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http://cjb.sagepub.com/content/38/8/779The online version of this article can be found at:

DOI: 10.1177/0093854811409004

2011 38: 779 originally published online 10 June 2011Criminal Justice and BehaviorDaryl G. Kroner, Tamara Kang, Jeremy F. Mills, Andrew J.R. Harris and Michelle M. Green

Screening Form Among Women OffendersReliabilities, Validities, and Cutoff Scores of the Depression Hopelessness Suicide

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779

CRIMINAL JUSTICE AND BEHAVIOR, Vol. 38 No. 8, August 2011 779-795

DOI: 10.1177/0093854811409004

2011 International Association for Correctional and Forensic Psychology

AUTHORS NOTE: Gratefully acknowledged are Caroline Page and Iliana Lilova for their assistance with

the study. Correspondence concerning this article should be addressed to Daryl G. Kroner, Southern IllinoisUniversity Carbondale; email: [email protected].

RELIABILITIES, VALIDITIES, AND CUTOFF

SCORES OF THE DEPRESSION HOPELESSNESS

SUICIDE SCREENING FORM AMONG WOMENOFFENDERS

DARYL G. KRONER

TAMARA KANGSouthern Illinois University Carbondale

JEREMY F. MILLSCarleton University

ANDREW J. R. HARRIS

MICHELLE M. GREEN

Correctional Service Canada

Depression and hopelessness can be associated with negative outcomes among offenders, such as reduced treatment impact,

institutional misconduct, suicide risk, and health care costs. This study evaluated the reliability and validity of the Depression

Hopelessness Suicide Screening Form (DHS) among women offenders. The DHS Depression and Hopelessness scales

showed good internal consistency and testretest reliability. Convergent and discriminant validities were supported through

the relationship of the DHS with other established scales of depression, mood, suicidal intentions, and psychological distress.

Optimal and conservative cutoff scores for the DHS Depression and Hopelessness scales were evaluated against criteria from

aDSM-IV-based interview. Discussion centers on the importance of gender-based norms when assessing women offenders.

Keywords: women offenders; gender-sensitive assessment; depression; hopelessness; offender cutoff scores

An overview of the offender literature would suggest that the assessment of depressionand hopelessness is often considered a lower priority, especially when compared to thefactors that typically predict institutional behavior and recidivism outcomes. Yet depression

and hopelessness can be associated with a host of negative consequences, such as self-

harm or suicide behaviors and reduced treatment impact and have indirect consequence of

co-occurring disorders, resulting in increased health care costs.

Depressions association with suicide-related thoughts and behaviors is well established

across varied populations (Dieserud, Roysamb, Ekeberg, & Kraft, 2001; Konick &

Gutierrez, 2005; Rudd, Joiner, & Rajab, 1996). Among 1,900 offenders in the Canadianfederal correctional system, lifetime depressive disorders ranged from 21.5% (stringent

criteria) to 29.8% (wide criteria ignoring severity and exclusions) of the sample (Motiuk &

Porporino, 1992). Hopelessness, defined as a system of negative expectancies concerning

himself and his future life (Beck, Weissman, Lester, & Trexler, 1974, p. 861), is also key

in the assessment of suicide risk (Dieserud et al., 2001; Dixon, Heppner, & Rudd, 1994;

Konick & Gutierrez, 2005; Rudd et al., 1996). Although some suicidal protocols ignore the

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780 CRIMINAL JUSTICE AND BEHAVIOR

measurement of depression and hopelessness (Correia, 2000), these two areas are essential

to suicide risk assessment.

In efforts to treat offenders, depression and hopelessness can be factors in how receptive

and responsive offenders are to interventions. In a multisite study, depression was shown

to be a more powerful factor among programs for women as compared to programs for

males (Staton-Tindall et al., 2007). The treatment engagement measures of counselor rap-

port and willingness to participate in treatment were the outcome variables. Depression was

more strongly related to these two treatment engagement variables for programs designed

for women than those designed for men.

Not only can there be a direct link between depression and related criminal justice out-

comes, but indirect consequences of depression can exasperate the impact of negative out-

comes. Individuals who suffer from depression often suffer from other disorders, typically

substance abuse, and specific personality disorders, such as borderline personality disorder.

In a recent meta-analysis, examining the co-occurrence of depression and personality disor-ders, a personality disorder doubled the risk of a poor outcome for depression (Newton-

Howes, Tryer, & Johnson, 2006). In a review of the costs of depression, Panzarino (1998)

argued that high-frequency users of medical services have higher rates of depression and are

more likely to have a co-occurring disorder with depression. This same relationship appears

to hold with offenders. Depression, as measured by self-report, was associated with chronic

ill health, but not with length of sentence served (Murdoch, Morris, & Holmes, 2008).

Rates of mental health symptoms and diagnosis generally differ between women and

men. For example, women typically have higher rates of affective disorders, whereas men

have higher rates of antisocial related disorders (Dohrenwend et al., 1992; Khan, Jacobson,

Gardner, Prescott, & Kendler, 2005; Piccinelli & Wilkinson, 2000). A multicountry, multi-

method study that examined common mental health disorders found that being a woman

increased the likelihood of a mental disorder (Patel, Araya, Lima, Ludermir, & Todd,

1999). When specific disorders such as depression are considered, women not only have

higher rates than men but also have higher rates of comorbidity (Afifi, 2007). Similar to the

different rates of comorbidity, how depression interacts with social supports differs

between women and men. In a two-wave, opposite-sex twin pair study, lack of global sup-

port predicted future depression in women but not in men (Kendler, Myers, & Prescott,

2005). Also, when the types of support were examined, lack of support from the co-twin,

other relatives, parents, and spouse was more strongly related with future likelihood ofdepression for women than for men. Thus, not only are rates of disorder likely to differ, but

the etiological pathway of a disorder is likely to differ between females and males.

As in the population at large, evidence suggests that female offenders are more likely to

experience depression than are male offenders (Ng et al., 2010). Also, unique factors

among women contribute to criminal justice outcomes. These unique factors have emerged

from the literature suggesting that women have different pathways to crime. These path-

ways include victimization and abuse, mental health, dysfunctional relationships, self-

esteem, self-efficacy, and parental distress (Salisbury, Van Voorhis, & Spiropoulos, 2009).

Female-centered instruments to measure these areas are called gender-responsive instru-

ments. Within the mental health domain, the use of two gender-responsive instruments of

current depression or anxiety and current psychosis resulted in better predictions of the

number of institutional misconducts over 6- and 12-month periods (Wright, Salisbury, &

Van Voorhis, 2007). The gender-responsiveness psychosis scale was the strongest predictor



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Kroner et al. /DHS AMONG WOMEN OFFENDERS 781

of misconducts (r= .26, 6 months; r= .31, 12 months), stronger than the gender-neutral

predictor scale of history of mental illness (r= .12, 6 months; r= .19, 12 months). Given

the different negative affect levels between female and male offenders and the potential

different pathways to crime, it is expected that the guidelines for interpreting results with

women offenders would benefit from the use of women-based norms and the development

of gender-specific cutoff scores.

Based on the above review, a single cutoff score is likely to be inappropriate for both

female and male offenders. Inappropriate cutoff scores can result in overclassification or

underclassification of the target construct or domain. Two common strategies may result in

overclassification among women offenders. First, if women have a lower base rate of an

outcome variable, a predictive instrument may unnecessarily classify women into a high

category. That is, the instruments cutoff scores may indicate a threshold for an event, when

that condition or future event is unlikely to occur. This type of overclassification can occur

when male-derived cutoff scores are used for security level classification. Typically, com-pared to their male counterparts, women offenders have a lower rate of institutional mis-

conducts and their offenses are less severe (Harer & Langan, 2001). In this situation, using

a cutoff score from a male-derived instrument will overclassify women offenders. That is,

too many women will be placed in a high level of security, when such a placement is not

warranted. Cutoff scores developed on male offenders have classified women offenders to

higher security both in New Zealand (Collie & Polascheck, 2003) and in the U.S. federal

system (Harer & Langan, 2001). The second situation of overclassification may result from

increased instrument scores not because of reasons directly related to crime-related needs

but because of past traumatic experiences. Increased scores can be a result of past traumatic

experiences, which may not typify a male experience. Whether because of base rate or

instrumentation, overclassification results in a misuse of correctional resources, placing

women in more restrictive environments than necessary.

The Depression Hopelessness Suicide Screening Form (DHS; Mills & Kroner, 2003)

was developed to screen for depression and hopelessness as well as gather information on

suicide risk factors such as history of suicide attempts, previous diagnosis for depression,

family members who have committed suicide, and suicidal ideation. In addition to screen-

ing for these risk factors, the DHS was also developed to overcome some drawbacks of the

more commonly used depression inventories. For example, items that referenced guilt were

not included in the DHS because they may have ambiguous meaning within a criminaljustice context. The source of guilt can be of either a legal factual nature (guilty of a crime)

or an affective nature (feeling guilty without a direct cause).

The purpose of this study was threefold. First, we wanted to report reliability and valid-

ity information on the DHS among female offenders. Validity was examined via conver-

gent and discriminant validities with established measures of affective functioning. In

addition, the efficacy of the DHS critical items was examined. Second, because of the

potential of misclassification with female offenders, optimal cutoff scores were developed.

Sensitivity, specificity, positive predictive power, and negative predictive power were

examined for two methods of deriving cutoff scores. To further facilitate a gender-based

interpretation, suggestions for content interpretation of the depression and hopelessness

scales were made. Third, because it was expected that the depression and hopelessness

scales would be correlated, the optimal cutoff score for each scale was compared for both

depression and hopelessness outcomes.

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METHOD

PARTICIPANTS

Participants were 98 Canadian federal women offenders on community release (age

M= 37.5, SD= 10.9), and demographic data were available for 92 cases. The offenders

were predominantly White and incarcerated for drug and substance use offenses. Of the

offenders, 15 (16.3%) had recorded previous suicide attempts, and 29.3% (n= 27) were

presently taking psychotropic medication (see Table 1 for other data).

MEASURES

Depression Hopelessness Suicide Screening Form. The DHS (Mills & Kroner, 2003) isa 39-item self-report psychometric instrument specifically developed to screen for the

presence of depression and hopelessness and provides indicators of current and prior sui-

cidal behaviors and thought processes. In addition to the two construct scales of Depression

and Hopelessness, there are 11 critical items measuring Suicidal Ideation, Cognitive

Suicide Indicators, and Historical Suicide Indicators. The DHS was validated on a sample

of male offenders in a medium-security institution (N= 272) and has demonstrated factor

structure consistent with the operationalized scales, construct validity, and internal consis-

tency (Cronbachs a= .87). The predictive accuracy of the DHS was confirmed in inmates

who experienced psychological distress (Mills & Kroner, 2005). The instrument is valid,reliable, and appropriate when used with male offenders (Mills & Kroner, 2004).

Profile of Mood States (POMS). The POMS (McNair, Lorr, & Droppleman, 1992) is a

65-item self-report measure of the participants mood. Participants are asked to report their

TABLE 1: Demographic Variables

n %

Race

White 65 70.7Black 13 14.1

North American Native 9 9.8

Asian 2 2.2

Other 3 3.3

Primary offenses

Drug offenses 34 37.0

Substance use offenses 34 37.0

Murder, attempted murder, manslaughter 17 18.5

Assaults, threats 15 16.3

Robbery, extortion 10 10.9

Fraud, forgery, false pretenses 5 5.4Property, loitering 4 4.3

Possession of weapons or explosives 2 2.2

Other offenses 5 5.4

Mental health functioning

Taking psychotropic medication 27 29.3

Previous suicide attempt 15 16.3

Note. N= 92.



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mood for three different time periods: For the present study participants reported their

mood during the past week. Six mood factors are identified and measured by the POMS:

TensionAnxiety, DepressionDejection, AngerHostility, VigorActivity, FatigueInertia,

and ConfusionBewilderment. Among women cancer patients, Cronbachs alpha for the

POMS scales ranged from .33 (DepressionDejection) to .78 (VigorActivity; Hack et al.,

2010). McNair et al. (1992) provided evidence of concurrent and predictive validities for

the POMS. The POMS was validated on a standardized sample of adults (N = 564;

Nyenhuis & Yamamoto, 1999) and has been examined in a sample of 1,350 offenders,

including female and male offenders (Samuelson, Carmody, Kabat-Zinn, & Bratt, 2007).

Beck Depression Inventory2nd Edition (BDI-II).The BDI-II (Beck, Steer, & Brown,

1996) is a 21-item self-report questionnaire developed to measure the severity of depres-

sion, each question being scored on a scale of 0 to 3. Total scores ranging from 0 to 13

represent minimal depression, total scores from 14 to 19 are mild depression, totalscores from 20 to 28 are moderate depression, and total scores from 29 to 63 represent

severe depression (Beck, Steer, & Brown, 1996). The questionnaire asks participants to

report how they have been feeling for the past 2 weeks. Questions include items relating to

symptoms of depression such as hopelessness and irritability as well as physical symptoms

such as fatigue. The BDI-II was validated on a sample of 117 incarcerated young adult

offenders aged 18 to 21 in the United Kingdom. The BDI-II had a high level of internal

consistency (Cronbachs a= .90). Furthermore, the study found convergent validity, which

was evident from the significant correlation between the BDI-II and BHS (r= .55,p < .001;

Palmer & Binks, 2008). Boothby and Durham (1999) confirmed that women and younger

offenders report higher scores on the BDI-II, which supported the view that mild and severedepression are more evident among women offenders. Perry and Gilbody (2009) estab-

lished that the BDI-II had better predictive validity (area under the curve [AUC] = .75) than

other related instruments when predicting actual self-harm behavior for their women

offender sample with a 4-year follow-up.

Beck Hopelessness Scale (BHS). The BHS (Beck & Steer, 1988) is a 20-item self-report,

truefalse questionnaire designed to measure three major aspects of hopelessness: feelings

about the future, loss of motivation, and expectations. The possible range of scores is 0 to

20. The BHS was validated on a sample of 544 university students and has demonstratedgood internal consistency (Cronbachsa= .88). The BHS has been used in a sample of 105

female offenders, with a correlation of .47 with suicide attempts (Chapman, Specht, &

Cellucci, 2005).

Brief Symptom Inventory (BSI). The BSI (Derogatis, 1993) is a 53-item self-report, multi-

dimensional measure of psychological distress. The scale was designed to test psychopathol-

ogy. The test is based on nine primary symptom dimensions: Somatization, Obsessive

Compulsiveness, Interpersonal Sensitivity, Depression, Anxiety, Hostility, Phobic Anxiety,

Paranoid Ideation, and Psychoticism. The items are scored on a 5-point scale from 0 (not at

all distressed) to 4 (extremely distressed). The BSI was validated on a sample of 200 peoplethat represented community, clinical, and forensic populations (Kellett, Beail, Newman, &

Frankish, 2003). All forensic participants demonstrated moderate to good Cronbachs alpha

and split-half alpha (a= .52 to .78). Among women offenders, the BSI scales correlations

with distress ranged from .37 to .54 (Warren, Hurt, Loper, & Chauhan, 2004).



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Beck Scale for Suicide Ideation (BSS). The BSS (Beck & Steer, 1991) is a 20-item scale

designed to quantify aspects of suicidal intent and ideation. It is used to assess negative

expectancies about the immediate and long-term future. The BSS is scored based on

the response of the participant. If the response indicates hopelessness, a score of 1 is

recorded, and if the participant indicates nonhopelessness, then a score of 0 is recorded, for

a possible total of 20. A score of 14 or higher is severe hopelessness (Palmer & Connelly,

2005). The BSS was validated on 314 university students and demonstrated good internal

consistency (Cronbachs a= .81). The measure is reliable and is appropriate for measuring

severity of suicide ideation in college students (Chioqueta & Stiles, 2006). The BSS has

been used in a sample of 123 adult male prison inmates from a Category B local prison in

England (Palmer & Connelly, 2005).

Structured Clinical Interview forDSM-IV Axis-I Disorders, Clinician Version (SCID-I).

The SCID-I (First, Spitzer, Gibbon, & Williams, 1997) is a semistructured interview fromwhichDSMdiagnosis can be made. Two construct outcome measures were taken from the

SCID-I. First was the diagnosis of Dysthymia, which incorporates multiple items scored

via the guide. Dysthymia measures mild depression, and for the purposes of this article is

labeled Mild Depression (1 =mild depression, 0 =absence). The second measure was a

single hopelessness item from the SCID interview and is labeled Hopelessness (1 =hope-

lessness, 0 =absence).

PROCEDURE

Offenders were approached to participate in a study examining emotional functioning inincarcerated women offenders. Data were collected by two women researchers, one at each

of two Canadian federal womens institutions between July 2007 and August 2008. One

institution was primarily French speaking, which resulted in approximately one-third of the

cases gathered in French. The researchers gathering the SCID-I data were blind to the self-

report results from the DHS, POMS, BDI-II, BHS, BSI, and BSS.

STATISTICAL ANALYSIS

Three categories of analyses were conducted. The first category of analysis included

basic reliabilities and convergent and discriminant validities. The second category ofanalyses examined optimal cutoff scores of the DHS Depression and Hopelessness scales.

The SCID-I derived measures of mild depression and hopelessness served as the construct

outcome criteria. Overall classification accuracy was assessed using receiver operating

characteristic (ROC) curves. Sensitivity refers to the DHS correctly identifying those with

either mild depression or hopelessness. Specificity refers to the DHS correctly identifying

those without mild depression or hopelessness. Both the sensitivity and specificity of the

DHS scales are needed to assess overall accuracy. Two strategies were used to determine

cutoff scores. First is a statistical optimal point that equally considers the sensitivity and

specificity parameters (Steadman, Scott, Osher, Agnese, & Robbins, 2005), which is calcu-lated with Youdens index (Bewick, Cheek, & Ball, 2004; Perkins & Schisterman, 2006).

Second, for a more conservative approach to the development of a cutoff score, the DHSs

sensitivity was emphasized over specificity (Ogloff, Roesch, & Hart, 1993; Reddon,

Vander Veen, & Munchua, 2001). Maximal negative predictive power (NPP) was used to



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derive the most conservative cutoff score. These two strategies incorporate the full range

of the DHSs continuous scores.

Using cutoff scores and not the full range of the DHSs continuous scores, the third

category of analyses compared the DHS Depression and Hopelessness scales optimal cut-

off scores. Given that the two scales are strongly correlated, we wanted to determine if the

Depression scales optimal cutoff score was better at detecting mild depression than the

Hopelessness optimal cutoff score and if the Hopelessness optimal cutoff score was better

at detecting hopelessness than the Depression optimal cutoff score. The benefit of these

analyses is that specific cutoff scores for each scale are used, as compared to the full range

of scores used by ROC curve analyses. By using a positive likelihood ratio and a negative

likelihood ratio, the use of specific cutoff scores (i.e., a Depression cutoff score and a

Hopelessness cutoff score) can directly translate into clinical use. A positive likelihood

ratio indicates how many times more likely the participants with the target condition are to

have a positive result than participants without the target condition. A negative likelihoodratio indicates how many times less likely the participants with the target condition are to

have a negative result than participants without the target condition (Kondratovich, 2008).

This comparison can be visually demonstrated in a likelihood graph. With the false positive

rate on the x-axis and the true positive rate on the y-axis, the first test score (i.e., Depression)

plotted is used as a reference for dividing the graph into four areas (Biggerstaff, 2000; see

Figure 1). The first test score produces two solid lines: One line represents the positive

likelihood ratio, passing through (0, 0) the bottom left of the graph; the second line repre-

sents the negative likelihood ratio, passing through (1, 1) the top right of the graph. The

second test score (i.e., Hopelessness cutoff score), the test of comparison, then falls into

one of the four areas. Each area represents (Area 1) overall superior classification, (Area 2)

better at detecting the absence of the condition (i.e., depression), (Area 3) better at detecting

the presence of the condition, and (Area 4) overall inferiority classification (see Figure 1). The

graph, with two reference points (D= one scales cutoff score, = the other scales cutoff

score; Figure 1), assists in comparing the abilities of two scales (Kondratovich, 2008). All

cutoff score analyses were conducted in R.

RESULTS

RELIABILITY ANALYSES, CONVERGENT AND

DISCRIMINANT VALIDITIES, AND STATISTICAL PREDICTIONS

Scales means, ranges, and Cronbachs alphas are presented in Table 2. The majority of

alphas were fairly strong, with DHS Depression and the DHS Hopelessness scales having

a Cronbachs alpha of .90. A subsample of 38 offenders repeated the DHS after 2 weeks.

Testretest coefficients were .80 (Depression), .86 (Hopelessness), and .87 (Total).

The correlations between the DHS scales and the BSI, POMS, BHS, and BDI are in

Table 3. In terms of convergent validity, the DHS Depression scale had stronger correla-

tions with other depression specific scales (i.e., SSI Depression, r=

.76; POMS DepressionDejection, r= .67) as compared to noncorresponding scales (i.e., BSI Phobic Anxiety, r= .46;

POMS TensionAnxiety, r= .53). With the Beck scales, the corresponding DHS Depression

(r= .74) and DHS Hopelessness correlations (r= .76) were stronger than the noncorre-

sponding correlations (DHS Depression and BHS, r= .65; DHS Hopelessness and BDS,



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Figure 1: Optimal Cutoff Scores of Depression and Hopelessness in Predicting Mild Depression

r= .68). The other relatively strong correlations with the DHS Depression and Hopelessness

scales are relevant for elaborating on the DHSs construct validity. Relatively strong cor-

relations between DHS Depression and the BSI Obsessive Compulsive, Paranoid Ideation,

and Psychoticism scales were found. With the POMS, strong correlations were with the

DepressionDejection, Fatigue, and Confusion scales. With the DHS Hopelessness scale,

relatively strong correlations were with the BSI Paranoid Ideation and Psychoticism scales

and with the POMS DepressionDejection and Confusion scales.Critical items from the DHS were correlated with selected corresponding items from the

BSI, BDI-II, and BSS and a suicidal item from the interview (see Table 4). The DHS

Suicidal Ideation and Cognitive Suicidal Indicators had stronger correlations with the BSI

death items than with the DHS Historical Suicide Indicators. A reverse situation was

found with the interview item of previous suicide attempt. The DHS Historical Suicide

Indicators had stronger correlations with this interview item than the Suicide Ideation and

Cognitive Suicide Indicators.

CUTOFF SCORES

Cutoff scores for the Depression and Hopelessness scales were developed using a statis-

tically optimal and a conservative approach. With Youdens index, the optimal cut point for

the Depression scale predicting mild depression was a raw score of 5 (see Table 5). With

maximal NPP, the conservative cut point for the Depression scale was also a raw score of 5.



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TABLE 2: Scale Statistics

M SD Range a

DHSDepression 5.3 4.8 017 .90Hopelessness 1.9 2.8 010 .90Total 8.1 6.1 027 .94

Brief Symptom InventorySomatization 6.2 6.1 023 .85Obsessive Compulsive 7.4 6.0 024 .88Interpersonal Sensitivity 4.2 4.0 016 .85Depression 5.6 5.5 022 .88Anxiety 6.0 5.6 022 .79Hostility 3.6 4.6 020 .89Phobic Anxiety 4.0 5.3 019 .88Paranoid Ideation 5.9 4.6 019 .78Psychoticism 5.1 4.9 020 .81

Profile of Mood States

TensionAnxiety 12.2 7.5 236 .83DepressionDejection 15.5 12.7 056 .93AngerHostility 10.8 10.6 048 .93VigorActivity 16.6 7.3 132 .88Fatigue 8.6 7.1 028 .92Confusion 10.8 5.1 332 .74Friendliness 17.9 4.9 728 .72Beck Depression Inventory 15.8 11.5 046 .92Beck Hopelessness Scale 4.5 3.6 117 .83

Note. N= 98. DHS = Depression Hopelessness Suicide Screening Form. By comparison, male offender DHSDepression (M= 2.5, SD= 3.3) and Hopelessness (M= 0.6, SD= 1.6) means were considerably lower (Mills &Kroner, 2004).

TABLE 3: Convergent and Discriminant Validities of the DHS Depression and Hopelessness Scales

DHS

Depression Hopelessness Total

Brief Symptom InventorySomatization .39 .21 .34Obsessive Compulsive .64 .54 .63Interpersonal Sensitivity .56 .53 .59

Depression .76 .73 .79Anxiety .51 .42 .50Hostility .53 .49 .54Phobic Anxiety .46 .39 .46Paranoid Ideation .62 .56 .63Psychoticism .70 .63 .71

Profile of Mood StatesTensionAnxiety .53 .46 .54DepressionDejection .67 .67 .71AngerHostility .52 .51 .55

VigorActivity -.38 -.25 -.35Fatigue .61 .48 .59Confusion .51 .49 .53Friendliness -.22 -.20 -.22Beck Depression Inventory .74 .68 .76Beck Hopelessness Scale .65 .76 .73

Note. DHS = Depression Hopelessness Suicide Screening Form. Correlations in bold are convergent correlations,which are expected to be higher than other correlations.



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The sensitivity of the Depression scale in predicting mild depression was quite strong (.90).

With Youdens index, the optimal cut point for the Hopelessness scale in predicting hope-

lessness was a raw score of 3 (see Table 6). With maximal NPP, the conservative cut point

for the Hopelessness scale was also a raw score of 3. The Hopelessness scales sensitivity

was weaker than the Depression scale in predicting mild depression, but the Hopelessness

scale had relatively stronger specificity (.80 vs. .64) in predicting hopelessness.

In the present study, the DHSs restriction of range and distributional characteristics

likely contributed to the lack of differences between the optimal and conservative cutoffscores. The DHS items covered a broad range of serious depression and hopelessness areas,

and therefore individual items are not likely to be in the midrange of endorsement (i.e.,

30%70%). If the items were in the endorsement midrange, the optimal and conservative

cutoff scores would likely differ.

TABLE 4: Zero-Order Correlations Between the Critical Items From Corresponding Depression and

Hopelessness Scales and the DHS

Suicide Ideation

Cognitive

Suicide

Indicators Historical Suicide Indicators

#56 #62 #66 #67 #17 #35 #23 #29 #41 #47 #53

Brief Symptom Inventory

Death item .47** .35** .19 .35** .29** .35** .24* .37** .12 .19 .10

Beck Depression Inventory

Suicide thoughts or wishes .53** .42** .08 .61** .36** .56** .45** .41** .33** .39** .34**

Beck Suicide Inventory

No wish to live .45** .80** .45** .59** .45** .55** .31** .38** .22* .35** .42**

Wish to die .57** .64** .48** .63** .47** .69** .42** .45** .35** .46** .35**

Interview

Previous suicide attempt .11 .16 .10 .32** .21* .29** .42** .50** .55** .62** .19

Note. DHS = Depression Hopelessness Suicide Screening Form. #56 = Serious thoughts of suicide; #62 = Lifeis not worth living; #66 = I have a plan to hurt myself; #67 = I would rather be dead; #17 = Suicide is not anoption for me; #35 = If circumstances get too bad, suicide is always an option; #23 = I have had seriousthoughts of suicide in the past; #29 = I have intentionally hurt myself; #41 = In the past I have attempted sui-cide; #47 = I have attempted suicide more than once in the past; #53 = I have attempted suicide in the pasttwo years. The previous suicide attempt item came from the interview.*p< .05. **p< .01.

TABLE 5: Predictive Utility of Cutoff Scores for the DHS Depression, Hopelessness, and Total Scale

Scores for the Mild Depression Criterion

DHS Cutoff Scores Sensitivity Specificity PPP NPP

Optimal Cutoff Score (Youden index)

Depression (5) .90 .64 .40 .96

Hopelessness (4) .47 .86 .47 .86

Total (5) .90 .59 .36 .96

Maximal NPP

Depression (5) .90 .64 .40 .96

Hopelessness (2) .58 .71 .34 .86

Total (5) .90 .59 .36 .96

Note. DHS = Depression Hopelessness Suicide Screening Form; PPP = positive predictive power; NPP =negative predictive power. The statistical predictions of mild depression, measured by the area under the curve,were .77 (95% CI = .67.86) for the DHS Depression scale, .67 (95% CI = .59.75) for the DHS Hopelessnessscale, and .76 (95% CI = .65.87) for the DHS total score.



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COMPARISON OF DEPRESSION AND HOPELESSNESS CUTOFF SCORES

Even though the AUC results favored the Depression scale in predicting mild depression

(AUC = .77), using a specific cutoff scoreas compared to using all the scales data points

may lead to different results. As shown in Figure 1, the graph represents the potential of the

Hopelessness scale to assist in the prediction of mild depression. The two lines dividing the

graph are based on the Depression cutoff score of 5. A Hopelessness scale cutoff score of

4 is superior, in detecting both the absence and presence of mild depression, than a

Depression scale cutoff score of 5. In Figure 2, the reverse results occurred. The two lines

dividing the graph are based on the Hopelessness cutoff score of 3. Using a Depressionscale cutoff score of 13, the Depression scale is superior, in detecting both the absence and

the presence of hopelessness.

DISCUSSION

The DHS measures an aspect of negative affect that is central to mental health function-

ing and is also related to self-injurious behavior. The results of the present study of women

offender norms, reliabilities, and validities of the DHS lend support to the usage of the

measure across gender. In addition, various cutoff scores that potentially increase the prac-tical utility of the DHS among women offenders were examined.

RELIABILITIES AND VALIDITIES

As a self-report measure, the DHS scale demonstrated good internal consistency, similar

to other depression measures with women offenders (Salisbury & Van Voorhis, 2009). Test

retest reliability suggests adequate stability for both the Depression and Hopelessness

scales, yet within a range that is able to potentially change over time. Compared to male

offender data, the current means of the Depression and Hopelessness scales are consistently

higher. Male offenders from multiple prison samples have Depression scale scores approx-imately half those of female offenders and Hopelessness scores one quarter lower than

those of current female samples (Mills & Kroner, 2004, 2005). Taken together, these results

suggest that DHS scores of female offenders will be higher than those of male offenders.

TABLE 6: Predictive Utility of Cutoff Scores for the DHS Depression, Hopelessness, and Total Scale

Scores for the Hopelessness Criteria

DHS Cutoff Scores Sensitivity Specificity PPP NPP

Optimal Cutoff Score (Youden index)

Depression (13) .62 .95 .67 .94

Hopelessness (3) .69 .80 .24 .94

Total (17) .62 .94 .62 .94

Maximal NPP

Depression (5) .92 .61 .28 .98

Hopelessness (3) .69 .80 .24 .94

Total (1) 1.0 .15 .16 1.0

Note. DHS = Depression Hopelessness Suicide Screening Form; PPP = positive predictive power; NPP =negative predictive power. Results for predicting hopelessness were .82 (95% CI = .72.92) for the DHSDepression scale, .77 (95% CI = .69.85) for the DHS Hopelessness scale, and .82 (95% CI = .70.93) for theDHS total score.



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This is consistent with overall femalemale offender differences in the literature. On mea-

sures of depression and anxiety, women offenders tend to obtain higher scores (Henning,

Jones, & Holdford, 2003; Robbins, Monahan, & Silver, 2003; Staton-Tindall et al., 2007).

The pattern of convergent and discriminant relationships generally supports the con-

struct validity of the DHS Depression and Hopelessness scales. The Depression scale had

stronger correlations with other depression measures and weaker correlations with closely

related measures, such as anxiety. The pattern of correlations was similar for the Hopelessnessscale, with the exception of a weaker correlation with fatigue. A pattern of expected conver-

gent and discriminant results was also noted with the Beck scales. Overall, the correlations

were relatively stronger between scales measuring the same construct (depression and depres-

sion) than between scales measuring different constructs (depression and hopelessness).

With the DHS, critical items also showed a pattern of convergent and discriminant cor-

relations among related items from other scales. The DHS ideation and cognitive indicator

items (i.e., suicide is always an option) had overall stronger correlations with intention-

type items from the BSI and Beck scales than with an item addressing the occurrence of

previous suicide attempts. Conversely, the DHS Historical Suicide Indicators had stronger

correlations with the previous suicide attempt item than with the intention-type items from

the BSI and Beck scales. Taken together, there is some support for the item content validity

of the DHSs critical items.

Figure 2: Optimal Cutoff Scores of Hopelessness and Depression in Predicting Hopelessness



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DHS CUTOFF SCORES

The purpose of including specific cutoff scores is to produce DHS scores that are spe-

cific to women offenders and to enable a direct clinical application of the present results.

Comparing the current results with those of other female correctional samples can place thesensitivity and specificity rates within a broader context. Using a screening tool for general

psychopathology, with Axis I and Axis II as predictive criteria, Ford, Trestman, Wiesbrock,

and Zhang (2007) found optimal sensitivity rates between .54 and .63. With the DHS

Depression scale (cutoff score = 5), the sensitivity rate was .90. This Depression cutoff

score had a strong ability to detect those with mild depression. It appears that the DHS

Depression content area covers a broad spectrum of the contributors to mild depression.

The DHS Hopelessness scale (cutoff score = 3) had a sensitivity rate of .69, which is simi-

lar to the Ford et al. sensitivity rates between .54 and .63. With regard to specificity, Ford

et al.s rates were between .79 and .94. With the DHS Depression scale, the rate was lower,

at .64. Thus, the Depression scale detects mild depression well, but likely includes content

of more serious forms of depression, which reduces the scales specificity. In addition, the

current sample of women offenders may not have a high rate of more serious depression.

Although the full range of DHS Depression and Hopelessness scores shows convergent

and discriminant validities, the application of specific cutoff scores for specific criteria in

the lower range is not so clear. With specific cutoff scores, the Depression scale uniquely

contributed to the prediction of hopelessness and the Hopelessness scale uniquely contrib-

uted to the prediction of mild depression. It may be that the cutoff scores being at the lower

end of the distribution may limit the prediction of narrowly defined outcomes. With more

broadly defined criteria and greater severity, each scale may be better able to uniquelypredict its respective outcomes.

Given that the optimal cutoff scores for male offenders were between 8 and 10 for the

total DHS scores (Mills & Kroner, 2005), cutoff scores for the DHS among female offend-

ers should be specific to them. The use of other, male-derived cutoff scores would mis-

classify women offenders for mild depression and hopelessness. Also, the scale means are

higher than those of male offenders. Drawing on the frequency argument in the gender-

responsiveness literature (Van Voorhis, Wright, Salisbury, & Bauman, 2010), the different

endorsement rates of depression and hopelessness would preclude a direct crossover

application of male-derived DHS basic norms. Thus, in terms of differential endorsement

rates, the present results provide some support for gender-specific interpretation guidelines

(i.e., cutoff scores) for instruments used to assess women offenders.

In addition to endorsement rates, the consequences of depression and hopelessness may

differ between female and male offenders. Benda (2005) found support for depression

contributing to recidivism for women, but not for men. In predicting self-harm among

women offenders, depression demonstrated stronger predictability than hopelessness

(Perry & Gilbody, 2009), although others suggest that hopelessness may have a stronger

role (Chapman et al., 2005). Wright et al. (2007) found current depression or anxiety to be

predictive of prison misconduct among women at both 6-month and 12-month follow-up

times. In addition to the direct consequences of depression and hopelessness, the interactionbetween depression or hopelessness and institutional characteristics may differ between

female and male offenders. For example, Wolff and Shi (2009) found women to feel more

safe in prison and experience less staff-on-offender victimization. Thus, the inability of



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depression in the current study to predict major depression may be related to either the

specific expression patterns of major depression among incarcerated women or an interac-

tion between depression and characteristics of institutional confinement.

INTERPRETATION OF DHS RESULTS IN WOMEN

The above cutoff scores and convergent and discriminant validities may assist in deter-

mining which scores are used for interpretation of the DHS among women offenders. To

further facilitate the interpretation of the DHS, the following comments below, derived from

the data in Table 3, may highlight a more gender-specific interpretation of the DHS scales:

With women offenders, elevated DHS Depression scores are associated with fatigue, beingmuddled, forgetfulness, feeling exhausted, sluggish, and tense. Elevated scores are associatedwith feeling alone, difficulties concentrating, and difficulty in trusting others.

With women offenders, elevated DHS Hopelessness scores are associated with difficulty in makingdecisions, feeling below others, and feeling that others dislike you. There is a pervasive feelingthat something is wrong.

Although the present results support gender-specific norms of the DHS, there is some sup-

port for the measurement of depression and hopelessness being equally valid between

female and male offenders. The convergent and discriminant validities for the Depression

and Hopelessness scales were in the expected direction, similar to what has been found

with male offenders (Mills & Kroner, 2005). Also, the critical items demonstrated the

expected convergent and discriminant validities. Even with adequate validities, having a

closely related normative sample is a top priority. Normative samples are essential to aproper clinical interpretation (Nunnally & Bernstein, 1994). In choosing appropriate norms

for interpretation, consideration should be given to context (i.e., community vs. maximum

security), recency of the norms, and then basic demographics, such as gender, age, and race

(Kroner, Mills, Gray, & Talbert, 2011).

The current study has its limitations. First, the expression of depressive symptoms may

have skewed the self-report of depression and hopelessness toward overreporting. This

may have contributed to a lack of relationship between the self-report measures of depres-

sion and the diagnosis of major depression. Second, the two outcome criteria were different

measurement models. The mild depression criteria involved a standardized rating scale that

has been well researched, whereas the hopelessness criterion was one item. Typically single-

item measures are subjected to reliability criticisms. Third, this study was of a cross-

sectional design. Prediction is an important aspect of validity within criminal justice

settings. The depression and hopelessness self-report measures were gathered at the same

time as the criteria rating measures. The researchers who gathered the interview data were not

aware of the self-report results, which limited potential contamination but precluded a truly

predictive design. Research design issues may explain why with women offenders hope-

lessness is less predictive of future self-harm (i.e., Perry & Gilbody, 2009) and relatively

more predictive of women offender past history of self-harm (i.e., Chapman et al., 2005).

Another limitation is that the DHS has not been used with nonoffender women, as to pro-vide comparisons with women offenders. In the application of measures to women offenders,

Blanchette and Brown (2006) argue that measures developed on women offenders are

optimal, with the development of specific cutoff scores for women offenders as an option.



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Even with unique women cutoff scores, it should be noted that the basic reliabilities and

validities are similar to those of male offenders.

CONCLUSIONS

Other areas of women offender assessment, such as risk assessment, have shown that

gender-neutral instruments can work with women offenders (Blanchette & Motiuk, 2004;

Folsom & Atkinson, 2007; Holtfreter & Cupp, 2007). But whole-scale application of

instruments to a specific population will result in unwanted shortcomings. As with criminal

justice risk assessment, aspects of the DHS basic validities for the Depression and

Hopelessness scales function similarly among male offenders, but the interpretation and

interpretation guidelines should be unique for female offenders.

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Daryl G. Kroner, PhD, is an assistant professor in the Department of Criminology and Criminal Justice at Southern Illinois

University Carbondale. His current projects include mental health assessment of female offenders, dynamic risk assessment

during community supervision, evaluating community interventions, and treatment of offenders with mental illness.

Tamara Kang is a doctoral student in psychology at the University of Texas, El Paso. As a McNair Scholar student, she

completed her undergraduate degree at Southern Illinois University Carbondale. Her research interests include affective

functioning among women offenders.

Jeremy F. Mills, PhD, CPsych, is a psychologist with a practice in forensic, correctional, and counseling psychology in

Kingston, Ontario, Canada. In addition, he serves as adjunct research professor in the Department of Psychology at Carleton

University in Ottawa. He is a fellow of the American Psychological Association, and his research interests include violence

risk assessment, violence risk communication, and the assessment of suicide risk.

Andrew J. R. Harris, PhD, CPsych, is a senior research manager at Correctional Service Canada National Headquarters. His

clinical and research interests center around risk assessment for sexual offenders, with a particular emphasis on the assess-

ment of dynamic risk of reoffense.

Michelle M. Green is a doctoral student in social/personality psychology at Brock University. She recently completed her

masters thesis exploring stress, social support, and health risk behaviors as mediators of the forgivenesshealth relation.

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