Dataset Information

The Development and Validation of the Perceived Competence Scale for Disaster Mental Health Workforce.

ABSTRACT: OBJECTIVE:This study was conducted to validate a Perceived Competence Scale for Disaster Mental Health Workforce (PCS-DMHW) designed to measure the core competences of mental health workers in disaster response situations at individual and organizational levels. core competences essentially required in disaster response situations were defined on the basis of literature review, focus-group interview with disaster response professionals, and expert judgment. METHODS:The preliminary items of the PCS-DMHW thus generated were administered to 509 participants consisted of mental health professionals and semi-professionals. The data retrieved from questionnaires were equally divided by two halves. The final items were determined through the exploratory factor analysis of the half data (n=255), and the construct validity was tested by performing the confirmatory factor analysis and criterion-related validity test of the remaining half data (n=254). RESULTS:Three factors were derived from the individual competences scale; 1) perceived competence of knowledge and skill, 2) ethic, and 3) qualification. And three factors were derived from the organizational competence scale; 1) teamwork, 2) network, and 3) followship. CONCLUSION:The PCS-DMHW demonstrated fairly high reliability and validity. Finally, the necessity of continuous validation study and the application modalities of this scale in education and training settings were discussed.

SUBMITTER: Yoon HY

PROVIDER: S-EPMC6877459 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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The Development and Validation of the Perceived Competence Scale for Disaster Mental Health Workforce.

Yoon Hyae-Young HY Choi Yun-Kyeung YK

Psychiatry investigation 20191115 11

<h4>Objective</h4>This study was conducted to validate a Perceived Competence Scale for Disaster Mental Health Workforce (PCS-DMHW) designed to measure the core competences of mental health workers in disaster response situations at individual and organizational levels. core competences essentially required in disaster response situations were defined on the basis of literature review, focus-group interview with disaster response professionals, and expert judgment.<h4>Methods</h4>The preliminary ...[more]

PMID: 31760717

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Project description:ObjectivesEstablish reliability, concurrent and convergent validity of the Pittsburgh Fatigability Scale (PFS) Mental subscale.DesignCross-sectional.SettingOlder adults from two University of Pittsburgh registries, Baltimore Longitudinal Study of Aging (BLSA), and Long Life Family Study (LLFS).ParticipantsPFS Mental subscale validation was conducted using three cohorts: (1) Development Sample (N = 664, 59.1% women, age 74.8 ± 6.4 years, PFS Mental scores 10.3 ± 9.1), (2) Validation Sample I-BLSA (N = 430, 51.9% women, age 74.5 ± 8.2 years, PFS Mental scores 9.4 ± 7.9), and (3) Validation Sample II-LLFS (N = 1,917, 54.5% women, age 72.2 ± 9.3 years, PFS Mental scores 7.5 ± 8.2).MeasurementsDevelopment Sample, Validation Sample I-BLSA, and Validation Sample II-LLFS participants self-administered the 10-item Pittsburgh Fatigability Scale. Validation Sample II-LLFS completed cognition measures (Trail Making Tests A and B), depressive symptomatology (Center for Epidemiologic Studies-Depression Scale, CES-D), and global fatigue from two CES-D items.ResultsIn the Development Sample and Validation Sample I-BLSA, confirmatory factor analysis showed all 10 items loaded on two factors: social and physical activities (fit indices: SRMSR = 0.064, RMSEA = 0.095, CFI = 0.91). PFS Mental scores had strong internal consistency (Cronbach's α = 0.85) and good test-retest reliability (ICC = 0.78). Validation Sample II-LLFS PFS Mental scores demonstrated moderate concurrent and construct validity using Pearson (r) or Spearman (ρ) correlations against measures of cognition (Trail Making Tests A (r = 0.14) and B (r = 0.17) time), depressive symptoms (r = 0.31), and global fatigue (ρ = 0.21). Additionally, the PFS Mental subscale had strong convergent validity, discriminating according to established clinical or cognitive testing cut points, with differences in PFS Mental scores ranging from 3.9 to 7.6 points (all P < .001). All analyses were adjusted for family relatedness, field center, age, sex, and education.ConclusionsThe validated PFS Mental subscale may be used in clinical and research settings as a sensitive, one-page self-administered tool of perceived mental fatigability in older adults.

Project description:Disasters have substantial consequences for population mental health. Social media data present an opportunity for mental health surveillance after disasters to help identify areas of mental health needs. We aimed to 1) identify specific basic emotions from Twitter for the greater New York City area during Hurricane Sandy, which made landfall on October 29, 2012, and to 2) detect and map spatial temporal clusters representing excess risk of these emotions.We applied an advanced sentiment analysis on 344,957 Twitter tweets in the study area over eleven days, from October 22 to November 1, 2012, to extract basic emotions, a space-time scan statistic (SaTScan) and a geographic information system (QGIS) to detect and map excess risk of these emotions.Sadness and disgust were among the most prominent emotions identified. Furthermore, we noted 24 spatial clusters of excess risk of basic emotions over time: Four for anger, one for confusion, three for disgust, five for fear, five for sadness, and six for surprise. Of these, anger, confusion, disgust and fear clusters appeared pre disaster, a cluster of surprise was found peri disaster, and a cluster of sadness emerged post disaster.We proposed a novel syndromic surveillance approach for mental health based on social media data that may support conventional approaches by providing useful additional information in the context of disaster. We showed that excess risk of multiple basic emotions could be mapped in space and time as a step towards anticipating acute stress in the population and identifying community mental health need rapidly and efficiently in the aftermath of disaster. More studies are needed to better control for bias, identify associations with reliable and valid instruments measuring mental health, and to explore computational methods for continued model-fitting, causal relationships, and ongoing evaluation. Our study may be a starting point also for more fully elaborated models that can either prospectively detect mental health risk using real-time social media data or detect excess risk of emotional reactions in areas that lack efficient infrastructure during and after disasters. As such, social media data may be used for mental health surveillance after large scale disasters to help identify areas of mental health needs and to guide us in our knowledge where we may most effectively intervene to reduce the mental health consequences of disasters.

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The Development and Validation of the Perceived Competence Scale for Disaster Mental Health Workforce.

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The Development and Validation of the Perceived Competence Scale for Disaster Mental Health Workforce.

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