. Wherever possible, we will
make documents describing study findings available via the study website (www.rightforme.org). We do not intend
to draw on the services of professional writers for the development of presentations, papers, or reports.
Participant-Level Data
To facilitate transparency and maximise the usefulness of data collected in the study, we will make an anonymised
copy of the final participant-level data set and essential analysis syntax available to others for research purposes
via data sharing on request and/or a digital repository, before October 2018.
Declaration of Interests
All authors have completed the ICMJE uniform disclosure at www.icmje.org/coi_disclosure.pdf. Rachel Thompson
reports a grant from PCORI during the conduct of the study and non-financial support from PCORI outside the
submitted work. Rachel Thompson also reports ownership of copyright in several patient decision aids and a role
as an editor of the text, ‘Shared Decision Making in Health Care’ but has not received any personal income
connected to this ownership or role. Ruth Manski, Kyla Donnelly, Gabrielle Stevens, Daniela Agusti, Tina Foster,
Deborah Johnson, Zhongze Li, Ardis Olson, and Tor Tosteson report a grant from PCORI during the conduct of the
study. Michelle Banach and Krishna Upadhya report personal fees from Dartmouth College during the conduct of
the study. Maureen Boardman reports a grant from PCORI and other payments from Dartmouth College during the
conduct of the study. Pearl Brady reports personal fees and non-financial support from Dartmouth College during
the conduct of the study and non-financial support from Dartmouth College outside the submitted work. Christina
Colón Bradt reports personal fees and non-financial support from Dartmouth College during the conduct of the
study. Judy Norsigian reports personal fees from Dartmouth College during the conduct of the study and non-
financial support from PCORI outside the submitted work. Melissa Nothnagle reports personal fees and other
payments from Dartmouth College during the conduct of the study. Melissa Nothnagle also reports a role as a
health care provider and clinic representative in a clinic participating in the study. Heather Shepherd reports a role
as a developer of the AskShareKnow program intervention components and related survey items that were
adapted for use in the study but has not received any personal income connected to this role. Lisa Stern reports
personal fees from Dartmouth College during the conduct of the study; grants from Bayer Health Care Inc., Teva
Pharmaceuticals, and Gilead Pharmaceuticals Inc. outside the submitted work; and personal fees from Hologic Inc.
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outside the submitted work. Lyndal Trevena reports other payments from Dartmouth College during the conduct
of the study. Glyn Elwyn reports a grant from PCORI during the conduct of the study and personal fees from Emmi
Solutions LLC, Washington State Health Department, Oxford University Press, the National Quality Forum,
SciMentum LLC, EBSCO Health, &think LLC, and ACCESS Federally Qualified Health Centers outside the submitted
work. Glyn Elwyn also reports ownership of copyright in the CollaboRATE measure of shared decision-making, the
Observer OPTION measure of shared decision-making, and several patient decision aids.
ROLES AND RESPONSIBILITIES
Protocol Contributors
Rachel Thompson, Kyla Donnelly, and Glyn Elwyn conceived the study. All authors contributed to the design of the
study and/or the development of study interventions, data collection protocols, or other materials. Rachel
Thompson drafted the manuscript. All authors contributed to revisions of the draft and gave approval for
publication of the manuscript.
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care: preventing unintended pregnancy in adults. Women’s Heal Issues. 2002;12(2):79–95.
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Contraceptive Technology. 20th ed. New York, NY: Ardent Media; 2011.
28. Brehaut JC, O’Connor AM, Wood TJ, Hack TF, Siminoff L, Gordon E, et al. Validation of a decision regret
scale. Med Decis Making. 2003;23(4):281–92.
29. O’Connor A. User Manual - Decision Regret Scale. Ottawa; 1996.
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item measure. Perspect Sex Reprod Health. 2009 Dec;41(4):238–43.
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32. Cahill S, Singal R, Grasso C, King D, Mayer K, Baker K, et al. Do ask, do tell: high levels of acceptability by
patients of routine collection of sexual orientation and gender identity data in four diverse American
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33. US Census Bureau. The American Community Survey 2015. Washington, DC; 2015.
34. Jones RK, Finer LB, Singh S. Characteristics of U.S. Abortion Patients, 2008. New York; 2010.
35. Chew LD, Griffin JM, Partin MR, Noorbaloochi S, Grill JP, Snyder A, et al. Validation of screening questions
for limited health literacy in a large VA outpatient population. J Gen Intern Med. 2008 May;23(5):561–6.
36. Chew LD, Bradley K a., Boyko EJ. Brief questions to identify patients with inadequate health literacy. Fam
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37. Wallace LS, Rogers ES, Roskos SE, Holiday DB, Weiss BD. Brief report: Screening items to identify patients
with limited health literacy skills. J Gen Intern Med. 2006;21(8):874–7.
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administration of the Short Literacy Survey. J Health Commun. 2015;20(7):835–42.
39. Sarkar U, Schillinger D, López A, Sudore R. Validation of self-reported health literacy questions among
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40. Porter SR. Raising response rates: What works? New Dir Institutional Res. 2004;2004(121):5–21.
41. Brueton VC, Tierney JF, Stenning S, Meredith S, Harding S, Nazareth I, et al. Strategies to improve retention
in randomised trials: a Cochrane systematic review and meta-analysis. BMJ Open. 2014;4(2):e003821.
42. Barr PJ, Forcino RC, Thompson R, Ozanne EM, Arend R, Castaldo MG, et al. Evaluating CollaboRATE in a
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43. Edwards A, Elwyn G, Hood K, Atwell C, Robling M, Houston H, et al. Patient-based outcome results from a
cluster randomized trial of shared decision making skill development and use of risk communication aids in
general practice. Fam Pr. 2004 Aug;21(4):347–54.
44. Hintze J. PASS 2008. NCSS, LLC. Kaysville, UT; 2008.
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for journal editors, authors, and peer reviewers. BMJ. 2010 Jan;340:c181.
47. Donner A, Klar N. Pitfalls of and controversies in cluster randomization trials. Am J Public Health. 2004
Mar;94(3):416–22.
48. Eldridge SM, Ashby D, Feder GS. Informed patient consent to participation in cluster randomized trials: an
empirical exploration of trials in primary care. Clin Trials. 2005 Jan;2(2):91–8.
49. Food and Drug Administration. Guidance for clinical trial sponsors: Establishment and operation of clinical
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50. International Committee of Medical Journal Editors. Recommendations for the Conduct, Reporting, Editing,
and Publication of Scholarly Work in Medical Journals. 2015.
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Right For Me: Protocol for a cluster randomised trial of two interventions for facilitating shared decision-‐making about contraceptive methods Study Objectives, Research Questions, Hypotheses, and Analytic Plan OBJECTIVES RESEARCH QUESTIONS HYPOTHESES ANALYTIC PLAN The first objective of this study is to evaluate the effect of (1) a video + prompt card that encourage patients to ask three specific questions in the health care visit, and (2) decision aids + training for health care providers in their use, on shared decision-‐making about contraceptive methods in the health care visit.
1 Does implementing the video + prompt card increase the rate of shared decision-‐making about contraceptive methods compared to usual care?
We hypothesise that implementing the video + prompt card will increase the rate of shared decision-‐making about contraceptive methods compared to usual care.
The primary outcome for the analysis is shared decision-‐making about contraceptive methods, a binary variable. To account for the cluster randomized design, the analysis will use random effects logistic regression for binary outcome variables as implemented in SAS PROC GLIMMIX, with a random intercept for clinic. The analysis will adjust for the clinic-‐level pre-‐existing rate of shared decision-‐making and any other participant characteristics that differ across trial arms. Contrasts between group rates will be performed using the model results to address research questions 1-‐3.
2 Does implementing the decision aids + training increase the rate of shared decision-‐making about contraceptive methods compared to usual care?
We hypothesise that implementing the decision aids + training will increase the rate of shared decision-‐making about contraceptive methods compared to usual care.
3 Does implementing the video + prompt card and the decision aids + training result in greater increases in the rate of shared decision-‐making about contraceptive methods compared to usual care than implementing either of the interventions alone?
We hypothesise that implementing the video + prompt card and the decision aids + training will result in greater increases in the rate of shared decision-‐making about contraceptive methods compared to usual care than implementing the video + prompt card alone or the decision aids + training alone.
4 What patient characteristics and other factors modify the effect of implementing the interventions on the rate of shared decision-‐making about contraceptive methods?
This heterogeneity of treatment effects (HTE) analysis is exploratory (i.e., hypothesis generating) and thus no a priori hypotheses for this research question have been developed.
We will use the same modelling techniques to assess modifiers of the shared decision-‐making rate effects seen for research questions 1-‐3 by fitting interaction terms with the intervention group variables. The modifiers considered will be age, gender identity, health insurance, health literacy, educational attainment, ethnicity, race, exposure
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to interventions (three variables), exposure to other interventions (one variable), and pre-‐existing shared decision-‐making. In reporting the modifier analyses, p-‐values will be shown adjusted for multiple comparisons.
The second objective is to evaluate the effect of these interventions on several other outcomes (see Outcomes and Measures).
For each of the secondary outcomes:
5 Does implementing the video + prompt card increase or decrease (as relevant) the [rate/level] of [secondary outcome] compared to usual care?
We hypothesise that implementing the video + prompt card will increase the rate of • conversation about contraception, • optimal satisfaction with the conversation about
contraception, • optimal values concordance of intended contraceptive
method(s), • use of intended contraceptive method(s), • optimal adherence to contraceptive method(s) used, • optimal satisfaction with contraceptive method(s) used; decrease the level of • decision regret; and decrease the rate of • unintended pregnancy (pregnancy timing preferences), • unintended pregnancy (pregnancy seeking), and • unwelcome pregnancy compared to usual care. Analyses pertaining to the secondary outcomes of intended contraceptive method(s), intention to use a highly effective contraceptive method, contraceptive method(s) used, and use of a highly effective contraceptive method are exploratory and thus no a priori hypotheses for these secondary outcomes have been developed.
We will conduct separate analyses to answer these research questions for each of the 14 secondary outcomes. We will use a random effects regression for either categorical or continuous outcomes with a random intercept for clinic to account for clustering. The analysis will adjust for participant characteristics that differ across trial arms. Contrasts between group rates or means will be performed as with the primary outcome. For analyses pertaining to the secondary outcome, Conversation About Contraception, we will use three denominators: (a) all participants, (b) all participants except those not at risk of unintended pregnancy, and (c) all participants except those who reported that they did not want or need to talk about contraception.
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For analyses pertaining to the secondary outcome, Intended Contraceptive Method(s), we will use three denominators: (a) all participants, (b) all participants except those not at risk of unintended pregnancy, and (c) all participants except those who reported that they did not want or need to use a birth control method. For analysis pertaining to the secondary outcome, Intention to Use a Highly Effective Contraceptive Method, we will use three denominators: (a) all participants, (b) all participants except those not at risk of unintended pregnancy, and (c) all participants except those who reported that they did not want or need to use a birth control method. In reporting the secondary analyses, p-‐values will be shown adjusted for multiple comparisons.
6 Does implementing the decision aids + training increase or decrease (as relevant) the [rate/level] of [secondary outcome] compared to usual care?
We hypothesise that implementing the decision aids + training will increase the rate of • conversation about contraception, • optimal satisfaction with the conversation about
contraception, • optimal values concordance of intended contraceptive
method(s), • use of intended contraceptive method(s), • optimal adherence to contraceptive method(s) used, • optimal satisfaction with contraceptive method(s) used; decrease the level of • decision regret; and decrease the rate of • unintended pregnancy (pregnancy timing preferences), • unintended pregnancy (pregnancy seeking), and • unwelcome pregnancy compared to usual care. Analyses pertaining to the secondary outcomes of intended contraceptive method(s), intention to use a highly effective contraceptive method, contraceptive method(s) used, and use of a highly effective contraceptive method are exploratory and thus no a priori hypotheses for these secondary outcomes have been developed.
7 Does implementing the video + prompt
card and the decision aids + training result in greater increases or decreases (as relevant) in the [rate/level of [secondary outcome] compared to usual care than implementing either of the interventions alone?
We hypothesise that implementing the video + prompt card and the decision aids + training will result in greater increases in the rate of • conversation about contraception, • optimal satisfaction with the conversation about
contraception, • optimal values concordance of intended contraceptive
method(s), • use of intended contraceptive method(s), • optimal adherence to contraceptive method(s) used,
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• optimal satisfaction with contraceptive method(s) used; greater decreases in the level of • decision regret; and greater decreases in the rate of • unintended pregnancy (pregnancy timing preferences), • unintended pregnancy (pregnancy seeking), and • unwelcome pregnancy compared to usual care than implementing the video + prompt card alone or the decision aids + training alone. Analyses pertaining to the secondary outcomes of intended contraceptive method(s), intention to use a highly effective contraceptive method, contraceptive method(s) used, and use of a highly effective contraceptive method are exploratory and thus no a priori hypotheses for these secondary outcomes have been developed.
The third objective is to evaluate the (1) feasibility of the interventions (operationalised as rates of patient exposure to the interventions) and (2) their acceptability to patients.
8 Of participants receiving care in a trial arm implementing the video + prompt card, what proportion report having watched the whole video?
We hypothesise that, of participants receiving care in a trial arm implementing the video + prompt card, at least 70% will report having watched the whole video.
Proportions and confidence intervals will be reported both separately by clinic and for all clinics as a whole.
9 Of participants receiving care in a trial arm implementing the video + prompt card, what proportion report having received the prompt card?
We hypothesise that, of participants receiving care in a trial arm implementing the video + prompt card, at least 70% will report having received the prompt card.
10 Of participants receiving care in a trial arm implementing the decision aids + training, what proportion report having used a decision aid together with a health care provider?
We hypothesise that, of participants receiving care in a trial arm implementing the decision aids + training, at least 70% will report having used a decision aid together with a health care provider.
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11 Is the proportion of participants who report having watched the whole video higher among those receiving care in a trial arm implementing both the video + prompt card and decision aids + training than in a trial arm implementing only the video + prompt card?
We hypothesise that the proportion of participants who report having watched the whole video will be higher among those receiving care in a trial arm implementing both the video + prompt card and decision aids + training than in a trial arm implementing only the video + prompt card.
We will conduct three analyses. To account for the cluster randomized design, the analyses will use random effects logistic regression, as described above. The analyses will adjust for any participant characteristics that differ across trial arms. In reporting analyses, p-‐values will be shown adjusted for multiple comparisons. 12 Is the proportion of participants who
report having received the prompt card higher among those receiving care in a trial arm implementing both the video + prompt card and decision aids + training than in a trial arm implementing only the video + prompt card?
We hypothesise that the proportion of participants who report having received the prompt card will be higher among those receiving care in a trial arm implementing both the video + prompt card and decision aids + training than in a trial arm implementing only the video + prompt card.
13 Is the proportion of participants who report having used a decision aid together with a health care provider higher among those receiving care in a trial arm implementing both the decision aids + training and video + prompt card than in a trial arm implementing only the decision aids + training?
We hypothesise that the proportion of participants who report having used a decision aid together with a health care provider will be higher among those receiving care in a trial arm implementing both the decision aids + training and video + prompt card than in a trial arm implementing only the decision aids + training.
14 What proportion of participants who report having watched the whole video would recommend it to a friend?
We hypothesise that a majority of participants who report having watched the whole video would recommend it to a friend.
Proportions and confidence intervals will be reported both separately by clinic and for all clinics as a whole.
15 What proportion of participants who report having received the prompt card would recommend it to a friend?
We hypothesise that a majority of participants who report having received the prompt card would recommend it to a friend.
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16 What proportion of participants who report having used a decision aid together with a health care provider would recommend it to a friend?
We hypothesise that a majority of participants who report having used a decision aid together with a health care provider would recommend it to a friend.
17 Is the proportion of participants who would recommend the video to a friend higher among those receiving care in a trial arm implementing both the video + prompt card and decision aids + training than in a trial arm implementing only the video + prompt card?
We hypothesise that the proportion of participants who would recommend the video to a friend will be higher among those receiving care in a trial arm implementing both the video + prompt card and decision aids + training than in a trial arm implementing only the video + prompt card.
We will conduct three analyses. To account for the cluster randomized design, the analyses will use random effects logistic regression, as described above. The analyses will adjust for any participant characteristics that differ across trial arms. In reporting analyses, p-‐values will be shown adjusted for multiple comparisons.
18 Is the proportion of participants who would recommend the prompt card to a friend higher among those receiving care in a trial arm implementing both the video + prompt card and decision aids + training than in a trial arm implementing only the video + prompt card?
We hypothesise that the proportion of participants who would recommend the prompt card to a friend will be higher among those receiving care in a trial arm implementing both the video + prompt card and decision aids + training than in a trial arm implementing only the video + prompt card.
19 Is the proportion of participants who would recommend the decision aids to a friend higher among those receiving care in a trial arm implementing both the decision aids + training and video + prompt card than in a trial arm implementing only the decision aids + training?
We hypothesise that the proportion of participants who would recommend the decision aids to a friend will be higher among those receiving care in a trial arm implementing both the decision aids + training and video + prompt card than in a trial arm implementing only the decision aids + training.
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1
SPIRIT 2013 Checklist: Recommended items to address in a clinical trial protocol and related documents*
Section/item Item No
Description Addressed on page number
Administrative information
Title 1 Descriptive title identifying the study design, population, interventions, and, if applicable, trial acronym 1
(Note, because of the
number of words
required to accurately
describe the population,
this has been omitted)
Trial registration 2a Trial identifier and registry name. If not yet registered, name of intended registry 2
2b All items from the World Health Organization Trial Registration Data Set TRDS items are largely
replicated in the
clinicaltrials.gov registry
in which study is
registered
Protocol version 3 Date and version identifier N/A
(Published protocol will
be date stamped)
Funding 4 Sources and types of financial, material, and other support 1
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2
Roles and
responsibilities
5a Names, affiliations, and roles of protocol contributors 22
(Note, all protocol
contributors are authors
whose affiliations will be
published in the article)
5b Name and contact information for the trial sponsor 1
5c Role of study sponsor and funders, if any, in study design; collection, management, analysis, and
interpretation of data; writing of the report; and the decision to submit the report for publication,
including whether they will have ultimate authority over any of these activities
1
5d Composition, roles, and responsibilities of the coordinating centre, steering committee, endpoint
adjudication committee, data management team, and other individuals or groups overseeing the trial,
if applicable (see Item 21a for data monitoring committee)
N/A
Introduction
Background and
rationale
6a Description of research question and justification for undertaking the trial, including summary of
relevant studies (published and unpublished) examining benefits and harms for each intervention
3-4; 5-6
6b Explanation for choice of comparators 3
Objectives 7 Specific objectives or hypotheses 4
Trial design 8 Description of trial design including type of trial (eg, parallel group, crossover, factorial, single group),
allocation ratio, and framework (eg, superiority, equivalence, noninferiority, exploratory)
4-5
Methods: Participants, interventions, and outcomes
Study setting 9 Description of study settings (eg, community clinic, academic hospital) and list of countries where
data will be collected. Reference to where list of study sites can be obtained
5
Eligibility criteria 10 Inclusion and exclusion criteria for participants. If applicable, eligibility criteria for study centres and
individuals who will perform the interventions (eg, surgeons, psychotherapists)
5, 9
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3
Interventions 11a Interventions for each group with sufficient detail to allow replication, including how and when they will
be administered
5-7
11b Criteria for discontinuing or modifying allocated interventions for a given trial participant (eg, drug
dose change in response to harms, participant request, or improving/worsening disease)
N/A
11c Strategies to improve adherence to intervention protocols, and any procedures for monitoring
adherence (eg, drug tablet return, laboratory tests)
7, 13
11d Relevant concomitant care and interventions that are permitted or prohibited during the trial 7
Outcomes 12 Primary, secondary, and other outcomes, including the specific measurement variable (eg, systolic
blood pressure), analysis metric (eg, change from baseline, final value, time to event), method of
aggregation (eg, median, proportion), and time point for each outcome. Explanation of the clinical
relevance of chosen efficacy and harm outcomes is strongly recommended
9-15
Participant timeline 13 Time schedule of enrolment, interventions (including any run-ins and washouts), assessments, and
visits for participants. A schematic diagram is highly recommended (see Figure)
8
Sample size 14 Estimated number of participants needed to achieve study objectives and how it was determined,
including clinical and statistical assumptions supporting any sample size calculations
16-18
Recruitment 15 Strategies for achieving adequate participant enrolment to reach target sample size 15
Methods: Assignment of interventions (for controlled trials)
Allocation:
Sequence
generation
16a Method of generating the allocation sequence (eg, computer-generated random numbers), and list of
any factors for stratification. To reduce predictability of a random sequence, details of any planned
restriction (eg, blocking) should be provided in a separate document that is unavailable to those who
enrol participants or assign interventions
8-9
Allocation
concealment
mechanism
16b Mechanism of implementing the allocation sequence (eg, central telephone; sequentially numbered,
opaque, sealed envelopes), describing any steps to conceal the sequence until interventions are
assigned
N/A
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Implementation 16c Who will generate the allocation sequence, who will enrol participants, and who will assign
participants to interventions
8-9, 19-20
Blinding (masking) 17a Who will be blinded after assignment to interventions (eg, trial participants, care providers, outcome
assessors, data analysts), and how
8-9
17b If blinded, circumstances under which unblinding is permissible, and procedure for revealing a
participant’s allocated intervention during the trial
N/A
Methods: Data collection, management, and analysis
Data collection
methods
18a Plans for assessment and collection of outcome, baseline, and other trial data, including any related
processes to promote data quality (eg, duplicate measurements, training of assessors) and a
description of study instruments (eg, questionnaires, laboratory tests) along with their reliability and
validity, if known. Reference to where data collection forms can be found, if not in the protocol
7-8, 9-15
18b Plans to promote participant retention and complete follow-up, including list of any outcome data to
be collected for participants who discontinue or deviate from intervention protocols
15-16
Data management 19 Plans for data entry, coding, security, and storage, including any related processes to promote data
quality (eg, double data entry; range checks for data values). Reference to where details of data
management procedures can be found, if not in the protocol
18
Statistical methods 20a Statistical methods for analysing primary and secondary outcomes. Reference to where other details
of the statistical analysis plan can be found, if not in the protocol
18
20b Methods for any additional analyses (eg, subgroup and adjusted analyses) 18
20c Definition of analysis population relating to protocol non-adherence (eg, as randomised analysis), and
any statistical methods to handle missing data (eg, multiple imputation)
18
Methods: Monitoring
Data monitoring 21a Composition of data monitoring committee (DMC); summary of its role and reporting structure;
statement of whether it is independent from the sponsor and competing interests; and reference to
where further details about its charter can be found, if not in the protocol. Alternatively, an explanation
of why a DMC is not needed
20
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21b Description of any interim analyses and stopping guidelines, including who will have access to these
interim results and make the final decision to terminate the trial
20
Harms 22 Plans for collecting, assessing, reporting, and managing solicited and spontaneously reported
adverse events and other unintended effects of trial interventions or trial conduct
20
Auditing 23 Frequency and procedures for auditing trial conduct, if any, and whether the process will be
independent from investigators and the sponsor
N/A
Ethics and dissemination
Research ethics
approval
24 Plans for seeking research ethics committee/institutional review board (REC/IRB) approval 19
Protocol
amendments
25 Plans for communicating important protocol modifications (eg, changes to eligibility criteria,
outcomes, analyses) to relevant parties (eg, investigators, REC/IRBs, trial participants, trial registries,
journals, regulators)
20
Consent or assent 26a Who will obtain informed consent or assent from potential trial participants or authorised surrogates,
and how (see Item 32)
19-20
26b Additional consent provisions for collection and use of participant data and biological specimens in
ancillary studies, if applicable
N/A
Confidentiality 27 How personal information about potential and enrolled participants will be collected, shared, and
maintained in order to protect confidentiality before, during, and after the trial
18, 20
Declaration of
interests
28 Financial and other competing interests for principal investigators for the overall trial and each study
site
21-22
Access to data 29 Statement of who will have access to the final trial dataset, and disclosure of contractual agreements
that limit such access for investigators
21
Ancillary and post-
trial care
30 Provisions, if any, for ancillary and post-trial care, and for compensation to those who suffer harm
from trial participation
N/A
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Dissemination policy 31a Plans for investigators and sponsor to communicate trial results to participants, healthcare
professionals, the public, and other relevant groups (eg, via publication, reporting in results
databases, or other data sharing arrangements), including any publication restrictions
21
31b Authorship eligibility guidelines and any intended use of professional writers 21
31c Plans, if any, for granting public access to the full protocol, participant-level dataset, and statistical
code
20-21
Appendices
Informed consent
materials
32 Model consent form and other related documentation given to participants and authorised surrogates Supplementary files
Biological
specimens
33 Plans for collection, laboratory evaluation, and storage of biological specimens for genetic or
molecular analysis in the current trial and for future use in ancillary studies, if applicable
N/A
*It is strongly recommended that this checklist be read in conjunction with the SPIRIT 2013 Explanation & Elaboration for important clarification on the items.
Amendments to the protocol should be tracked and dated. The SPIRIT checklist is copyrighted by the SPIRIT Group under the Creative Commons
“Attribution-NonCommercial-NoDerivs 3.0 Unported” license.
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Right For Me: Protocol for a cluster randomised trial of two interventions for facilitating shared decision-making about
contraceptive methods
Journal: BMJ Open
Manuscript ID bmjopen-2017-017830.R1
Article Type: Protocol
Date Submitted by the Author: 08-Sep-2017
Complete List of Authors: Thompson, Rachel; Dartmouth College, The Dartmouth Institute for Health Policy and Clinical Practice Manski, Ruth; Dartmouth College, The Dartmouth Institute for Health
Policy and Clinical Practice Donnelly, Kyla; Dartmouth College, The Dartmouth Institute for Health Policy and Clinical Practice Stevens, Gabrielle; Dartmouth College, The Dartmouth Institute for Health Policy and Clinical Practice Agusti, Daniela; Dartmouth College, The Dartmouth Institute for Health Policy and Clinical Practice Banach, Michelle; Patient Partner Boardman, Maureen; Dartmouth College, Geisel School of Medicine Brady, Pearl; Patient Partner Colon Bradt, Christina; Patient Partner Foster, Tina; Dartmouth College, The Dartmouth Institute for Health Policy
and Clinical Practice Johnson, Deborah; Dartmouth College, Geisel School of Medicine Li, Zhongze; Dartmouth College, Geisel School of Medicine Norsigian, Judy; Stakeholder Partner Nothnagle, Melissa; Brown University, Warren Alpert Medical School Olson, Ardis; Dartmouth College, Geisel School of Medicine Shepherd, Heather; University of Sydney, Psycho-Oncology Cooperative Research Group Stern, Lisa; Planned Parenthood Northern California Tosteson, Tor; Dartmouth College, The Dartmouth Institute for Health Policy and Clinical Practice
Trevena, Lyndal; University of Sydney, School of Public Health Upadhya, Krishna; Johns Hopkins School of Medicine Elwyn, Glyn; Dartmouth College, The Dartmouth Institute for Health Policy and Clinical Practice
<b>Primary Subject Heading</b>:
Patient-centred medicine
Secondary Subject Heading: Reproductive medicine, Obstetrics and gynaecology, Public health, Health services research
Keywords: GYNAECOLOGY, PRIMARY CARE, PUBLIC HEALTH
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Right For Me: Protocol for a cluster randomised
trial of two interventions for facilitating shared
decision-making about contraceptive methods
Rachel Thompson, The Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth College
Ruth Manski, The Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth College
Kyla Z Donnelly, The Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth College
Gabrielle Stevens, The Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth College
Daniela Agusti, The Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth College
Michelle Banach, Patient Partner
Maureen B Boardman, Geisel School of Medicine, Dartmouth College
Pearl Brady, Patient Partner
Christina Colón Bradt, Patient Partner
Tina Foster, The Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth College
Deborah J Johnson, Geisel School of Medicine, Dartmouth College
Zhongze Li, Geisel School of Medicine, Dartmouth College
Judy Norsigian, Stakeholder Partner
Melissa Nothnagle, Warren Alpert Medical School, Brown University
Ardis L Olson, Geisel School of Medicine, Dartmouth College
Heather L Shepherd, Psycho-Oncology Cooperative Research Group, The University of Sydney
Lisa F Stern, Planned Parenthood Northern California
Tor D Tosteson, Geisel School of Medicine, Dartmouth College
Lyndal Trevena, School of Public Health, University of Sydney
Krishna K Upadhya, Johns Hopkins School of Medicine
Glyn Elwyn, The Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth College
Correspondence: Rachel Thompson, [email protected], +1 603 653 0860
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Funding: Research reported in this protocol was funded through a Patient-Centered Outcomes Research Institute
(PCORI) Award (CDR-1403-12221). Apart from requiring adherence to Methodology Standards that specify best
practices in the design and conduct of patient-centred outcomes research, the funder has had no role in study
design; writing of the protocol; or the decision to submit the report for publication. The views presented in this
protocol are solely the responsibility of the author(s) and do not necessarily represent the views of the Patient-
Centered Outcomes Research Institute (PCORI), its Board of Governors or Methodology Committee. The Patient-
Centered Outcomes Research Institute can be contacted at [email protected].
Acknowledgements: We thank Amina Hetu and Nitzy Bustamante for their contribution to the development of
study materials. We thank Shama Alam and Elizabeth Harman for participating in the production of study
interventions. We also thank those who provided valuable feedback on early drafts of the Right For Me decision
aids and other materials, including Amanda Beery, Ann Davis, Rachel Darche, Amanda Dennis, Candace Gibson,
Christina Lachance, Lindsay Smith, Michele Stranger-Hunter, Lawrence Swiader, Christina Warner, Jacki Witt,
Elisabeth Woodhams, and Lauren Zapata.
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ABSTRACT
Introduction: Despite the observed and theoretical advantages of shared decision-making in a range of clinical
contexts, including contraceptive care, there remains a paucity of evidence on how to facilitate its adoption. This
paper describes the protocol for a study to assess the comparative effectiveness of patient- and provider-targeted
interventions for facilitating shared decision-making about contraceptive methods.
Methods and analysis: We will conduct a 2x2 factorial cluster randomised controlled trial with four arms: (1) video
+ prompt card, (2) decision aids + training, (3) video + prompt card and decision aids + training, and (4) usual care.
The clusters will be clinics in the United States that deliver contraceptive care. The participants will be people who
have completed a health care visit at a participating clinic, were assigned female sex at birth, are aged 15 to 49
years, are able to read and write English or Spanish, and have not previously participated in the study. The primary
outcome will be shared decision-making about contraceptive methods. Secondary outcomes will be the
occurrence of a conversation about contraception in the health care visit, satisfaction with the conversation about
contraception, intended contraceptive method(s), intention to use a highly effective method, values concordance
of the intended method(s), decision regret, contraceptive method(s) used, use of a highly effective method, use of
the intended method(s), adherence, satisfaction with the method(s) used, unintended pregnancy, and unwelcome
pregnancy. We will collect study data via longitudinal patient surveys administered immediately after the health
care visit, 4 weeks later, and 6 months later.
Ethics and dissemination: We will disseminate results via presentations at scientific and professional conferences,
papers published in peer-reviewed, open-access journals, and scientific and lay reports. We will also make an
anonymised copy of the final participant-level data set available to others for research purposes.
Registration: ClinicalTrials.gov Identifier NCT02759939
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INTRODUCTION
Background and Rationale
Shared decision-making is the process of health care providers and patients making health decisions together.
While a number of conceptual definitions have been offered (1), the most common considers shared decision-
making a process in which providers and patients exchange information, deliberate about available options
together, and come to agreement on the option to implement (2). Shared decision-making is conceptually distinct
from paternalistic decision-making, which assumes that the patient’s preferences have no place in the decision-
making process, and from informed decision-making, which assumes that the provider’s only legitimate role in the
decision-making process is information provision (2,3).
Proponents of shared decision-making have described it as an “ethical imperative” (4) and the “pinnacle of patient-
centered care” (5). There is also a growing body of evidence of its generally positive impact on patient affective-
cognitive, behavioural, and health outcomes in a range of clinical contexts (6). In contraceptive care, shared
decision-making may represent a strategy for promoting health and wellbeing while safeguarding patient
autonomy, the importance of which is emphasised in key practice guidelines (7,8). For example, shared decision-
making about contraceptive methods may facilitate the prevention of unintended or unwelcome pregnancies by
increasing the likelihood that people choose methods aligned with their individual preferences and values, are
satisfied with the methods they adopt, and use them in a way that takes full advantage of their potential
contraceptive and other benefits. The anticipated gains from shared decision-making about contraceptive methods
may be particularly pronounced for members of minority racial and ethnic groups and people of low
socioeconomic status, who experience significant disparities in contraceptive care and outcomes (9).
Despite the numerous observed and theoretical advantages of shared decision-making, there remains a paucity of
evidence on how to facilitate its adoption. A recent systematic review of interventions for improving the adoption
of shared decision-making by health care providers found that, while interventions targeting patients alone (e.g.,
question prompt lists) or providers alone (e.g., audit and feedback) had some – if modest – positive effects on the
adoption of shared decision-making, effects were generally greater when interventions targeted both groups (10).
However, based on the small number and poor quality of available studies, reviewers were tentative in their
conclusions and advocated for further research to respond to this important knowledge gap. Answering this call,
this paper describes the protocol for a study that will assess the comparative effectiveness of patient- and
provider-targeted interventions for facilitating shared decision-making about contraceptive methods in the health
care visit.
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Objectives
The first objective of this study is to evaluate the effect of a patient-targeted intervention (a video + prompt card
that encourages patients to ask three specific questions in the health care visit) and a provider-targeted
intervention (decision aids + training in their use; see Interventions), on shared decision-making about
contraceptive methods in the health care visit. The second objective is to evaluate the effect of these interventions
on the occurrence of a conversation about contraception in the health care visit, satisfaction with the conversation
about contraception, intended contraceptive method(s), intention to use a highly effective method, values
concordance of the intended method(s), decision regret, contraceptive method(s) used, use of a highly effective
method, use of the intended method(s), adherence, satisfaction with the method(s) used, unintended pregnancy,
and unwelcome pregnancy (see Outcomes and Measures). The third objective is to evaluate the feasibility of the
interventions (operationalised as rates of patient exposure to the interventions) and their acceptability to
patients1.
Research Questions
There are four research questions pertaining to the first study objective: (1) Does implementing the video +
prompt card increase the rate of shared decision-making about contraceptive methods compared to usual care?
(2) Does implementing the decision aids + training increase the rate of shared decision-making about contraceptive
methods compared to usual care? (3) Does implementing the video + prompt card and the decision aids + training
result in greater increases in the rate of shared decision-making about contraceptive methods compared to usual
care than implementing either of the interventions alone? and (4) What patient characteristics and other factors
modify the effect of implementing the interventions on the rate of shared decision-making about contraceptive
methods? Research questions pertaining to the second and third study objectives, as well as study hypotheses, are
available in a supplementary file.
METHODS
Trial Design
We will conduct a 2x2 factorial cluster randomised controlled trial with four arms: (1) video + prompt card, (2)
decision aids + training, (3) video + prompt card and decision aids + training, and (4) usual care. This design will
enable us to assess the effect of the two interventions, both alone and together, as compared to usual care. The
clusters will be clinics (see Study Setting) and participants will be a subset of patients attending these clinics (see
Participants). While a cluster randomised controlled trial requires more participants than would a trial with a
1
We intend to evaluate the feasibility and acceptability of the interventions from the perspectives of health care providers and
other clinic staff in a separate, qualitative study.
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different approach to randomisation, we consider a cluster design most robust to prevent the contamination
possible if the unit of randomisation were to be patients or providers (11).
Study Setting
The trial will take place in 16 clinics in the Northeast United States, permitting the recommended minimum of four
clusters per trial arm to minimise potential confounding from cluster effects (11). Participating clinics may be
primary care and/or reproductive health care clinics but must deliver contraceptive care, which we define as
providing contraceptive methods on site, prescribing or referring people for contraceptive methods, and/or
counselling people about contraceptive methods. Participating clinics must also have sufficient patient flow that
staff are confident to be able to facilitate ten eligible patients, on average, completing a post-visit survey each
week. Within each clinic, contraceptive care may be provided by any person with relevant training (e.g., a
physician, nurse, physician assistant, nurse practitioner, midwife, non-medically-licensed counsellor). Participating
clinics may operate in hospital or community settings, be located in rural or urban areas, be publicly or privately
funded, and be for-profit or not-for-profit. Participating clinics may deliver services in more than one geographic
location but, to minimise contamination, may not employ someone who delivers contraceptive care in another
participating clinic and may not employ a study investigator. Participating clinics will receive monetary
compensation for the time expended by clinic staff on data collection and other administrative activities related to
their role in the study. A list of participating clinics may be requested.
Interventions
Video + Prompt Card (Patient-Targeted Intervention)
We developed a brief video intended to be viewed by patients in the clinic immediately before the health care
visit. The video was designed to enhance patients’ motivation, skills, and self-efficacy to ask their providers three
questions in the health care visit: (1) What are my options? (2) What are the possible pros and cons of those
options? and (3) How likely are each of those pros and cons to happen to me? Earlier iterations of these questions2
increased shared decision-making when used by unannounced standardised patients in a primary care setting in
Australia (12) and were the focus of the AskShareKnow program, a multi-pronged intervention that was feasible to
implement in a reproductive and sexual health care setting in Australia and acceptable to patients (13). The video
was adapted from a four-minute video that comprised one component of the AskShareKnow program (13). Our
adaptation features a patient sharing a personal account of her experiences of health care, communicating the
2
The first iteration was: (1) What are my options? (2) What are the possible benefits and harms of those options? and (3) How
likely are the benefits and harms of each option to occur? (12). The second iteration was: (1) What are my options? (2) What are
the possible benefits and harms of those options? and (3) How likely are each of those benefits and harms to happen to me?
(13).
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benefits of asking questions, normalising challenges associated with asking questions, and encouraging people to
ask the three target questions. The format and content of the adaptation responded to patient and stakeholder
perspectives solicited via discussions among the research team (which includes patient partners and stakeholder
representatives), focus groups with patients, and consultation with the patient featured in the adaptation, who has
since joined our research team. We developed versions of the video in English and Spanish, each with and without
on-screen captions. We will supply clinics with tablet computers programmed to view the videos and headphones.
We also developed a small prompt card intended to be distributed to patients who view the video. The card was
designed to remind patients of the three questions presented in the video. The prompt card was adapted from a
refrigerator magnet that comprised another component of the AskShareKnow program (13). Again, we developed
versions of the prompt card in English and Spanish. We will supply clinics with the prompt cards and display stands.
Decision Aids + Training (Provider-Targeted Intervention)
We developed seven one-page decision aids on contraceptive methods intended to be used by providers with
patients during the health care encounter. There are decision aids on long-acting reversible contraceptive
methods, short-acting reversible methods, barrier methods, natural methods, permanent methods, and
emergency methods, as well a decision aid that provides an overview of these six categories of contraceptive
methods. The decision aids were designed to help providers facilitate shared decision-making about contraceptive
methods in the health care visit. The format of the decision aids was adapted from that used in Option GridTM
decision aids for clinical encounters, which have been found to increase shared decision-making in osteoarthritis
care (14) and to be acceptable to physicians (15). We engaged patients and stakeholders in developing the decision
aids, including via a survey of patients and contraceptive care providers (16), patient focus groups, and review of
decision aid iterations by patient partners and stakeholder representatives. We developed versions of the
decisions aids in English and Spanish. We will supply clinics with tear-pads of the decision aids and display stands.
We also developed a five-minute training video and accompanying written guidance intended to be viewed by
providers before beginning to use the decision aids (and as frequently as desired thereafter). The training video
and frequently asked questions were designed to enhance providers’ motivation, skills, and self-efficacy to use the
decision aids to facilitate shared decision-making in the health care visit. The content of the training video was
informed by the Theoretical Domains Framework (17,18), which was devised to guide implementation research
that involves health care provider behaviour change. The video features an Obstetrician-Gynaecologist, Nurse
Practitioner, and patient representative explaining how decision aids can support the delivery of quality health
care and providing guidance on using the decision aids with patients. The written guidance reinforces and
elaborates on training video content. We will host the training video and frequently asked questions on the study
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website. One or more clinic representatives will be charged with encouraging and enabling relevant health care
providers in the clinic to review the training video and written guidance.
Implementation of Interventions
The strategies we developed to support adoption of the interventions purposefully omitted elements difficult to
scale (e.g., face-to-face training by intervention developers, periodic feedback on rates of patient exposure to the
interventions) to maximise the ecological validity of study findings. For the video and prompt card, we developed a
set of presentation slides for clinic staff that provides guidance on their objectives and implementation. The slide
deck will be hosted on the study website, along with a preview of the video and prompt card. One or more clinic
representatives will be charged with encouraging and enabling others in the clinic to review the slide deck. For the
decision aids and training, we also developed a set of presentation slides for clinic staff that provides guidance on
their objectives and implementation. The slide deck will be hosted on the study website. Again, one or more clinic
representatives will be charged with encouraging and enabling others in the clinic to review the slide deck. To
further approximate real-world conditions, we will not prevent clinics from implementing concomitant
interventions or care during the study.
Data Collection
We will collect study data via longitudinal patient surveys administered immediately after the index health care
visit (T1), 4 weeks (i.e., 28 days) after the index health care visit (T2), and 6 months (i.e., 182 days) after the index
health care visit (T3) (see Figure 1). Participants may elect to complete surveys in English or Spanish. The T1 survey
will be administered in clinics using tablet computers and the Qualtrics online survey platform (19). At the end of
the T1 survey, we will invite a subset of participants (see Participants) to give permission to be re-contacted for the
T2 and T3 surveys. Participants aged 20 years and older may elect to complete these surveys online (with email
communication) or on paper (with postal mail communication). Participants aged under 20 years may only elect to
complete these surveys online (with email communication) to safeguard their privacy. A unique password will be
used to link participant responses across surveys. Copies of the surveys may be requested.
Insert Figure 1 here
We have devised several strategies to maximise data quality. We chose to collect data via surveys rather than
interviews given the vulnerability of the topic area to social desirability bias (20). For the T1 survey, which will be
administered in clinics and collect data on participants’ care experiences and evaluations, we elected to use an
online survey completed via tablet computer to ensure no handling of surveys by clinic staff and thus reinforce the
confidentiality of responses. The study information sheet also reassures participants that no health care providers
from participating clinics will have access to identified participant-level data. For all surveys, we used programmed
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or instructional skips to ensure that participants will be asked only relevant questions, thereby minimising survey
fatigue. In the online surveys, we also implemented additional data quality strategies, such as pop-up messages
that notify participants of missed questions and invite them to respond prior to proceeding to the next page.
We will also administer the T1, T2, and T3 surveys to a group of patients who attend participating clinics before we
begin the trial. This ‘pilot’ data collection will replicate the trial data collection and thus, allow clinic staff time to
become proficient in data collection processes. A further advantage of this pilot data collection is that we can
assess equivalence between clinics in the usual rate of shared decision-making about contraceptive methods,
adopt stratified assignment of clinics to trial arms if warranted (see Assignment), and statistically adjust for the
usual rate of shared decision-making in relevant data analyses.
Assignment
Each clinic will be assigned to one of the four trial arms using permuted-block randomisation with an equal
allocation ratio to achieve balance in the number of clinics per trial arm. Should we observe non-equivalence
between clinics in the rate of shared decision-making about contraceptive methods during the pilot data collection
period, we will adopt stratified permuted-block randomisation. Specifically, we will rank clinics according to the
rate of shared decision-making and construct four strata based on this ranking, with one clinic assigned to each
trial arm in each stratum. The study statistician (TDT) and statistical analyst (ZL) will generate the allocation
sequence and assign clinics to trial arms. Due to the study design, it is not feasible to blind clinic staff, study
participants, or researchers to the trial arm to which each clinic has been assigned.
Participants
People who have completed a health care visit at a participating clinic, were assigned female sex at birth, are aged
15 to 49 years, are able to read and write English or Spanish, and have not previously participated in the study will
be eligible for the T1 survey. People who have not completed a visit at a participating clinic during the study period
(including a patient's parent or a person acting as a patient’s legal proxy), were not assigned female sex at birth,
are aged under 15 or over 49 years, are unable to read and write English or Spanish, or have previously
participated in the study will be ineligible for the T1 survey. To enable us to answer study research questions
without unnecessary participant burden, additional eligibility criteria will be imposed for the T2 and T3 surveys.
People who completed the T1 survey, experienced a contraceptive conversation in the health care visit, and
intended to use one or more contraceptive methods following the visit (see Outcomes and Measures) will be
eligible for the T2 and T3 surveys. People are not required to have completed the T2 survey to be eligible for the T3
survey.
Outcomes and Measures
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We consulted with patients and other stakeholders in the process of selecting study outcomes. We prioritised the
inclusion of patient-centred outcomes, including participants’ perceptions of the values concordance of their
intended contraceptive method(s), decision regret pertaining to their intended contraceptive method(s), and
satisfaction with the contraceptive method(s) used. To maximise the utility of study results for different audiences
and purposes, we also elected to include a small number of more conventional, public health-oriented outcomes,
such as use of a highly effective contraceptive method (21). All primary and secondary study outcomes are
presented in Table 1 and elaborated below.
To maximise data quality, we selected measures for the primary and secondary outcomes based on their brevity,
readability, availability in English and Spanish, psychometric properties, prior use in other studies or population-
level surveys, and use of patient-centred language and tone. Where we identified a suitable measure in English
that was not available in Spanish, we arranged for it to be translated. Where we could not identify a suitable
measure, we developed or adapted one in English and arranged for it to be translated.
Table 1. Outcomes and Timing of Measurement
T1 Survey T2 Survey T3 Survey
Conversation about contraception ●
Shared decision-making about contraceptive methods ●
Satisfaction with conversation about contraception ●
Intended contraceptive method(s) ●
Intention to use a highly effective contraceptive method ●
Values concordance of intended contraceptive method(s) ● ● ●
Decision regret about intended contraceptive method(s) ● ●
Contraceptive method(s) used ● ●
Use of a highly effective contraceptive method ● ●
Use of intended contraceptive method(s) ● ●
Adherence to contraceptive method(s) used ● ●
Satisfaction with contraceptive method(s) used ● ●
Unintended pregnancy (pregnancy timing preferences) ●
Unintended pregnancy (pregnancy seeking) ●
Unwelcome pregnancy ●
Primary Outcome
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Shared decision-making about contraceptive methods We will measure shared decision-making
about contraceptive methods in the health care visit using the three-item CollaboRATE (22,23). CollaboRATE was
developed in consultation with end users (23) and assesses people’s perceptions of the extent to which their
health care provider(s) shared information, elicited their preferences, and ensured their preferences were
integrated as decisions were made. We will use the version of CollaboRATE with a five-point response scale and
adopt the binary scoring approach (22). When used in this way in an experimental validation study, CollaboRATE
demonstrated concurrent validity via a strong, positive correlation with the 9-Item Shared Decision Making
Questionnaire (SDM-Q-9; (24)) and a moderate, positive correlation with the five-item Doctor Facilitation subscale
of the Perceived Involvement in Care Scale (PICS; (25)) (22). CollaboRATE also demonstrated discriminative validity,
intra-rater reliability, and sensitivity to change (22). Because the CollaboRATE items are not condition-specific, we
will use a customised opening statement to orientate participants to the conversation about contraception they
experienced in the health care visit.3
Secondary Outcomes
Conversation about contraception We will measure whether participants experienced a conversation
about contraception in the health care visit using a self-developed item. Due to divergent perspectives on the
circumstances under which a contraceptive conversation is indicated, we will report this outcome among (a) all
participants, (b) all participants except those not at risk of unintended pregnancy (see Other Data for definition
and measurement), and (c) all participants except those not at risk of unintended pregnancy and those who
reported that they did not want or need to talk about contraception.
Satisfaction with conversation about contraception We will measure participants' satisfaction with
the conversation about contraception in the health care visit using an item adapted from Weisman et al. (26).
Intended contraceptive method(s) We will measure what, if any, contraceptive method(s)
participants intend to use in the next four weeks using a self-developed checklist of 20 methods. The checklist
specifies common and brand names for some methods, encourages participants to review explanatory information
about the methods if unsure, and allows participants to select multiple methods or select “none of these”. We will
report this outcome among (a) all participants, (b) all participants except those not at risk of unintended pregnancy
(see Other Data for definition and measurement), and (c) all participants except those not at risk of unintended
pregnancy and those who reported that they did not want or need to use a birth control method.
3
To enhance the usefulness of data for future research, participants who did not experience a contraceptive conversation will
be asked to complete CollaboRATE with reference to the health care visit in general.
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Intention to use a highly effective contraceptive method We will use data on participants’ intended
contraceptive method(s) to derive a variable that represents whether they intend to use at least one highly
effective contraceptive method in the next four weeks. We consider highly effective contraceptive methods to
comprise the copper intrauterine device (IUD), the hormonal IUD, the contraceptive implant, female sterilisation,
and male sterilisation, all of which have a typical-use unintended pregnancy rate of <1% in the first year of use
(27). We will report this outcome among (a) all participants, (b) all participants except those not at risk of
unintended pregnancy (see Other Data for definition and measurement), and (c) all participants except those not
at risk of unintended pregnancy and those who reported that they did not want or need to use a birth control
method.
Values concordance of intended contraceptive method(s) We will measure participants' perceptions
of the values concordance of their intended contraceptive method(s) (i.e., the degree of alignment between the
method(s) and their individual values and preferences) using the self-developed, single-item Measure of Alignment
of Choices (MATCH). MATCH contains an opening statement that orients the participant to the contraceptive
method(s) of interest and then asks either “How confident are you that this method is right for you?” or “How
confident are you that these methods are right for you?”. When we administer this measure at T2 and T3, we will
remind participants of their nominated intended contraceptive method(s).
Decision regret about intended contraceptive method(s) We will measure participants' feelings of
decision regret about the contraceptive method(s) they intended to use using an adaptation of the five-item
Decision Regret Scale (28,29). When we administer this measure at T2 and T3, we will remind participants of their
nominated intended contraceptive method(s).
Contraceptive method(s) used We will measure what, if any, contraceptive method(s) participants
used in the last four weeks using an adaptation of the checklist used to assess intended contraceptive method(s).
Use of a highly effective contraceptive method We will use data on the contraceptive method(s)
participants used to derive a variable that represents whether they used at least one highly effective contraceptive
method in the last four weeks.
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Use of intended contraceptive method(s) We will use data on participants’ intended contraceptive
method(s) and the contraceptive method(s) they used to derive a variable that represents whether participants
used their intended contraceptive method(s) in the last four weeks.4
Adherence to contraceptive method(s) used We will measure participants' adherence to the
contraceptive method(s) they used in the last four weeks using the self-developed, 21-item Adherence to Birth
Control (ABC) measure.
Satisfaction with contraceptive method(s) used We will measure participants' satisfaction with the
contraceptive method(s) they used in the last four weeks using a self-developed item. We will use a slightly
modified version of this item to measure satisfaction among participants who reported that they used none of the
listed contraceptive methods in the last four weeks.
Unintended pregnancy (pregnancy timing preferences) We will measure participants’ experience of
one or more unintended pregnancies, as defined by their pregnancy timing preferences, after the health care visit.
For each pregnancy experienced after the health care visit, we will measure the pregnancy timing preferences
participants’ held immediately before conception using an item adapted from the Pregnancy Risk Assessment
Monitoring System (PRAMS) Phase 7 questionnaire (30). We will classify participants either as having experienced
unintended pregnancy or not having experienced unintended pregnancy based on their responses.
Unintended pregnancy (pregnancy seeking) We will measure participants’ experience of one or more
unintended pregnancies, as defined by their pregnancy seeking, after the health care visit. For each pregnancy
experienced after the health care visit, we will measure participants’ pregnancy seeking immediately before
conception using an item adapted from Kavanaugh and Schwarz (31). We will classify participants either as having
experienced unintended pregnancy or not having experienced unintended pregnancy based on their responses.
Unwelcome pregnancy We will measure participants’ experience of one or more unwelcome
pregnancies after the health care visit. For each pregnancy experienced after the health care visit, we will measure
participants’ feelings on learning about the pregnancy using an item adapted from the PRAMS Phase 7
questionnaire (30). We will classify participants either as having experience unwelcome pregnancy or not having
experienced unwelcome pregnancy based on their responses.
4
For participants who complete the T2 survey on the target completion date, the four-week recall period adopted for the
assessment of contraceptive method(s) used in this survey will align with the four-week timeframe adopted in the assessment
of intended contraceptive method(s) in the T1 survey.
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Process Outcomes
Intervention exposure and question asking We will measure participants’ exposure to the video,
receipt of the prompt card, and use of the three questions in the health care visit using five items adapted from
Shepherd et al. (13), administered at T1. We will measure participants’ exposure to one or more of the decision
aids (including nature and timing of exposure) using a self-developed item administered at T1.
Acceptability of interventions We will measure the acceptability of the video, prompt card, and
decision aid(s) to participants using three self-developed items administered at T1.
Exposure to concomitant interventions We will measure exposure to other information on
contraception on the day of the health care visit using a self-developed item administered at T1.
Other Data
Visit date The T1 survey will automatically record the date and time of survey completion (and thus,
date of the health care visit) for each participant. We will use these data to distinguish between pilot and trial
participants.
Clinic We will measure the clinic in which each participant had their health care visit (and thus, trial
arm) using a self-developed item measure administered at T1. The T1 survey will also automatically record the
Internet Protocol (IP) address of the tablet computer on which the T1 survey is completed. We will use these data
to review the accuracy of patient-reported data on clinic, managing inconsistencies on a case-by-case basis.
Previous contraceptive method(s) We will measure what, if any, contraceptive method(s) participants
used in the four weeks before the health care visit using an adaptation of the checklist used to assess intended
contraceptive method(s).
Pregnancies We will measure the number of pregnancies participants experienced after the health
care visit using a self-developed item administered at T3. When we administer this item, we will remind
participants of the date of their health care visit.
Explanatory questions and risk of unintended pregnancy At T1, we will ask participants who did not
experience a conversation about contraception to report one or more reasons for this from a self-developed list.
At T1, we will also ask participants who do not intend to use any of the contraceptive methods in the checklist to
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report one or more reasons for this from a self-developed list. We will use the self-reported data participants
provide in response to these questions to identify those not at risk of unintended pregnancy at the time of the
health care visit. We will consider participants to be not at risk of unintended pregnancy if they report that they
are pregnant, are trying to get pregnant, do not have ovaries or a uterus, have entered menopause, are infertile, or
do not plan to have vaginal sex with a person that produces sperm.
At T2 and T3, we will ask participants who had not used their intended contraceptive method(s) in the last
four weeks to report the reason(s) for this in an open-ended question. When administering the ABC measure at T2
and T3, we will provide a free text box after the adherence question(s) for each method to enable participants to
elaborate on their response(s). We will also provide a free text box at the end of the T2 and T3 surveys to enable
participants to share any other information they choose.
Participant and visit characteristics We will measure several participant and visit characteristics at T1.
We will measure participants’ age, ability to read and write English or Spanish, sex assigned at birth (32), visit
completion, previous study participation, and clinic (see above) to confirm study eligibility. We will also measure
participants’ current gender identity (32), race, ethnicity, and educational attainment (33), health insurance
coverage (34), and health literacy (35–39). We will measure participants’ reproductive history (i.e., number of
pregnancies, births, abortions, and miscarriages) using four self-developed items. We will also document the
language in which each participant completed the survey.
Recruitment and Retention
Prospective participants will be made aware of the opportunity to take part in the study on the day of their health
care visit via study posters and information sheets displayed in participating clinics and/or through communication
with clinic staff. We have adopted several strategies for achieving adequate participant enrolment and maximising
participant retention, informed by both reviews of empirical evidence (40,41) and patient and stakeholder
perspectives. To help achieve adequate participant enrolment, we developed engaging recruitment materials that
use a study name and branding designed with patient input. We adopted inclusive eligibility criteria (see
Participants) and elected to allow participation without a commitment to complete all three surveys. We will also
compensate participants with a $10 gift card for completing the T1 survey.
To maximise retention of participants enrolled in the study and minimise nonresponse error, we adopted both
online and paper completion modes for the T2 and T3 surveys for participants aged 20 years and older (see Data
Collection). We will provide people who elect to complete the surveys on paper with an addressed, reply-paid
envelope to facilitate survey return. We elected to administer the sending and receiving of T2 and T3 surveys from
the research institution, thereby removing the responsibility from clinic staff. We have also developed survey
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invitation and reminder schedules customised to the survey mode. For the online completion mode, we will send
two daily email reminders to participants who have not completed the T2 or T3 survey and will also send an email
prompt one week in advance of the T2 survey invitation to encourage completion on the target date (see Figure 2).
For the paper completion mode, we will send a similar mail prompt one week in advance of the T2 and T3 survey
invitations, but will not send daily mail reminders due to anticipated variation in mail delivery times and the
potential for such reminders to arrive simultaneously or overlap (see Figure 2). Again, we will compensate
participants with a $10 gift card for completing each of the T2 and T3 surveys.
Insert Figure 2 here
Sample Size and Power
Sample Size
Each of the 16 participating clinics will be expected to facilitate ten eligible patients completing the T1 survey per
week on average. Thus, we estimate that 1,040 participants per trial arm will complete the T1 survey during the
trial period. We estimate that 728 participants per trial arm (70%) will experience a conversation about
contraception and thus comprise the sample for the primary outcome analysis. We estimate that 70% of the
participants who experience a contraceptive conversation will be eligible for and agree to be invited to complete
the T2 and T3 surveys. Of these, we estimate that 80% will complete the T2 survey and that 70% will complete the
T3 survey (see Figure 3).
Insert Figure 3 here
Additionally, we estimate that, in each clinic, 130 pilot participants will complete the T1 survey, 91 pilot
participants will experience a conversation about contraception, and 51 and 45 pilot participants will complete the
T2 and T3 surveys, respectively.
Power
The study was powered to answer Research Questions 1, 2, and 3 (see Research Questions). As outlined above, we
estimate a sample size of 728 participants per trial arm for the primary outcome analysis (see Figure 3). We base
our detectable difference calculations on tests comparing the proportion of participants who experience shared
decision-making about contraceptive methods (the primary outcome) between trial arms, assuming a proportion
of 66% in the usual care arm (42). Given the fixed number of clusters per trial arm and the estimated sample size,
we determine a detectable increase of 16% (from 66% to 82%) in the proportion of participants who experience
shared decision-making, based on a z-test test comparing two proportions with clustered data, with an estimated
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intra-cluster correlation coefficient (ICC) of 0.03 (43), a two-sided significance level of 5%, and a power of 80%. If
we apply a Bonferroni correction for the three possible comparisons versus the usual care arm to retain a nominal
family-wise significance level of 5%, we can detect an increase of 18.1% in the proportion of participants who
experience shared decision-making. These calculations show that we will have a sufficient sample size to detect
meaningful changes in shared decision-making. All calculations were done using the PASS 2008 sample size
package (44) based on standard methods (45).
Data Management and Analysis
Data Management
The surveys will collect direct and indirect participant identifiers. To minimise risks to participant privacy, only
three people from the study team (the principal investigator, the project manager, and the data manager) will be
allowed to access highly identifying participant-level data and files. The people in these roles will be responsible for
sending and receiving T2 and T3 surveys and associated correspondence; entering, cleaning, and recoding data;
and securely storing and transferring identified participant-level data and files. They will also be responsible for
deleting or destroying highly identifying information (i.e., participant names, email addresses, and mailing
addresses) from all documents and files upon the completion of the study and otherwise anonymising data prior to
sharing it. Our anonymisation process will take into account 28 direct and indirect patient identifiers (46). To
maximise the utility of study data, we will store both identified data (excluding highly identifying information) and
anonymised data indefinitely. A comprehensive data management plan may be requested.
Data Analysis
Analysis Plan A data analysis plan is available in a supplementary file.
Protocol Nonadherence While we will report rates of protocol nonadherence (derived from patient
reports of exposure to the intended intervention(s)), the analyses for Research Questions 1, 2, and 3 will be
conducted by intention to treat. Patient exposure to the interventions may comprise one factor included in the
analyses for Research Question 4.
Treatment of Missing Data We will report rates of and reasons for missing data, whether due to
unanswered questions or participant attrition. In the treatment of missing data, we will assess (and report)
whether participants with missing data differ systematically from others on background or other characteristics,
clinic, or trial arm, and consider this in the interpretation of findings. Depending on the findings of this assessment,
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we will adopt listwise deletion of missing cases with adjustments for covariates associated with missingness,
multiple imputation, or equivalent methods (e.g., maximum likelihood estimates in mixed models).
Study Limitations
Three potential limitations warrant discussion. First, we chose to implement the trial in 16 clinics in reasonable
proximity to our research institution. This minimised costs and thus enabled us to enrol the recommended
minimum number of clusters per trial arm (11). However, potential confounding from cluster effects may have
been further minimised by a greater number of clinics and the racial, ethnic, and linguistic diversity of participants
enhanced by greater geographical diversity in clinics. Second, we chose to collect minimal contact information for
participants eligible for the T2 and T3 surveys. Given the sensitivity of the topic, we considered this important for
preventing both barriers to recruitment and risks to participants’ privacy. However, this simultaneously limited
opportunities for participant contact and may compromise retention. Third, while clinic estimates of the total
number of eligible patients during the study period will enable calculation of the participation rate, a lack of
information on the characteristics of all eligible patients will preclude conclusions about sample
representativeness.
ETHICS AND DISSEMINATION
Research Ethics Approval
Institutional Review Board approval for the study was granted by the Committee for the Protection of Human
Subjects (CPHS) at Dartmouth College (Study #00028721), as well as by an external Institutional Review Board
affiliated with one participating clinic.
Consent
When adopting a cluster randomised study design, it is not usually feasible to obtain participants’ consent to
randomisation (11,47,48). Instead, consent to randomisation is typically provided by a surrogate decision-maker at
the cluster level (47,48). We will obtain agreement to randomisation from a representative from each clinic and
will seek eligible patients’ informed consent to participate in data collection for the study.
To eliminate barriers to participation and minimise risks to participants, we were granted Institutional Review
Board approval for a waiver of documented informed consent and for a waiver of parental consent for participants
aged 15-17 years. In our modified consent process, clinic staff will provide potentially eligible patients with a tablet
computer (proactively and/or upon request) that displays an electronic version of the study information sheet. This
information sheet enables patients to self-assess their eligibility for the study, become informed about the study
purposes, processes, benefits, and risks, and elect whether to participate in the study. Patients who select ‘Yes’ in
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response to the question ‘Now that you have read this information, do you agree to participate in this study?’ that
follows this electronic information sheet will be taken as having given informed consent and will proceed to the T1
survey immediately. Paper copies of the information sheet will also be available in participating clinics. The study
information sheet may be requested.
Privacy and Confidentiality
We have adopted several strategies to protect the privacy of participants. We were granted Institutional Review
Board approval for a waiver of documented informed consent (see Consent) and will administer the provision of
participant compensation from the research institution so that no information on participants will be stored in any
clinic. The waver of documented informed consent also means that patients can participate in the study without
ever providing their name or contact details if they are willing to forego compensation. Participants aged under 20
years may only elect to complete the T2 and T3 surveys online (with email communication) to safeguard their
privacy. Participants aged 20 years and older who elect to complete the T2 and T3 surveys on paper will receive
(and send) all associated correspondence in unbranded envelopes. We will use an otherwise meaningless random
code generated during T1 survey completion to link participant surveys across the three time points. Finally, we
have restricted access to identified participant-level data and files (see Data Management).
Monitoring
Following internal institutional consultation, we determined that a formal Data and Safety Monitoring Board
(DSMB) was unnecessary due to the minimal risks associated with study participation and the focus of the study on
outcomes other than mortality or morbidity (49). We anticipate no harms arising from implementation of the
interventions. If we become aware of any harms or other adverse events, either through study data or other
avenues, we will review and address these according to standard institutional processes in consultation with the
relevant Institutional Review Board(s). We will also file regular reports on trial progress and any adverse events
with the Institutional Review Boards. Although we intend to conduct some analyses of pilot data collected before
assigning clinics to trial arms, we do not anticipate undertaking any interim analyses of trial outcome data and
have not devised any stopping guidelines.
Dissemination Policy
Full Protocol
Members of the scientific community and the public can access the full study protocol via this open access
publication. Substantive modifications to this protocol will be communicated to the relevant staff at participating
clinics during regular communications. Substantive modifications to this protocol will also be communicated to
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others via study meetings, written summaries, published modifications to the trial profile at clinicaltrials.gov,
and/or via statements in scientific papers or reports arising from the study.
Study Findings
We will disseminate study findings through various channels. We will deliver presentations at scientific
conferences and professional meetings and publish papers in peer-reviewed, open-access journals. We will adhere
to International Committee of Medical Journal Editors (ICMJE) recommendations pertaining to authorship roles
and responsibilities in papers arising from this study (50). We will also prepare a final report of study findings and
accompanying summary for lay audiences. We will disseminate these documents to participants and participating
clinics, health care providers, policy makers, the public, and other relevant groups. Wherever possible, we will
make documents describing study findings available via the study website (www.rightforme.org). We do not intend
to draw on the services of professional writers for the development of presentations, papers, or reports.
Data Sharing Statement
To facilitate transparency and maximise the usefulness of data collected in the study, we will make an anonymised
copy of the final participant-level data set and essential analysis syntax available to others for research purposes
via data sharing on request and/or a digital repository, before October 2018.
Declaration of Interests
All authors have completed the ICMJE uniform disclosure at www.icmje.org/coi_disclosure.pdf. RT reports a grant
from PCORI during the conduct of the study and non-financial support from PCORI outside the submitted work. RT
also reports ownership of copyright in several patient decision aids and a role as an editor of the text, ‘Shared
Decision Making in Health Care’ but has not received any personal income connected to this ownership or role.
RM, KZD, GS, DA, TF, DJJ, ZL, ALO, and TDT report a grant from PCORI during the conduct of the study. MB and KKU
report personal fees from Dartmouth College during the conduct of the study. MBB reports a grant from PCORI
and other payments from Dartmouth College during the conduct of the study. PB reports personal fees and non-
financial support from Dartmouth College during the conduct of the study and non-financial support from
Dartmouth College outside the submitted work. CCB reports personal fees and non-financial support from
Dartmouth College during the conduct of the study. JN reports personal fees from Dartmouth College during the
conduct of the study and non-financial support from PCORI outside the submitted work. MN reports personal fees
and other payments from Dartmouth College during the conduct of the study. MN also reports a role as a health
care provider and clinic representative in a clinic participating in the study. HLS reports a role as a developer of the
AskShareKnow program intervention components and related survey items that were adapted for use in the study
but has not received any personal income connected to this role. LFS reports personal fees from Dartmouth
College during the conduct of the study; grants from Bayer Health Care Inc., Teva Pharmaceuticals, and Gilead
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Pharmaceuticals Inc. outside the submitted work; and personal fees from Hologic Inc. outside the submitted work.
LT reports other payments from Dartmouth College during the conduct of the study. GE reports a grant from
PCORI during the conduct of the study and personal fees from Emmi Solutions LLC, Washington State Health
Department, Oxford University Press, the National Quality Forum, SciMentum LLC, EBSCO Health, &think LLC, and
ACCESS Federally Qualified Health Centers outside the submitted work. GE also reports ownership of copyright in
the CollaboRATE measure of shared decision-making, the Observer OPTION measure of shared decision-making,
and several patient decision aids.
ROLES AND RESPONSIBILITIES
Protocol Contributors
RT, KZD, and GE conceived the study. RT, RM, KZD, GS, DA, MB, MBB, PB, CCB, TF, DJJ, ZL, JN, MN, ALO, HLS, LFS,
TDT, LT, KKU, and GE contributed to the design of the study (e.g., selection of interventions, development of
participant and clinic eligibility criteria, selection of assignment approach, selection of study outcomes) and/or the
development of study interventions, recruitment materials (e.g., study posters, information sheets), and data
collection materials and protocols (e.g., patient surveys, survey invitation and reminder schedules). RT drafted the
manuscript. RT, RM, KZD, GS, DA, MB, MBB, PB, CCB, TF, DJJ, ZL, JN, MN, ALO, HLS, LFS, TDT, LT, KKU, and GE
contributed to revisions of the draft and gave approval for publication of the manuscript.
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FIGURE LEGENDS
Figure 1. Data collection schematic
Figure 2. Survey invitation and reminder schedule
Figure 3. Estimated sample sizes per trial arm
*Estimates of the total number of patients eligible for the study will be provided by clinics based on routinely collected data
^Sample for primary outcome analyses
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Right For Me: Protocol for a cluster randomised trial of two interventions for facilitating shared decision-making about contraceptive methods
Study Objectives, Research Questions, Hypotheses, and Analytic Plan
Objectives Research Questions Hypotheses Analytic Plan
The first objective of this study is to evaluate the effect of (1) a video + prompt card that encourage patients to ask three specific questions in the health care visit, and (2) decision aids + training for health care providers in their use, on shared decision-making about contraceptive methods in the health care visit.
1 Does implementing the video + prompt card increase the rate of shared decision-making about contraceptive methods compared to usual care?
We hypothesise that implementing the video + prompt card will increase the rate of shared decision-making about contraceptive methods compared to usual care.
The primary outcome for the analysis is shared decision-making about contraceptive methods, a binary variable. To account for the cluster randomized design, the analysis will use random effects logistic regression for binary outcome variables as implemented in SAS PROC GLIMMIX, with a random intercept for clinic. The analysis will adjust for the clinic-level pre-existing rate of shared decision-making and any other participant characteristics that differ across trial arms. Contrasts between group rates will be performed using the model results to address research questions 1-3.
2 Does implementing the decision aids + training increase the rate of shared decision-making about contraceptive methods compared to usual care?
We hypothesise that implementing the decision aids + training will increase the rate of shared decision-making about contraceptive methods compared to usual care.
3 Does implementing the video + prompt card and the decision aids + training result in greater increases in the rate of shared decision-making about contraceptive methods compared to usual care than implementing either of the interventions alone?
We hypothesise that implementing the video + prompt card and the decision aids + training will result in greater increases in the rate of shared decision-making about contraceptive methods compared to usual care than implementing the video + prompt card alone or the decision aids + training alone.
4 What patient characteristics and other factors modify the effect of implementing the interventions on the rate of shared decision-making about contraceptive methods?
This heterogeneity of treatment effects (HTE) analysis is exploratory (i.e., hypothesis generating) and thus no a priori hypotheses for this research question have been developed.
We will use the same modelling techniques to assess modifiers of the shared decision-making rate effects seen for research questions 1-3 by fitting interaction terms with the intervention group variables. The modifiers considered will be age, gender identity, health insurance, health literacy,
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educational attainment, ethnicity, race, exposure to interventions (three variables), exposure to other interventions (one variable), and pre-existing shared decision-making.
In reporting the modifier analyses, p-values will be shown adjusted for multiple comparisons.
The second objective is to evaluate the effect of these interventions on several other outcomes (see Outcomes and Measures).
For each of the secondary outcomes:
5 Does implementing the video + prompt card increase or decrease (as relevant) the [rate/level] of [secondary outcome] compared to usual care?
We hypothesise that implementing the video + prompt card will increase the rate of conversation about contraception, optimal satisfaction with the conversation about contraception, optimal values concordance of intended contraceptive method(s), use of intended contraceptive method(s), optimal adherence to contraceptive method(s) used, optimal satisfaction with contraceptive method(s) used; decrease the level of decision regret; and decrease the rate of unintended pregnancy (pregnancy timing preferences), unintended pregnancy (pregnancy seeking), and unwelcome pregnancy compared to usual care.
Analyses pertaining to the secondary outcomes of intended contraceptive method(s), intention to use a highly effective contraceptive method, contraceptive method(s) used, and use of a highly effective contraceptive method are exploratory and thus no a priori hypotheses for these secondary outcomes have been developed.
We will conduct separate analyses to answer these research questions for each of the 14 secondary outcomes.
We will use a random effects regression for either categorical or continuous outcomes with a random intercept for clinic to account for clustering. The analysis will adjust for participant characteristics that differ across trial arms. Contrasts between group rates or means will be performed as with the primary outcome.
For analyses pertaining to the secondary outcome, Conversation About Contraception, we will use three denominators: (a) all participants, (b) all participants except those not at risk of unintended pregnancy, and (c) all participants except those not at risk of pregnancy and those who reported that they did not want or need to talk about contraception.
6 Does implementing the decision aids + training increase or decrease (as relevant) the [rate/level] of [secondary outcome] compared to usual care?
We hypothesise that implementing the decision aids + training will increase the rate of conversation about contraception, optimal satisfaction with the conversation about contraception, optimal values concordance of intended contraceptive method(s), use of intended contraceptive method(s), optimal adherence to contraceptive method(s) used, optimal satisfaction with contraceptive method(s) used; decrease the level of decision regret; and decrease the rate of unintended pregnancy (pregnancy timing preferences), unintended pregnancy (pregnancy seeking), and unwelcome pregnancy compared
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to usual care.
Analyses pertaining to the secondary outcomes of intended contraceptive method(s), intention to use a highly effective contraceptive method, contraceptive method(s) used, and use of a highly effective contraceptive method are exploratory and thus no a priori hypotheses for these secondary outcomes have been developed.
For analyses pertaining to the secondary outcome, Intended Contraceptive Method(s), we will use three denominators: (a) all participants, (b) all participants except those not at risk of unintended pregnancy, and (c) all participants except those not at risk of unintended pregnancy and those who reported that they did not want or need to use a birth control method.
For analysis pertaining to the secondary outcome, Intention to Use a Highly Effective Contraceptive Method, we will use three denominators: (a) all participants, (b) all participants except those not at risk of unintended pregnancy, and (c) all participants except those not at risk of unintended pregnancy and those who reported that they did not want or need to use a birth control method.
In reporting the secondary analyses, p-values will be shown adjusted for multiple comparisons.
7 Does implementing the video + prompt card and the decision aids + training result in greater increases or decreases (as relevant) in the [rate/level of [secondary outcome] compared to usual care than implementing either of the interventions alone?
We hypothesise that implementing the video + prompt card and the decision aids + training will result in greater increases in the rate of conversation about contraception, optimal satisfaction with the conversation about contraception, optimal values concordance of intended contraceptive method(s), use of intended contraceptive method(s), optimal adherence to contraceptive method(s) used, optimal satisfaction with contraceptive method(s) used; greater decreases in the level of decision regret; and greater decreases in the rate of unintended pregnancy (pregnancy timing preferences), unintended pregnancy (pregnancy seeking), and unwelcome pregnancy compared to usual care than implementing the video + prompt card alone or the decision aids + training alone.
Analyses pertaining to the secondary outcomes of intended contraceptive method(s), intention to use a highly effective contraceptive method, contraceptive method(s) used, and use of a highly effective contraceptive method are exploratory and thus no a priori hypotheses for these secondary outcomes have been developed.
The third objective is to evaluate the (1) feasibility of the interventions (operationalised as rates of patient exposure to the interventions) and (2) their acceptability to patients.
8 Of participants receiving care in a trial arm implementing the video + prompt card, what proportion report having watched the whole video?
We hypothesise that, of participants receiving care in a trial arm implementing the video + prompt card, at least 70% will report having watched the whole video.
Proportions and confidence intervals will be reported both separately by clinic and for all clinics as a whole.
9 Of participants receiving care in a trial arm implementing the video + prompt card, what proportion report having received the prompt card?
We hypothesise that, of participants receiving care in a trial arm implementing the video + prompt card, at least 70% will report having received the prompt card.
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10 Of participants receiving care in a trial arm implementing the decision aids + training, what proportion report having used a decision aid together with a health care provider?
We hypothesise that, of participants receiving care in a trial arm implementing the decision aids + training, at least 70% will report having used a decision aid together with a health care provider.
11 Is the proportion of participants who report having watched the whole video higher among those receiving care in a trial arm implementing both the video + prompt card and decision aids + training than in a trial arm implementing only the video + prompt card?
We hypothesise that the proportion of participants who report having watched the whole video will be higher among those receiving care in a trial arm implementing both the video + prompt card and decision aids + training than in a trial arm implementing only the video + prompt card.
We will conduct three analyses. To account for the cluster randomized design, the analyses will use random effects logistic regression, as described above. The analyses will adjust for any participant characteristics that differ across trial arms. In reporting analyses, p-values will be shown adjusted for multiple comparisons. 12 Is the proportion of participants
who report having received the prompt card higher among those receiving care in a trial arm implementing both the video + prompt card and decision aids + training than in a trial arm implementing only the video + prompt card?
We hypothesise that the proportion of participants who report having received the prompt card will be higher among those receiving care in a trial arm implementing both the video + prompt card and decision aids + training than in a trial arm implementing only the video + prompt card.
13 Is the proportion of participants who report having used a decision aid together with a health care provider higher among those receiving care in a trial arm implementing both the decision aids + training and video + prompt card than in a trial arm implementing only the decision aids + training?
We hypothesise that the proportion of participants who report having used a decision aid together with a health care provider will be higher among those receiving care in a trial arm implementing both the decision aids + training and video + prompt card than in a trial arm implementing only the decision aids + training.
14 What proportion of participants who report having watched the whole video would recommend it to a friend?
We hypothesise that a majority of participants who report having watched the whole video would recommend it to a friend.
Proportions and confidence intervals will be reported both separately by clinic and for all clinics as a whole.
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15 What proportion of participants who report having received the prompt card would recommend it to a friend?
We hypothesise that a majority of participants who report having received the prompt card would recommend it to a friend.
16 What proportion of participants who report having used a decision aid together with a health care provider would recommend it to a friend?
We hypothesise that a majority of participants who report having used a decision aid together with a health care provider would recommend it to a friend.
17 Is the proportion of participants who would recommend the video to a friend higher among those receiving care in a trial arm implementing both the video + prompt card and decision aids + training than in a trial arm implementing only the video + prompt card?
We hypothesise that the proportion of participants who would recommend the video to a friend will be higher among those receiving care in a trial arm implementing both the video + prompt card and decision aids + training than in a trial arm implementing only the video + prompt card.
We will conduct three analyses. To account for the cluster randomized design, the analyses will use random effects logistic regression, as described above. The analyses will adjust for any participant characteristics that differ across trial arms. In reporting analyses, p-values will be shown adjusted for multiple comparisons. 18 Is the proportion of participants
who would recommend the prompt card to a friend higher among those receiving care in a trial arm implementing both the video + prompt card and decision aids + training than in a trial arm implementing only the video + prompt card?
We hypothesise that the proportion of participants who would recommend the prompt card to a friend will be higher among those receiving care in a trial arm implementing both the video + prompt card and decision aids + training than in a trial arm implementing only the video + prompt card.
19 Is the proportion of participants who would recommend the decision aids to a friend higher among those receiving care in a trial arm implementing both the decision aids + training and video + prompt card than in a trial arm implementing only the decision aids + training?
We hypothesise that the proportion of participants who would recommend the decision aids to a friend will be higher among those receiving care in a trial arm implementing both the decision aids + training and video + prompt card than in a trial arm implementing only the decision aids + training.
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1
SPIRIT 2013 Checklist: Recommended items to address in a clinical trial protocol and related documents*
Section/item Item No
Description Addressed on page number
Administrative information
Title 1 Descriptive title identifying the study design, population, interventions, and, if applicable,
trial acronym
1
(Note, because of the number of
words required to accurately
describe the population, this has
been omitted)
Trial registration 2a Trial identifier and registry name. If not yet registered, name of intended registry 3
2b All items from the World Health Organization Trial Registration Data Set TRDS items are largely replicated
in the clinicaltrials.gov registry in
which study is registered
Protocol version 3 Date and version identifier N/A
(Published protocol will be dated)
Funding 4 Sources and types of financial, material, and other support 2
Roles and
responsibilities
5a Names, affiliations, and roles of protocol contributors 1, 21
5b Name and contact information for the trial sponsor 2
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2
5c Role of study sponsor and funders, if any, in study design; collection, management,
analysis, and interpretation of data; writing of the report; and the decision to submit the
report for publication, including whether they will have ultimate authority over any of these
activities
2
5d Composition, roles, and responsibilities of the coordinating centre, steering committee,
endpoint adjudication committee, data management team, and other individuals or
groups overseeing the trial, if applicable (see Item 21a for data monitoring committee)
N/A
Introduction
Background and
rationale
6a Description of research question and justification for undertaking the trial, including
summary of relevant studies (published and unpublished) examining benefits and harms
for each intervention
4-5, 6-7, Supplementary file
6b Explanation for choice of comparators 4
Objectives 7 Specific objectives or hypotheses 5, Supplementary file
Trial design 8 Description of trial design including type of trial (eg, parallel group, crossover, factorial,
single group), allocation ratio, and framework (eg, superiority, equivalence, noninferiority,
exploratory)
5-6, 9
Methods: Participants, interventions, and outcomes
Study setting 9 Description of study settings (eg, community clinic, academic hospital) and list of
countries where data will be collected. Reference to where list of study sites can be
obtained
6
Eligibility criteria 10 Inclusion and exclusion criteria for participants. If applicable, eligibility criteria for study
centres and individuals who will perform the interventions (eg, surgeons,
psychotherapists)
6, 9
Interventions 11a Interventions for each group with sufficient detail to allow replication, including how and
when they will be administered
6-8
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3
11b Criteria for discontinuing or modifying allocated interventions for a given trial participant
(eg, drug dose change in response to harms, participant request, or improving/worsening
disease)
N/A
11c Strategies to improve adherence to intervention protocols, and any procedures for
monitoring adherence (eg, drug tablet return, laboratory tests)
8, 14
11d Relevant concomitant care and interventions that are permitted or prohibited during the
trial
8
Outcomes 12 Primary, secondary, and other outcomes, including the specific measurement variable
(eg, systolic blood pressure), analysis metric (eg, change from baseline, final value, time
to event), method of aggregation (eg, median, proportion), and time point for each
outcome. Explanation of the clinical relevance of chosen efficacy and harm outcomes is
strongly recommended
9-15
Participant timeline 13 Time schedule of enrolment, interventions (including any run-ins and washouts),
assessments, and visits for participants. A schematic diagram is highly recommended
(see Figure)
8
Sample size 14 Estimated number of participants needed to achieve study objectives and how it was
determined, including clinical and statistical assumptions supporting any sample size
calculations
16-17
Recruitment 15 Strategies for achieving adequate participant enrolment to reach target sample size 15-16
Methods: Assignment of interventions (for controlled trials)
Allocation:
Sequence
generation
16a Method of generating the allocation sequence (eg, computer-generated random
numbers), and list of any factors for stratification. To reduce predictability of a random
sequence, details of any planned restriction (eg, blocking) should be provided in a
separate document that is unavailable to those who enrol participants or assign
interventions
9
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4
Allocation
concealment
mechanism
16b Mechanism of implementing the allocation sequence (eg, central telephone; sequentially
numbered, opaque, sealed envelopes), describing any steps to conceal the sequence
until interventions are assigned
N/A
Implementation 16c Who will generate the allocation sequence, who will enrol participants, and who will
assign participants to interventions
9, 15, 18-19
Blinding (masking) 17a Who will be blinded after assignment to interventions (eg, trial participants, care
providers, outcome assessors, data analysts), and how
9
17b If blinded, circumstances under which unblinding is permissible, and procedure for
revealing a participant’s allocated intervention during the trial
N/A
Methods: Data collection, management, and analysis
Data collection
methods
18a Plans for assessment and collection of outcome, baseline, and other trial data, including
any related processes to promote data quality (eg, duplicate measurements, training of
assessors) and a description of study instruments (eg, questionnaires, laboratory tests)
along with their reliability and validity, if known. Reference to where data collection forms
can be found, if not in the protocol
8-9, 9-15
18b Plans to promote participant retention and complete follow-up, including list of any
outcome data to be collected for participants who discontinue or deviate from intervention
protocols
15-16
Data management 19 Plans for data entry, coding, security, and storage, including any related processes to
promote data quality (eg, double data entry; range checks for data values). Reference to
where details of data management procedures can be found, if not in the protocol
17
Statistical methods 20a Statistical methods for analysing primary and secondary outcomes. Reference to where
other details of the statistical analysis plan can be found, if not in the protocol
17, Supplementary file
20b Methods for any additional analyses (eg, subgroup and adjusted analyses) 17, Supplementary file
20c Definition of analysis population relating to protocol non-adherence (eg, as randomised
analysis), and any statistical methods to handle missing data (eg, multiple imputation)
17-18
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5
Methods: Monitoring
Data monitoring 21a Composition of data monitoring committee (DMC); summary of its role and reporting
structure; statement of whether it is independent from the sponsor and competing
interests; and reference to where further details about its charter can be found, if not in
the protocol. Alternatively, an explanation of why a DMC is not needed
19
21b Description of any interim analyses and stopping guidelines, including who will have
access to these interim results and make the final decision to terminate the trial
19
Harms 22 Plans for collecting, assessing, reporting, and managing solicited and spontaneously
reported adverse events and other unintended effects of trial interventions or trial conduct
19
Auditing 23 Frequency and procedures for auditing trial conduct, if any, and whether the process will
be independent from investigators and the sponsor
N/A
Ethics and dissemination
Research ethics
approval
24 Plans for seeking research ethics committee/institutional review board (REC/IRB)
approval
18
Protocol
amendments
25 Plans for communicating important protocol modifications (eg, changes to eligibility
criteria, outcomes, analyses) to relevant parties (eg, investigators, REC/IRBs, trial
participants, trial registries, journals, regulators)
19
Consent or assent 26a Who will obtain informed consent or assent from potential trial participants or authorised
surrogates, and how (see Item 32)
18-19
26b Additional consent provisions for collection and use of participant data and biological
specimens in ancillary studies, if applicable
N/A
Confidentiality 27 How personal information about potential and enrolled participants will be collected,
shared, and maintained in order to protect confidentiality before, during, and after the trial
17, 19, 20
Declaration of
interests
28 Financial and other competing interests for principal investigators for the overall trial and
each study site
20-21
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6
Access to data 29 Statement of who will have access to the final trial dataset, and disclosure of contractual
agreements that limit such access for investigators
20
Ancillary and post-
trial care
30 Provisions, if any, for ancillary and post-trial care, and for compensation to those who
suffer harm from trial participation
N/A
Dissemination policy 31a Plans for investigators and sponsor to communicate trial results to participants,
healthcare professionals, the public, and other relevant groups (eg, via publication,
reporting in results databases, or other data sharing arrangements), including any
publication restrictions
20
31b Authorship eligibility guidelines and any intended use of professional writers 20
31c Plans, if any, for granting public access to the full protocol, participant-level dataset, and
statistical code
19-20
Appendices
Informed consent
materials
32 Model consent form and other related documentation given to participants and authorised
surrogates
19
Biological
specimens
33 Plans for collection, laboratory evaluation, and storage of biological specimens for genetic
or molecular analysis in the current trial and for future use in ancillary studies, if
applicable
N/A
*It is strongly recommended that this checklist be read in conjunction with the SPIRIT 2013 Explanation & Elaboration for important clarification on the items.
Amendments to the protocol should be tracked and dated. The SPIRIT checklist is copyrighted by the SPIRIT Group under the Creative Commons
“Attribution-NonCommercial-NoDerivs 3.0 Unported” license.
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