A phubbing scale tested in Bangladesh, Iran, and Pakistan: confirmatory factor, network, and Rasch analyses.

BACKGROUND: Phubbing, a phenomenon of ignoring others in face-to-face conversations due to mobile phone use, can be assessed using a Phubbing Scale (PS). Recently, the PS has been shortened into an eight-item version, the PS-8. However, psychometric properties of the PS-8 among Iranian, Bangladeshi and Pakistani individuals remain understudied, especially using advanced psychometric testing, such as Rasch and network analyses. METHODS: Participants residing in Iran, Bangladesh, and Pakistan (n = 1902; 50.4% females; mean age = 26.3 years) completed the PS-8 and the Internet Disorder Scale-Short Form (IDS9-SF) via an online survey. Network analysis was used to examine if PS-8 items were differentiated from IDS9-SF items; confirmatory factor analysis (CFA) was used to examine the factor structure and measurement invariance of the PS-8; Rasch modeling was used to examine the dimensionality of the PS-8 and differential item functioning (DIF). RESULTS: Network analysis showed that PS-8 items were clustered together with a distance to the IDS9-SF items. The CFA results supported a two-factor structure of the PS-8, and the two-factor structure was found to be invariant across countries and women and men. Rasch model results indicated that the two PS-8 subscales were both unidimensional and did not display DIF across countries and gender/sex. CONCLUSION: The PS-8 is a feasible and robust instrument for healthcare providers, especially mental health professionals, to quickly assess and evaluate individuals' phubbing behaviors.

A network analysis of the Internet Disorder Scale-Short Form (IDS9-SF): A large-scale cross-cultural study in Iran, Pakistan, and Bangladesh.

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. Supplementary Information: The online version contains supplementary material available at 10.1007/s12144-022-03284-8.

A mediating role for mental health in associations between COVID-19-related self-stigma, PTSD, quality of life, and insomnia among patients recovered from COVID-19.

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.