{"paper_id":"27942e44-2668-4cde-a371-aef3fb3fc437","body_text":"Sleep quality among healthcare providers during conflict crisis in the Gaza Strip: A cross-sectional study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Sleep quality among healthcare providers during conflict crisis in the Gaza Strip: A cross-sectional study Mohammed Afana¹, Ahmed Alhaj, Hassan M. Abu Rhama³, Yasser Alshaer This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7056032/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Healthcare providers working in conflict zones face unique occupational and psychological challenges that significantly impair sleep quality. In the Gaza Strip, prolonged exposure to violence and humanitarian crises exacerbates these challenges, yet data on the sleep health of this critical workforce remain scarce. Objective This cross-sectional study aimed to assess the prevalence and patterns of sleep disturbances among healthcare providers at Nasser Medical Complex during the 2023–2025 Israel-Gaza conflict, and to examine associations between sleep quality and psychological distress. Methods A purposive sample of 400 healthcare providers (70% nurses, 20% physicians, 10% non-medical staff) completed the Pittsburgh Sleep Quality Index (PSQI) and a sociodemographic questionnaire between May and July 2025. Descriptive statistics evaluated sleep quality prevalence and scores. Results Thirty-five percent of participants reported poor sleep quality (PSQI > 5). Additionally, 40% reported sleeping less than 6–7 hours nightly. Sleep disturbances were frequent, including difficulty initiating sleep (50% reporting problems weekly or more), nighttime awakenings (60%), loud snoring (37.5%), and breathing pauses (20%). Physical discomfort during sleep—such as back pain and breathing difficulties—was prevalent. Married participants and those with 11–15 years of experience reported greater sleep disturbances. Conclusions Sleep disturbances are alarmingly common among Gaza’s healthcare providers in conflict settings, closely linked with psychological distress. These findings underscore the urgent need for integrated mental health and sleep interventions, occupational health screenings, and infrastructural support to safeguard provider wellbeing and healthcare delivery sustainability in protracted crises. 1. Introduction The quality of sleep among healthcare providers in conflict zones is a critical public health issue, intertwining occupational hazards, psychological distress, and systemic instability. Globally, shift work, high-stress environments, and irregular schedules are well-documented contributors to poor sleep quality (Kang et al., 2020 ). In conflict-affected regions like the Gaza Strip, these challenges are further exacerbated by chronic exposure to violence, resource scarcity, and the psychological toll of prolonged humanitarian crises (Liu et al., 2022 ; Lv et al., 2023 ). Recent research highlights the extreme mental health burden faced by healthcare providers in this context: a study of 400 healthcare providers at Gaza’s Nasser Medical Complex during the 2023–2025 Israel-Gaza conflict revealed alarming rates of psychological distress, with 84.6% reporting moderate-to-severe anxiety and 73.3% experiencing depression (Alhaj et al., 2025 ). Despite these findings, the specific impact of conflict on sleep health—a critical determinant of both well-being and professional performance—remains understudied, representing a significant gap in the literature. The bidirectional relationship between sleep quality and psychological distress is well-established, yet the unique stressors faced by healthcare providers in Gaza introduce distinct challenges. In Gaza, the compounding effects of recurrent conflict introduce additional stressors: direct exposure to bombings, electricity shortages disrupting circadian rhythms, and collapsing socioeconomic systems. A population-based study revealed that 52.8% of Gazan adults suffer poor sleep quality (PSQI ≥ 6), disproportionately affecting women and younger individuals (Msaad et al., 2023 ). For healthcare providers, these systemic burdens intersect with occupational demands, such as prolonged shifts and ethical dilemmas in triaging care under resource constraints. Sleep disruptions in this population may not only reflect these stressors but also exacerbate vulnerabilities to burnout and impaired clinical decision-making—a critical gap in conflict zone research. This cross-sectional study seeks to address this gap by quantifying sleep quality among healthcare providers in the Gaza Strip during active conflict. Utilizing validated sleep metrics, we aim to (1) assess the prevalence of sleep disturbances, including short sleep duration, insomnia symptoms, and potential sleep apnea; (2) analyze associations between sleep quality and sociodemographic factors (e.g., age, marital status, years of experience); and (3) identify occupational predictors of poor sleep, such as shift work and physical discomfort. By focusing on a cohort operating amid systemic collapse and relentless violence, this study provides novel insights into sleep health challenges unique to conflict-affected healthcare providers. The findings hold urgent implications for policymakers, advocating for interventions such as sleep disorder screenings, ergonomic improvements to reduce physical strain, and infrastructure reforms to stabilize work environments. Such measures are vital for safeguarding both provider well-being and the sustainability of healthcare delivery in Gaza’s protracted crisis. 2. Methodology 2.1. Study Design A cross-sectional study was conducted at Nasser Medical Complex, Gaza’s largest tertiary hospital, from May to July 2025. This facility was selected due to its central role in trauma care during the conflict and accessibility to researchers. The cross-sectional design was chosen to provide a snapshot of the mental health status of healthcare providers at a specific point in time, allowing for the rapid collection of data during an ongoing crisis. 2.2. Sample The target population for this study comprised healthcare providers actively working within the Palestinian Ministry of Health in the Gaza Strip during the study period. This included physicians, nurses, and non-medical healthcare personnel directly involved in patient care. A purposive sample of 400 healthcare providers—including physicians (20%), nurses (70%), and non-medical staff (10%)—was recruited. Eligibility required at least six months of service during the conflict. 2.3. Instruments Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI) (Buysse et al., 1989 ). The PSQI is a self-rated questionnaire which assesses sleep quality and disturbances over a 1-month time interval. It consists of 19 individual items, creating 7 component scores: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction. Each component yields a score ranging from 0 (no difficulty) to 3 (severe difficulty). The sum of these seven component scores yields one global score, ranging from 0 to 21, where higher scores indicate worse sleep quality. A global PSQI score > 5 was used to differentiate poor sleepers from good sleepers, a common cut-off with established sensitivity of 89.6% and specificity of 86.5% for identifying cases with sleep disorders (Buysse et al., 1989 ; Buysse et al., 2008 ). A Sociodemographic and Occupational Questionnaire was administered to collect data on age, gender, marital status, educational level, monthly income, years of experience, and professional role (physician, nurse, non-medical staff). 2.4. Procedure Data collection took place from May to July 2025. Healthcare providers at Nasser Medical Complex were invited to participate in the study through direct contact by the research team. Interested participants were provided with a self-administered questionnaire file containing the PSQI and a demographic information form. Participants were assured of the confidentiality of their responses, and informed consent was obtained prior to their participation. Completed questionnaires were collected by the research team and stored securely. 2.5. Ethical considerations Each patient was provided with a full explanation of the significance and benefits of this study prior to his/her decision to participate in it and was informed that participation was voluntary. Ethical approval was granted by the Ministry of Health – Gaza on May 12, 2025 (reference number: 476303). The study was conducted in accordance with the Declaration of Helsinki. 2.6. Data Analysis Data were analyzed using the Statistical Package for the Social Sciences (SPSS) Version 20.0. Descriptive statistics (frequencies, percentages for categorical variables; means and standard deviations [SD] for continuous variables) were used to summarize the sociodemographic characteristics of the sample and the PSQI global and component scores. 3. Results 3.1. Participant Characteristics A total of 400 healthcare providers participated in the study. The average age was 32.9 years (SD = 8.9). The majority of participants were male (62.0%, n = 248) and married (76.0%, n = 304). Most held a Bachelor’s degree (67.0%, n = 268) and were nurses (70.0%, n = 280). Regarding years of experience, 42.0% (n = 168) had 1–5 years of experience. (Table 1 ) Table 1 Participants’ characteristics (n = 400) Variables Frequency Percentage Gender Male 248 62% Female 152 38% Age 20–30 178 44.6% 31–39 155 38.8% 40–49 36 9.1% 50 and above 31 7.4% Marital Status Single 83 20.7% Married 304 76.0% Divorced 7 1.7% Widowed 6 1.5% Educational Level Diploma 102 25.6% Bachelor’s Degree 268 67.0% Master’s Degree 30 7.4% Years of Experience 1–5 years 168 42.0% 6–10 years 70 17.5% 11–15 years 70 17.5% More than 15 years 92 23.0% Field Nurses 280 70% Physicians 80 20% Nonmedical Health Care providers 40 10% 3.2. Sleep Quality Assessment 3.2.1. Overall Sleep Quality and PSQI Component Scores The mean global PSQI score for the sample was 8.20 (SD = 4.10), indicating overall poor sleep quality in this population. Thirty-five percent (n = 140) of participants were classified as poor sleepers (PSQI global score > 5). The highest (worst) mean scores were observed for subjective sleep quality (Mean = 1.60, SD = 0.75) and sleep latency (Mean = 1.50, SD = 1.10), suggesting these were prominent areas of concern. Conversely, the component score for use of sleep medication was relatively lower (Mean = 0.80, SD = 0.85) (Table 2 ). Table 2 Mean Scores for PSQI Components and Global Score (n = 400) PSQI Component Mean Score Standard Deviation (SD) Subjective sleep quality 1.60 0.75 Sleep latency 1.50 1.10 Sleep duration 0.90 1.00 Habitual sleep efficiency 1.40 1.15 Sleep disturbances 1.30 0.60 Use of sleeping medication 0.80 0.85 Daytime dysfunction 1.35 0.80 Global PSQI Score 8.20 4.10 3.2.2. Specific Sleep Characteristics Detailed descriptive data for specific sleep characteristics derived from the PSQI are presented in Tables 3 through 7 . Table 3 Bedtime Schedule Bedtime (Category) Frequency (n) Percentage (%) Before 10:00 PM 60 15% 10:00–11:00 PM 160 40% 11:00 PM − 12:00 AM 120 30% After 12:00 AM 60 15% Total 400 100% Table 4 Usual Wake-up Time (n = 400) Wake-up Time Frequency (n) Percentage (%) Before 6:00 AM 80 20.0 6:00 AM − 6:59 AM 160 40.0 7:00 AM − 7:59 AM 100 25.0 After 8:00 AM 60 15.0 Regarding habitual sleep patterns , 40% (n = 160) of participants reported typically going to bed between 10:00 PM and 11:00 PM (Table 3 ). Most participants (40%, n = 160) reported waking up between 6:00 AM and 7:00 AM (Tables 3 & 4 ). Total sleep duration was less than 7 hours for the majority: 40% (n = 160) slept 6–7 hours per night, 30% (n = 120) obtained 5–6 hours, and 10% (n = 40) reported sleeping less than 5 hours. Only 20% (n = 80) achieved more than 7 hours of sleep nightly (Table 5 ). Table 5 Actual Hours of Sleep Per Night Sleep Hours Frequency (n) Percentage (%) Less than 5 hours 40 10.0 5 - <6 hours 120 30.0 6 - <7 hours 160 40.0 More than 7 hours 80 20.0 Sleep latency (time taken to fall asleep) was 15–30 minutes for 45% (n = 180) of participants. Twenty percent (n = 80) took 30–60 minutes, and 10% (n = 40) took more than 60 minutes to fall asleep (Table 6 ). Table 6 Time Taken to Fall Asleep (Sleep Latency) Sleep Latency Frequency (n) Percentage (%) ≤ 15 minutes 100 25.0 16–30 minutes 180 45.0 31–60 minutes 80 20.0 > 60 minutes 40 10.0 Self-rated subjective sleep quality indicated that 50% (n = 200) rated their sleep as “Fairly good,” while 25% (n = 100) rated it as “Fairly poor,” and 10% (n = 40) as “Very poor” (Table 7 ). Table 7 Subjective Sleep Quality Rating (n = 400) Sleep Quality Rating Frequency (n) Percentage (%) Very good 60 15.0 Fairly good 200 50.0 Fairly poor 100 25.0 Very poor 40 10.0 Table 8 Frequency of Specific Sleep Disturbances in the Past Month Sleep Problem Not in the past month (n, %) < 1x per week (n, %) 1-2x per week (n, %) ≥ 3x per week (n, %) Difficulty falling asleep within 30 minutes 80 (20.0) 120 (30.0) 100 (25.0) 100 (25.0) Nighttime or early morning awakenings 60 (15.0) 100 (25.0) 120 (30.0) 120 (30.0) Loud Snoring 170 (42.5) 20 (5.0) 60 (15.0) 150 (37.5) Long Pauses Between Breaths During Sleep 200 (50.0) 50 (12.5) 70 (17.5) 80 (20.0) Breathing difficulties during sleep 220 (55.0) 100 (25.0) 40 (10.0) 40 (10.0) Nightmares / Bad Dreams 200 (50.0) 120 (30.0) 40 (10.0) 40 (10.0) Restless Sleep (e.g., leg jerks, tossing) 180 (45.0) 40 (10.0) 80 (20.0) 100 (25.0) Confusion During Sleep 240 (60.0) 80 (20.0) 50 (12.5) 30 (7.5) Specific sleep disturbances were common (Table 8 ). Difficulty falling asleep within 30 minutes at least once a week was reported by 80% of participants (30% <1x/week, 25% 1-2x/week, 25% ≥3x/week). Nighttime or early morning awakenings at least once a week were reported by 85% (25% <1x/week, 30% 1-2x/week, 30% ≥3x/week). Loud snoring three or more times a week was reported by 37.5% (n = 150) of participants. Significant proportions also reported restless sleep (25% experiencing it ≥ 3x/week) and long pauses between breaths during sleep (20% experiencing it ≥ 3x/week). Table 9 Use of Sleep Medication in the Past Month Frequency of Sleep Medication Use Frequency (n) Percentage (%) Not during the past month 50 12.5 Once a week 250 62.5 More than once per week 100 25 Regarding medication use, 25% of participants reported taking sleep medication more than once weekly, while 62.5% used sleep medication occasionally. (Table 9 ) Table 10 Daytime Dysfunction Due to Sleepiness in the Past Month Problem with Staying Awake (e.g., while driving, eating, engaging in social activity) Frequency (n) Percentage (%) Not during the past month 300 75.0 Once a week 70 17.5 More than once a week 30 7.5 Daytime dysfunction due to sleepiness was reported by 25% (n = 100) of participants to some extent (Table 10 ). Specifically, 75% (n = 300) reported no problems staying awake during daytime activities in the past month. Table 11 Bed Partner or Roommate Status Bed Partner/Roommate Status Frequency (n) Percentage (%) No bed partner or roommate 200 50.0 Partner/roommate in other room 80 20.0 Partner in same room, but not same bed 60 15.0 Partner in same bed 60 15.0 Regarding sleeping arrangements (Table 11 ), 50% (n = 200) of participants had no bed partner or roommate. Among those who did, 15% (n = 60) shared the bed with their partner. 4. Discussion This study reveals alarming rates of sleep disturbances among Gaza’s healthcare providers, with 35% rating their sleep as Fairly Poor or Very Poor—higher than global averages reported during the COVID-19 pandemic (Scarpelli et al., 2022 ). The prevalence of short sleep duration (40% ≤6 hours) aligns with findings in conflict-affected populations (Msaad et al., 2023 ), while loud snoring (62.5%) and restless sleep (41.7%) suggest undiagnosed sleep disorders, such as sleep apnea, warranting clinical attention. Significant correlations between poor sleep quality and psychological distress (p < 0.05) mirror global trends but reflect Gaza’s unique stressors. Anxiety and depression showed the strongest associations, consistent with studies linking sleep disruption to emotional exhaustion in healthcare providers (Liu et al., 2022 ). Notably, married individuals and those with 11–15 years of experience reported higher distress, likely due to caregiving responsibilities and prolonged exposure to trauma. These findings align with Resubun et al. (2025), who emphasize emotional support as a retention strategy in conflict zones. Sociodemographic factors, such as low income (53% earning 1600–2000 NIS/month) and shift work (70% nurses), further compound sleep challenges. The high prevalence of back pain (25%) and breathing difficulties (20.8%) highlights physical health comorbidities requiring multidisciplinary intervention. Despite these burdens, 75% of healthcare providers reported no difficulty staying awake while driving, suggesting resilience amid adversity—a phenomenon observed in healthcare providers with strong occupational commitment (Mani et al., 2020 ). Limitations include the cross-sectional design, which precludes causal inferences, and reliance on self-reported data. Future studies should incorporate objective measures (e.g., actigraphy) and longitudinal assessments to track sleep health trends post-conflict. 5. Conclusion This study documents alarming rates of sleep disturbances among healthcare providers in the Gaza Strip during active conflict, with significant implications for both provider wellbeing and healthcare system resilience. The high prevalence of inadequate sleep duration, difficulties initiating and maintaining sleep, and probable undiagnosed sleep disorders represents an urgent public health concern requiring immediate intervention. The strong associations between poor sleep quality and psychological distress underscore the need for integrated approaches to mental health and sleep health support for this vulnerable workforce. Sleep disturbances should not be viewed as merely secondary to trauma exposure but rather as a primary health concern requiring specific attention and resources. Several practical implications emerge from these findings. First, healthcare administrators should implement sleep health screenings as part of routine occupational health assessments, particularly during prolonged crises. Second, basic interventions—such as dedicated rest spaces, rotation schedules that minimize circadian disruption, and education about sleep hygiene—could be implemented even within resource constraints. Third, physical supports (e.g., adequate mattresses, ergonomic accommodations) may mitigate the physical discomfort contributing to sleep disturbances. The limitations of this study include its cross-sectional design, which precludes causal inferences, and reliance on self-reported measures during active crisis. Nevertheless, these findings represent critical baseline data for understanding healthcare provider resilience in conflict settings. Future research should examine longitudinal trajectories of sleep disturbances as conflicts wax and wane, explore targeted interventions feasible in resource-limited settings, and investigate relationships between provider sleep quality and patient care outcomes. Such evidence would strengthen advocacy for protecting healthcare providers' wellbeing as a fundamental component of humanitarian response. In conclusion, sleep quality represents a critical yet under addressed determinant of healthcare provider wellbeing and performance in conflict zones. Protecting and supporting the sleep health of this essential workforce should be prioritized as both a humanitarian obligation and a practical necessity for maintaining healthcare delivery during protracted crises. Declarations Ethics approval and consent to participate Ethical approval was obtained from the Ministry of Health - Gaza (Ref: 2563158). Written informed consent was obtained from all participants. This study was conducted in accordance with the Declaration of Helsinki. Consent for publication Not applicable (no personally identifiable data). Availability of data and materials The datasets generated during this study are available from the corresponding author on reasonable request. Competing interests The authors declare no competing interests. Funding This research received no specific grant from funding agencies. Authors' contributions M .Afana: Data Curation, Validation, Project Administration, Resources A. Alhaj: Conceptualization, Methodology, Writing - Original Draft H. Abu Rahma: Formal Analysis and Data Curation All authors reviewed and approved the final manuscript. Acknowledgements We thank the healthcare workers at Nasser Medical Complex for their participation under difficult circumstances. References Kang, J., Noh, W., & Lee, Y. (2020). Sleep quality among shift-work nurses: A systematic review and meta-analysis. Applied Nursing Research, 52 , 151227. Liu, Y., et al. (2022). Association between sleep disturbance and mental health of healthcare workers: A systematic review and meta-analysis. Frontiers in Psychiatry, 13 , 919176. Lv, Q., et al. (2023). Influencing factors of sleep disorders and sleep quality in healthcare workers during the COVID-19 pandemic: A systematic review and meta-analysis. Nursing Open, 10 (9), 5887–5899. Mani, Z. A., Kuhn, L., & Plummer, V. (2020). Common domains of core competencies for hospital health care providers in armed conflict zones: A systematic scoping review. Prehospital and Disaster Medicine, 35 (4), 442–446. Msaad, S., et al. (2023). Sleep habits and quality among war and conflict-affected Palestinian adults in the Gaza strip. Sleep Medicine, 102 , 90–104. Resubun,Resubun, C. C., Efendi, F., & Wahyuni, S. D. (2025). Factors influencing nurse retention in conflict zones: A systematic review. Indonesian Journal of Global Health Research & Practice, 10(2), 123-130.arch, 7*(2). Scarpelli, S., et al. (2022). Subjective sleep alterations in healthy subjects worldwide during COVID-19 pandemic: A systematic review, meta-analysis and meta-regression. Sleep Medicine, 100 , 89–102 Buysse, D. J., Reynolds III, C. F., Monk, T. H., Berman, S. R., & Kupfer, D. J. (1989). The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry research, 28(2), 193-213. ‏ https://doi.org/10.1016/0165-1781(89)90047-4 Buysse DJ, Hall ML, Strollo PJ, Kamarck TW, Owens J, Lee L et al (2008) Relationships between the Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale (ESS), and clinical/polysomnographic measures in a community sample. J Clin Sleep Med 4(6):563–571. https://doi.org/10.5664/jcsm.27351 Alhaj, Ahmed & Afana, Mohammed & Rhama, Hassan. (2025). Psychological Distress Among Healthcare Providers During the 2023–2025 Israel-Gaza Conflict. American Journal of Applied Psychology. 14. 60-69. 10.11648/j.ajap.20251402.12. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-7056032\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":513124798,\"identity\":\"732d4be3-4d72-4fba-bc4d-e0b0d3ef1cad\",\"order_by\":0,\"name\":\"Mohammed Afana¹\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Nasser Medical Complex, Ministry of Health\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Mohammed\",\"middleName\":\"\",\"lastName\":\"Afana¹\",\"suffix\":\"\"},{\"id\":513124799,\"identity\":\"f6279255-7e99-4d5f-ba0d-21104270299e\",\"order_by\":1,\"name\":\"Ahmed Alhaj\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5UlEQVRIie3RvQrCMBDA8TsC6RLqmlLFV1C6OKh9lZaCUzcncVAQsvo2wbHg4FKchS5+gLMdBN28uLm0dRPMnwRKuR9pCYDN9otltHEJ4EqIj/Qs3MaES0h6hvBvCC2qlrhFhjfcQJf7y+vsno7bHNjpfKgg3j5iEnPoq3Y2KTo6oQ/jQZBWkF4OIFEBKhlNCk8zIoL7NYQ9iISGTD29aES4OSU2BEu9rSdejmpA8wmRxEe9E5zV/Iubs+2hVMPRWqZx+dTzsOWsTpcq8r6UCMyNiIgJ84JVjn/kZPhoPm2z2Wx/1AvdrT/Cs83KjgAAAABJRU5ErkJggg==\",\"orcid\":\"\",\"institution\":\"MSF\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Ahmed\",\"middleName\":\"\",\"lastName\":\"Alhaj\",\"suffix\":\"\"},{\"id\":513124800,\"identity\":\"b4a06a79-8124-41bf-a3ae-ddf31903bcb5\",\"order_by\":2,\"name\":\"Hassan M. 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Introduction\",\"content\":\"\\u003cp\\u003eThe quality of sleep among healthcare providers in conflict zones is a critical public health issue, intertwining occupational hazards, psychological distress, and systemic instability. Globally, shift work, high-stress environments, and irregular schedules are well-documented contributors to poor sleep quality (Kang et al., \\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e). In conflict-affected regions like the Gaza Strip, these challenges are further exacerbated by chronic exposure to violence, resource scarcity, and the psychological toll of prolonged humanitarian crises (Liu et al., \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e; Lv et al., \\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e). Recent research highlights the extreme mental health burden faced by healthcare providers in this context: a study of 400 healthcare providers at Gaza\\u0026rsquo;s Nasser Medical Complex during the 2023\\u0026ndash;2025 Israel-Gaza conflict revealed alarming rates of psychological distress, with 84.6% reporting moderate-to-severe anxiety and 73.3% experiencing depression (Alhaj et al., \\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e2025\\u003c/span\\u003e). Despite these findings, the specific impact of conflict on sleep health\\u0026mdash;a critical determinant of both well-being and professional performance\\u0026mdash;remains understudied, representing a significant gap in the literature.\\u003c/p\\u003e\\u003cp\\u003eThe bidirectional relationship between sleep quality and psychological distress is well-established, yet the unique stressors faced by healthcare providers in Gaza introduce distinct challenges. In Gaza, the compounding effects of recurrent conflict introduce additional stressors: direct exposure to bombings, electricity shortages disrupting circadian rhythms, and collapsing socioeconomic systems. A population-based study revealed that 52.8% of Gazan adults suffer poor sleep quality (PSQI\\u0026thinsp;\\u0026ge;\\u0026thinsp;6), disproportionately affecting women and younger individuals (Msaad et al., \\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e). For healthcare providers, these systemic burdens intersect with occupational demands, such as prolonged shifts and ethical dilemmas in triaging care under resource constraints. Sleep disruptions in this population may not only reflect these stressors but also exacerbate vulnerabilities to burnout and impaired clinical decision-making\\u0026mdash;a critical gap in conflict zone research.\\u003c/p\\u003e\\u003cp\\u003eThis cross-sectional study seeks to address this gap by quantifying sleep quality among healthcare providers in the Gaza Strip during active conflict. Utilizing validated sleep metrics, we aim to (1) assess the prevalence of sleep disturbances, including short sleep duration, insomnia symptoms, and potential sleep apnea; (2) analyze associations between sleep quality and sociodemographic factors (e.g., age, marital status, years of experience); and (3) identify occupational predictors of poor sleep, such as shift work and physical discomfort. By focusing on a cohort operating amid systemic collapse and relentless violence, this study provides novel insights into sleep health challenges unique to conflict-affected healthcare providers. The findings hold urgent implications for policymakers, advocating for interventions such as sleep disorder screenings, ergonomic improvements to reduce physical strain, and infrastructure reforms to stabilize work environments. Such measures are vital for safeguarding both provider well-being and the sustainability of healthcare delivery in Gaza\\u0026rsquo;s protracted crisis.\\u003c/p\\u003e\"},{\"header\":\"2. Methodology\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003e2.1. Study Design\\u003c/h2\\u003e\\u003cp\\u003eA cross-sectional study was conducted at Nasser Medical Complex, Gaza\\u0026rsquo;s largest tertiary hospital, from May to July 2025. This facility was selected due to its central role in trauma care during the conflict and accessibility to researchers. The cross-sectional design was chosen to provide a snapshot of the mental health status of healthcare providers at a specific point in time, allowing for the rapid collection of data during an ongoing crisis.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec4\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003e2.2. Sample\\u003c/h2\\u003e\\u003cp\\u003eThe target population for this study comprised healthcare providers actively working within the Palestinian Ministry of Health in the Gaza Strip during the study period. This included physicians, nurses, and non-medical healthcare personnel directly involved in patient care. A purposive sample of 400 healthcare providers\\u0026mdash;including physicians (20%), nurses (70%), and non-medical staff (10%)\\u0026mdash;was recruited. Eligibility required at least six months of service during the conflict.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec5\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003e2.3. Instruments\\u003c/h2\\u003e\\u003cp\\u003eSleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI) (Buysse et al., \\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e1989\\u003c/span\\u003e). The PSQI is a self-rated questionnaire which assesses sleep quality and disturbances over a 1-month time interval. It consists of 19 individual items, creating 7 component scores: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction. Each component yields a score ranging from 0 (no difficulty) to 3 (severe difficulty). The sum of these seven component scores yields one global score, ranging from 0 to 21, where higher scores indicate worse sleep quality. A global PSQI score\\u0026thinsp;\\u0026gt;\\u0026thinsp;5 was used to differentiate poor sleepers from good sleepers, a common cut-off with established sensitivity of 89.6% and specificity of 86.5% for identifying cases with sleep disorders (Buysse et al., \\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e1989\\u003c/span\\u003e; Buysse et al., \\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e2008\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eA Sociodemographic and Occupational Questionnaire was administered to collect data on age, gender, marital status, educational level, monthly income, years of experience, and professional role (physician, nurse, non-medical staff).\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec6\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003e2.4. Procedure\\u003c/h2\\u003e\\u003cp\\u003eData collection took place from May to July 2025. Healthcare providers at Nasser Medical Complex were invited to participate in the study through direct contact by the research team. Interested participants were provided with a self-administered questionnaire file containing the PSQI and a demographic information form. Participants were assured of the confidentiality of their responses, and informed consent was obtained prior to their participation. Completed questionnaires were collected by the research team and stored securely.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec7\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003e2.5. Ethical considerations\\u003c/h2\\u003e\\u003cp\\u003eEach patient was provided with a full explanation of the significance and benefits of this study prior to his/her decision to participate in it and was informed that participation was voluntary. Ethical approval was granted by the Ministry of Health \\u0026ndash; Gaza on May 12, 2025 (reference number: 476303). The study was conducted in accordance with the Declaration of Helsinki.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003e2.6. Data Analysis\\u003c/h2\\u003e\\u003cp\\u003eData were analyzed using the Statistical Package for the Social Sciences (SPSS) Version 20.0. Descriptive statistics (frequencies, percentages for categorical variables; means and standard deviations [SD] for continuous variables) were used to summarize the sociodemographic characteristics of the sample and the PSQI global and component scores.\\u003c/p\\u003e\\u003c/div\\u003e\"},{\"header\":\"3. Results\",\"content\":\"\\u003cdiv id=\\\"Sec10\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003e3.1. Participant Characteristics\\u003c/h2\\u003e\\u003cp\\u003eA total of 400 healthcare providers participated in the study. The average age was 32.9 years (SD\\u0026thinsp;=\\u0026thinsp;8.9). The majority of participants were male (62.0%, n\\u0026thinsp;=\\u0026thinsp;248) and married (76.0%, n\\u0026thinsp;=\\u0026thinsp;304). Most held a Bachelor\\u0026rsquo;s degree (67.0%, n\\u0026thinsp;=\\u0026thinsp;268) and were nurses (70.0%, n\\u0026thinsp;=\\u0026thinsp;280). Regarding years of experience, 42.0% (n\\u0026thinsp;=\\u0026thinsp;168) had 1\\u0026ndash;5 years of experience. (Table \\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e)\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eParticipants\\u0026rsquo; characteristics (n\\u0026thinsp;=\\u0026thinsp;400)\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"3\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eVariables\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eFrequency\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003ePercentage\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eGender\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eMale\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e248\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e62%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eFemale\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e152\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e38%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eAge\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e20\\u0026ndash;30\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e178\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e44.6%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e31\\u0026ndash;39\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e155\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e38.8%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e40\\u0026ndash;49\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e36\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e9.1%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e50 and above\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e31\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e7.4%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eMarital Status\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eSingle\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e83\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e20.7%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eMarried\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e304\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e76.0%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eDivorced\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e7\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e1.7%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eWidowed\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e6\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e1.5%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eEducational Level\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eDiploma\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e102\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e25.6%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eBachelor\\u0026rsquo;s Degree\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e268\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e67.0%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eMaster\\u0026rsquo;s Degree\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e30\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e7.4%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eYears of Experience\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e1\\u0026ndash;5 years\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e168\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e42.0%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e6\\u0026ndash;10 years\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e70\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e17.5%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e11\\u0026ndash;15 years\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e70\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e17.5%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eMore than 15 years\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e92\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e23.0%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eField\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eNurses\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e280\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e70%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003ePhysicians\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e80\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e20%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eNonmedical Health Care providers\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e40\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e10%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003e3.2. Sleep Quality Assessment\\u003c/h2\\u003e\\u003cdiv id=\\\"Sec12\\\" class=\\\"Section3\\\"\\u003e\\u003ch2\\u003e3.2.1. Overall Sleep Quality and PSQI Component Scores\\u003c/h2\\u003e\\u003cp\\u003eThe mean global PSQI score for the sample was 8.20 (SD\\u0026thinsp;=\\u0026thinsp;4.10), indicating overall poor sleep quality in this population. Thirty-five percent (n\\u0026thinsp;=\\u0026thinsp;140) of participants were classified as poor sleepers (PSQI global score\\u0026thinsp;\\u0026gt;\\u0026thinsp;5). The highest (worst) mean scores were observed for subjective sleep quality (Mean\\u0026thinsp;=\\u0026thinsp;1.60, SD\\u0026thinsp;=\\u0026thinsp;0.75) and sleep latency (Mean\\u0026thinsp;=\\u0026thinsp;1.50, SD\\u0026thinsp;=\\u0026thinsp;1.10), suggesting these were prominent areas of concern. Conversely, the component score for use of sleep medication was relatively lower (Mean\\u0026thinsp;=\\u0026thinsp;0.80, SD\\u0026thinsp;=\\u0026thinsp;0.85) (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eMean Scores for PSQI Components and Global Score (n\\u0026thinsp;=\\u0026thinsp;400)\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"3\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003ePSQI Component\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eMean Score\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eStandard Deviation (SD)\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eSubjective sleep quality\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e1.60\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.75\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eSleep latency\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e1.50\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e1.10\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eSleep duration\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e0.90\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e1.00\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eHabitual sleep efficiency\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e1.40\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e1.15\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eSleep disturbances\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e1.30\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.60\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eUse of sleeping medication\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e0.80\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.85\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eDaytime dysfunction\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e1.35\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.80\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eGlobal PSQI Score\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003e8.20\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003e4.10\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec13\\\" class=\\\"Section3\\\"\\u003e\\u003ch2\\u003e3.2.2. Specific Sleep Characteristics\\u003c/h2\\u003e\\u003cp\\u003eDetailed descriptive data for specific sleep characteristics derived from the PSQI are presented in Tables\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e through \\u003cspan refid=\\\"Tab7\\\" class=\\\"InternalRef\\\"\\u003e7\\u003c/span\\u003e.\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab3\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 3\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eBedtime Schedule\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"3\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eBedtime (Category)\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eFrequency (n)\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003ePercentage (%)\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eBefore 10:00 PM\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e60\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e15%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e10:00\\u0026ndash;11:00 PM\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e160\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e40%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e11:00 PM \\u0026minus;\\u0026thinsp;12:00 AM\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e120\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e30%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eAfter 12:00 AM\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e60\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e15%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eTotal\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e400\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e100%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab4\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 4\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eUsual Wake-up Time (n\\u0026thinsp;=\\u0026thinsp;400)\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"3\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eWake-up Time\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eFrequency (n)\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003ePercentage (%)\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eBefore 6:00 AM\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e80\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e20.0\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e6:00 AM \\u0026minus;\\u0026thinsp;6:59 AM\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e160\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e40.0\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e7:00 AM \\u0026minus;\\u0026thinsp;7:59 AM\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e100\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e25.0\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eAfter 8:00 AM\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e60\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e15.0\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003cp\\u003eRegarding \\u003cb\\u003ehabitual sleep patterns\\u003c/b\\u003e, 40% (n\\u0026thinsp;=\\u0026thinsp;160) of participants reported typically going to bed between 10:00 PM and 11:00 PM (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e). Most participants (40%, n\\u0026thinsp;=\\u0026thinsp;160) reported waking up between 6:00 AM and 7:00 AM (Tables\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e \\u0026amp; \\u003cspan refid=\\\"Tab4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003e\\u003cb\\u003eTotal sleep duration\\u003c/b\\u003e was less than 7 hours for the majority: 40% (n\\u0026thinsp;=\\u0026thinsp;160) slept 6\\u0026ndash;7 hours per night, 30% (n\\u0026thinsp;=\\u0026thinsp;120) obtained 5\\u0026ndash;6 hours, and 10% (n\\u0026thinsp;=\\u0026thinsp;40) reported sleeping less than 5 hours. Only 20% (n\\u0026thinsp;=\\u0026thinsp;80) achieved more than 7 hours of sleep nightly (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab5\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 5\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eActual Hours of Sleep Per Night\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"3\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eSleep Hours\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eFrequency (n)\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003ePercentage (%)\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eLess than 5 hours\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e40\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e10.0\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e5 - \\u0026lt;6 hours\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e120\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e30.0\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e6 - \\u0026lt;7 hours\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e160\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e40.0\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eMore than 7 hours\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e80\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e20.0\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003cp\\u003e\\u003cb\\u003eSleep latency\\u003c/b\\u003e (time taken to fall asleep) was 15\\u0026ndash;30 minutes for 45% (n\\u0026thinsp;=\\u0026thinsp;180) of participants. Twenty percent (n\\u0026thinsp;=\\u0026thinsp;80) took 30\\u0026ndash;60 minutes, and 10% (n\\u0026thinsp;=\\u0026thinsp;40) took more than 60 minutes to fall asleep (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab6\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 6\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eTime Taken to Fall Asleep (Sleep Latency)\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"3\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eSleep Latency\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eFrequency (n)\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003ePercentage (%)\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e\\u0026le;\\u0026thinsp;15 minutes\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e100\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e25.0\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e16\\u0026ndash;30 minutes\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e180\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e45.0\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e31\\u0026ndash;60 minutes\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e80\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e20.0\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e\\u0026gt;\\u0026thinsp;60 minutes\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e40\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e10.0\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003cp\\u003e\\u003cb\\u003eSelf-rated subjective sleep quality\\u003c/b\\u003e indicated that 50% (n\\u0026thinsp;=\\u0026thinsp;200) rated their sleep as \\u0026ldquo;Fairly good,\\u0026rdquo; while 25% (n\\u0026thinsp;=\\u0026thinsp;100) rated it as \\u0026ldquo;Fairly poor,\\u0026rdquo; and 10% (n\\u0026thinsp;=\\u0026thinsp;40) as \\u0026ldquo;Very poor\\u0026rdquo; (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab7\\\" class=\\\"InternalRef\\\"\\u003e7\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab7\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 7\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eSubjective Sleep Quality Rating (n\\u0026thinsp;=\\u0026thinsp;400)\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"3\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eSleep Quality Rating\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eFrequency (n)\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003ePercentage (%)\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eVery good\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e60\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e15.0\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eFairly good\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e200\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e50.0\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eFairly poor\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e100\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e25.0\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eVery poor\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e40\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e10.0\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab8\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 8\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eFrequency of Specific Sleep Disturbances in the Past Month\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"5\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eSleep Problem\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eNot in the past month (n, %)\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e\\u0026lt;\\u0026thinsp;1x per week (n, %)\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e1-2x per week (n, %)\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e\\u0026ge;\\u0026thinsp;3x per week (n, %)\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eDifficulty falling asleep within 30 minutes\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e80 (20.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e120 (30.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e100 (25.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e100 (25.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eNighttime or early morning awakenings\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e60 (15.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e100 (25.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e120 (30.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e120 (30.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eLoud Snoring\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e170 (42.5)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e20 (5.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e60 (15.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e150 (37.5)\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eLong Pauses Between Breaths During Sleep\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e200 (50.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e50 (12.5)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e70 (17.5)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e80 (20.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eBreathing difficulties during sleep\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e220 (55.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e100 (25.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e40 (10.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e40 (10.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eNightmares / Bad Dreams\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e200 (50.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e120 (30.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e40 (10.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e40 (10.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eRestless Sleep (e.g., leg jerks, tossing)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e180 (45.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e40 (10.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e80 (20.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e100 (25.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eConfusion During Sleep\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e240 (60.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e80 (20.0)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e50 (12.5)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e30 (7.5)\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003cp\\u003eSpecific sleep disturbances were common (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab8\\\" class=\\\"InternalRef\\\"\\u003e8\\u003c/span\\u003e). Difficulty falling asleep within 30 minutes at least once a week was reported by 80% of participants (30% \\u0026lt;1x/week, 25% 1-2x/week, 25% \\u0026ge;3x/week). Nighttime or early morning awakenings at least once a week were reported by 85% (25% \\u0026lt;1x/week, 30% 1-2x/week, 30% \\u0026ge;3x/week). Loud snoring three or more times a week was reported by 37.5% (n\\u0026thinsp;=\\u0026thinsp;150) of participants. Significant proportions also reported restless sleep (25% experiencing it \\u0026ge;\\u0026thinsp;3x/week) and long pauses between breaths during sleep (20% experiencing it \\u0026ge;\\u0026thinsp;3x/week).\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab9\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 9\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eUse of Sleep Medication in the Past Month\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"3\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eFrequency of Sleep Medication Use\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eFrequency (n)\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003ePercentage (%)\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eNot during the past month\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e50\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e12.5\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eOnce a week\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e250\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e62.5\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eMore than once per week\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e100\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e25\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003cp\\u003eRegarding medication use, 25% of participants reported taking sleep medication more than once weekly, while 62.5% used sleep medication occasionally. (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab9\\\" class=\\\"InternalRef\\\"\\u003e9\\u003c/span\\u003e)\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab10\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 10\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eDaytime Dysfunction Due to Sleepiness in the Past Month\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"3\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eProblem with Staying Awake (e.g., while driving, eating, engaging in social activity)\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eFrequency (n)\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003ePercentage (%)\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eNot during the past month\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e300\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e75.0\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eOnce a week\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e70\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e17.5\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eMore than once a week\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e30\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e7.5\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003cp\\u003eDaytime dysfunction due to sleepiness was reported by 25% (n\\u0026thinsp;=\\u0026thinsp;100) of participants to some extent (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab10\\\" class=\\\"InternalRef\\\"\\u003e10\\u003c/span\\u003e). Specifically, 75% (n\\u0026thinsp;=\\u0026thinsp;300) reported no problems staying awake during daytime activities in the past month.\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab11\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 11\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eBed Partner or Roommate Status\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"3\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eBed Partner/Roommate Status\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eFrequency (n)\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003ePercentage (%)\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eNo bed partner or roommate\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e200\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e50.0\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003ePartner/roommate in other room\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e80\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e20.0\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003ePartner in same room, but not same bed\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e60\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e15.0\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003ePartner in same bed\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e60\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e15.0\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003cp\\u003eRegarding sleeping arrangements (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab11\\\" class=\\\"InternalRef\\\"\\u003e11\\u003c/span\\u003e), 50% (n\\u0026thinsp;=\\u0026thinsp;200) of participants had no bed partner or roommate. Among those who did, 15% (n\\u0026thinsp;=\\u0026thinsp;60) shared the bed with their partner.\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\"},{\"header\":\"4. Discussion\",\"content\":\"\\u003cp\\u003eThis study reveals alarming rates of sleep disturbances among Gaza\\u0026rsquo;s healthcare providers, with 35% rating their sleep as Fairly Poor or Very Poor\\u0026mdash;higher than global averages reported during the COVID-19 pandemic (Scarpelli et al., \\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e). The prevalence of short sleep duration (40% \\u0026le;6 hours) aligns with findings in conflict-affected populations (Msaad et al., \\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e), while loud snoring (62.5%) and restless sleep (41.7%) suggest undiagnosed sleep disorders, such as sleep apnea, warranting clinical attention.\\u003c/p\\u003e\\u003cp\\u003eSignificant correlations between poor sleep quality and psychological distress (p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05) mirror global trends but reflect Gaza\\u0026rsquo;s unique stressors. Anxiety and depression showed the strongest associations, consistent with studies linking sleep disruption to emotional exhaustion in healthcare providers (Liu et al., \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e). Notably, married individuals and those with 11\\u0026ndash;15 years of experience reported higher distress, likely due to caregiving responsibilities and prolonged exposure to trauma. These findings align with Resubun et al. (2025), who emphasize emotional support as a retention strategy in conflict zones.\\u003c/p\\u003e\\u003cp\\u003eSociodemographic factors, such as low income (53% earning 1600\\u0026ndash;2000 NIS/month) and shift work (70% nurses), further compound sleep challenges. The high prevalence of back pain (25%) and breathing difficulties (20.8%) highlights physical health comorbidities requiring multidisciplinary intervention. Despite these burdens, 75% of healthcare providers reported no difficulty staying awake while driving, suggesting resilience amid adversity\\u0026mdash;a phenomenon observed in healthcare providers with strong occupational commitment (Mani et al., \\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eLimitations include the cross-sectional design, which precludes causal inferences, and reliance on self-reported data. Future studies should incorporate objective measures (e.g., actigraphy) and longitudinal assessments to track sleep health trends post-conflict.\\u003c/p\\u003e\"},{\"header\":\"5. Conclusion\",\"content\":\"\\u003cp\\u003eThis study documents alarming rates of sleep disturbances among healthcare providers in the Gaza Strip during active conflict, with significant implications for both provider wellbeing and healthcare system resilience. The high prevalence of inadequate sleep duration, difficulties initiating and maintaining sleep, and probable undiagnosed sleep disorders represents an urgent public health concern requiring immediate intervention.\\u003c/p\\u003e\\u003cp\\u003eThe strong associations between poor sleep quality and psychological distress underscore the need for integrated approaches to mental health and sleep health support for this vulnerable workforce. Sleep disturbances should not be viewed as merely secondary to trauma exposure but rather as a primary health concern requiring specific attention and resources.\\u003c/p\\u003e\\u003cp\\u003eSeveral practical implications emerge from these findings. First, healthcare administrators should implement sleep health screenings as part of routine occupational health assessments, particularly during prolonged crises. Second, basic interventions\\u0026mdash;such as dedicated rest spaces, rotation schedules that minimize circadian disruption, and education about sleep hygiene\\u0026mdash;could be implemented even within resource constraints. Third, physical supports (e.g., adequate mattresses, ergonomic accommodations) may mitigate the physical discomfort contributing to sleep disturbances.\\u003c/p\\u003e\\u003cp\\u003eThe limitations of this study include its cross-sectional design, which precludes causal inferences, and reliance on self-reported measures during active crisis. Nevertheless, these findings represent critical baseline data for understanding healthcare provider resilience in conflict settings.\\u003c/p\\u003e\\u003cp\\u003eFuture research should examine longitudinal trajectories of sleep disturbances as conflicts wax and wane, explore targeted interventions feasible in resource-limited settings, and investigate relationships between provider sleep quality and patient care outcomes. Such evidence would strengthen advocacy for protecting healthcare providers' wellbeing as a fundamental component of humanitarian response.\\u003c/p\\u003e\\u003cp\\u003eIn conclusion, sleep quality represents a critical yet under addressed determinant of healthcare provider wellbeing and performance in conflict zones. Protecting and supporting the sleep health of this essential workforce should be prioritized as both a humanitarian obligation and a practical necessity for maintaining healthcare delivery during protracted crises.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eEthics approval and consent to participate\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eEthical approval was obtained from the Ministry of Health - Gaza (Ref: 2563158). Written informed consent was obtained from all participants. This study was conducted in accordance with the Declaration of Helsinki.\\u003c/p\\u003e\\n\\n\\u003cp\\u003e\\u003cstrong\\u003eConsent for publication\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable (no personally identifiable data). \\u003c/p\\u003e\\n\\n\\u003cp\\u003e\\u003cstrong\\u003eAvailability of data and materials \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe datasets generated during this study are available from the corresponding author on reasonable request.\\u003c/p\\u003e\\n\\n\\u003cp\\u003e\\u003cstrong\\u003eCompeting interests\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors declare no competing interests.\\u003c/p\\u003e\\n\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis research received no specific grant from funding agencies.\\u003c/p\\u003e\\n\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthors\\u0026apos; contributions \\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eM .Afana: Data Curation, Validation, Project Administration, Resources \\u003c/p\\u003e\\n\\u003cp\\u003eA. Alhaj: Conceptualization, Methodology, Writing - Original Draft \\u003c/p\\u003e\\n\\u003cp\\u003eH. Abu Rahma: Formal Analysis and Data Curation\\u003c/p\\u003e\\n\\u003cp\\u003eAll authors reviewed and approved the final manuscript.\\u003c/p\\u003e\\n\\n\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgements\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eWe thank the healthcare workers at Nasser Medical Complex for their participation under difficult circumstances.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eKang, J., Noh, W., \\u0026amp; Lee, Y. (2020). Sleep quality among shift-work nurses: A systematic review and meta-analysis. \\u003cem\\u003eApplied Nursing Research, 52\\u003c/em\\u003e, 151227.\\u003c/li\\u003e\\n\\u003cli\\u003eLiu, Y., et al. (2022). Association between sleep disturbance and mental health of healthcare workers: A systematic review and meta-analysis. \\u003cem\\u003eFrontiers in Psychiatry, 13\\u003c/em\\u003e, 919176.\\u003c/li\\u003e\\n\\u003cli\\u003eLv, Q., et al. (2023). Influencing factors of sleep disorders and sleep quality in healthcare workers during the COVID-19 pandemic: A systematic review and meta-analysis. \\u003cem\\u003eNursing Open, 10\\u003c/em\\u003e(9), 5887\\u0026ndash;5899.\\u003c/li\\u003e\\n\\u003cli\\u003eMani, Z. A., Kuhn, L., \\u0026amp; Plummer, V. (2020). Common domains of core competencies for hospital health care providers in armed conflict zones: A systematic scoping review. \\u003cem\\u003ePrehospital and Disaster Medicine, 35\\u003c/em\\u003e(4), 442\\u0026ndash;446.\\u003c/li\\u003e\\n\\u003cli\\u003eMsaad, S., et al. (2023). Sleep habits and quality among war and conflict-affected Palestinian adults in the Gaza strip. \\u003cem\\u003eSleep Medicine, 102\\u003c/em\\u003e, 90\\u0026ndash;104.\\u003c/li\\u003e\\n\\u003cli\\u003eResubun,Resubun, C. C., Efendi, F., \\u0026amp; Wahyuni, S. D. (2025). Factors influencing nurse retention in conflict zones: A systematic review. Indonesian Journal of Global Health Research \\u0026amp; Practice, 10(2), 123-130.arch, 7*(2).\\u003c/li\\u003e\\n\\u003cli\\u003eScarpelli, S., et al. (2022). Subjective sleep alterations in healthy subjects worldwide during COVID-19 pandemic: A systematic review, meta-analysis and meta-regression. \\u003cem\\u003eSleep Medicine, 100\\u003c/em\\u003e, 89\\u0026ndash;102\\u003c/li\\u003e\\n\\u003cli\\u003eBuysse, D. J., Reynolds III, C. F., Monk, T. H., Berman, S. R., \\u0026amp; Kupfer, D. J. (1989). The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry research, 28(2), 193-213.\\u003cstrong\\u003e\\u003cem\\u003e\\u003cspan dir=\\\"RTL\\\"\\u003e\\u0026rlm;\\u003c/span\\u003e\\u003c/em\\u003e\\u003c/strong\\u003e\\u003cstrong\\u003e\\u003cem\\u003ehttps://doi.org/10.1016/0165-1781(89)90047-4\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/li\\u003e\\n\\u003cli\\u003eBuysse DJ, Hall ML, Strollo PJ, Kamarck TW, Owens J, Lee L et al (2008) Relationships between the Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale (ESS), and clinical/polysomnographic measures in a community sample. J Clin Sleep Med 4(6):563\\u0026ndash;571. https://doi.org/10.5664/jcsm.27351\\u003c/li\\u003e\\n\\u003cli\\u003eAlhaj, Ahmed \\u0026amp; Afana, Mohammed \\u0026amp; Rhama, Hassan. (2025). Psychological Distress Among Healthcare Providers During the 2023\\u0026ndash;2025 Israel-Gaza Conflict. American Journal of Applied Psychology. 14. 60-69. 10.11648/j.ajap.20251402.12.\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":true,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true},\"keywords\":\"\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-7056032/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-7056032/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003ch2\\u003eBackground\\u003c/h2\\u003e\\u003cp\\u003eHealthcare providers working in conflict zones face unique occupational and psychological challenges that significantly impair sleep quality. In the Gaza Strip, prolonged exposure to violence and humanitarian crises exacerbates these challenges, yet data on the sleep health of this critical workforce remain scarce.\\u003c/p\\u003e\\u003ch2\\u003eObjective\\u003c/h2\\u003e\\u003cp\\u003eThis cross-sectional study aimed to assess the prevalence and patterns of sleep disturbances among healthcare providers at Nasser Medical Complex during the 2023\\u0026ndash;2025 Israel-Gaza conflict, and to examine associations between sleep quality and psychological distress.\\u003c/p\\u003e\\u003ch2\\u003eMethods\\u003c/h2\\u003e\\u003cp\\u003eA purposive sample of 400 healthcare providers (70% nurses, 20% physicians, 10% non-medical staff) completed the Pittsburgh Sleep Quality Index (PSQI) and a sociodemographic questionnaire between May and July 2025. Descriptive statistics evaluated sleep quality prevalence and scores.\\u003c/p\\u003e\\u003ch2\\u003eResults\\u003c/h2\\u003e\\u003cp\\u003eThirty-five percent of participants reported poor sleep quality (PSQI\\u0026thinsp;\\u0026gt;\\u0026thinsp;5). Additionally, 40% reported sleeping less than 6\\u0026ndash;7 hours nightly. Sleep disturbances were frequent, including difficulty initiating sleep (50% reporting problems weekly or more), nighttime awakenings (60%), loud snoring (37.5%), and breathing pauses (20%). Physical discomfort during sleep\\u0026mdash;such as back pain and breathing difficulties\\u0026mdash;was prevalent. Married participants and those with 11\\u0026ndash;15 years of experience reported greater sleep disturbances.\\u003c/p\\u003e\\u003ch2\\u003eConclusions\\u003c/h2\\u003e\\u003cp\\u003eSleep disturbances are alarmingly common among Gaza\\u0026rsquo;s healthcare providers in conflict settings, closely linked with psychological distress. These findings underscore the urgent need for integrated mental health and sleep interventions, occupational health screenings, and infrastructural support to safeguard provider wellbeing and healthcare delivery sustainability in protracted crises.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Sleep quality among healthcare providers during conflict crisis in the Gaza Strip: A cross-sectional study\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-09-11 21:46:06\",\"doi\":\"10.21203/rs.3.rs-7056032/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"963ef6a2-70be-4d4c-8587-d9fdb71979f4\",\"owner\":[],\"postedDate\":\"September 11th, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2025-12-03T03:38:35+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2025-09-11 21:46:06\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-7056032\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-7056032\",\"identity\":\"rs-7056032\",\"version\":[\"v1\"]},\"buildId\":\"XKTyCvWXoU3ODBz1xrDgd\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}