Examining the Factor Structure of the DSM-5 Level 1 Cross-Cutting Symptom Measure

Gibbons, Alison; Farmer, Cristan; Js, Shaw; Chung, Joo‐Ho

doi:10.1101/2021.04.28.21256253

Cited by 5 publications

(5 citation statements)

References 22 publications

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“…This measure is one of the core common data elements that NIMH researchers are expected to collect. 19 Using data from all enrolled study participants, we performed a series of exploratory and confirmatory factor analyses and identified a six-factor solution which was robust across age, sex, and calendar time (see https://doi.org/10.1101/2021.04.28.21256253 20 ). Each factor captured symptoms related to a general construct of psychopathology, which we provisionally termed: mood, worry, activation, somatic, thoughts, and substance use.…”

Section: Distressmentioning

confidence: 99%

COVID-19 and Mental Health: Predicted Mental Health Status is Associated with Clinical Symptoms and Pandemic-Related Psychological and Behavioral Responses

Chung

Gibbons

Atlas

et al. 2021

Preprint

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Background: The COVID 19 pandemic led to dramatic threats to health and social life. Study objectives are to develop a prediction model leveraging subsample of known Patient/Controls and evaluate the relationship of predicted mental health status to clinical outcome measures and pandemic-related psychological and behavioral responses during lockdown (spring/summer 2020). Methods: Online cohort study conducted by National Institute of Mental Health Intramural Research Program. Convenience sample of English speaking adults (enrolled 4/4 to 5/16/20; n=1,992). Enrollment measures: demographics, clinical history, functional status, psychiatric and family history, alcohol/drug use. Outcome measures (enrollment and q2 weeks/6 months): distress, loneliness, mental health symptoms, and COVID 19 survey. NIMH IRP Patient/Controls survey responses informed assignment of Patient Probability Scores (PPS) for all participants. Regression models analyzed the relationship between PPS and outcome measures. Outcomes: Mean age 46.0, female (82.4%), white (88.9 %). PPS correlated with distress, loneliness, depression, and mental health factors. PPS associated with negative psychological responses to COVID 19. Worry about mental health (OR 1.46) exceeded worry about physical health (OR 1.13). PPS not associated with adherence to social distancing guidelines but was with stress related to social distancing and worries about infection of self/others. Interpretation: Mental health status (PPS) was associated with concurrent clinical ratings and COVID 19 specific negative responses. A focus on mental health during the pandemic is warranted, especially among those with mental health vulnerabilities. We will include PPS when conducting longitudinal analyses of mental health trajectories and risk and resilience factors that may account for differing clinical outcomes. Funding: NIMH (ZIAMH002922); NCCIH (ZIAAT000030)

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Section: Distressmentioning

confidence: 99%

COVID-19 and Mental Health: Predicted Mental Health Status is Associated with Clinical Symptoms and Pandemic-Related Psychological and Behavioral Responses

Chung

Gibbons

Atlas

et al. 2021

Preprint

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“…The CCSM consists of 23 items scored on a 5‐point Likert scale (‘ not at all ’ to ‘ nearly every day ’) that assess individuals' experiences of mental health symptoms over the past 2 weeks across 13 psychiatric domains including depression, anger, mania, anxiety, somatic symptoms, suicidal ideation, psychosis, sleep problems, memory, repetitive thoughts and behaviours, dissociation, personality functioning and substance use (Cronbach's α = 0.90). Previous factor analytic studies have suggested that the CCSM items can be organised into a bi‐factor structure with a general psychopathology factor and two specific factors (internalising and thought disorders) (Gibbons et al, 2021). Alternatively, it has also been suggested that a two‐factor or six‐factor model without a p factor would fit well (Gibbons et al, 2021).…”

Section: Methodsmentioning

confidence: 99%

“…Previous factor analytic studies have suggested that the CCSM items can be organised into a bi-factor structure with a general psychopathology factor and two specific factors (internalising and thought disorders) (Gibbons et al, 2021). Alternatively, it has also been suggested that a two-factor or six-factor model without a p factor would fit well (Gibbons et al, 2021). In the present study, only 12 of the 13 domains were measured as substance use was measured separately using the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) (Humeniuk et al, 2008).…”

Section: Psychopathologymentioning

confidence: 99%

Investigating general and specific psychopathology factors with nuance‐level personality traits

Hang

Speyer

Haring

et al. 2022

Personality & Mental Health

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Mental health disorders share substantial variance, prompting researchers to develop structural models that can capture both generalised psychopathology risk and disorder/symptom-specific variation. This study investigated the associations of the general and specific psychopathology factors with multiple personality trait hierarchy levels: broad domains, their facets and nuances (N = 1839 Estonian adults). A bi-factor model with a general 'p' factor and specific factors for internalising problems, thought disorders and substance use best represented psychopathology structure. Although traits' predictive accuracy varied across psychopathology factors, nuances (the lowest level personality units) provided higher predictive accuracy and higher discriminant validity than domains. For example, traits related to high vulnerability, depression and immoderation and low friendliness and achievement striving were most strongly associated with the p factor. Nuances may prove useful for predicting and understanding general and specific psychopathology forms.

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“…The current study’s findings in Figure 1 reported an excellent model fit for CAM. Thus, CAM is a valid instrument to measure criminal thinking as it fulfills both criteria (EFA and CFA) suggested by researchers (Gibbons et al , 2021; Lace and Merz, 2020) to ensure the construct validity of the instrument. Furthermore, indices (e.g.…”

Section: Structural Validation Of Criminal Attitude Measurementioning

confidence: 99%

Measuring criminal thinking among convicts imprisoned in Punjab prisons of Pakistan

Ishfaq,

Kamal

2023

JCP

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Purpose This study aims to differentiate crime-related characteristics (such as the number of cases filed against current convictions and criminal history) based on the criminal thinking prevailing among convicts. However, because of the low reliability of subscales and poor structural validity of indigenous and translated versions of international instruments, a new instrument criminal attitude measure (CAM) was extracted to measure criminal thinking patterns among convicts incarcerated in central prisons of Punjab. Design/methodology/approach A cross-sectional research design was used. Data was collected from 1,949 male convicts (extracting mutually exclusive data from 649 respondents for EFA and 1,300 respondents for confirmatory factor analysis [CFA]). Both data samples were collected from convicts incarcerated in the nine (all) central jails of Punjab, Pakistan. Findings The results of this study showed poor model fit for both the indigenous criminal thinking scale and the translated version of criminogenic cognition scale. CAM was extracted through principal component analysis and proposed as a 15-item questionnaire with five factors extracted through varimax rotation. Those five factors are power orientation, mollification, entitlement, mistrust toward authorities and short-term orientation. The results of CFA for CAM confirmed the proposed five-factor structure for the construct. Findings based on MANOVA further found that CAM differentiates between the thinking patterns of recidivists, convicts with multiple charges filed against them in current convictions and convicts with a familial criminal record. The findings of this study showed that CAM is a practical, valid and reliable instrument for measuring criminal thinking among convicts. Research limitations/implications In this study, using the survey method was inevitable because of the restrictions imposed by the granted permission. However, this time duration was extended because of the courtesy of the Superintendent and Deputy Superintendent of each jail. This study is focused on a male sample only, and the findings cannot be generalized to females. The phenomena proposed (based on large data sets) in this study can further be elaborated using qualitative research designs and methods (using a small sample with an in-depth study). So, it is also suggested to test this new instrument on a comparative study between prisoners and non-prisoners to explore whether scale can differentiate between these two groups. Practical implications A short-scale and easy-to-administer instrument was developed for assessing major criminogenic needs among convicts for prison management, i.e. assigning barracks, allocating treatment and also detecting changes in attitude after imprisonment. Originality/value To the best of the authors’ knowledge, this study is the first study to explore and validate the construct of criminal attitudes among convicts using both the EFA and CFA. A small and valid instrument facilitates the measurement of criminogenic needs among prisoners. Data was collected from all central jails in Punjab. This study explored comparatively less researched crime characteristics in a relatively large sample.

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Examining the Factor Structure of the DSM-5 Level 1 Cross-Cutting Symptom Measure

Cited by 5 publications

References 22 publications

COVID-19 and Mental Health: Predicted Mental Health Status is Associated with Clinical Symptoms and Pandemic-Related Psychological and Behavioral Responses

COVID-19 and Mental Health: Predicted Mental Health Status is Associated with Clinical Symptoms and Pandemic-Related Psychological and Behavioral Responses

Investigating general and specific psychopathology factors with nuance‐level personality traits

Measuring criminal thinking among convicts imprisoned in Punjab prisons of Pakistan

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