Browsing by Author "Pakpour, Amir H."

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A Network Analysis of the Fear of COVID-19 Scale (FCV-19S)
(Daffodil International University, 2022-06-02) Lecuona, Oscar; Lin, Chung-Ying; Rozgonjuk, Dmitri; Norekvål, Tone M.; Iversen, Marjolein M.; Mamun, Mohammed A.; Griffiths, Mark D.; Lin, Ting-I; Pakpour, Amir H.
The rapid spread of the coronavirus disease 2019 (COVID-19) has led to high levels of fear worldwide. Given that fear is an important factor in causing psychological distress and facilitating preventive behaviors, assessing the fear of COVID-19 is important. The seven-item Fear of COVID-19 Scale (FCV-19S) is a widely used psychometric instrument to assess this fear. However, the factor structure of the FCV-19S remains unclear according to the current evidence. Therefore, the present study used a network analysis to provide further empirical evidence for the factor structure of FCV-19S. A total of 24,429 participants from Iran (n = 10,843), Bangladesh (n = 9906), and Norway (n = 3680) completed the FCV-19S in their local language. A network analysis (via regularized partial correlation networks) was applied to investigate the seven FCV-19S items. Moreover, relationships between the FCV-19S items were compared across gender (males vs. females), age groups (18–30 years, 31–50 years, and >50 years), and countries (Iran, Bangladesh, and Norway). A two-factor structure pattern was observed (three items concerning physical factors, including clammy hands, insomnia, and heart palpitations; four items concerning psychosocial factors, including being afraid, uncomfortable, afraid of dying, and anxious about COVID-19 news). Moreover, this pattern was found to be the same among men and women, across age groups and countries. The network analysis used in the present study verified the two-factor structure for the FCV-19S. Future studies may consider using the two-factor structure of FCV-19S to assess the fear of COVID-19 during the COVID-19 era.
A Network Analysis of the Internet Disorder Scale–Short Form (IDS9-SF)
(Daffodil International University, 2022-06-09) Mamun, Mohammed A.; Al‑Mamun, Firoj; Ullah, Irfan; Hosen, Ismail; Zia, Syed Ahsan; Poorebrahim, Ali; Pourgholami, Morteza; Lin, Chung‑Ying; Pontes, Halley M.; Griffiths, Mark D.; Pakpour, Amir H.
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.
A Network Analysis of the Internet Disorder Scale–Short Form (IDS9-Sf)
(Springer, 2022-06-09) Mamun, Mohammed A.; Al‑Mamun, Firoj; Ullah, Irfan; Hosen, Ismail; Zia, Syed Ahsan; Poorebrahim, Ali; Pourgholami, Morteza; Lin, Chung‑Ying; Pontes, Halley M.; Griffiths, Mark D.; Pakpour, Amir H.
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.
Sleep Duration During the COVID-19 Pandemic in Bangladesh: A Gis-Based Large Sample Survey Study
(2023-02-27) Al‑Mamun, Firoj; Hussain, Nur; Sakib, Najmuj; Hosen, Ismail; Rayhan, Istihak; Abdullah, Abu Hasnat; Bhuiyan, A. K. M. Israfil; Sarker, Md. Abedin; Hossain, Sahadat; Zou, Liye; Manzar, Md. Dilshad; Lin, Chung‑Ying; Sikder, Md. Tajuddin; Muhit, Mohammad; Pakpour, Amir H.; Goza, David; Griffiths, Mark D.; Mamun, Mohammed A.
Although several studies have been conducted in Bangladesh regarding sleep problems during the COVID-19 pandemic, none have utilized a large nationwide sample or presented their findings based on nationwide geographical distribution. Therefore, the aim of the present study was to explore the total sleep duration, night-time sleep, and daily naptime and their associated factors as well as geographic information system (GIS) distribution. A cross-sectional survey was carried out among 9730 people in April 2020, including questions relating to socio-demographic variables, behavioral and health factors, lockdown, depression, suicidal ideation, night sleep duration, and naptime duration. Descriptive and inferential statistics, both linear and multivariate regression, and spatial distribution were performed using Microsoft Excel, SPSS, Stata, and ArcGIS software. The results indicated that 64.7% reported sleeping 7–9 h a night, while 29.6% slept less than 7 h nightly, and 5.7% slept more than 9 h nightly. 43.7% reported 30–60 min of daily nap duration, whereas 20.9% napped for more than 1 h daily. Significant predictors of total daily sleep duration were being aged 18–25 years, being unemployed, being married, self-isolating 4 days or more, economic hardship, and depression. For nap duration, being aged 18–25 years, retired, a smoker, and a social media user were at relatively higher risk. The GIS distribution showed that regional division areas with high COVID-19 exposure had higher rates of non-normal sleep duration. Sleep duration showed a regional heterogeneity across the regional divisions of the country that exhibited significant associations with a multitude of socioeconomic and health factors.