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This article emphasizes the importance of using subjective measures, such as sleep diaries, to assess insomnia. It argues that objective measures like polysomnography (PSG) are not suitable for diagnosing or treating insomnia, as they are only effective for sleep disorders with underlying pathologies. Sleep diaries are considered more accurate because they capture an individual's perception of sleep continuity over multiple nights. The article also discusses the limitations of objective measures, such as EEG-based devices and wearables, in accurately assessing sleep continuity in individuals with insomnia. It concludes that until a pathophysiological measure is discovered for insomnia, sleep diaries remain the optimal method for assessing sleep continuity disturbance. The Insomnia Severity Index (ISI) is often recommended as the best measure for assessing insomnia, but it has its own limitations. Insomnia is a psychophysiological condition that can be evaluated using a combination of subjective and objective measures, and it is important to understand the strengths and limitations of each method and explore discrepancies between them. The document also provides a list of references covering various aspects of insomnia, including its impact on neuropsychological performance, cognitive impairment, pharmacotherapy for older adults, perception of sleep, use of placebos in treatment, actigraphy as a measurement tool, and assessment and management of insomnia. These references offer a comprehensive overview of current research and understanding of insomnia. [Extracted from the article]

The present study investigated the roles birthplace and acculturation play in sleep estimates among Hispanic/Latino population at the US–Mexico border. Data were collected in 2016, from N = 100 adults of Mexican descent from the city of Nogales, AZ, at the US–Mexico border. Sleep was assessed with the Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index categorized as none, mild, moderate, and severe, and Multivariable Apnea Prediction Index (MAP) categorized as never, infrequently, and frequently. Acculturation was measured with the Acculturation Rating Scale for Mexican-Americans II (ARSMA-II). The sample consisted of majority Mexican-born (66%, vs. born in the USA 38.2%). Being born in the USA was associated with 55 fewer minutes of nighttime sleep (p =.011), and 1.65 greater PSQI score (p =.031). Compared to no symptoms, being born in the USA was associated with greater likelihood of severe difficulty falling asleep (OR = 8.3, p =.030) and severe difficulty staying asleep (OR = 11.2, p =.050), as well as decreased likelihood of breathing pauses during sleep (OR = 0.18, P =.020). These relationships remained significant after Mexican acculturation was entered in these models. However, greater Anglo acculturation appears to mediate one fewer hour of sleep per night, poorer sleep quality, and reporting of severe difficulty falling asleep and staying asleep. Among individuals of Mexican descent, being born in the USA (vs Mexico) is associated with about 1 hour less sleep per night, worse sleep quality, more insomnia symptoms, and less mild sleep apnea symptoms. These relationships are influenced by acculturation, primarily the degree of Anglo rather than the degree of Mexican acculturation. [ABSTRACT FROM AUTHOR]

Rationale: Obstructive sleep apnea (OSA) is a common condition that is usually treated by continuous positive airway pressure (CPAP) therapy, but poor adherence is common and is associated with worse patient outcomes and experiences. Patient satisfaction is increasingly adopted as a quality indicator by healthcare systems., Objective: We tested the hypothesis that peer-driven intervention effected through interactive voice-response(PDI-IVR) system leads to better patient satisfaction (primary outcome), care-coordination, and CPAP adherence when compared to active-control., Methods: We performed a 6-month randomized, parallel-group, controlled trial with CPAP naïve patients recruited from four centers and CPAP-adherent patients who were trained to be mentors delivering support through an IVR system., Measurements and Results: In 263 patients, intention-to-treat analysis global satisfaction for sleep-specific services was better in the intervention group (4.57+0.71 Likert scale score) than in the active-control group (4.10+1.13; P<0.001). CPAP adherence was greater in intervention group (4.5+0.2 hours/night; 62.0+3.0% of nights >4 hours usage) versus active-control group (3.7+0.2 hours/night; 51.4+3.0% of nights >4 hours usage; P=0.014 and P=0.023). When compared to active-control group, Patient Assessment of Chronic Illness Care ratings was moderately increased by an adjusted difference of 0.33+0.12 (P=0.009); Consumer Assessment of Healthcare Provider and Systems ratings was not different (adjusted difference of 0.46+0.26; P=0.076); and Client Perception of Coordination Questionnaire was mildly better in the intervention group (adjusted difference 0.15+0.07; P=0.035)., Conclusion: Patient satisfaction with care delivery, CPAP adherence, and care-coordination was improved by peer-driven intervention through an IVR system. New payor policies compensating peer-support may enable implementation of this approach. Clinical trial registration available at www., Clinicaltrials: gov, ID: NCT02056002.

The National Heart, Lung, and Blood Institute convened a virtual workshop in September 2022 to discuss "Optimal Instruments for Measurement of Diet, Physical Activity, and Sleep." This report summarizes the proceedings, identifying current research gaps and future directions for measuring different lifestyle behaviors in adult population-based studies. Key discussions centered on integrating report-based methods, like questionnaires, with device-based assessments, including wearables and physiological measures such as biomarkers and omics to enhance self-reported metrics and better understand the underlying biologic mechanisms of chronic diseases. Emphasis was placed on the need for data harmonization, including the adoption of standard terminology, reproducible metrics, and accessible raw data, to enhance the analysis through artificial intelligence and machine learning techniques. The workshop highlighted the importance of standardizing procedures for integrated behavioral phenotypes using time-series data. These efforts aim to refine data accuracy and comparability across studies and populations, thereby advancing our understanding of lifestyle behaviors and their impact on chronic disease outcomes over the life course.