Background and Objective: Patients with neuromuscular diseases (NMDs) are at high risk for sleep problems, may lead to significant morbidity. Central sleep apnea (CSA), obstructive sleep apnea (OSA), hypopnea, and nocturnal hypoventilation are common in children with NMDs. Polysomnography (PSG) is the gold standard for evaluating and diagnosing sleep breathing disorders in children and adolescents with NMDs. This study aimed to evaluate clinical symptoms and PSG findings among them.

Materials and Methods: This retrospective cross-sectional study included 22 children and adolescents aged 18 years or younger referred to the sleep department of Qods Children’s Hospital, Qazvin, Iran, between 2017 and 2022.

Results: PSG was performed in 22 children with NMD, with a mean age of 65 months. Spinal muscular atrophy (SMA) was the most common diagnosis (45.4%). The most common sleep problems were sleep-disordered breathing (SDB) (86.4%), followed by restless sleep (9%). The mean sleep efficiency was 79.2%, and the mean apnea-hypopnea index (AHI) was 22.2 events per hour of total sleep time (TST). Hypopnea, OSA, and CSA were observed in 36%, 22%, and 7% of patients, respectively. The mean oxygen desaturation index (ODI) was 12.5, and the mean arousal index was 22.7. The sleep architecture was mildly disturbed with a reduction in rapid eye movement (REM) sleep.

Conclusion: SDB is prevalent among children and adolescents with NMDs. Based on the severity of symptoms, nonin-vasive ventilation (NIV) and medical treatments were initiated. PSG is essential for early diagnosis and management and may reduce morbidity and mortality of patients with NMDs.

Background and Objective: This study aimed to investigate the effects of transcranial direct current stimulation (tDCS) on processing speed, life satisfaction, and emotional states in students with poor sleep quality.
Materials and Methods: A semi-experimental pretest-posttest design with a control group was applied. Twenty-seven students with poor sleep quality were selected via convenience sampling. The Pittsburgh Sleep Quality Index (PSQI), the Reaction Time Index (RTI) task from the Cambridge Neuropsychological Test Automated Battery (CANTAB), the Symbol Digit Modalities Test (SDMT), the Satisfaction with Life Scale (SWLS), and Depression, Anxiety, and Stress Scale-21 (DASS-21) were used to collect data. After the pretest, participants were randomly assigned to the intervention (n = 14) or control group (n = 13). The intervention comprised ten 20-minute tDCS sessions at two mA, with the anode over F3 and the cathode over F4. Data were analyzed via analysis of covariance (ANCOVA).
Results: After controlling for pretest scores, the intervention and control groups demonstrated a significant difference in posttest processing speed (computer-based and non-computer-based tests) and the anxiety subscale of the negative emotional states . No significant differences were found regarding sleep quality or life satisfaction.
Conclusion: tDCS improved processing speed and reduced negative emotional states, but did not significantly improve sleep quality or life satisfaction.

Background and Objective: Sleep problems are common in school-aged children and may have negative impacts on their health. This study aimed to determine the sleep disorder patterns in school-aged children and evaluate their associ-ation with maternal anxiety, stress, and depression.

Materials and Methods: This cross-sectional study was conducted between October 2018 and September 2019 and included children aged 7-12 years using convenience sampling. The Persian version of the BEARS questionnaire, which incorporates five basic sleep domains (Bedtime problems, Excessive sleepiness, Awakenings during the night, Regulari-ty of sleep, Snoring), was used to assess sleep disorders. Maternal anxiety, stress, and depression were measured using the short form of the Depression, Anxiety, and Stress Scale (DASS), a caregiver self-report tool. Multivariable logistic regression was applied to assess the association between child sleep problems and maternal mental health.

Results: In the 99 children included, the most common sleep problem was nocturnal awakening, with 48.5% experienc-ing it. Excessive daytime sleepiness was the second most common problem, affecting 38.4% of children. In the multi-variable-adjusted model, awaking during the night [odds ratio (OR): 3.16, 95% confidence interval (CI): 1.27-7.82] and bedtime problems (OR: 4.20, 95% CI: 1.16-15.20) showed a positive association with moderate to severe levels of maternal anxiety, stress, and depression.

Conclusion: The prevalence of sleep problems among school-aged children underscores the need for family awareness and education about sleep problems.

Background and Objective: With the rapid global growth of the elderly population, identifying factors associated with their psychological and social well-being has become increasingly important. This study aimed to compare sleep health, psychological hardiness, and social responsibility between community-dwelling older adults and nursing home residents.

Materials and Methods: This causal-comparative (ex post facto) study examined differences between two naturally existing groups of older adults. A total of 120 participants (50 nursing home residents and 70 community-dwelling older adults) were recruited through convenience sampling. Data were collected using the Personal-Social Responsibility Questionnaire, the Sleep Health Scale (SHS) by Brandolim Becker et al., and the Kobasa Hardiness Scale. Data were ana-lyzed using SPSS software through descriptive statistics and independent samples t-tests with a significance level of 0.05.

Results: The mean age of participants was 66 years. Sleep health scores were significantly higher among community-dwelling older adults (19.31 ± 3.65) than nursing home residents (15.72 ± 3.11) [t(118) = -5.65, P = 0.001]. Similarly, social responsibility was significantly higher in community-dwelling participants (36.33 ± 6.13) compared with nursing home residents (24.74 ± 5.14) [t(118) = -10.91, P = 0.001]. No significant difference was observed in psychological hardiness between groups (P = 0.41).

Conclusion: The living environment appears to be associated with the sleep health and social responsibility of older adults, whereas psychological hardiness remains relatively stable across living conditions. These findings provide valu-able insights for policymakers and healthcare professionals in designing programs to improve the quality of life (QOL) in the older population.

Background and Objective: Children with autism spectrum disorder (ASD) often suffer from language disorders; however, those who experience sleep problems usually have more severe impairments in various domains of language and communication. Given the essential role of language in communication, this study aimed to investigate the effect of enhancing understanding of embodied conceptual metaphors on the sleep status of children with autism experiencing sleep problems.

Materials and Methods: This study employed a within-subjects design. The study population consisted of boys with autism aged 7-12 years. A total of 34 children with sleep disorders were selected using purposive sampling. Pre-test data were obtained using the Children's Sleep Habits Questionnaire (CSHQ), which includes items related to the cognitive, emotional, and communication difficulties in children with autism, such as sleep anxiety, sleep onset delay, bed-time resistance, and daytime sleepiness. Participants then underwent 20 sessions designed to enhance their understanding of conceptual metaphors. The CSHQ was readministered as a post-test and follow-up to evaluate the effect of language-based intervention on sleep problems.

Results: Repeated-measures analysis of variance (ANOVA) demonstrated a significant positive effect of enhancing understanding of embodied conceptual metaphors on sleep improvement in children with autism experiencing sleep problems (P < 0.0001).

Conclusion: Enhancing understanding of embodied conceptual metaphors may be effective in improving sleep prob-lems in children with autism, potentially through reducing sleep anxiety and increasing communication abilities.

Background and Objective: The global aging population is increasing. Aging is associated with a gradual decrease in physiological activities and an increased risk of chronic diseases and sleep disorders. This study aimed to determine the prevalence and risk factors of sleep quality among elderly people.

Materials and Methods: This cross-sectional study was conducted on 894 elderly individuals aged 60 years or older, selected using a multistage sampling method in Varamin City, Tehran Province, Iran. Data were collected using the Pittsburgh Sleep Quality Index (PSQI). Mean and frequency were used for descriptive analysis, and multivariable logistic regression was used to identify risk factors for poor sleep quality. P-value < 0.05 was considered statistically significant, and Stata software was used for data analysis.

Results: Of the participants, 509 (56.5%) were women, and the mean age was 69.1 ± 7.5 years. The overall prevalence of poor sleep quality was 39.8%. Multivariable logistic regression analysis showed that poor sleep quality was signifi-cantly associated with female sex [male odds ratio (OR)=0.5, 95% confidence interval (CI): 0.4-0.7], coronary heart disease (CHD) (OR=1.9, 95% CI: 1.5-3.0), gastrointestinal (GI) disease (OR=1.8, 95% CI: 1.5-3.0), and depression (OR=3.6, 95% CI: 2.1-6.2). There was no relationship between age, marital status, occupation, education, financial sta-tus, and other diseases with sleep quality (P > 0.05).

Conclusion: Poor sleep quality among elderly individuals was relatively common and more prevalent among women. Moreover, comorbidities such as depression, CHD, and GI diseases were identified as factors affecting the quality of sleep in elderly people.

Background and Objective: Shift work can lead to irregular circadian rhythms, sleep loss, and fatigue. This study aimed to determine the effect of a fatigue management program on the alertness of emergency nurses.

Materials and Methods: This quasi-experimental study was conducted among emergency nurses at an educational hospital in Mashhad City, Iran. All participants completed the Depression, Anxiety, and Stress Scale (DASS), the Karolinska Sleepiness Scale (KSS), and the Swedish Occupational Fatigue Inventory (SOFI), and underwent the Psy-chomotor Vigilance Test (PVT) before and after the intervention. The intervention included optimizing the shift sched-ule to a fast-rotating clockwise system with one day off after each night shift. In a one-day pre-intervention workshop, nurses were trained to take 2-hour naps during the night shift and to drink coffee at a recommended dose equivalent to 50-150 mg of caffeine. Environmental light exposure was optimized using an adjustable light box. Data were analysed using SPSS software.

Results: The study cohort comprised 25 participants, with a mean age of 30.88 ± 5.75 years, of whom 16(64%) were men. Two dimensions of SOFI (indifferent and uninterested) showed a significant improvement after the intervention (P = 0.027 and P = 0.016, respectively). The mean reaction time on the PVT did not differ significantly before and after the intervention (P = 0.70).

Conclusion: Optimizing the shift schedule and implementing a fatigue management program alone did not significantly improve alertness. Other contributing factors, such as sleep-wake behavior on non-working days, second-job status, and personal habits, should also be addressed.

Given the rapid advancement of artificial intelli-gence (AI), I aim to emphasize the emerging po-tential of AI in sleep medicine while also address-ing the challenges related to its adoption and im-plementation in clinical settings. AI has signifi-cantly enhanced our understanding of sleep pat-terns, enabling more precise diagnosis and per-sonalized treatment plans. Beyond sleep tracking, AI contributes to telemedicine, smartwatches, and more.