This is a revised version of the GADQ (Roemer, Borkovec, Posa, & Borkovec, 1995) designed to diagnose Generalized Anxiety Disorder (GAD) based on DSM-IV and DSM-5 criteria. This 9 item self-report questionnaire was modeled after the ADIS-IV but diagnostic criteria have remained unchanged in GAD-5. Thus, it includes four yes/no questions designed to assess whether the participant has experienced excessive and uncontrollable worry, a section where the participant writes his or her most frequent worry topics, and a question about whether the participant has experienced worry more days than not. If participants indicate that they have not experienced worry more days than not, they are asked to skip the remaining questions. The remainder of the questionnaire includes a checklist of the 6 GAD symptoms. Two final questions require the participant to rate the degree of distress and of interference resulting from the worry on an 8-point Likert scale, a rating of 0 being none, 4 being moderately, and 8 being very severely. This questionnaire can be scored two different ways: (a) determination whether an individual meets diagnostic criteria, and (b) creation of a sum total score. Participants were said to meet GAD criteria if they indicated: (1) having experienced excessive and uncontrollable worry (i.e., they answered yes to item 1 or item 4, or the combination of items 2 and 3, or any other combination of the 1st four items that indicated that the individual worried excessively and uncontrollably), (2) the worry occurred more days than not for at least six months (i.e., they answered yes to item 6), (3) they worried about a number of events or activities (i.e., they indicated three or more worry topics on item 5), (4) they reported experiencing three or more of six symptoms during the past six months (i.e., they checked off three or more symptoms in response to item 7) and the symptoms have caused at least moderate distress or moderate impairment (i.e., they scored 4 or more on item 8 or 9). To create a total score, all yes answers were coded as 1 and all no answers as 0 (e.g. items (1) Do you experience excessive worry? (2) Is your worry excessive in intensity, frequency, or amount of distress it causes, (3) Do you find it difficult to control your worry? (4) Do you worry about minor things? and (6) worry more days than not over the prior six months). In addition, for item 5 which asks for a list of most frequent worry topics, individuals were given 1 point for each topic listed up to 6 and this total was divided by three. Similarly, for item 7, participants were given 1 point for each physical symptom they experienced up to six and this total was divided by three. Finally, the numbers circled for items 8 and 9 (i.e., degree of distress and interference) were each divided by four and these numbers were added together. Because the questionnaire requests that individuals skip the remaining items when they do not endorse initial criteria, such skipped items were scored as 0. Total scores ranged from 0 to 13. Receiver Operating Characteristic analyses examined the optimal cut-off to discriminate participants with GAD from those with social phobia, panic disorder, and nonanxious controls. Results showed that the optimal balance between sensitivity and specificity was achieved with a cutoff point of 5.7. This cutoff leads to a sensitivity of 83% (25 of 30) and a specificity of 89% (101 of 113). Thus, using this cutoff, the rate of false positive diagnoses by the GAD-Q-IV was 11% and the rate of false negative diagnoses assigned by the GAD-Q-IV was 17%. Kappa agreement between the ADIS-IV and the GAD-Q-IV was .67 with 88% of participants correctly classified. The GAD-Q-IV also demonstrated retest reliability. The GAD-Q-IV at Time 2 was reliably predicted by Time 1 score c2 (1, N = 148) = 42.1, p < .001 and 92% (136/148) of the sample showed stability across time in terms of their categorization. Convergent and discriminant validity were also demonstrated by results showing that the GADQ-IV was significantly more highly correlated (r = .66) with the Penn State Worry Questionnaire (PSWQ) than it was with the PTSD checklist (r = .45) or with the Social interaction Anxiety Scale (r = .34) and in another sample, the correlation between the GAD-Q-IV and PSWQ (r = .55), t (145) = 2.27, p < .05 was significantly higher than the correlation between the GAD-Q-IV and Panic Disorder Severity Scale (r = .30) and higher than the correlation between the GAD-Q-IV and Zung self-rating Depression Scale (r = .26). Students diagnosed GAD by the GAD-Q-IV were not significantly different on two GAD (PSWQ, and Response to Relaxation and Arousal Questionnaire) than a GAD community sample, but both groups had significantly higher scores than students identified as not meeting criteria for GAD, demonstrating clinical validity of the GAD-Q-IV. As noted above, the scale can also be used to determine if participants meet full GAD diagnostic criteria, which is a more stringent criterion than the original 5.7 cutoff endorsed by Newman et al. (2002). Using this criterion, Newman et al. found 96% specificity and 67% sensitivity in detecting GAD. Also, in a primary care psychotherapy seeking sample, Moore, Anderson, Barnes, Haigh, and Fresco (2014) found that requiring participants to meet full DSM–IV criteria was the optimal strategy for identifying. The measure also showed excellent and similar psychometric properties across 4 racial groups (Robinson et al., 2010). Another study showed that the scale also had excellent sensitivity and specificity of identifying GAD in older adults (Staples et. al., 2012) and in postpartum mothers (Pierson et al., 2017).
Moore, M. T., Anderson, N. L., Barnes, J. M., Haigh, E. A. P., & Fresco, D. M. (2014). Using the GAD-Q-IV to identify generalized anxiety disorder in psychiatric treatment seeking and primary care medical samples. Journal of Anxiety Disorders, 28, 25-30. doi:10.1016/j.janxdis.2013.10.009
Newman, M. G., Zuellig, A. R., Kachin, K. E., Constantino, M. J., Przeworski, A., Erickson, T., & Cashman-McGrath, L. (2002). Preliminary reliability and validity of the Generalized Anxiety Disorder Questionnaire-IV: A revised self-report diagnostic measure of generalized anxiety disorder. Behavior Therapy, 33, 215-233. doi:10.1016/S0005-7894(02)80026-0
Newman, M. G., Zuellig, A. R., Kachin, K. E., Constantino, M. J., Przeworski, A., Erickson, T., & Cashman-McGrath, L. (2002). Generalized Anxiety Disorder Questionnaire-IV (GAD-Q-IV). PsycTESTS. doi:10.1037/t04994-000
Pierson, M. E., Prenoveau, J. M., Craske, M. G., Netsi, E., & Stein, A. (2017). Psychometric properties of the Generalized Anxiety Disorder Questionnaire - IV (GAD-Q-IV) in postpartum mothers. Psychological Assessment, 29, 1391-1399. doi:10.1037/pas0000443
Robinson, C. M., Klenck, S. C., & Norton, P. J. (2010). Psychometric properties of the Generalized Anxiety Disorder Questionnaire for DSM-IV among four racial groups. Cognitive Behaviour Therapy, 39, 251-261. doi:10.1080/16506073.2010.486841
Staples, A. M., & Mohlman, J. (2012). Psychometric properties of the GAD-Q-IV and DERS in older, community-dwelling GAD patients and controls. Journal of Anxiety Disorders, 26, 385-392. doi:10.1016/j.janxdis.2012.01.005
The SPDQ is a 29-item self-report measure can be used to diagnose social phobia based on DSM-5 criteria. It is scored by using a sum total response. This scoring system was devised in an attempt to create a score that would best enable detection of the presence of social phobia. To create a total score, all yes answers were coded as 1 and all no answers as 0 (e.g. items (1) Nervous or fearful of social situations? (2) Overly worried that you may embarrass yourself, (3) Do you try to avoid social situations? (24) Experience fear each time? (25) Fear come on as soon as you encounter the situation? (26) Is social fear excessive or unreasonable? Additional items (e.g., 4a, 5a, 6a, 7a, 8a, 9a,10a, 11a, 12a, 13a, 14a, 15a, 16a, 17a, 18a, 19a) were each divided by four, whereas distress and interference items (i.e., 27 and 28) were divided by 2 and these numbers were added to the total. Total scores ranged from 0 to 31. In order to determine the ability of the SPDQ, to discriminate people with social phobia from those with GAD, panic disorder, and from nonanxious control participants, Receiver Operating Characteristics (ROCs) of this measure were analyzed comparing the SPDQ to ADIS diagnosis. The optimal balance between sensitivity and specificity was achieved with a cutoff point of 7.38. This cutoff leads to a sensitivity of 82% (49 of 60) and a specificity of 85% (55 of 65). Thus, using this cutoff, the rate of false positive diagnoses by the SPDQ was 15% and the rate of false negative diagnoses assigned by the SPDQ was 18%. Kappa agreement between the ADIS and the SPDQ was .66 with 83% of participants correctly classified. Results of Cronbach's Alpha showed that the SPDQ was highly internally consistent (.92). Guttman split-half reliability also showed high internal consistency r(462) = .89. In addition convergent and discriminant validity were established by findings that the SPDQ was significantly more highly correlated with the Social Interaction Anxiety Scale (r = .64) than it was with the PTSD checklist (r = .29), the Civilian Mississippi Scale (r = .34), the Penn State Worry Questionnaire (r = .32) or the GADQ-IV (r = .29), the PDSS (r = .31), the GADQ-IV (r = ..28), the BDI (r = .32). In another sample, the correlation between the SPDQ and Social Avoidance and Distress Scale (r = .61) was significantly higher than the correlation between the SPDQ and Panic Disorder Severity Scale (r = .31), between the SPDQ and GAD-Q-IV (r = ..28), between the SPDQ and Beck Depression Inventory (r = .32), as well as the between the SPDQ and the Penn State Worry (r = .38). Results of the Logistic Regression showed that the SPDQ score at Time 2 was reliably predicted by Time 1 score 2 (1, N = 142) = 47.6, p < .001 and that 88% (125/142) of the sample showed stability across time in terms of their categorization. The clinical relevance of student participants who met or failed to meet social phobia criteria based on the SPDQ (using the cutoff of 7.38), was demonstrated by showing that the FNE, SAD and SISST scores of the SPDQ identified socially phobic (n = 31) undergraduates were not significantly different from 35 clinical community participants but were significantly different than SPDQ identified nonsocially phobic (n = 112) undergraduates. The scale can also be used to determine if participants meet full social phobia diagnostic criteria, which is a more stringent criterion than the original 7.38 cutoff endorsed by Newman et al. (2003). Using this criterion, Newman et al. found 95% specificity, and 57%, sensitivity.
Newman, M. G., Kachin, K. E., Zuellig, A. R., Constantino, M. J., & Cashman-McGrath, L. (2003). The Social Phobia Diagnostic Questionnaire: Preliminary validation of a new self-report diagnostic measure of social phobia. Psychological Medicine, 33, 623-635. doi:10.1017/S0033291703007669
Newman, Michelle G. (2003). Social Phobia Diagnostic Questionnaire (SPDQ). PsycTESTS. doi:10.1037/t04987-000
The PDSR is a 24-item self-report measure designed to diagnose panic disorder based on DSM-IV and DSM-5 criteria. It was modeled after the panic disorder module of the Anxiety Disorders Interview Schedule for DSM–IV (ADIS-IV; Brown et al., 1994), a well-validated structured interview. Thus, questions follow a hierarchical structure in which items central to diagnosis appear first, followed by additional questions administered only if central symptoms are present. The first four items assess whether a person has had recurrent and unexpected panic attacks, and if so, the total number of lifetime panic attacks. The next three questions assess worry and change in behavior in response to panic attacks. Next, the PDSR includes a list of 12 symptoms associated with panic attacks and assesses whether these symptoms were experienced during the most severe panic attack. Individuals then rate distress and interference caused by panic attacks on a 0–4 Likert scale ranging from none to severe. The PDSR concludes with a question to verify that most panic attacks peaked within 10 min, as well as two questions to rule out substance and medically related causes for the panic attacks. The readability of the PDSR is equivalent to Grade 6.3. In terms of convergent and discriminant validity, the PDSR was more highly correlated with the Panic Disorder Severity Scale–Self-Report (PDSS-SR; r =.80) than it was with the PTSD Checklist (r =.26), t(359) = 7.25, p < .001; the Social Interaction Anxiety Scale (r=.17), t(389) = 9.24, p < .001; the Zung Self-Rating Depression Scale (r = .25), t(146) = 8.59, p < .001; the GAD–Q–IV (r = .30), t(146) = 8.93, p < .001; the Personal Report of Confidence as a Speaker (r = .01), t(146) = 12.32, p < .001; the PSWQ (r = .15), t(146) = 10.82, p < .001; the Social Avoidance and Distress scale (r = .31), t(146) = 11.03, p < .001; and the Fear of Negative Evaluation scale (r = .20), t(146) = 10.53, p < .001. The validity of the PDSR was supported by comparisons between PDSR diagnoses and clinician –based ADIS (Di Nardo et al., 1994) diagnoses of treatment seeking individuals with panic disorder, GAD, social phobia, and a nonanxious comparison group. The optimal balance between sensitivity and specificity was achieved with a cutoff score of 8.75. This cutoff resulted in a sensitivity of 89% (24 of 27 participants) and a specificity of 100% (112 of 112 participants). Thus, using this cutoff, the rate of false positive cases identified by the PDSR was 0%, and the rate of false negative cases identified was 11%. Kappa agreement between the ADIS–IV and the PDSR was .93 with 95% Diagnoses made by the PDSR yielded a 0% false positive rate and an 11% false negative rate. The PDSR has demonstrated good -retest reliability in a college sample (r =.92), and 99% of the sample showed stability across time in terms of categorization with a Kappa agreement of .85 between time 1 and time 2. Odds ratios indicated that someone classified as meeting panic disorder criteria at Time 1 was 1,625 times more likely to be classified as meeting panic disorder criteria at Time 2 than someone not classified as meeting the criteria at Time 1. To test the clinical relevance of the PDSR-identified undergraduates, comparisons were made between PDSS–SR scores of PDSR-identified panic disordered students (n = 49), PDSR-identified non-panic disordered students (n = 388), and the 27 SCID–I/P-diagnosed community participants. Univariate analyses of variance showed significant main effects on the PDSS–SR, F(2, 464)= 247.79, p < .001. Bonferroni corrections indicated that whereas the PDSR-identified non-panic-disordered students differed significantly from both the student panic disordered group and the clinical community cohort (all ps < .001), the PDSR-identified student panic disordered group was not significantly different from the clinical community group on the PDSS–SR
Newman, M. G., Holmes, M., Zuellig, A. R., Kachin, K. E., & Behar, E. (2006). The reliability and validity of the Panic Disorder Self-Report: A new diagnostic screening measure of panic disorder. Psychological Assessment, 18, 49-61. doi:10.1037/1040-3590.18.1.49
Newman, Michelle G., Holmes, Marilyn, Zuellig, Andrea R., Kachin, Kevin E., & Behar, Evelyn. (2006). Panic Disorder Self-Report (PDSR). PsycTESTS. doi:10.1037/t01750-000
Based on the Contrast Avoidance model (Newman & Llera, 2011), the 5-item Emotional Coping Questionnaire for Contrast Avoidance (Llera & Newman, 2014) was developed to assess the extent to which worry, relaxation, and neutral inductions help people cope with exposure to film clips representing fearful, sad, and humorous emotions. This questionnaire was designed for use in a between-groups experimental design in which participants were assigned into one of three conditions: a worry condition, a relaxation condition, and a neutral thought activity condition. Items for this instrument were adapted from the Why Worry Scale–II (Gosselin et al., 2003). The Questionnaire utilizes a 5-point Likert scale (1 = not at all true, 2 = slightly true, 3 = somewhat true, 4 = very true, 5 = absolutely true) for 5 questions in each of three inductions (worry, relaxation, and neutral) to rate the extent to which respondents' assigned induction type helped them cope with their emotions when negative events occurred in the film clips. Three items target the extent to which prior inductions facilitated emotional coping during the films, while two reverse-scored items target the opposite effect. Higher scores suggest that individuals found inductions to be more helpful in coping with negative emotional exposures, whereas low scores suggest inductions were found to be unhelpful in coping with exposures. In a sample of university students with and without generalized anxiety disorder, Cronbach's alpha for this measure was .73. Each item also demonstrated high and significant item-total correlations, ranging from .57 to .74. This measure correlated significantly with the Penn State Worry Questionnaire (PSWQ; Meyer et al., 1990; r = .508, p < .001) and the Generalized Anxiety Disorder Questionnaire-IV (GAD-Q-IV; Newman et al., 2002; r = .488, p < .001), demonstrating convergent validity. Llera and Newman (2014) showed that although induced worry led to similar effects on concurrent anxiety and subsequent reactivity to emotional stimuli for both high and low worriers, there was a significant difference between these two groups in the degree to which they indicated that worry had helped cope with the sharp shift in emotions elicited by the negative emotional videos using this measure.
Llera, S. J., & Newman, M. G. (2014). Rethinking the role of worry in generalized anxiety disorder: Evidence supporting a model of Emotional Contrast Avoidance. Behavior Therapy, 45, 283-299. doi:10.1016/j.beth.2013.12.011
Llera, S. J., & Newman, M. G. (2014). Emotional Coping Questionnaire for Contrast Avoidance. PsycTESTS. doi:10.1037/t34265-000
This 25 item measure was developed to test whether participants had a tendency to endorse avoidance of a negative contrast that was not specific to the use of worry. By eliminating worry from the equation, this questionnaire allows one to test contrast avoidance within any diagnostic group, not just GAD. Thus, it taps into any effort to elicit and sustain negative emotion as a means to avoid a negative contrast and to increase the likelihood of a positive contrast. The questionnaire was developed to explicitly addressed the three major tenets of the Contrast Avoidance Model (Individuals diagnosed with some mental health problems are threatened by sharp shifts in negative emotion, such individuals intentionally create and sustain negative emotion to avoid a negative emotional contrast, such individuals also experience discomfort with resting positive states, but do not avoid transient positive states (Positive emotional contrasts). Items are rated on a 5-point Likert scale from not at all true to absolutely true. Items are summed to create a total score with higher scores indicatng greater contrast avoidance. Results of exploratory and confirmatory factor analyses showed that the best fitting model included two conceptually distinct latent factors. The first factor (F1: Creating and Sustaining Negative Emotion to Avoid Negative Contrasts) combined the second and third tenets of the CA model, including negative emotion generation to avoid negative contrasts and preference for enabling positive contrasts. The second factor (F2: Discomfort with Emotional Shifts) was comprised of items reflecting the first tenet of the CA model, focused on the perceived threat of emotional shifts. Supporting the internal consistency of the CAQ-GE, the point estimate reliability for the total scale was ρ =0.99, with comparable estimates for each subscale (Factor 1, ρ =0.99; Factor 2, ρ= 0.90). Supporting the construct validity of the CAQ-GE, individuals diagnosed with GAD scored significantly higher than a non-anxious group on each CAQ subscale with large effect sizes for all comparisons (Cohen’s d’s ranging from 1.89-3.02). ROC curve analyses supported the CAQ-GE to predict group membership with an AUC of 0.96 (95% confidence interval: 0.931–.997, SE = 0.02, p < 0.001). This suggests the probability of a person with GAD scoring higher than a non-anxious person on the CAQ-GE was 96%. As expected, both the CAQ-GE scales and all subscale scores had significantly stronger positive correlations with convergent measures (GAD-Q-IV, PSWQ, and the PTEQ negative and strong emotions subscales) than with measures of sensation seeking (AISS). The same pattern emerged for analyses using fear of happiness (PTEQ happiness subscale) as the divergent construct. The CAQ-GE and its subscales also demonstrated sufficient test-retest reliability (Total CAQ-GE: r =0.93; Factor 1: r =0.91; Factor 2: r = 0.83).
Llera, S. J., & Newman, M. G. (2017). Development and validation of two measures of emotional contrast avoidance: The Contrast Avoidance Questionnaires. Journal of Anxiety Disorders, 49, 114-127. doi:10.1016/j.janxdis.2017.04.008
This 30 item measure examines the tendency for participants to endorse using worry to induce and sustain negative emotion as a means to avoid a negative contrast and increase the likelihood of experiencing a positive emotional contrast. The questionnaire was developed to explicitly addressed the three major tenets of the Contrast Avoidance Model of Worry (Individuals diagnosed with some mental health problems are threatened by sharp shifts in negative emotion, such individuals intentionally worry to create and sustain negative emotion to avoid a negative emotional contrast, such individuals also experience discomfort with resting positive states, but do not avoid transient positive states (Positive emotional contrasts). Items are rated on a 5-point Likert scale from not at all true to absolutely true and are summed to create a total score with higher scores indicatng greater contrast avoidance. Separate consecutive analyses across three large samples led to a replicable factor structure. Results of exploratory and confirmatory factor analyses showed that the best fitting model included three conceptually distinct latent factors. The first factor (F1: Worry to Avoid Negative Emotional Shifts) is the central tenet of the model with respect to worry. The second factor (F2: Worry Creates and Sustains Negative Emotion) reflects the major foundational argument of the CA model: that worry does not avoid negative emotion, but rather creates and sustains negative emotion. The third factor (F3: Worry to Create Positive Contrast) was comprised of items reflecting a preference for using worry to experience positive contrasts. Supporting its internal consistency, the point estimate reliability for the total scale was ρ= 0.98, with similarly robust estimates for each subscale (Factor 1, ρ= 0.98; Factor 2, ρ =0.94; Factor 3, ρ= 0.93). Supporting the construct validity of the CAQ-W, individuals diagnosed with GAD scored significantly higher than a non-anxious group on each CAQ subscale and subscale with large effect sizes for all comparisons (Cohen’s d’s ranging from 1.95-3.18). ROC curve analyses supported the ability of the CAQ-W to predict group membership showing the AUC was 0.98 (95% confidence interval: 0.948–1.0, SE = 0.01, p < 0.001).This suggests the probability of a person with GAD scoring higher than a non-anxious person on the CAQ-W was 98%. A CAQ-W score ≥65 leads to a sensitivity of 89.7 and a specificity of 87.5, with 88.3% of participants correctly classified. As expected, both the CAQ-W cales and all subscale scores had significantly stronger positive correlations with convergent measures (GAD-Q-IV, PSWQ, and the PTEQ negative and strong emotions subscales) than with measures of sensation seeking (AISS). The same pattern emerged for the majority of analyses using fear of happiness (PTEQ happiness subscale) as the divergent construct. The CAQ-W produced a strong retest reliability across two weeks for the overall scale score (r = 0.90), and its subscales (Factor 1: r =0.85; Factor 2: r = 0.81; Factor 3: r = 0.87).
Llera, S. J., & Newman, M. G. (2017). Development and validation of two measures of emotional contrast avoidance: The Contrast Avoidance Questionnaires. Journal of Anxiety Disorders, 49, 114-127. doi:10.1016/j.janxdis.2017.04.008
The 45-item Perseverative Cognitions Questionnaire (PCQ; Szkodny & Newman, 2019) was developed to measure multi-dimensional characteristics of worry, rumination, and obsessive thinking. The measure also addresses measurement concerns about assessing and comparing different types of repetitive thought in tandem. Items are rated on a 6-point Likert-type scale (0 = strongly disagree; 5 = strongly agree). Subscales include Lack of Controllability; Preparing for the Future; Expecting the Worst; Searching for Causes/Meaning; Dwelling on the Past; Thinking Discordant with Ideal Self. In creating this questionnaire, the authors first reviewed thoroughly theoretical and empirical literature on conceptualizations of these constructs across disciplines to identify distinct and overlapping features. A sample of 1,390 were randomly divided into three equal subsamples. Samples 1 and 2 were used for initial item derivation and Sample 3 was used to validate the PCQ structure derived in Samples 1 and 2. An initial Principal Component and Exploratory Factor Analysis supported a 6-factor solution with factor loadings ranging from .67 to .89. A subsequent confirmatory factor analysis with a separate sample found the χ2 was significant, χ2(930) = 2220.96, p < .001, and other fit indices supported a six-factor model fit (CFI = .98; SRMR = .056; RMSEA = .055, 90% confidence interval for RMSEA [.052, .058], RMSEA p for close fit = .0036). Internal Consistency: Coefficient alphas ranged from .87 to .96 (Total PCQ α = .96). Test-Retest Reliability: The mean number of days between T1 and T2, T2 and T3, and T1 and T3 were 8.45, 8.07, and 16.54, respectively. Average alphas ranged from .87 (i.e., LC) to .97 (i.e., DP). Over 1- and 2-week intervals; the authors found high retest reliability for the PCQ scales (βs ranging from .73 to .95). Convergent Validity: Positive associations were exhibited with related constructs, including worry, rumination, obsessive thinking, negative affect, generalized anxiety disorder (GAD), depression, and obsessive compulsive disorder, and negative associations with measures of positive affect. Discriminant Validity: Although the PCQ was moderately correlated with measures of suicidality, ill temper, and insomnia, it was consistently more highly associated with measures of anxiety and depression. Incremental Validity: The PCQ explained an additional 2.9% of the variance (p < .001) when predicting GAD symptoms.
Szkodny, L. E., & Newman, M. G. (2019). Delineating characteristics of maladaptive repetitive thought: Development and preliminary validation of the Perseverative Cognitions Questionnaire. Assessment, 26, 1084-1104. doi:10.1177/1073191117698753
Szkodny, L. E., & Newman, M. G. (2019). Perseverative Cognitions Questionnaire (PCQ, PCQ-45). PsycTESTS. doi:10.1037/t73751-000
This is a novel set of stimuli for emotion elicitation. The Image Stimuli for Emotion Elicitation (ISEE), are the first set of stimuli for which there was an unbiased initial selection method and with images specifically selected for high retest correlation coefficients and high agreement across time. In order to protect against a researcher's subjective bias in screening initial pictures, Kim and colleagues 2018 crawled 10,696 images from the biggest image hosting website (Flickr.com) based on a computational selection method. In the initial screening study, participants rated stimuli twice for emotion elicitation across a 1-week interval and 1620 images were selected based on the number of ratings of participants and retest reliability of each picture. Using this set of stimuli, a second phase of the study was conducted, again having participants rate images twice with a 1-week interval, in which we found a total of 158 unique images that elicited various levels of emotionality with both good reliability and good agreement over time. The newly developed pictorial stimuli set is expected to facilitate cumulative science on human emotions and can be used in a variety of experimental studies.