sleep quality

We are writing to express our appreciation for the recent article titled "Effectiveness of Combining Medication and Lifestyle Modification with Iranian Traditional Medicine Measures Compared to Medication Alone on the Sleep Quality of Children with Attention-Deficit Hyperactivity Disorder" by Rahimi et al., published in the Journal of Pediatric Perspectives (2025; 13(1):19219-19241). This study addresses a critical and often overlooked aspect of Attention-Deficit Hyperactivity Disorder (ADHD) management -sleep quality in children- and provides valuable insights into the potential benefits of integrating lifestyle modifications with traditional pharmacological treatments. The findings contribute significantly to the growing body of research on holistic approaches to managing ADHD, and we commend the authors for their important work.

Hemodialysis patients experience a wide range of physical and psychological challenges that can negatively impact their quality of life, including fatigue, poor treatment adherence, and disrupted sleep patterns.

This study aimed to determine the impact of a self-management program on fatigue, treatment adherence, and sleep quality in hemodialysis patients.

This quasi-experimental study, utilizing a pre-test-post-test design with a control group, was conducted in Zahedan teaching hospitals in 2021. A total of 60 hemodialysis patients were recruited through convenience sampling and non-randomly allocated to either the intervention (n = 30) or control group (n = 30). The intervention group participated in a self-management program, which included four educational sessions during hemodialysis. The control group received routine care without any intervention. Data were collected at baseline, one month, and three months after the intervention using the Multidimensional Fatigue Inventory (MFI-20), End-Stage Renal Disease Adherence Questionnaire (ESRD-AQ), and Pittsburgh Sleep Quality Index (PSQI). Data analysis was performed using chi-square, independent t-test, ANOVA, and F test with SPSS version 16 and R version 3.0.1. A significance level of P < 0.05 was considered.

The mean sleep quality scores showed no significant difference between the intervention and control groups at any time point (P = 0.636), and the main effects of time, group, and their interaction were not statistically significant. Similarly, fatigue scores did not show significant differences over time (P = 0.234), between groups (P = 0.375), or in the time-group interaction (P = 0.350). However, in terms of treatment adherence, while the main effects of time (P = 0.083) and the time-group interaction (P = 0.155) were not significant, a significant difference was observed between the groups (P = 0.013), indicating improved adherence in the intervention group compared to the control group.

The self-management program had a positive effect on treatment adherence but did not lead to significant improvements in fatigue or sleep quality among hemodialysis patients. Given the chronic nature of the disease and the multifactorial influences on sleep and fatigue, future studies with larger sample sizes and longer follow-up periods are recommended to assess the long-term effectiveness of self-management interventions in this population.

Sleep disorders significantly impact the daily functioning and overall well-being of elderly individuals. Given that non-pharmacological treatments generally yield more sustainable results than medications, this study aimed to evaluate the effectiveness of sleep health education in improving the sleep quality of elderly individuals with diabetes attending a diabetes clinic in Gorgan, Iran.

This randomized controlled clinical trial was conducted in 2022. A total of 64 eligible elderly patients with diabetes who visited the Gorgan diabetes clinic were randomly assigned to either the intervention or control group. The intervention group received a one-week sleep health education program. Data were collected using the Pittsburgh Sleep Quality Index, administered to both groups at baseline and again one and two months after the intervention. Chi-square and Friedman tests were used to analyze the data using SPSS 21, with a significance level of p < 0.05.

At baseline, the total sleep quality score was 9.66 in the control group and 8.78 in the intervention group. A statistically significant difference in the total sleep quality score was observed only in the intervention group across the three assessment points (baseline, one month, and two months post-intervention) (p < 0.001). In the intervention group, all components of sleep quality, except for sleep adequacy and use of sleep medications, showed a statistically significant difference across the three stages (p < 0.05).

Considering the demonstrated effectiveness of sleep health education on the sleep quality of elderly individuals with diabetes, it is recommended that healthcare personnel prioritize and integrate sleep health education for this population.

Sleep disorders directly relate to diabetes and its management. The study objective was to examine the effect of the mindfulness-based stress reduction (MBSR) intervention on mental health and sleep quality (SQ) in women with type 2 diabetes mellitus (T2DM) in Isfahan health care centers in Iran.

Eighty women with T2DM were enrolled in this randomized clinical trial performed at Imam Ali Comprehensive Urban Health Center in Isfahan in 2019. The patients were randomly assigned to the intervention (8 sessions of 2 hours of MBSR training) and control (standard care) groups. SQ and mental health were assessed and compared via the Pittsburgh SQ Index and the Depression, Anxiety, and Stress Scale-21 before and after the intervention in both groups by SPSS 20 using the chi-square test, independent t-test, and paired-samples t-test.

A post-intervention reduction in the overall quality of sleep index was observed in both intervention and control groups (0.7±0.2, P=0.1 and 0.17±0.07, P=0.6, respectively). There was a significant difference between the subjective SQ and the sleep duration before and after treatment in the intervention group (a score reduction of 0.2±0.09 and 0.3±0.12, respectively, P=0.03). Depression, anxiety, and stress scores also decreased significantly after treatment in the intervention group, indicating an improvement in mental health (4.3±2.1, P<0.001, 5±2.7, P<0.001, and 3.7±1.5, P<0.001, respectively).

Overall, mental health, subjective quality, and sleep duration improved in patients with T2DM undergoing MBSR training.

Restless legs syndrome (RLS) significantly affects sleep quality. A lack of awareness regarding this condition often results in delays in both diagnosis and treatment.

This study aimed to assess the prevalence of RLS and identify comorbidities associated with the disorder.

This cross-sectional study was conducted on patients with RLS registered in the sleep clinic at Mashhad University of Medical Sciences from 2019 to 2024. The diagnosis of RLS was made using the four minimum criteria established by the International Restless Legs Syndrome Study Group (IRLSSG). The Pittsburgh Sleep Quality Index (PSQI ≥ 6), Epworth Sleepiness Scale (ESS ≥ 10), Insomnia Severity Index (ISI), and Depression Anxiety Stress Scales (DASS-21) were employed to evaluate sleep quality, excessive daytime sleepiness, insomnia, and mood disorders, respectively. Data analysis was performed using STATA version 7 software, with a significance threshold set at (P < 0.05).

The prevalence of RLS was found to be 9.2%. The average RLS score for men was 15.71 ± 13.19, while for women it was 19.35 ± 11.72 (P = 0.004). A significant negative correlation was observed between RLS scores and sleep duration (P < 0.001). Conversely, there were significant positive correlations between RLS scores and sleep latency, PSQI, ISI, and DASS-21 (P < 0.001). Rare variants of RLS, including restless head, back, bladder, abdomen, and perineum syndrome, were identified in a total of 11 cases (3.6%) among the participants.

Enhancing awareness of RLS and its comorbidities is crucial for the accurate diagnosis and management of patients, which can subsequently improve sleep quality and alleviate mood disorders. It is important to recognize that restlessness mimicking RLS can manifest in different areas of the body.

Rheumatoid arthritis is a chronic, systemic, inflammatory disease classically affecting the small joints of the hands and feet.

The purpose of this research was to investigate the effect of emotion regulation training based on the Gross model on the psychological well-being and sleep quality of women with psychosomatic disorders (rheumatic and joint pains).

This semi-experimental study was conducted based on a pretest-posttest design and a control group. The statistical population of this study consisted of all women with psycho-physical disorders in Farahan City, among which 40 individuals were selected through the convenience sampling method and then randomly allocated to either the experimental or control group) n=20 each (. The required data were collected using the Ryff Psychological Well-Being and Pittsburgh Sleep Quality Index. Emotion regulation techniques were taught using Gross’s standard training protocol in eight 90-minute sessions, while the control group was on the waiting list. The data were analyzed using the analysis of covariance in SPSS-23 software. 

The study’s results indicate that instructing women with psychosomatic disorders on how to handle their emotions using the Gross model can greatly enhance their mental health (P<0.01). Moreover, the findings from the analysis of covariance revealed that Emotion Regulation Training based on the Gross model led to enhancements in sleep quality in women with psychosomatic disorders (P<0.01).

The outcomes of this study have the potential to enhance the overall well-being and sleep quality of individuals experiencing rheumatic and joint pains.

 Human papillomavirus (HPV) is a well-established oncogenic virus implicated in cervical, oropharyngeal, and anogenital malignancies. Emerging evidence suggests its potential role in thyroid cancer pathogenesis. Patients with thyroid cancer frequently experience obstructive sleep apnea (OSA), which may be exacerbated by thyroid dysfunction. Thyroidectomy has been reported to improve sleep quality; however, the interplay between HPV infection, thyroid cancer progression, and postoperative sleep improvements remains inadequately understood. This meta-analysis systematically evaluates the impact of thyroidectomy on sleep parameters in thyroid cancer patients, with a specific focus on those affected by HPV.

To quantify the effects of thyroidectomy on sleep quality in patients with thyroid cancer, particularly those with HPV infection. This study assesses improvements in key OSA indicators, including the Apnea-Hypopnea Index (AHI), Epworth Sleepiness Scale (ESS), and nocturnal oxygen saturation, while elucidating the clinical implications of the HPV-thyroid cancer association.

A comprehensive literature search was conducted across PubMed, Embase, Scopus, and the Cochrane Library for studies published between January 2010 and December 2024. Eligible studies included randomized controlled trials (RCTs), cohort studies, and case-control studies evaluating postoperative sleep outcomes in thyroid cancer patients with documented HPV status. Two independent reviewers conducted data extraction and quality assessment, resolving discrepancies through consensus. The methodological rigor of the included studies was evaluated using the Newcastle-Ottawa Scale (NOS) and the Cochrane risk of bias tool. A meta-analysis was performed using the DerSimonian and Laird random-effects model, with heterogeneity assessed via Cochran’s Q and I2 statistics. Publication bias was examined using funnel plots and Egger’s test.

Out of 203 screened records, 11 studies (comprising 1,432 participants) met the inclusion criteria. Thyroidectomy led to statistically and clinically significant improvements in sleep quality. The mean preoperative AHI of 42.8 ± 8.6 declined to 36.6 ± 8.4 postoperatively (Hedges’ g = -0.38, 95% CI: -0.67 to -0.09, P = 0.01), reflecting a moderate yet meaningful improvement in OSA severity. Daytime sleepiness showed a substantial reduction, with ESS scores decreasing from 15.3 ± 4.7 to 7.5 ± 6.07, demonstrating a marked enhancement in daily functioning. The HPV infection was associated with a 2.2-fold increased risk of thyroid cancer (OR = 2.199, 95% CI: 1.31 - 3.23, P < 0.05), reinforcing its potential role in thyroid carcinogenesis. Moderate heterogeneity was observed in OSA-related outcomes (I2 = 59.27%, P = 0.01), while the HPV-thyroid cancer association displayed minimal heterogeneity (I2 = 0.00%, P = 0.64).

Thyroidectomy significantly enhances sleep quality in thyroid cancer patients, with notable reductions in AHI and ESS scores, underscoring its clinical benefit. The strong association between HPV and thyroid cancer highlights the potential necessity of HPV screening in thyroid cancer risk assessment and postoperative surveillance. These findings advocate for the consideration of HPV as a modifiable risk factor, warranting further research into tailored screening protocols and refined postoperative strategies to optimize patient outcomes.

Sleep quality is crucial in heart failure (HF) patients, yet its associations with clinical, demographic, and psychosocial factors remain underexplored. This study examined these relationships to identify predictors of poor sleep quality.

Study Design:

 A cross-sectional study.

This cross-sectional was conducted on 354 HF patients at Shahid Chamran Heart Hospital, Isfahan, Iran (September 2023-2024). Pittsburgh Sleep Quality Index (PSQI) and Hospital Anxiety and Depression Scale (HADS) were used to evaluate sleep quality, anxiety, and depression, respectively. Random forest (RF) modeling and ordinary least squares (OLS) regression identified predictors of poor sleep quality.

Poor sleep quality (PSQI>7) was observed in 18% of patients who were older (70.00±6.30, P<0.001) and had lower ejection fraction (EF) (23.75±12.79%, P<0.001). This group also had higher systolic blood pressure (BP 140.67±12.50 mmHg, P=0.014). Complex medication regimens, including angiotensin-converting enzyme (ACE) inhibitors, beta-blockers, and diuretics, were associated with poor sleep (P<0.001). Moreover, depression (HADS-depression: 5.36±0.70, P<0.001) and anxiety (HADS-anxiety: 4.84±1.32, P<0.001) were correlated with poor sleep. The RF model had an area under the curve of 0.79, and OLS regression (R2=0.280) highlighted New York Heart Association (NYHA) class and medication type as significant predictors.

Overall, poor sleep quality in HF patients was related to older age, reduced cardiac function, higher blood pressure (BP), complex medication regimens, and increased anxiety and depression. Accordingly, multidimensional management strategies are needed to improve sleep outcomes.

The elderly's sleep quality and social support are important variables related to quality of life and factors affecting successful aging.Therefore, the present study was conducted to determine the relationship between the elderly's sleep quality and social support. In this descriptive cross-sectional analytical study, the research population included 150 older people referring to elderly care centers living in Qaem Shahr,Iran, and the sampling method was convenience. To collect information, the Pittsburgh Sleep Quality Index, and the Philips̍ Social Support Questionnaire used as self-report. The data were analyzed using SPSS software version 26. The results of the Spearman test showed a significant negative relationship between the sleep quality score and social support. However, there is a significant relationship between the social support score and the educational level of the elderly. This study's findings emphasize the major role of social support in ensuring adequate sleep quality in the elderly. Therefore, it is recommended that policymakers in this field develop programs centered on social support to improve the sleep quality and health of the elderly.

Statement of the Problem:

 In the literature, the relationship between sleep quality and periodontal diseases has been mentioned, but still there is a lack of consensus and a valid conclusion in the results obtained.

This study aimed to compare the sleep quality of patients with periodontitis and their healthy counterparts. The correlation between sleep quality score and age, gender, occupation, brushing pattern, and the severity of periodontal disease was also investigated.

This case-control study was conducted on 106 patients with periodontitis and 106 controls with healthy periodontium referring to the Periodontology Department of Yazd Dental School from December 2021 to April 2022. The sleep quality of the two groups was assessed by the Pittsburgh Sleep Quality Index (PSQI). Data were analyzed by ANOVA, t-test, and linear regression to assess possible correlations between the sleep quality score and demographic variables, tooth brushing pattern, and presence of periodontitis and its severity (alpha=0.05).

Totally, 149 females (70.3%) and 63 males (29.7%) with the mean age of 34.17±8.29 years, participated in this study. The sleep quality score had no significant correlation with age, gender, occupation, or tooth brushing pattern (p> 0.05). However, the sleep quality had a significant correlation with periodontitis (OR= 1.15, CI 95%: 1.02-1.29, p= 0.01). The sleep quality score had no significant correlation with the severity of periodontal disease (p= 0.225).

Sleep quality of patients with periodontitis was significantly lower than that of healthy controls.

Social support and sleep quality can be beneficial in both self-care behaviors and health outcomes in subjects with type 2 diabetes (T2DM). The aim of this study was to analyze the relationship between glycemic index, social support and sleep quality in patients with T2DM.

In a cross-sectional study, 156 men and 144 women with T2DM were enrolled from July to September 2020. Level of self-care activities, social support, and sleep quality were measured with validated and appropriate questionnaires, and clinical characteristics were acquired from patients’ medical records.

The mean age of the participants was 50.83±7.14 years. According to this study, more than 60% of participants had poor selfcare behaviors (37.68±12.94) and poor sleep quality (7.55±3.80) and the overall average of the social support score was moderate (67.73±19.85). A significant negative association was noticed between HbA1c and selfcareactivities and social support score (r=-0.346, p<0.001 and r=-0.309, p<0.001, respectively). There was a significant positive relationship between HbA1c and Pittsburgh Sleep Quality Index (PSQI) score (r=0.469, p<0.001). Also, a significant negative association was observed between social support and PSQI score (r=-0.393, p<0.001).

Glycemic control, self-care behaviors, high social support, and optimal sleep quality are suggested to be considered in diabetes management guidelines and policy making.

 Occupational exposure to electromagnetic fields has attracted attention due to potential health effects. This cross-sectional study investigates the impact of static magnetic fields (SMFs) exposure on the sleep quality of workers in a combined cycle power plant.

 A total of 185 workers participated in this study. Magnetic flux density was measured using the calibrated HI-3550 magnetic field personal monitor. The Pittsburgh Sleep Quality Index Questionnaire was employed to assess the sleep quality. Data analysis was conducted using the SPSS version 19 software, employing ANOVA, logistic regression, and Chi-square statistical tests.

 The participants had an average age of 42.16 ± 5.03 years and an average work experience of 15.29 ± 3.38 years. The average magnetic flux density of the SMF, measured at 22.65 ± 2.23 m. The average sleep quality score was 7.25 out of 21. Among the workers, 46.48% reported poor sleep quality, while 53.52% reported good sleep quality. In addition, workers exposed to higher magnetic field levels were more likely to have poor sleep quality compared to those with lower exposure (P < 0.05). The analysis of various factors affecting sleep quality indicated significant associations with marital status, age, and exposure to magnetic fields. Results show with the increase of each unit of age, the chance of having bad sleep quality increased by 0.32 units (95% confidence interval [CI]: 0.11–0.56). Furthermore, with the increase of each unit of magnetic field exposure, the chance of having bad sleep quality increased by 0.16 units (95% CI: 0.09–0.34).

 The findings suggest that even exposure to magnetic fields below the permissible limits may contribute to poor sleep quality. As magnetic field exposure increases, the likelihood of experiencing poor sleep quality also rises.