Older Adults’ Motivators and Barriers to Using Mindfulness Apps for Stress Management in Brain Health Interventions: Interview Study

<strong>Background:</strong> Population aging is driving a rapid rise in dementia cases worldwide, posing a major challenge for health care systems around the globe, including in the Netherlands. Digital multidomain lifestyle interventions, which target multiple lifestyle domains simultaneously, can protect against cognitive decline in at-risk older adults but struggle to sustain engagement. Addressing stress in these interventions is crucial, as it can directly increase dementia risk and may promote unhealthy behaviors in other domains targeted in these interventions, including physical activity, diet, and sleep. <strong>Objective:</strong> This study explores the motivators and barriers for Dutch adults aged 60 years and older to use mindfulness apps for stress management within digital multidomain lifestyle interventions. Despite their potential, it remains unclear which stress-related needs would motivate older adults to use mindfulness apps in these interventions and whether these apps effectively address those needs. Moreover, little is known about how older adults practice mindfulness independently in everyday settings alongside other lifestyle priorities. <strong>Methods:</strong> We conducted 15 semistructured interviews with former participants of a 26-week multidomain lifestyle intervention study (the “HELI” [Hersenfuncties na Leefstijlinterventie] study) that included a mindfulness app for stress management. Participants (8 females; age range 61-73 years) were first invited to describe their practices to improve brain health to see whether stress and mindfulness emerged spontaneously. Follow-up questions and scenarios explored experiences with stress and mindfulness before these concepts were explicitly introduced midway through the interview, providing insight into their roles in participants’ lives free from associations with the terms. Data were analyzed using template analysis. <strong>Results:</strong> Older adults reported experiencing fewer minor daily stressors than earlier in life and having developed effective coping strategies with age. These strategies often included elements associated with mindfulness, such as acceptance and deliberate attention to the present moment. However, many frequently worried at night about major concerns, including personal health, the well-being of loved ones, and global issues. These findings suggest that older adults may be more motivated to use mindfulness apps to cope with nighttime worry than with minor daily stressors. At the same time, older adults reported barriers to using mindfulness apps, including negative associations with the term “mindfulness” (eg, perceived as too spiritual) and challenges in maintaining focus during exercises. <strong>Conclusions:</strong> We discuss how older adults develop mindfulness skills with age and how these skills help older adults cope with daily stressors but not with nighttime rumination. Specifically, we argue that diminished cognitive resources at night, fewer distractions, and metacognitive patterns may sustain worry before sleep. This study highlights the importance of tailoring multidomain lifestyle interventions to the unique challenges of older adults. We also offer recommendations to present mindfulness in ways that help older adults stay focused during practice.

Beyond the auditory: anxiety bridges sleep disturbances and depressive symptoms to tinnitus handicap

BackgroundTinnitus is closely associated with psychological factors including anxiety, depression, and sleep disturbances. However, how these variables interact to influence tinnitus severity remains poorly understood, warranting further exploration.MethodsThis retrospective study analyzed data from 285 patients with tinnitus, utilizing the Tinnitus Handicap Inventory (THI), Self-Rating Depression Scale (SDS), Self-Rating Scale of Sleep (SRSS), and Self-Rating Anxiety Scale (SAS) as assessment instruments. Univariate and multivariate regression analyses were performed to identify psychosocial factors associated with THI scores. Structural equation modeling (SEM) was employed to examine the mediating role of anxiety—specifically, whether sleep disturbances and depression exacerbate tinnitus handicap indirectly through heightened anxiety. Subgroup analyses were further conducted to evaluate the stability of this psychological mediation pathway across different demographic and clinical subgroups (e.g., age, gender, disease duration).ResultsTinnitus severity was significantly positively correlated with scores on the SRSS, SDS, and SAS (all P < 0.05). Multivariate regression analysis identified age, sleep quality (SRSS), and anxiety (SAS) as independent predictors of increased Tinnitus Handicap Inventory (THI) scores. Structural equation modeling further confirmed that SAS partially mediated the relationship between SRSS and THI (mediation effect: 31.7%) and fully mediated the relationship between SDS and THI. Subgroup analyses revealed that the mediating effect of anxiety was more pronounced in middle-aged and elderly individuals, females, and patients with left-sided tinnitus.ConclusionAnxiety serves as a central mediating mechanism linking sleep disturbances and depressive symptoms to tinnitus severity. The present findings demonstrate that anxiety not only directly exacerbates tinnitus-related handicap but also mediates the influence of sleep and mood disturbances on tinnitus distress. These findings underscore the critical role of anxiety in personalized tinnitus treatment.
<![CDATA[Learn why insomnia and daytime sleepiness signal psychiatric risk, and how screening for apnea, delayed phase, and fatigue sharpens treatment.]]>

Conceptualizing Acceptance and Knowledge as Process Variables in Internet-Delivered and Therapist-Supported Cognitive Behavioral Therapy and Acceptance and Commitment Therapy in Primary Care for Insomnia: Pilot Feasibility and Process-Oriented Randomized Controlled Trial

Background: Internet-based interventions for insomnia show promise, but understanding the process variables, such as knowledge acquisition and psychological acceptance, is crucial for enhancing digital adherence and clinical effectiveness. Objective: This study aimed to evaluate the feasibility, adherence, and preliminary clinical signals of 2 therapist-assisted interventions—internet-delivered cognitive behavioral therapy (iCBT) and internet-delivered acceptance and commitment therapy (iACT)—for insomnia in a primary care setting. Methods: This was a pilot randomized controlled trial. Adults seeking help for insomnia (n=18) were recruited via primary care and randomized to either a 5-module iCBT or iACT program delivered via a secure digital platform with weekly therapist feedback. Blinding of participants and therapists was not possible due to the nature of the interventions. Primary outcomes included the Insomnia Severity Index; secondary outcomes included the 9-item Patient Health Questionnaire, 7-item Generalized Anxiety Disorder, and WHO Disability Assessment Schedule. A novel sleep knowledge test was used as a process variable. The data were analyzed using split-plot analyses of variance (intention-to-treat or last observation carried forward and complete case analysis) and nonparametric Friedman and Kruskal-Wallis tests. Results: A total of 18 participants were randomized (iCBT: n=9; iACT: n=9). High attrition was observed, with only 33.3% (n=3) of iCBT and 55.6% (n=5) of iACT participants completing all modules. The iACT group demonstrated a significant within-group reduction in insomnia severity (=.01, Friedman test), whereas iCBT results were nonsignificant (=.10, Friedman test). No significant between-group differences were found for any clinical or process variables. Participants rated both treatments as credible (Credibility/Expectancy Questionnaire scores remained stable), though qualitative feedback indicated a need for more flexible, less burdensome content. Conclusions: This pilot study demonstrates that while internet-delivered insomnia treatments are feasible and credible in primary care, high attrition remains a significant barrier. Preliminary signals suggest that iACT may be a viable alternative to iCBT, potentially offering better adherence. Larger, fully powered pilot randomized controlled trials (estimated N=404) with refined recruitment and automated retention strategies are required to determine definitive comparative efficacy and the mediating role of sleep knowledge and acceptance. Trial Registration: Research and Development in the Västra Götaland Region (FoU i VGR) 272866;
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Melatonin for Kids: Is It Safe?

If you’ve spent any time talking to other parents about sleep, you’ve probably heard about melatonin. One person swears by it. Someone else warns against it. And if your child is struggling to fall asleep, it can be hard to know what to believe.

Melatonin is widely available, often marketed as a “natural” sleep aid, and increasingly used to help kids of all ages. But it may not be the right solution. The key is knowing when it makes sense, when it doesn’t, and how to make it work best as part of a bigger sleep plan.

What is melatonin?

Melatonin is a hormone the body produces naturally to regulate sleep. As it gets dark, the brain releases melatonin to signal that it’s time to wind down. Light exposure at night — especially blue light from screens — can disrupt the body’s natural rhythm so you don’t feel sleepy even when it’s bedtime.

“Melatonin supplements can help facilitate that circadian rhythm, that 24-hour sleep cycle,” says Rohn Nahmias, DO, a child and adolescent psychiatrist at the Child Mind Institute. Because it’s sold over the counter, melatonin seems to be harmless. In practice, clinicians are much more cautious. While they tend to consider it relatively low risk, with few side effects, they still don’t view it as something to take casually or indefinitely.

That’s because there are real gaps in what we know about melatonin — especially when kids take it regularly over long periods. “The longest study was about four years, and they did not find any issues,” says Judith Owens, MD, MPH, a pediatric sleep expert and professor of neurology at Harvard Medical School. “But the data are very limited in subject numbers and long-term follow-up.”

So, the question parents often ask — is melatonin safe for kids? — doesn’t have a simple yes or no answer. The more useful question may be whether melatonin is right for your kid and what guidelines should you follow if you’re going to give it to them.  

That’s why it’s especially important to consult your child’s pediatrician or tell them if you’ve already started your child on melatonin. “Because melatonin is over the counter, families often forget to mention it,” says Dr. Nahmias. But doctors need to know about supplements, especially if a child is on other medications or has additional health concerns.

Melatonin can be helpful in the right situations, but using it without looking deeper can be “kind of slapping a Band-Aid onto a problem,” Dr. Nahmias says. In his practice, he always wants to rule out anxiety, mood concerns, or a medical issue that may be impacting sleep (such as snoring, breathing problems, or pain) before introducing something new like melatonin.

When melatonin can help

Melatonin is most useful when the issue is falling asleep, not staying asleep. For example, if your child has persistent trouble falling asleep — not just occasional bedtime resistance — and you have already tried using behavioral strategies.

The immediate-release melatonin sold in the United States is primarily helpful for sleep onset. (A prolonged-release form approved in the UK and EU may help with staying asleep, but it’s not available here.) Melatonin can also help with circadian rhythm issues like delayed sleep-wake phase disorder, when a child or teen’s natural sleep and wake times are much later than their schedule allows. “That is the other real indication for melatonin,” Dr. Owens says.

How to use melatonin thoughtfully

If melatonin does make sense for your child, experts agree: Start low and go slow. Dr. Nahmias recommends beginning with 1 to 2 milligrams for kids four and up and increasing the dose only if needed — up to 3 milligrams for kids ages 6–10. Many children respond well to low amounts. More than 5 milligrams, he says, isn’t much more effective and is more likely to cause side effects like grogginess or irritability. Dr. Owens emphasizes a similarly cautious approach: Use the lowest effective dose, monitor whether it’s actually helping, and reassess regularly rather than letting it quietly become an open-ended routine.

Dr. Nahmias recommends using melatonin in “clusters” — short, purposeful stretches of nightly use to help realign the circadian rhythm — and then pulling back to use as needed. A cluster might make sense for a few weeks after travel, during a tough transition, or while the family works on behavioral changes.

If a child needs melatonin every night for months, that’s a signal to dig deeper. “That tells me that there’s something likely going on underneath that’s not being addressed,” Dr. Nahmias says.

Side effects and safety

Melatonin is generally well tolerated, but knowing the possible side effects can help you catch problems early. The most common is grogginess the next morning. Others include irritability, headaches, dizziness, stomach upset, and — in toddlers and younger children — increased bedwetting. Some children may also experience vivid dreams or nightmares, though these tend to be mild.

Check in with your child’s pediatrician if side effects appear, your child needs melatonin frequently or for more than a short period, the dose keeps creeping up, sleep problems get worse, or if you notice signs of anxiety, depression, or ADHD that might be driving their sleep struggles.

One important safety note: melatonin gummies look like candy, and Dr. Owens describes an “astronomical increase” in calls to poison control centers and emergency room visits related to melatonin in children, largely due to accidental ingestion. Store melatonin — especially gummies — like any other medication: out of reach, ideally in a locked cabinet. Never present them to children as a treat.

A bigger concern: what’s actually in the bottle

Melatonin isn’t tightly regulated in the United States, which means the dose on the label may not match what’s actually in the product. Studies have found that 22 out of 25 over-the-counter melatonin gummies were labeled inaccurately, with some containing far more melatonin than advertised.

Dr. Owens describes the variability as “huge” and says she was genuinely shocked by the findings. When shopping, look for products with a USP Verified mark. USP (United States Pharmacopeia) is an independent nonprofit that tests supplements to confirm the product contains what the label says, in the correct amount, and without harmful contaminants.

Melatonin for kids with ADHD or autism

There’s solid evidence that melatonin can benefit children with neurodevelopmental conditions, particularly autism and ADHD, who are more likely to have disrupted sleep-wake cycles. “There is a pretty robust literature supporting efficacy, without a lot of side effects,” Dr. Owens says about children on the autism spectrum.

But Dr. Nahmias encourages parents of kids with autism or ADHD to take a closer look at bedtime routines before turning to melatonin. “Both of those populations of kids do best when there is structure put into their day,” he says. He recommends having a posted list of the sleep routine that a child needs to accomplish as a helpful visual reminder that will start to become second nature as it is built into their evening.

If getting to sleep is still an issue, trying melatonin makes sense. But for kids with autism and ADHD, it may take more time to see an effect. “It can be helpful to give it a bit longer to re-right the sleep cycle,” Dr. Nahmias says. “Trying it for two to three months may be more beneficial than just a few weeks.”

 Many neurodivergent kids may also need to stay on melatonin longer than neurotypical children. “This makes it absolutely imperative that administration of melatonin for these children is under the supervision of a health professional who can monitor efficacy and side effects, and recommend periodic ‘off-drug holidays,’” Dr. Owens says. The goal is to get sleep back on track and consistent for some time. Once that goal is achieved, Dr. Nahmias adds, “it is important that there be attempts to take breaks from the medication or try lower doses.”

When melatonin is not likely to help

Melatonin is often used in situations where it’s unlikely to make much difference. That’s not a criticism of parents — sleep deprivation is exhausting, and it’s natural to reach for something that seems gentle and accessible. But if the real issue is an inconsistent routine, untreated anxiety, or an unidentified medical problem, melatonin may only be a temporary solution. The real problem will persist and need diagnosis and treatment.

For younger children — kids under five, especially — sleep problems are almost always better addressed with changes in habits and routines rather than supplements. For kids under two, “there’s no reason to use melatonin… and really, honestly, under five, for the most part,” Dr. Owens says. At those ages, behavioral approaches almost always work better.

What to try before using melatonin

Small, consistent changes in sleep habits can make a real difference — and unlike a supplement, these strategies can help children build skills that support sleep for years to come. Dr. Nahmias focuses on what’s often called sleep hygiene: a consistent bedtime and wake time, a predictable wind-down routine, and a sleep environment that actually supports rest, like keeping the bedroom dark, cool, and quiet. “The bed is meant for one thing and one thing only, and that is for sleep,” he says, emphasizing no TV or cellphones before bed. Even small amounts of light can interfere with the body’s natural melatonin production.

He also suggests addressing anxiety, rumination, or bedtime fears directly. “Behavioral interventions, time and time again, have really been shown to be very effective,” Dr. Owens says. For younger children, that might mean learning to fall asleep without a parent in the room. For older kids and teens, it often means setting limits around devices and making sure the schedule they’re keeping is actually realistic.

Making a melatonin plan

Melatonin is a tool that works best with a plan behind it. Before starting, write down what problem you’re actually trying to solve. Is your child unable to fall asleep before 11pm? Waking during the night? Scared to sleep alone? Anxious about school?

A simple sleep log can make your conversation with your child’s doctor much more useful. For a week or two, track bedtime, approximate time asleep, any night wakings, morning wake time, screen use, and whether melatonin was used and, if so, at what dose. Dr. Owens calls sleep diaries “invaluable” because they reveal patterns that are nearly impossible to see when everyone’s tired and running on memory. That information helps you and your child’s doctor decide whether melatonin is worth trying, whether it’s working, and when it might be time to stop — keeping the focus not just on getting through tonight, but on helping your child build the sleep habits they’ll carry with them for years.

Frequently Asked Questions

Is melatonin safe for kids?

Melatonin is generally considered low risk and can be helpful for some children who have trouble falling asleep, especially when used short term and under a doctor’s guidance. But experts caution that there are still gaps in research about long-term use in kids, so it shouldn’t be treated as harmless or used casually without looking at underlying issues.

Can you OD on melatonin?

Accidental overuse can happen, especially because melatonin gummies may look like candy to young children. In recent years, there has been a major increase in poison control and ER visits related to accidental ingestion, so melatonin should always be stored like any medication — out of reach and ideally locked away.

Is melatonin bad for kids?

Melatonin is not inherently “bad” for kids, but it’s not the right solution for every sleep problem. If poor sleep is caused by anxiety, inconsistent routines, or a medical issue, melatonin may only mask the problem.

How much melatonin is safe for kids?

Experts recommend starting with the lowest effective dose. Some clinicians suggest starting with 1–2 milligrams for children ages four and up, and generally not exceeding 3 milligrams for kids ages 6–10 unless advised by a doctor.

The post Melatonin for Kids: Is It Safe? appeared first on Child Mind Institute.

Open-Source Algorithm Advances Precision Menstrual Health Beyond Fertility

Scientists at SRI International have developed an algorithm that analyzes menstrual cycle data to uncover hidden connections to overall health and aging, moving beyond the fertility focus of most previous research. In a study published in Science Advances, the tool revealed how aging influences key changes during the menstrual cycle and identified markers of individual variability that could be leveraged for the development of personalized approaches to menstrual health. 

“Across the reproductive life stage, a woman living in the United States would have, on average, 450 menstrual cycles, out of which [approximately] 3.2 cycles result in pregnancy. Yet, most of the focus on menstrual health—including research, medical training, customers apps, and patents—are centered solely on the reproductive aspect, and fail to leverage these 99% non-conceptive menstrual cycles as health indicators,” writes Marie Gombert-Labedens, PhD, postdoctoral researcher at SRI International and lead author of the study. 

The menstrual cycle is a complex process that is tightly connected to an individual’s health, influencing many physiological processes including metabolic and immune functions. Gombert-Labedens and colleagues believe that tracking the rhythms of the menstrual cycle can be a valuable yet underexplored diagnostic tool—similar to how cardiac rhythms are routinely monitored to diagnose a wide range of cardiovascular conditions or how circadian rhythms can indicate metabolic disorders. 

However, more work needs to be done in menstrual health research to identify the most relevant metrics, their relationship with health conditions, and the extent to which individual variations may require a personalized approach. To aid the research community in this endeavor, the team developed the WAVES algorithm, which stands for ‘women’s health assessment through variability in endocrine-related signals.’

Using the WAVES algorithm, the researchers analyzed data from 5,674 menstrual cycles from 753 participants between 18 and 42 years old, including daily temperature measurements, vaginal secretions, age, reproductive history and sexual activity. Results showed that aging was associated with measurable changes in the menstrual cycle, including higher average temperatures, shorter cycles, and a decrease in regularity across multiple metrics. 

Gombert-Labedens and colleagues also looked at individual variability across all metrics, as menstrual cycles are known to vary widely from person to person both in terms of length and regularity. “Although the menstrual cycle is typically described as 28 days long, research based on large datasets indicate that this is more the exception than the rule, as only 12.4% of individuals present 28-day cycles,” she stated. 

Their analysis revealed that each participant showed individual patterns concerning mean body temperature across cycles, minimum and maximum temperature measurements, and the duration of both the full cycle and its phases. “These findings suggest that, across cycles from the same individual, each person has their own temperature baseline measurement around which the menstrual fluctuations are organized and are highly stable,” noted Gombert-Labedens. 

As an open-source platform, the WAVES algorithm is now available to researchers worldwide studying menstrual cycle patterns, helping them parse through large amounts of data to identify relevant biomarkers associated with health, disease, and treatment response. 

“The menstrual cycle is a rich yet underused source of physiological information,” Gombert-Labedens concludes. “This work suggests that the WAVES algorithm can be used for advancing digital biomarker discovery, and highlights the relevance of a personalized approach in the development of next-generation tools for women’s health.” 

The post Open-Source Algorithm Advances Precision Menstrual Health Beyond Fertility appeared first on Inside Precision Medicine.

Lifestyle, psychological and demographic predictors of anxiety: insights from a large-scale survey and machine learning analysis

ObjectiveAnxiety is influenced by a combination of lifestyle, psychological, and demographic factors. This study aimed to evaluate these associations and explore the potential of machine learning in predicting anxiety severity.MethodsAnxiety levels were evaluated using a large survey-based dataset of 11, 000 adults alongside demographic, physiological, and psychological measures. Descriptive statistics and inferential analyses were conducted in IBM SPSS to identify associations between key variables. Several machine learning regression algorithms, including linear, regularized, and ensemble models, were implemented in Python to predict anxiety levels. Model performance was evaluated using standard error metrics.ResultsOur findings revealed significant associations of anxiety with stress and sleep duration, while demographic attributes such as family history of anxiety and occupation also influenced outcomes. Ensemble machine learning algorithms achieved superior performance compared to single and linear-model approaches. Feature importance analysis identified stress, sleep, and caffeine intake as top predictors of anxiety.ConclusionsThe integration of statistical approaches with machine learning applications highlights the multifactorial nature of anxiety and demonstrates the potential of predictive modeling in mental health care. Future research should emphasize longitudinal designs and the incorporation of biological and digital markers to enhance clinical applicability and prediction.

Seasonal and gender-specific patterns in prescriptions for hypnotic and sedative medications in primary care

IntroductionPopulation-level prevalence of sleep disorders can be assessed using prescription data for hypnotic and sedative medications. Such prescribing patterns exhibit seasonality that may be linked to variations in daylight exposure. The aim of this study was to analyze temporal trends in prescriptions for drugs with sedative-hypnotic properties.MethodsPrescription data for hypnotics and sedatives were analyzed retrospectively and stratified by month, year, and patient gender. Seasonal patterns, associations with day length, and the effects of transitions between daylight saving time and standard time were examined. Changes in prescription numbers during the COVID-19 pandemic were also assessed. Relative differences in prescription counts were evaluated using incidence rate ratios (IRR).ResultsPrescription numbers were lowest in summer (May–August) and highest in winter and early spring. Increasing day length was significantly associated with reduced prescription rates. A decline in prescriptions occurred earlier and was more pronounced in men (February–September; IRR 0.88–0.95), whereas in women the changes were weaker and mainly limited to summer months (June–August; IRR 0.94–0.97), with a slight increase observed in February. During the COVID-19 pandemic, prescription numbers decreased significantly. Transitions between standard and daylight saving time exerted measurable short-term effects on sleep-related health at the population level.ConclusionsBased on data from a single primary care center in Poland, prescribing patterns for hypnotic and sedative medications demonstrate clear seasonality and significant gender differences. Longer daylight exposure and transitions to daylight saving time are associated with lower prescription rates. The COVID-19 pandemic substantially disrupted previous trends in sleep medication prescribing, which may be related to reduced access to healthcare services and changes in healthcare delivery. In addition, transitions between standard and daylight saving time were associated with statistically significant short-term changes in prescription rates.

Feasibility of Videoconference-Based Cognitive Behavioral Therapy for Somatic Symptom Disorder: Single-Arm Pilot Trial

Background: Somatic symptom disorder (SSD) is a mental disorder marked by persistent somatic symptoms and maladaptive health-related thoughts, feelings, or behaviors. Cognitive behavioral therapy has been shown to be effective in treating SSD, reducing patients’ somatic symptoms, depressive symptoms, and anxiety symptoms. However, challenges remain—including limited access to treatment. Videoconference-based cognitive behavioral therapy (vCBT) has emerged as a promising approach, offering flexible and tailored treatment while addressing the shortage of medical resources and potentially reducing patient dropout. Objective: This study examined the feasibility of vCBT for patients with SSD and explored secondary outcomes related to the physical component of health-related quality of life (HRQOL) as assessed using the Medical Outcomes Study 36-Item Short Form Health Survey (SF-36) physical component summary (PCS) score and other exploratory clinical outcomes. Methods: This single-arm pilot trial evaluated feasibility as the primary outcome assessed via recruitment rate, retention rate, session completion rate, and safety. Ten participants with SSD were enrolled, and all received 6 weekly 50-minute vCBT sessions. Secondary outcomes included physical HRQOL (SF-36 PCS) as the key secondary outcome, as well as mental HRQOL, depressive symptoms, somatic symptom severity, anxiety symptoms, health anxiety, pain, insomnia, and generic HRQOL. These outcomes were measured at the preintervention (week 0) and postintervention (week 6) time points and 1-month follow-up (week 10) and were analyzed using 2-sided paired tests. Results: All feasibility criteria were met, with a recruitment rate of 83.3% (10/12), a retention rate of 100% (10/10), a session completion rate of 100% (10/10), and no adverse events reported. The SF-36 PCS score improved by 4.99 points at the postintervention time point, representing a large within-group effect (Cohen =0.99, 95% CI 0.21‐1.74). Medium to large improvements were also observed in mental HRQOL, depressive symptoms, anxiety symptoms, health anxiety, pain, insomnia, and generic HRQOL, and most of these improvements were observed at the 1-month follow-up. Conclusions: Our findings indicate that vCBT is a feasible and safe approach for SSD, with findings suggesting acceptability and preliminary evidence of effectiveness. Trial Registration: University Hospital Medical Information Network Clinical Trials Registry UMIN000046138; https://center6.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno=R000052664
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Sleep quality and its associated factors among women of reproductive age in Ethiopia: a systematic review and meta-analysis

BackgroundQuality sleep is vital for women’s health during reproductive years, affecting both physical and mental well-being. In Ethiopia, socio-economic and cultural factors worsen sleep issues, but data on this demographic are scarce. This systematic review and meta-analysis assesses the prevalence of poor sleep quality among Ethiopian women and identifies contributing factors, aiming to inform interventions and policies to improve sleep health in low-resource settings.MethodThis systematic review followed PRISMA guidelines and searched PubMed, Scopus, and Web of Science for observational studies. We included studies utilizing the Pittsburgh Sleep Quality Index (PSQI), as it is the most widely validated tool for assessing subjective sleep quality across diverse populations. Reviewers independently screened articles using Rayyan and assessed study quality with the Joanna Briggs Institute tools. Data were analyzed using Stata version 17. To account for potential clinical and methodological variability across studies, a random-effects model was employed to pool results, with heterogeneity assessed using statistics and the Cochrane’s Q test. Publication bias and sensitivity analyses were also performed.ResultNine studies involving 4,376 women of reproductive age (15–49 years) in Ethiopia were included. The pooled prevalence of poor sleep quality was 49.17% (95% CI: 35.29, 63.08). Significant predictors of poor sleep quality included intimate partner violence (OR: 3.24), depression (OR: 3.37), unplanned pregnancy (OR: 2.71), multigravidity (OR: 2.61), and substance use (OR: 2.24).ConclusionA systematic review indicates that nearly half of Ethiopian women of reproductive age experience poor sleep quality. Key factors include unplanned pregnancies, substance use history, intimate partner violence, previous depression, stress, being in the third trimester, and comorbidities; these need urgent attention and the implementation of screening and preventive measures. Future research should focus on effective interventions to improve sleep quality in these populations.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42023455867.