The Detailed Assessment of Posttraumatic Stress–Second Edition (DAPS-2): Initial Psychometric Evaluation in an MTurk-Recruited,Trauma-Exposed Community Sample

Abstract

The Detailed Assessment of Posttraumatic Stress (DAPS; Briere, 2001) is a comprehensive questionnaire that assesses posttraumatic stress disorder (PTSD) diagnostic criteria as well as peritraumatic responses and associated problems such as dissociation, suicidality, and substance abuse. DAPS scores have demonstrated excellent reliability, validity, and clinical utility, performing as well or better than leading PTSD questionnaires. The present study was an initial psychometric evaluation of the unreleased DAPS (DAPS-2), revised for Diagnostic and Statistical Manual of Mental Disorders–Fifth edition (DSM-5), in an MTurk-recruited mixed trauma sample (N = 367). DAPS-2 PTSD scale and associated features scales demonstrated high internal consistency and strong convergent and discriminant validity. In confirmatory factor analyses, the DSM-5 four-factor model of PTSD provided adequate fit, but the leading seven-factor model provided superior fit. These results indicate the DAPS-2 is a psychometrically sound measure of DSM-5 PTSD symptoms.

Keywords

detailed assessment of posttraumatic stress psychometric evaluation posttraumatic stress disorder assessment

The Detailed Assessment of Posttraumatic Stress (DAPS; Briere, 2001) is a comprehensive, multiscale questionnaire that assesses trauma exposure and trauma-related symptomatology. Based on the posttraumatic stress disorder (PTSD) diagnostic criteria in the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders–Fourth edition (DSM-IV; American Psychiatric Association, 1994), the DAPS consists of 104 items. These are divided into 13 scales assessing trauma exposure, peritraumatic distress and dissociation, and core symptoms of PTSD, as well as trauma-related functional impairment, associated problems including posttraumatic dissociation, suicidality, substance abuse, and positive and negative response bias. The DAPS can be administered in 20 to 30 minutes and scored in 10 to 20 minutes by individuals with no specialized training. Additionally, the DAPS items are written at a sixth-grade reading level, and DAPS scores are standardized by gender on trauma-exposed adults from the general population, increasing its usefulness for a wide variety of settings and individuals.

With its multiple scales and broad-spectrum approach, the DAPS was designed to address limitations of widely used PTSD measures such as the PTSD Checklist (PCL; Weathers, Litz, Herman, Huska, & Keane, 1993) and the Posttraumatic Stress Diagnostic Scale (PDS; Foa, Cashman, Jaycox, & Perry, 1997). In addition to its coverage of peritraumatic responses, a wide range of associated clinical features, and response bias, the DAPS goes beyond the PCL by assessing trauma exposure and functional impairment, and beyond the PDS by including multiple items for most PTSD symptoms. These additional items provide multiple opportunities for respondents to endorse complex or difficult-to-understand symptoms. This feature is particularly valuable in conducting confirmatory factor analysis (CFA) of PTSD symptoms because all leading CFA models of PTSD include at least one factor with only two symptoms (Armour et al., 2015). Having only one item per symptom limits the models that can be evaluated (Brown, 2015; Witte, Domino, & Weathers, 2015). Last, the DAPS provides a comprehensive clinical assessment of PTSD and comorbid concerns with less participant burden and provider expertise required than clinical interviews like the Clinician-Administered PTSD Scale (CAPS; Blake et al., 1995), which are considered the “gold standard,” or most widely accepted criterion.

Despite these valuable features, the DAPS has received surprisingly little empirical attention. The most extensive presentation of DAPS psychometric information is in the professional manual (Briere, 2001), which provides strong support for the psychometric properties of DAPS scores. As reported in the manual, all DAPS scales have high internal consistency in clinical, community, and university samples. Regarding validity evidence, DAPS PTSD scores are positively associated with number of lifetime traumas, interpersonal nature of the exposure, and peritraumatic distress. Also, DAPS PTSD symptom scales demonstrate good convergent and discriminant validity in that they correlate strongly with other measures of reexperiencing, avoidance, and hyperarousal and less strongly with measures of depression, mania, and somatic complaints. In addition, the DAPS has good diagnostic utility, with high sensitivity (.88) and specificity (.86) in predicting PTSD diagnostic status based on the DSM-IV version of the CAPS.

Apart from the manual, no dedicated psychometric evaluations of the DAPS have been published. However, the DAPS has been used in other studies and has performed as well or better than leading PTSD questionnaires. For example, in a report on the development of the PTSD Checklist for DSM-5 (PCL-5; Weathers, Litz, et al., 2013), the DAPS demonstrated stronger construct validity than the PCL, PCL-5, and PDS, as evidenced by a pattern of predicted associations with convergent and discriminant measures (Blevins, Weathers, Davis, Witte, & Domino, 2015). Furthermore, Witte et al. (2015) demonstrated the value of the unique features of the DAPS in a study evaluating potential order effects in self-rated assessments of PTSD. Specifically, because the DAPS presents PTSD symptoms in a different order than the DSM-correspondent PCL and PDS, and has multiple items for most PTSD symptoms, Witte et al. (2015) were able to test for and ultimately rule out the impact of order effects on the results of structural validity studies of PTSD.

Some of the associated features scales of the DAPS have also been evaluated in the literature. For example, Briere, Scott, and Weathers (2005) used the DAPS to assess both transient and persistent dissociation in trauma survivors as a predictor for PTSD symptoms. DAPS Trauma-Specific Dissociation (T-DIS) subscale scores, which indicate the presence or relative absence of persistent dissociation, were predictive of PTSD status, with high specificity (.97) and moderate sensitivity (.57). Also, Young, Merali, and Ruff (2009) examined the validity scales of the DAPS in relation to the validity scales of the Millon Clinical Multiaxial Inventory–III (MCMI-III; Millon et al., 1997) and Ruff Neurobehavioral Inventory (RNBI; Ruff & Hibbard, 2003) in a sample of motor vehicle accident pain patients without a traumatic brain injury or neurological damage. DAPS positive and negative bias scores correlated predictably with scores from the MCMI-III and RNBI validity scales, indicating that the DAPS may accurately detect faking good as well as “cries for help” or malingering in challenging populations.

In sum, the DAPS has many desirable features, and the manual and additional empirical reports indicate that it is psychometrically sound. The DAPS provides a comprehensive assessment of PTSD clinical presentations, affording broader coverage than the PCL or PDS. Thus, the DAPS yields essential information for making diagnostic and treatment decisions with trauma survivors and does so with less participant response burden and provider expertise needed than a clinical interview.

The DAPS was recently revised for DSM-5 (American Psychiatric Association, 2013). The revised version (DAPS-2) has 15 new items, making it a 119-item measure, with four subscales reflecting DSM-5 PTSD criteria. The original DAPS reexperiencing subscale (RE) retained the same 10 items assessing DSM-5 Criterion B symptoms. In keeping with DSM-5, the DAPS avoidance and numbing subscale (AV) was split into (a) an avoidance subscale (AV), with four original AV items assessing effortful avoidance of trauma reminders; and (b) a new negative alterations in cognition and mood (NACM) subscale, with the other six original AV items, plus four new cognitive items (distrust in others, feeling permanently changed, self-blame, and negative view of self) and four new trauma-related emotional distress items (anxiety, shame, humiliation, or guilt about what happened). The hyperarousal subscale (AR) is now the revised alterations in arousal and reactivity subscale (AR), with the addition of four items assessing aggression and reckless behavior (getting into physical fights, losing temper easily, yelling at people, and being reckless). All items from DAPS associated features scales were retained without modifications for DAPS-2.

Given DSM-5 changes to the DAPS, the aim of the present study was to provide the initial psychometric evaluation of the DAPS-2. Psychometric properties evaluated were (a) internal consistency of DAPS-2 scales, including total PTSD (PTS-T), the four PTSD subscales (RE, AV, NACM, and AR), Suicidality (SUI), Trauma-Related Dissociation (T-DIS), Substance Use (SUB), and Functional Impairment (IMP); (b) convergent and discriminant validity of PTS-T, SUI, and T-DIS; and (c) structural validity of PTS-T.

Regarding DAPS-2 PTSD scales, we hypothesized that DAPS-2 PTS-T and the four PTSD subscales would demonstrate high internal consistency, as evidenced by alpha coefficients >.80 and moderate to high item-scale total correlations and interitem correlations. We further hypothesized that DAPS-2 PTS-T would demonstrate good convergent and discriminant validity with strong effect sizes for construct validity, as evidenced by r_contrast-CV and r_alerting-CV > .70, (Westen & Rosenthal, 2003). Specifically, we expected PTS-T to correlate (a) most strongly with the PCL-5 total (r ≥ .80); (b) nearly as strongly with traumatic intrusions and traumatic avoidance scales on the expanded version of the Inventory of Depression and Anxiety Symptoms (IDAS-II; Watson et al., 2012; rs =.70-.79), (c) moderately with closely related constructs of dissociation, depression, and anxiety (rs = .40-.69); and (d) weakly with a conceptually unrelated measure of appetite gain (r = .20). Additionally, we hypothesized that this pattern of convergent and discriminant correlations for the DAPS-2 PTS-T would be highly similar to the pattern observed for the PCL-5.

Regarding the associated features scales of the DAPS-2, we hypothesized that SUI, T-DIS, SUB, and IMP would demonstrate high internal consistency, as evidenced by alpha coefficients > .80. We further hypothesized that SUI would correlate strongly with a measure of suicidal ideation (r ≥ .80); moderately with measures of depression, anxiety, interpersonal needs, and hopelessness (rs = .40-.69); and weakly with measures of acquired capability for suicidal behavior and discomfort intolerance (r < .30), a pattern of correlations previously demonstrated for other measures of suicidality (Van Orden et al., 2010; Van Orden, Witte, Gordon, Bender, & Joiner, 2008). We also expected T-DIS to be highly correlated with another measure of dissociation (r > .80), and moderately correlated with measures of less-related constructs such as depression and anxiety (rs = .60-.79).

Last, regarding structural validity of the DAPS-2 PTSD items, we used CFA to evaluate four measurement models of DSM-5 PTSD symptoms that are widely used to study other leading PTSD measures (Armour et al., 2015; Blevins et al., 2015): the four-factor DSM-5, six-factor externalizing, six-factor anhedonia, and seven-factor hybrid models (see Table 1). We expected the fit to be adequate for the four-factor DSM-5 model and better for the six- and seven-factor PTSD models (Armour et al., 2015).

Table 1.

Symptom Mappings for Confirmatory Factor Analysis (CFA) of DAPS-2 PTS-T Factor Structure.

DAPS-2 Item	Symptom	Item description	DSM-5	Externalizing behavior	Anhedonia	Hybrid
30, 38, 46	B1	Memories	RE	RE	RE	RE
54	B2	Dreams	RE	RE	RE	RE
50, 62	B3	Flashbacks	RE	RE	RE	RE
34, 42	B4	Cued distress	RE	RE	RE	RE
61, 66	B5	Cued physical reactions	RE	RE	RE	RE
55	C1	Avoiding internal reminders	AV	AV	AV	AV
31, 51, 63	C2	Avoiding external reminders	AV	AV	AV	AV
39	D1	Dissociative amnesia	NACM	NACM	NACM	NACM
67^a, 69^b, 72^b, 75^b	D2	Negative beliefs	NACM	NACM	NACM	NACM
78^b	D3	Blame	NACM	NACM	NACM	NACM
70^b, 73^b, 76^b, 79^b	D4	Negative feelings	NACM	NACM	NACM	NACM
35	D5	Loss of interest	NACM	NACM	AN	AN
43	D6	Detachment or estrangement	NACM	NACM	AN	AN
47, 59	D7	Numbing	NACM	NACM	AN	AN
40^a, 71^b, 74^b, 80^b	E1	Irritability or aggressive behavior	AR	EX	DA	EX
77^b	E2	Reckless behavior	AR	EX	DA	EX
60, 64	E3	Hypervigilance	AR	AA	AA	AA
44, 68	E4	Startle	AR	AA	AA	AA
32, 36	E5	Concentration	AR	DA	DA	DA
48	E6	Sleep	AR	DA	DA	DA
52^c, 56^c		Nonspecific arousal	AR	AA	AA	AA

Note. DAPS-2 = Detailed Assessment of Posttraumatic Stress–Second edition, revised for DSM-5; PTS-T = Posttraumatic Stress Total scale; RE = Reexperiencing; AV = Avoidance; NACM = Negative Alterations in Cognitions and Mood; AR = Alterations in Arousal and Reactivity; EX = Externalizing Behaviors; AN = Anhedonia; DA = Dysphoric Arousal; AA = Anxious Arousal.

DAPS-2 item included in CFAs that does not precisely fit a specific DSM-5 PTSD symptom. ^bDAPS-2 item added for DSM-5 symptom coverage. ^cDAPS-2 item included in CFAs that does not precisely fit a specific symptom within the AR cluster.

Method

Participants and Procedure

Participants were recruited through Amazon’s open-source Mechanical Turk system, which is an efficient, anonymous, and inexpensive recruitment method that reaches a diverse audience of online workers called MTurkers (Chandler & Shapiro, 2016; Hauser, Paolacci, & Chandler, 2019; Miller, Crowe, Weiss, Maples-Keller, & Lynam, 2017). Despite concerns that MTurkers completing surveys online are a restricted, nonnaive convenience sample likely to engage in misrepresentation, cheating, or inattentive responding (Crump et al., 2013; Enochson & Culbertson, 2015; Klein et al, 2013 as cited in Hauser et al., 2019), research has indicated that MTurk generally yields a similar or higher level of data quality as other convenience samples like college students (Hauser et al., 2019; Kees, Berry, Burton, & Sheehan, 2017; Miller et al., 2017).

In accordance with MTurk best practices (Chandler & Shapiro, 2016), possible participants were unobtrusively screened for eligibility criteria of at least 18 years of age, English fluency, and self-identification as having experienced a very stressful life event. With the limitations of MTurk in mind, we screened data and excluded participants from analyses for reasons that may indicate low-effort or low-attention responding such as whole and partial (> 80% missing) survey noncompletion (n = 89 and 56, respectively), unusually fast response times according to pilot testing (i.e., <15 minutes; n = 96), and repeat participation (n = 13), leaving an eligible sample of 550 male and female adults. Participants completed a demographics questionnaire and the measures described below and received $2 as compensation. Mean completion time was 36.7 minutes (min = 15.1; max = 130.6). Participation was anonymous.

Trauma exposure, as defined by DSM-5 Criterion A, was evaluated through review of participants’ responses on the extended version of the Life Events Checklist–5 (LEC-5; Weathers, Blake, et al., 2013b) and written narratives of their index event. The first and fourth authors independently reviewed participants’ LEC-5 responses and written narratives to determine Criterion A status and event type. Interrater agreement for Criterion A status was very high (κ = 0.88, p < .001). Disagreements between raters were resolved through discussion with the raters and the second author, an expert in assessment of trauma exposure and PTSD. Of the 550 eligible participants, 28 were excluded because they did not provide a trauma narrative. An additional 155 were excluded because their index event did not meet Criterion A.

The final sample consisted of 367 individuals with an average age of 36.9 (SD = 12.0; range = 18-74), of whom 44.7% were married, 49.6% were parents, 19.9% were students, and 13.1% were military veterans. The majority of the sample identified as female (59.1%), heterosexual (85.2%), and Caucasian (76.6%). A minority of participants identified their race as Asian (14.4%), Black (5.4%), Native/Indigenous, (1.9%), or Hispanic/Latino (4.9%) and their sexual orientation as homosexual (3.8%) or bisexual (9.9%). The most prevalent event types were transportation accident (32.2%), sexual assault (21.8%), physical assault (10.9%), assault with a weapon (7.9%), and other serious work or recreational accident (6.8%). Provisional DSM-5 PTSD diagnostic status was determined based on the PCL-5, by considering items rated 2 = moderate or higher as symptoms endorsed, and then following the DSM-5 PTSD diagnostic rule (1 reexperiencing symptom, 1 avoidance symptom, 2 NACM symptoms, and 2 hyperarousal symptoms). Based on this approach, 76 (20.7%) participants met criteria for a provisional DSM-5 PTSD diagnosis.

Measures

Descriptive statistics and alpha coefficients for all scales and subscales used in the study are presented in Table 2. Item-level descriptive statistics for DAPS-2 PTSD items are presented in Supplemental Table 1 available online. In addition to the DAPS-2, the following measures were administered.

Table 2.

Scale-Level Descriptive Statistics.

Variable	N	M	SD	Possible range	Obs. range	α
DAPS-2 scales
PTS-T	307	72.5	38.7	40-210	42-204	.99
RE	355	17.7	9.4	10-50	10-50	.96
AV	360	7.1	4.0	4-20	4-20	.89
NACM	341	24.3	13.6	14-70	14-67	.96
AR	341	23.8	13.0	14-70	14-69	.96
IMP	357	8.5	5.0	5-25	5-25	.93
PDST	358	27.5	6.8	8-40	9-40	.78
PDIS	361	18.0	7.3	6-30	6-30	.89
T-DIS	358	6.3	3.8	4-20	4-20	.93
SUB	359	13.1	6.2	10-50	10-47	.92
SUI	358	13.0	6.6	10-50	10-40	.95
PB	355	15.6	7.1	8-40	8-40	.84
NB	362	10.1	4.6	8-40	8-35	.86
PCL-5	350	18.3	19.8	0-80	0-79	.97
MDI	334	50.0	23.7	30-150	30-146	.98
IDAS-II scales
General Depression	335	44.6	17.6	20-100	20-96	.93
Dysphoria	345	21.4	10.2	10-50	10-50	.94
Lassitude	354	13.0	5.9	6-30	6-30	.87
Insomnia	355	13.7	6.5	6-30	6-30	.91
Suicidality	358	13.0	6.6	6-30	6-30	.92
Appetite Loss	359	5.6	3.1	3-15	3-15	.81
Appetite Gain	363	6.2	3.0	3-15	3-15	.81
Well-Being	358	21.1	7.5	8-40	8-40	.88
Ill Temper	361	8.9	4.5	5-25	5-24	.89
Mania	356	8.9	4.7	5-25	5-25	.90
Euphoria	357	8.4	4.0	5-25	5-22	.84
Panic	350	13.6	7.3	8-40	8-40	.93
Social Anxiety	355	11.8	6.2	6-30	6-30	.91
Claustrophobia	356	8.1	4.5	5-25	5-25	.91
Traumatic Intrusions	358	7.6	4.2	4-20	4-20	.91
Traumatic Avoidance	358	8.4	4.1	4-20	4-20	.88
Checking	360	5.7	3.1	3-15	3-15	.87
Ordering	359	9.3	4.3	5-25	5-24	.85
Cleaning	352	12.2	6.0	7-35	7-35	.92
DSI-SS	355	1.4	2.4	0-12	0-9	.93
INQ-R Scales
Thwarted Belongingness	364	12.1	6.4	4-28	4-28	.93
Perceived Burdensomeness	364	8.4	6.4	4-28	4-28	.96
DIS	364	7.5	3.0	0-12	0-12	.92
BHS	364	2.1	0.6	0-4	0-4	.80
ACSS-FAD	364	14.0	6.6	0-28	0-28	.83

Note. DAPS-2 = Detailed Assessment of Posttraumatic Stress–Second edition, revised for DSM-5; PTS-T = Posttraumatic Stress Total scale; RE = Reexperiencing subscale; AV = Avoidance subscale; NACM = Negative alterations in cognitions and mood subscale; AR = Arousal subscale; IMP = Functional Impairment scale; PDST = Peritraumatic Distress scale; PDIS = Peritraumatic Dissociation scale; T-DIS = Trauma-Related Dissociation scale; SUB = Substance Use scale; SUI = Suicidality scale; PB = Positive Bias scale; NB = Negative Bias scale; PCL-5 = PTSD Checklist for DSM-5; MDI = Multiscale Dissociation Inventory; IDAS-II = Inventory of Depression and Anxiety Symptoms–Second edition; DSI-SS = Depressive Symptoms Inventory–Suicidality Subscale; INQ-R = Interpersonal Needs Questionnaire–Revised; DIS = Discomfort Intolerance Scale; BHS = Beck Hopelessness Scale; ACSS-FAD = Acquired Capability for Suicide Scale–Fearlessness about Death.

Life Events Checklist

The LEC-5 (Weathers, Blake, et al., 2013b) is the trauma exposure screener for the Clinician Administered PTSD Scale for DSM-5 (CAPS-5; Weathers, Blake, et al., 2013a). The basic version of the LEC-5 consists of 17 categories of traumatic events. For each category, respondents indicate whether it happened to them, they witnessed it, they learned about it, they were exposed to it as part of their job, they are not sure if it fits, or it does not apply to them. The LEC-5 is used only as a screener to identify an index event for symptom inquiry and has not been evaluated psychometrically as a formal measure of trauma exposure. On the extended version, used in this study, respondents also identify their worst event and answer several questions to determine if it meets Criterion A for PTSD. In the current study, participants also label and briefly describe the worst event experience and are instructed to complete the PTSD symptom measures that follow in reference to the worst event.

PTSD Checklist for DSM-5

The PCL-5 (Weathers, Litz, et al., 2013) is a 20-item questionnaire measure of PTSD. Respondents indicate how much they were bothered by each PTSD symptom in the past month on a 5-point scale from 0 = not at all to 4 = extremely (Weathers, Litz, et al., 2013). The PCL-5 has been shown to be psychometrically sound, with high internal consistency and test–retest reliability, as well as strong convergent and discriminant validity (Blevins et al., 2015; Bovin et al., 2016; Wortmann et al., 2016). In the current study, alpha for PCL-5 PTSD full scale was .97.

Multiscale Dissociation Inventory

The Multiscale Dissociation Inventory (MDI; Briere, 2002) is a 30-item questionnaire measure of dissociative symptomatology. The MDI measures six different types of dissociative responses that can accompany individual reactions to trauma such as disengagement, depersonalization, memory disturbance, and others. Respondents indicate the frequency of each dissociative symptom over the past month on a 5-point scale from 1 = never to 5 = very often. Normative scores on the MDI are based on a standardization sample of 444 trauma-exposed individuals. The MDI has been demonstrated to be a psychometrically sound measure of dissociation in several samples and populations (Briere, 2002). In the current study, alpha for MDI dissociation full scale was .98.

Inventory of Depression and Anxiety Symptoms

The IDAS-II (Watson et al., 2012) is a 99-item questionnaire measure of depression, anxiety, and related symptomatology. The IDAS-II consists of 99 items, organized into a General Depression scale and 18 other nonoverlapping scales. Respondents indicate how much they have experienced each symptom on a 5-point scale from 1 = not at all to 5 = extremely. IDAS-II scales have demonstrated high internal consistency and good convergent and discriminant validity with other questionnaire and interview measures of depression, mania, and anxiety (Watson et al., 2012). In the current study, alphas for IDAS-II scales ranged from .81 to .94.

Depressive Symptom Inventory–Suicidality Subscale

The Depressive Symptom Inventory–Suicidality Subscale (DSI-SS; Metalsky & Joiner, 1997) is a four-item questionnaire measure of suicidality. Respondents indicate the frequency and intensity of their suicidal ideation and behaviors in the previous 2 weeks, for which higher scores indicate greater severity of suicidal ideation. In the current study, alpha for the DSI-SS was .93.

Interpersonal Needs Questionnaire–Revised

The Interpersonal Needs Questionnaire–Revised (INQ-R; Van Orden, Cukrowicz, Witte, & Joiner, 2012) is a 15-item questionnaire measure derived from the interpersonal theory of suicide and developed to measure thwarted belongingness and perceived burdensomeness—two hypothesized proximal causes of desire for suicide. Respondents indicate agreement with recent perceptions of themselves and others on a 7-point scale from 1 = not at all true for me to 7 = very true for me, for which higher scores indicate higher levels of perceived burdensomeness or thwarted belongingness. In the current study, alphas for INQ-R perceived burdensomeness and thwarted belongingness were .96, and .92, respectively.

Acquired Capability for Suicide Scale–Fearlessness About Death

The Acquired Capability for Suicide Scale–Fearlessness About Death (ACSS-FAD; Ribeiro et al., 2014) is a 7-item version of the original 20-item ACSS, a questionnaire measure of insensitivity to death, which is theorized as a contributor to suicidal behavior and distinct from desire for death. Psychometric investigation of the ACSS-FAD supports the construct validity and use of this shortened version (Ribeiro et al., 2014). Respondents indicate the extent to which statements about fearlessness of death describe them on a 5-point scale from 0 = not at all like me to 4 = very much like me. In the current study, alpha for the ACSS-FAD was .85.

Discomfort Intolerance Scale

The Discomfort Intolerance Scale (DIS; Schmidt et al., 2006) is a two-item questionnaire measure that assesses the degree to which respondents are capable of tolerating sensations of physical discomfort. Respondents indicate the extent to which statements about tolerating pain describe them on a 7-point scale from 0 = not at all like me to 6 = extremely like me. In the current study, alpha for the DIS was .92.

Beck Hopelessness Scale

The Beck Hopelessness Scale (BHS; Beck & Steer, 1988) is a 20-item, true–false questionnaire measure of positive and negative beliefs about the future. The BHS has been found to be psychometrically sound across diverse clinical and nonclinical populations (Beck, Schuyler, & Herman, 1974; Beck, Weissman, Lester, & Trexler, 1974). Following Yip and Cheung (2006), a four-item version of the BHS was used, for which alpha was .80.

Data Analysis

We conducted latent variable modeling using Mplus version 7 (Muthén & Muthén, 1998-2013). For all other analyses, we used IBM SPSS version 22.0. We evaluated internal consistency for PTS-T, SUI, and T-DIS with alpha and examination of item-scale total and interitem correlations. We assessed convergent and discriminant validity for PTS-T, SUI, and T-DIS using Pearson correlations between scores. We also calculated effect size correlations, r_alerting-CV and r_contrast-CV, (Westen & Rosenthal, 2003) to quantify degree of correspondence between predicted and obtained correlations between the DAPS-2 PTS-T, PCL-5, and criterion measures. All variables were positively skewed, as is typical with most measures of psychopathology in nonclinical samples. We detected three multivariate outliers (0.8%) which were retained in the final sample due to insufficient evidence they were not part of the target population and no substantive change in results with their removal.

We examined the latent factor structure of DAPS-2 PTS-T items using CFA using the robust maximum likelihood estimator (MLR; Brown, 2006; Chou & Bentler, 1995; Curran, West, & Finch, 1996). The covariance coverage matrix indicated that the proportion of data present for each pairwise combination of variables was .97 to 1.0. To handle missing data, we used full information maximum likelihood (FIML; Enders, 2010; Schafer & Graham, 2002).

DAPS-2 items were allowed to load onto factors as specified by a given model (see Table 1), and the residual variances of items measuring the same symptom were allowed to correlate (see Witte et al., 2015). Because the DAPS-2 has multiple items for many PTSD symptoms, researchers have more flexibility when selecting items to scale the latent variables, in order to avoid common problems of misspecification and inflated factor loadings or model fit (Brown, 2015; Rasmussen, Verkuilen, Jayawickreme, Wu, & McCluskey, 2019; Witte et al., 2015). Specifically, scaling latent variables using symptoms assessed with multiple items better ensures that all symptoms representing the factors are included. In the current study, CFA factors were identified or scaled using items that correspond to a PTSD symptom assessed with multiple DAPS-2 items (i.e., Item 31 instead of 55 for AV; Item 67 instead of Item 39 for NACM; Item 47 instead of 35 or 43 for Anhedonia).

For the purposes of CFA with the full DAPS-2, all items were included in the models. However, four DAPS items (40, 52, 56, and 67) do not precisely fit a DSM-5 symptom. Item 40 (People irritating you more than they did before the experience) partially fits DSM-5 PTSD criterion D4 (persistent negative emotional state), but best fits E1 in the hyperarousal cluster, so we included it under DAPS-2 AR. Item 67 (Feeling like you won’t have much of a future) best fits DSM-5 criterion D2, which is an expanded version of DSM-IV criterion C7, so we included it under NACM. Items 52 (Feeling more restless since it happened) and 56 (Feeling jumpy or on edge since it happened) do not fit a specific DSM-5 hyperarousal symptom, yet clearly belong on the hyperarousal cluster, so we also included these under AR. Following Witte et al. (2015), we allowed items 40, 52, 56, and 67 to load onto corresponding symptom clusters with no correlated residuals. Also, we ran CFAs for the DSM-5 four-factor model with and without items 40, 52, 56, and 67, and model fit did not substantially differ.

For all models, we evaluated model fit using a variety of fit indices: χ² (p ≥ .05), Bentler’s comparative fit index (CFI ≥ .90; Bentler, 1990), Tucker–Lewis index (TLI ≥ .90; Bentler, 1990), and standardized root mean square residual (SRMR < .08; Hu & Bentler, 1999). The 90% confidence intervals for root mean square error of approximation (RMSEA) were also evaluated according to the close-fit (i.e., retained if p > .05), and poor-fit (retained if upper limit of 90% confidence interval ≥ .10) hypotheses (Browne & Cudeck, 1993; Kline, 2011). The DSM-5 four-factor, six-factor externalizing, and six-factor anhedonia models are all nested within the seven-factor hybrid model. Thus, we performed nested model comparisons using the robust χ² difference test (Satorra & Bentler, 2001). Finally, we compared all models using the Akaike information criterion (AIC; Anderson, Burnham, & Thompson, 2000) and the Bayesian information criterion (BIC; Kass & Wasserman, 1995), for which lower values indicate greater likelihood to replicate and are preferred (Kline, 2011). Additionally, post hoc power analyses (MacCallum, Browne, & Sugawara, 1996) revealed adequate power in the sample for tests of close and not-close fit for all models (N = 367, df = 619-634, power = 1.000).

Results

DAPS-2 PTSD Scales

Internal Consistency

Internal consistency was high for DAPS-2 PTS-T and the four DSM-5 symptom clusters. Alpha was .99 for PTS-T, .96 for RE, .89 for AV, .96 for NACM, and .96 for AR. See Table 2 for full scale and subscale descriptive statistics. Corrected item-total correlations across all 42 DAPS-2 PTSD items ranged from .63 to .88, with a mean of .81. Interitem correlations ranged from .44 to .89, with a mean of .65. Many interitem correlations exceeded the upper end of the range of .15 to .50 recommended by Clark and Watson (1995). See Supplemental Table 1 (available online) for item-level descriptive statistics.

Convergent and Discriminant Validity

As shown in Table 3, regarding convergent validity, PTS-T generally correlated as expected with measures of PTSD and constructs theoretically differentially related to PTSD including dissociation, general depression, panic, obsessive–compulsive disorder, and appetite loss. Construct validity effect size correlations between DAPS-2 PTS-T and criterion measures were high (r_contrast-CV = 0.78; r_alerting-CV = 0.80) and similar to the pattern of associations produced by the PCL-5 and criterion measures (see Table 3).

Table 3.

Predicted and Observed Correlations Between PTSD Measures and Criterion Measures, Raw λs, and Integer Values of Raw λs.

Criterion variable	Observed correlations		Predicted correlations and λs
Criterion variable	DAPS-2, r (pr)	PCL-5, r (pr)	Predicted r	Raw λs	Raw λs as integers
DAPS-2 PTS-T	—	.91 (.86)	.80	.24	2
PCL-5 total	.91 (.86)	—	.80	.24	2
IDAS-II Traum Int	.67 (.43)	.73 (.42)	.70	.14	1
IDAS-II Traum Av	.60 (.30)	.70 (.39)	.70	.14	1
MDI Drl	.75 (.64)	.77 (.69)	.60	.04	0
MDI Dpr	.74 (.64)	.76 (.69)	.60	.04	0
IDAS-II Gen Dep	.62** (.14*)	.70** (.16*)	.60	.04	0
IDAS-II Panic	.69 (.41)	.71 (.39)	.50	−.06	−1
IDAS-II Soc Anx	.59 (.19)	.66 (.23)	.50	−.06	−1
IDAS-II OCD	.47** (.16*)	.55 (.20)	.40	−.16	−2
IDAS-II App Gain	.32** (−.03)	.37** (.01)	.20	−.36	−4

Note. N = 367. DAPS-2 = Detailed Assessment of Posttraumatic Stress–Second edition, revised for DSM-5; PTS-T = Posttraumatic Stress Total scale; PCL-5 total = PTSD Checklist for DSM-5 total; IDAS-II = Inventory of Depression and Anxiety Symptoms–Second edition; IDAS-II Traum Int = IDAS-II, Traumatic Intrusions Scale; IDAS-II Traum Av = IDAS-II, Traumatic Avoidance Scale; MDI Drl = Multiscale Dissociation Inventory, Derealization Scale; MDI Dpr = MDI, Depersonalization Scale; IDAS-II Gen Dep = IDAS-II, General Depression Scale; IDAS-II Panic = IDAS-II, Panic Scale; IDAS-II Soc Anx = IDAS-II, Social Anxiety Scale; IDAS-II OCD = IDAS-II, Obsessive–Compulsive Disorder–Checking Behavior Scale; IDAS-II App Gain = IDAS-II, Appetite Gain Scale. Partial correlations, controlling for IDAS-II Dysphoria, are reported in parentheses.

p < .05. **p < .01.

Although the discriminant correlations fit the hypothesized pattern, in general they were higher than predicted. To determine if this was due in part to the influence of nonspecific distress on self-report measures, we calculated partial correlations between DAPS-2 PTS-T, PCL-5, and each of the criterion measures, controlling for IDAS-II Dysphoria, conceptually the best measure of nonspecific distress in the battery. This analysis revealed a much more sharply delineated pattern of convergent and discriminant correlations. The partial correlation between PTS-T and PCL-5 remained high (.86), but partial correlations with the other criterion measures were substantially lower than the bivariate correlations (see Table 3).

DAPS-2 Associated Features Scales

Internal Consistency

As shown in Table 2, internal consistency was high for all DAPS-2 associated features scales.

Convergent and Discriminant Validity

Suicidality Scale

Regarding convergent validity, SUI was most strongly correlated with measures of suicidal ideation, plan, and intent, including the DSI-SS (r = .71, p < .001) and the IDAS-II SUI (r = .73, p < .001) as expected. SUI was also strongly related to INQ-R Perceived Burdensomeness (r = .70, p < .001). Regarding discriminant validity, SUI was moderately correlated with IDAS-II General Depression (r = .55, p < .001), weakly correlated with INQ-R Thwarted Belongingness (r = .28, p < .001), and very weakly correlated with the ACSS-FAD (r = −.02, p = .75), DIS (r = .02, p = .68) and BHS (r = .13, p = .01) which were lower than expected.

Trauma-Related Dissociation Scale

Regarding convergent validity, T-DIS was strongly correlated with MDI Depersonalization and Derealization, (r = .78, r = .78, p < .001). T-DIS was also very strongly related to PCL-5 scores (r = .84, p < .001). Regarding discriminant validity, T-DIS was moderately correlated with IDAS-II General Depression (r = .59, p < .001) and IDAS-II Panic (r = .63, p < .001).

Latent Factor Structure

CFA results replicated previous factor analytic findings that the DSM-5 model has adequate fit, but that more complex models provide better fit (Armour et al., 2015). For the DSM-5 model, fit was adequate according to some fit statistics (SRMR = 0.04), but not others (χ² = 1640.95, df = 782, p < .001; TLI = .89; CFI = .90). We rejected the null hypotheses that the fit was either close (RMSEA p = .02) or poor (90% confidence interval [0.051, 0.058]). Additional CFA results for the DSM-5 four-factor model without items 40, 52, 56, and 67 produced marginal differences in fit statistics that did not affect overall model fit characterization.

In the current sample, robust χ² difference tests demonstrated that the seven-factor hybrid model fit the data significantly better than the DSM-5 four-factor (χ² = 93.49, df = 15, p < .001), six-factor externalizing (χ² = 59.75, df = 6, p < .001), and six-factor anhedonia (χ² = 22.02, df = 6, p = .001) models of PTSD symptoms (see Table 4 for fit statistics for each model). Moreover, both six-factor models had significantly better fit with the data than the DSM-5 four-factor model (externalizing χ² = 29.17, df = 9, p = .001; anhedonia χ² = 69.15, df = 9, p < .001). The seven-factor hybrid model also demonstrated the lowest Akaike (AIC = 31673.41) and Bayesian (BIC = 32368.56) information criterion values, indicating that it is the most likely of the four models to replicate in subsequent samples. According to fit statistics, the fit of the hybrid model was adequate (i.e., χ², CFI, TLI) to superior (i.e., RMSEA, SRMR). The standardized loadings of items on to the latent factors were all statistically significant and greater than .63 (see Supplemental Table 2 available online). The correlations among latent variables were all significant and greater than .53 (see Supplemental Table 3 available online). Specifically, the Dysphoric Arousal, Anxious Arousal, Anhedonia, and Avoidance clusters were all very highly intercorrelated (r ≥ .91).

Table 4.

Fit statistics for Models of PTSD Symptom Structure Using the DAPS-2.

Model	χ²	df	p	RMSEA [90% CI]	p	SRMR	CFI	TLI
Four-factor DSM-5 model	1640.95	782	<.001	.055 [.051, .058]	.019	.037	.903	.893
Six-factor Externalizing model	1607.67	773	<.001	.054 [.051, .058]	.031	.036	.906	.895
Six-factor Anhedonia model	1540.87	773	<.001	.052 [.048, .056]	.187	.041	.913	.903
Seven-factor Hybrid model	1515.06	767	<.001	.052 [.048, .055]	.248	.040	.916	.905

Note. N = 367 for all models. DAPS-2 = Detailed Assessment of Posttraumatic Stress–Second edition, revised for DSM-5; CI = Confidence Interval; DSM-5 = Diagnostic and Statistical Manual of Mental Disorders–Fifth edition; RMSEA = root mean square error of approximation; SRMR = standardized root mean square residual; CFI = Bentler’s comparative fit index; TLI = Tucker–Lewis index.

Discussion

This study provided an initial psychometric evaluation of revised DSM-5 version of the DAPS, that is, the DAPS-2, which has not yet been released. Although existing psychometric research on the DAPS is limited, the results of the present study support the reliability and construct validity of DAPS-2 scores for measuring PTSD symptoms in a trauma-exposed, diverse community sample.

First, as expected, DAPS-2 PTSD total scores demonstrated high internal consistency. However, alpha coefficients and interitem correlations were very high, indicating that the DAPS-2 PTS-T has a large number of items that are strongly related and potentially redundant. The associated features scales of the DAPS-2 (SUI, T-DIS, SUB, and IMP) also demonstrated high internal consistency, as evidenced by high coefficient alphas and strong item-total and interitem correlations.

Second, as expected, DAPS-2 PTS-T scores demonstrated patterns of convergent and discriminant correlations that corresponded with predictions for highly, moderately, and weakly related constructs and were similar to the pattern of discriminant correlations found for the PCL-5, providing good evidence of construct validity. Many discriminant correlations were higher than predicted, indicating a greater than expected overlap between measures of conceptually distinct constructs in this sample. This may be attributable in part either to heterogeneity of the sample, with some participants having very high levels of psychopathology and others having low levels, or to the influence of nonspecific distress on responses to self-rated measures of psychopathology. The latter possibility was supported by the finding that partial correlations between the PTS-T, PCL-5, and criterion measures while controlling for nonspecific distress resulted in a much more sharply delineated pattern of convergent and discriminant associations.

Third, we found evidence of good convergent and discriminant validity for both the SUI and T-DIS scales of the DAPS-2 in that scores produced the expected patterns of convergent and discriminant correlations with related and unrelated constructs. These findings support the use of the DAPS-2 for the assessment of conditions that are frequently comorbid with PTSD. Last, as expected, factor analytic results for the DAPS-2 were consistent with the growing volume of literature exhibiting the relatively better fit of the seven-factor hybrid model (Armour et al., 2015) and other empirical models compared with the theoretically derived DSM-5 implicit four-factor model. Furthermore, in the present study, the DAPS-2 PTSD total scale performed similarly to the PCL-5 in CFA, providing additional evidence for the DAPS-2’s structural validity.

Taken together, the findings provide substantial evidence that the DAPS-2 is a psychometrically sound questionnaire for assessing PTSD and related concerns in a community sample. In combination with past side-by-side comparisons of the DAPS-2 to other leading PTSD questionnaires, this study illustrates that the DAPS-2 is likely to provide more comprehensive information and a slightly higher level of PTSD construct validity compared to other DSM-5 correspondent measures like the PCL-5. The length of the DAPS-2 is both a weakness—prohibiting use in routine clinical screening contexts—and a strength—allowing for the most comprehensive assessment of PTSD symptoms and comorbid concerns to date. It is important to note that this study illustrated the DAPS-2 can be completed within a short time-frame by respondents, reducing concern about participant burden. It appears the DAPS-2 is particularly well-suited for conceptualization and planning in assessment and treatment contexts, where it is desirable to gather information about suicide risk, response style, PTSD symptoms, and other relevant concerns for treatment selection, response, and interfering behaviors. In addition, these findings indicate the properties of the DAPS-2 are also advantageous for researchers examining the PTSD construct.

One notable limitation is the very high alphas and interitem correlations for DAPS-2 PTS-T, which suggest redundancy and warrant further exploration. Since alpha is a function of both the interitem correlations and scale length, it is likely that the length of the DAPS-2 contributed to high alphas. Large interitem correlations may also be due to the use of a heterogeneous sample in which some individuals endorsed either very high PTSD symptoms or very low PTSD symptoms.

However, perhaps the most salient source of large interitem correlations is the purposeful inclusion of multiple items that capture slightly different aspects of multifaceted symptoms. While excessively high internal consistency may be a concern for the DAPS-2, we would argue that the redundancy this implies results from deliberately unpacking complex PTSD symptoms and including multiple items for each aspect of a given symptom. In this sense, the redundancy can be seen as a strength in that it results from the DAPS-2’s comprehensive and molecular coverage of symptom content. This, as we have noted, makes the DAPS-2 uniquely advantageous for certain research applications such as CFA, as well as for detailed clinical assessment of trauma survivors. Because of its length and extensive content coverage, the DAPS-2 is not well-suited as a brief screening measure for PTSD, but would be a valuable resource when a more comprehensive assessment of a PTSD clinical presentation is needed.

Another notable concern is the presence of high factor intercorrelations in the CFA models, especially in the seven-factor hybrid model, in which the Dysphoric Arousal, Anxious Arousal, and Anhedonia clusters were all highly intercorrelated (r > .91). This is a typical finding in CFA studies of PTSD (Elhai et al., 2011; Rasmussen et al., 2019; Reddy, Anderson, Liebschutz, & Stein, 2013; Silverstein, Dieujuste, Kramer, Lee, & Weathers, 2018), so is not a specific issue for the DAPS-2, but it contributes to ongoing discourse about whether such highly correlated latent factors represent distinct constructs (see Silverstein et al., 2018). In a recent critical review of 23 DSM-5 CFA papers utilizing 27 samples, Rasmussen et al. (2019) note high factor intercorrelations are likely prevalent across CFA models of most complex psychopathology constructs. They suggest the high interfactor covariance is explained by (a) magnified associations between constructs due to general psychological distress and high comorbidity, (b) inclusion of unnecessary factors that are not conceptually distinct or uniquely relevant to the construct, and (c) misspecifications of nonzero cross loadings in CFA models that inflate relationships among factors. Although outside the scope of the current study, future researchers should explore alternatives to CFA modeling to evaluate and address potential statistical bias.

There are several limitations of the present study. First, only questionnaire measures were used, so correlations may have been inflated due to shared method variance. The use of questionnaire data also restricted us to identifying provisional prevalence rates of PTSD in the samples as opposed to diagnostic status from a clinical interview. In future investigations of the DAPS-2, it will be particularly important to administer a diagnostic interview for PTSD, such as the CAPS-5, to evaluate diagnostic utility. Second, participants were a community sample of English-speaking adults who experienced a Criterion A traumatic event. Only 20.7% of participants met DSM-5 criteria for a provisional PTSD diagnosis, so the current findings may not generalize to a clinical sample with a higher prevalence of PTSD and possibly higher levels of comorbid psychopathology.

Third, participants were recruited through MTurk. It is possible that this diverse sample of online MTurk workers does not represent the typical community sample of trauma-exposed adults. However, participants reported a variety of traumatic experiences, ranging from moderate to very severe in intensity, which is likely similar to the range of traumatic events experienced in the general population. Researchers have also raised concerns about the validity of data sourced from MTurk, including that participants may answer inattentively or in a socially desirable manner, share answers online, or even use automated “bots” to respond to questions (Bai, 2018). To address this concern, we followed general principles outlined by Chandler and Shapiro (2016) including (a) ensuring the visual survey design was easy to read and not tedious; (b) limiting participants to fluent English speakers; (c) prescreening unobtrusively for the target population (e.g., individuals with a stressful life event); (d) reorienting participants to their previously identified “worst event”; and (e) excluding participants with low-effort or low-attention responding. Other researchers note that MTurk is a valuable recruitment tool when used carefully, the quality of data produced by MTurk generally compares favorably with other samples, and the incident rate of participant misrepresentation, cheating, and inattentiveness is low and similar to college-recruited samples (Hauser et al., 2019).

Despite these limitations, the present study provides substantial evidence that the DAPS-2 is a psychometrically sound assessment tool for DSM-5 PTSD and related symptomatology. On its release, the DAPS-2 will be the most comprehensive PTSD questionnaire available, providing detailed assessment of all DSM-5 PTSD criteria, as well as peritraumatic responses, common comorbid problems including dissociation, suicidality, and substance abuse, and positive and negative response bias. The present study contributes to the relatively modest psychometric literature on the DAPS and supports the use of the DAPS-2 for a wide range of clinical and research applications.

Supplemental Material

Supplemental_Table_1_DAPS_Revised – Supplemental material for The Detailed Assessment of Posttraumatic Stress–Second Edition (DAPS-2): Initial Psychometric Evaluation in an MTurk-Recruited, Trauma-Exposed Community Sample

Supplemental material, Supplemental_Table_1_DAPS_Revised for The Detailed Assessment of Posttraumatic Stress–Second Edition (DAPS-2): Initial Psychometric Evaluation in an MTurk-Recruited, Trauma-Exposed Community Sample by Jessica M. Petri, Frank W. Weathers, Tracy K. Witte and Madison W. Silverstein in Assessment

Supplemental Material

Supplemental_Table_2_DAPS_Revised – Supplemental material for The Detailed Assessment of Posttraumatic Stress–Second Edition (DAPS-2): Initial Psychometric Evaluation in an MTurk-Recruited, Trauma-Exposed Community Sample

Supplemental material, Supplemental_Table_2_DAPS_Revised for The Detailed Assessment of Posttraumatic Stress–Second Edition (DAPS-2): Initial Psychometric Evaluation in an MTurk-Recruited, Trauma-Exposed Community Sample by Jessica M. Petri, Frank W. Weathers, Tracy K. Witte and Madison W. Silverstein in Assessment

Supplemental Material

Supplemental_Table_3_DAPS_Revised – Supplemental material for The Detailed Assessment of Posttraumatic Stress–Second Edition (DAPS-2): Initial Psychometric Evaluation in an MTurk-Recruited, Trauma-Exposed Community Sample

Supplemental material, Supplemental_Table_3_DAPS_Revised for The Detailed Assessment of Posttraumatic Stress–Second Edition (DAPS-2): Initial Psychometric Evaluation in an MTurk-Recruited, Trauma-Exposed Community Sample by Jessica M. Petri, Frank W. Weathers, Tracy K. Witte and Madison W. Silverstein in Assessment

Footnotes

Authors’ Note

Reproduced by special permission of the Publisher, Psychological Assessment Resources, Inc., 16204 N. Florida Avenue, Lutz, FL 33549, from the Detailed Assessment of Posttraumatic Stress by John Briere, PhD. Copyright 1998, 2000, 2001 by PAR. Further reproduction is prohibited without permission from PAR, Inc. Madison W. Silverstein is now affiliated with Loyola University New Orleans, New Orleans, LA, USA.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by Dr. John Briere, who contributed funds for participant reimbursement and provided the new DAPS items to be evaluated. He had no role in the design or conduct of the research, analyses or interpretation of data, writing of the report, or decision to submit the article for publication.

ORCID iD

Jessica M. Petri

Supplemental Material

Supplemental material for this article is available online.

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