Introduction
Patients with COVID‐19 often suffer from psychological problems such as post‐traumatic stress disorder (PTSD) and self‐stigmatization that may negatively impact their quality of life and sleep. This study examined mental health as a potential mediating factor linking self‐stigmatization and PTSD to quality of life and sleep.
Methods
Using a cross‐sectional design, 844 people who had recovered from COVID‐19 were called and interviewed. Data were collected using structured scales. Structural equation modeling was applied to assess fitness of a mediation model including self‐stigma and PTSD as independent factors and quality of life and insomnia as dependent variables.
Results
Mental health, COVID‐19‐related self‐stigma, and mental quality of life were associated. Insomnia, PTSD, and COVID‐19‐related self‐stigma displayed significant direct associations (r = .334 to 0.454; p < .01). A mediation model indicated satisfactory goodness of fit (CFI = 0.968, TLI = 0.950, SRMR = 0.071, RMSEA = 0.068). Mental health as a mediator had negative relationships with COVID‐19‐related self‐stigma, PTSD, and insomnia and positive associations with quality of life.
Conclusion
Mental health may mediate effects of COVID‐19‐related self‐stigma and PTSD on quality of life and insomnia. Designing programs to improve mental health among patients with COVID‐19 may include efforts to reduce negative effects of PTSD and COVID‐19‐related self‐stigma on quality of life and insomnia.
Aim
This study tested the construct validity (i.e., factor structure) of the Persian Mindful Attention Awareness Scale (MAAS) on a sample of male prisoners.
Methods
All the participants (mean±SD age = 39.44±7.94 years) completed three scales—the Persian MAAS, the Insomnia Severity Index (ISI), and the 12-item General Health Questionnaire (GHQ-12). Confirmatory factor analysis (CFA) and Rasch analysis with differential item functioning (DIF) were applied to examine the construct validity of the MAAS. Specifically, the DIF was tested across different insomnia status (using ISI with a cutoff of 15), psychiatric well-being status (using GHQ-12 with a cutoff of 12), and age (using mean age of 39.44 as the cutoff).
Results
The CFA results showed a single factor solution for the Persian MAAS. The Rasch results showed all MAAS items fit in the construct (infit mean square [MnSq] = 0.72 to 1.41; outfit MnSq = 0.74 to 1.39) without displaying DIF items (DIF contrast = -0.34 to 0.31 for insomnia condition; -0.22 to 0.25 for psychiatric well-being; -0.26 to 0.29 for age).
Conclusions
The Persian version of the MAAS is, therefore, a valid instrument to measure mindfulness among Iranian male prisoners.
The Internet Disorder Scale–Short Form (IDS9-SF) is a validated instrument assessing internet disorder which modified the internet gaming disorder criteria proposed in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5). However, the relationships between the nine items in the IDS9-SF are rarely investigated. The present study used network analysis to investigate the features of the IDS9-SF among three populations in Bangladesh, Iran, and Pakistan. Data were collected (N = 1901; 957 [50.3%] females; 666 [35.0%] Pakistani, 533 [28.1%] Bangladesh, and 702 [36.9%] Iranians) using an online survey platform (e.g., Google Forms). All the participants completed the IDS9-SF. The central-stability-coefficients of the nine IDS9-SF items were 0.71, 0.89, 0.96, 0.98, 0.98, 1.00, 0.67, 0.79, and 0.91, respectively. The node centrality was stable and interpretable in the network. The Network Comparison Test (NCT) showed that the network structure had no significant differences among Pakistani, Bangladeshi, and Iranian participants (p-values = 0.172 to 0.371). Researchers may also use the IDS9-SF to estimate underlying internet addiction for their target participants and further explore and investigate the phenomenon related to internet addiction.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.