Evidence map›Paper›PMID 42009849›Full record

ArticleSleep & breathing = Schlaf & Atmung2026

Mapping the central symptom structure of the insomnia severity index (ISI-7) and sleep duration: a network analysis.

Mohammed A Mamun, Abdullah Al Habib, Moneerah Mohammad ALmerab, Firoj Al-Mamun

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Article in Sleep & breathing = Schlaf & Atmung, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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4 authors.

Mohammed A MamunCHINTA Research Bangladesh, Savar, 1342, Dhaka, Bangladesh. mamun@thechinta.org.ORCID http://orcid.org/0000-0002-1728-8966
Abdullah Al HabibCHINTA Research Bangladesh, Savar, 1342, Dhaka, Bangladesh.ORCID http://orcid.org/0009-0009-3508-8093
Moneerah Mohammad ALmerabDepartment of Psychology, College of Education and Human Development, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia.ORCID http://orcid.org/0000-0003-4987-0309
Firoj Al-MamunCHINTA Research Bangladesh, Savar, 1342, Dhaka, Bangladesh. firoj@thechinta.org.ORCID http://orcid.org/0000-0003-4611-9624

Funding

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6 · The paper itself

Abstract

purposeInsomnia symptoms and abnormal sleep durations adversely affect mental health and daily life, yet the complex relationships among individual symptoms remain understudied. There is a notable lack of item-level network analyses integrating the Insomnia Severity Index (ISI-7) with sleep duration categories. This study addressed this gap by using network analysis to identify central symptoms and assess gender differences within the insomnia-sleep duration structure.

methodsA cross-sectional study was conducted among 466 job-seeking graduates from two major public universities in Bangladesh. Insomnia symptoms were assessed using the validated Bangla ISI-7, and sleep duration was categorized according to National Sleep Foundation guidelines. Network analysis (EBICglasso) was used to estimate the symptom network, compute node centrality and predictability, and test network invariance by gender using Network Comparison Tests.

resultsNetwork analysis revealed a highly interconnected structure, with the strongest association between short and long sleep duration (regularized partial correlation = -0.80), which primarily reflects their mutually exclusive dummy coding rather than a substantive clinical antagonism. Dense positive connections were observed among ISI symptoms, especially between "distress caused by sleep difficulties" (ISI7) and "noticeability of sleep problem" (ISI6; edge weight = 0.48). Centrality analysis identified short sleep duration (strength = 1.26; predictability index = 0.69), ISI7 (strength = 1.20), and ISI6 (strength = 1.15) as the most central nodes. The network showed acceptable stability (CS-coefficient = 0.52). No statistically significant gender differences were found in network structure or centrality (global strength: males = 3.61, females = 3.56; p = 0.86), indicating structural invariance.

conclusionsThese findings suggest that symptoms such as distress about sleep and short sleep duration may represent promising targets for future intervention research. Interventions focusing on these symptoms may help improve sleep health. Future research should utilize longitudinal designs and include broader mental health measures to better understand the dynamics of insomnia.

Indexed as

Severity of Illness IndexSleep DurationSleep Initiation and Maintenance DisordersAdultBangladeshCross-Sectional StudiesFemaleHumansMalePsychometricsSex FactorsYoung AdultBangladeshInsomniaInsomnia severity indexNetwork analysisSleep durationSymptom network

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.