bluuebunny/crossref_metadata_2025_split huggingface dataset:
1093 TikTok Made Me Do It: An Analysis of the Scientific Evidence Supporting TikTok’s Recommendations for Better Sleep
Authors: Gillis Brian , VanAntwerp Joycelyn , Scott Emily , Peltz Jack 
Published: April 2024

Abstract

Introduction
Like it or not, the public looks to social media for health advice. In one large survey, adults listed social media as their second place for health information following their primary care provider, and most individuals reported that they do not verify the accuracy of information with a healthcare provider. Given the public’s apparent confidence in health advice shared on social media, it is important that content creators share medically sound advice. To that end, we sought to understand the scientific evidence supporting sleep tips shared on TikTok.

Methods
We transcribed the most-viewed TikTok videos on November 15-16, 2023, that used the tag #sleephacks, #sleephygiene, or #sleeptips. Two researchers coded each video to identify all sleep tips; a third researcher coded &gt;25% of videos for validity. A total of 295 sleep tips (including repeated recommendations) were coded across 58 videos. Tips were then organized by theme and were compared to findings from empirical articles in peer-reviewed journals on Google Scholar. Research-based evidence in support of sleep tips was defined as shorter sleep latency, longer sleep duration, more slow-wave or rapid eye movement sleep, higher sleep satisfaction, or less daytime sleepiness in randomized or non-randomized controlled trials or correlational (cross-sectional regression) associations.

Results
N = 35 unique sleep tips were identified, grouped around 7 themes: calming activities (e.g., breathwork prior to bed), use of electronics (e.g., limiting screen time before bed), environment (e.g., sleeping in a cool, dark room), foods/substances to avoid (e.g., caffeine before bed), foods/substances to use (e.g., magnesium), schedule (e.g., consistent bed and wake times), and other sleep-related behaviors (e.g., mouth taping). Of the 35 tips, we found empirical support for 33, of which 26 had evidence from randomized controlled trials, 2 were supported by controlled trials without randomization, and 5 were backed by correlational associations.

Conclusion
Most sleep tips shared on TikTok are supported by empirical evidence. While much of the health advice shared on the platform remains unregulated and unreviewed by health professionals, current information about sleep hygiene and sleep environment is generally backed by scientific support.

Support (if any)
1095 Adaptation of SIESTA (Sleep for Inpatients: Empowering Staff to Act) Protocol for Acute Stroke Rehabilitation
Authors: Siddiqui Sehar , Ramos Bianca , Ram Kavita , Billeh Lauren , Sunderrajan Aashna , Sindorf Jacob , Barnes Alyah , Masangkay Alyssa , Martinez Maylyn , Morris Linda , Prabhakaran Shyam , O’Brien Megan , Prokup Sara , Jayaraman Arun , Arora Vineet 
Published: April 2024

Abstract

Introduction
Improving sleep for patients with stroke is vital due to the importance of sleep for neuroplasticity and functional recovery. While sleep interventions have been successful in reducing nocturnal disruptions for hospitalized patients, few interventions have been tested for patients with stroke in an acute rehabilitation setting. We aimed to adapt the successful hospital protocol SIESTA (Sleep for Inpatients: Empowering Staff to Act) to an acute stroke rehabilitation setting.

Methods
Surveys and focus groups with nurses caring for patients with stroke on inpatient floors at Shirley Ryan AbilityLab informed the development of the adapted protocol, SIESTA-Rehab. The protocol included educational video modules for nurses regarding sleep hygiene and sleep apnea screening, sleep enhancing measures (eye masks, quiet signs), a nurse badge card with a checklist reinforcing protocol components, and advocacy for patient sleep at shift handoff. Two nurse champions were recruited to monitor protocol implementation. Periodic re-education was conducted to account for nurse turnover. Ongoing fidelity interviews using the Consolidated Framework for Implementation Research (CFIR) framework assessed intervention perceptions.

Results
We initially trained 27 (93%) nurses using the training module. Fidelity interviews of over 20 nurses in the years post-implementation demonstrated over 57% of nurses recalled sleep masks and “cluster care” as part of the protocol. Moreover, more than 75% of nurses considered the protocol to be “straightforward” and “part of the workflow.” Nurses perceived the protocol positively, noting it “could be really beneficial for patients and their long-term health,” and have incorporated behavioral changes into their routine since being educated on sleep hygiene. Nurses also reported understanding the importance of sleep for stroke patients, stating sleep “helps in their recovery and feeling well rested for the day so that they can participate in therapy” and understood “how [they] affect that in [their] roles” as nurses.

Conclusion
The SIESTA protocol can be successfully adapted to an acute rehabilitation setting for stroke patients, as evidenced by positive staff responses to sleep-promoting interventions, ease of protocol incorporation, and high staff compliance. Ongoing work is investigating patient perceptions and outcomes following implementation of this sleep protocol.

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1098 Hypoglossal Nerve Stimulation Program Analysis and Financial Impact over 6 Months
Authors: Richardson Stephen , Hope Christopher 
Published: April 2024

Abstract

Introduction
Inspire hypoglossal nerve stimulation (HNS) is being increasingly utilized as an alternative treatment for moderate to severe obstructive sleep apnea in select patients who fail positive airway pressure therapy. There is substantial cost and effort in developing an HNS program. We report on a programmatic and financial analysis in a non-academic, community-based sleep center 2 years into its HNS program.

Methods
A retrospective review of all clinic visits was performed for a 6-month period from January 2022 through June 2022. Visits were reviewed as being referred for, or discussing HNS as a treatment option, for inclusion in the analysis. Included visits were categorized as new or follow up visit, and data was extracted including referring provider specialty, insurer, and if the visit resulted in ordering of a sleep study, referral to ENT, if the patient qualified for HNS, and billing for interrogation/programming of the stimulator. Financial impact was estimated by multiplying the average reimbursement rate for associated CPT codes by the number of CPT's generated.

Results
During this study period, our HNS program generated 215 patient visits, which accounted for 9% of total clinical volume. 81 were new evaluations and 134 were follow-ups. Of the new patients, 77 were referred for interest in HNS, most commonly from primary care or self-referred (33% each). Forty-four polysomnograms and 18 home sleep apnea tests were performed related to these visits. A total of 93 HNS programming/interrogation services were performed. The total revenue generated across all services was estimated at $83,276.

Conclusion
This observational program analysis revealed that offering HNS services generated a significant number of clinic visits, sleep studies ordered, and device interrogation services, accounting for increased clinical and study revenue. Marketing appears to have generated a significant number of self-referrals. Future research could include further analysis over a longer period of time and at other sleep clinic settings in an effort to make the results more generalizable.

Support (if any)
None.
0110 Insomnia Symptom Prevalence by Foster Care History from Adolescence to Adulthood
Authors: Rojo-Wissar Darlynn , Vieira Alyssa , Rech Megan , Alfano Candice , Parade Stephanie 
Published: April 2024

Abstract

Introduction
Known associations between stress and sleep suggest that early-life adversity faced by children who spend time in foster care (FC) confers vulnerability to sleep disturbances, though research in this population is scarce. We utilized data from a nationally representative longitudinal study to examine insomnia symptom prevalence by FC history from adolescence to adulthood.

Methods
Participants were from the National Longitudinal Study of Adolescent to Adult Health (N=6,954, representing 21,059,854), 1.5% had a history of FC involvement (N=123, representing 318,515), 50% were female, 65% were non-Hispanic (NH) white, 15% were NH Black, and 10% reported a resident parent receiving public assistance at Wave I (W1). Participants were in grades 7-12 during W1, grades 8-12 in Wave II (W2), ages 24-32 in Wave IV (W4), and ages 33-43 in Wave V (W5). Participants were considered positive for insomnia symptoms if they reported trouble falling asleep or staying asleep ≥ “3 times per week”, “often or every day”, or “almost every day or every day”. Design-based analyses were conducted, including use of sampling weights. Poisson regression was used to estimate whether relative risk for insomnia differed at each wave by FC history, and prevalence estimates were estimated at each wave, adjusting for demographic characteristics.

Results
The relative risk for insomnia symptoms was significantly greater among those with a FC history at W1 (p=.039), W2 (p=.001), and W4 (p=.000), but not W5 (p=.840). Insomnia symptom prevalences among those with versus without FC history were: 20% versus 11% (W1), 20% versus 8% (W2), 51% versus 27% (W4), and 31% versus 30% (W5).

Conclusion
Among individuals in the US, those with a FC history experience substantially higher risk for significant insomnia symptoms from adolescence to ages 24-32, but this difference disappears around ages 33-43. Addressing sleep issues in the FC population is of critical public health importance. Future research should examine how sleep disturbances contribute to poor health outcomes in the FC population.

Support (if any)
This research uses data from Add Health, funded by grant NICHD:P01 HD31921, NIA:U01 AG071448 and U01AG071450. DMR was supported by NIMH:5T32MH014592-39; the Sleep Research Society Foundation, NICHD:T32HD101392. DMR & SP received support from NIGMS:P20GM139767.
1106 Patient-Centric Design: Incorporating Patient Input into a Clinical Study of Idiopathic Hypersomnia and Narcolepsy
Authors: Nichols Deborah , Barker Emily , Akerman Sarah , Steininger Teresa , Macfadden Wayne 
Published: April 2024

Abstract

Introduction
Jazz DUET (Develop hypersomnia Understanding by Evaluating low-sodium oxybate Treatment; NCT05875974) is a phase 4, prospective, multicenter, single-arm, open-label interventional study that comprehensively evaluates low-sodium oxybate effects on sleep architecture and daytime/nighttime symptoms in participants with idiopathic hypersomnia or narcolepsy. Multiple assessments, including overnight polysomnography (PSG), are needed to generate robust, relevant data, but these assessments may impose a burden on study participants. A patient advisory board was convened to understand patient perspectives and assess opportunities to incorporate patient feedback into the study protocol.

Methods
Advisors completed a premeeting survey, then attended a 3-hour advisory board meeting with the study sponsor. Five main topics were discussed: feasibility of oxybate washout for participants entering the study on treatment, burden of assessments, relevance of specific symptom evaluation to participants, value of reporting individualized data back to participants, and burden of overnight visits.

Results
The advisory board included 2 people with idiopathic hypersomnia and 4 people with narcolepsy. All 6 advisors had experience with patient advocacy, and at least 1 had been a clinical trial participant; these experiences may help give voice to a broader patient community. Premeeting survey responses were reviewed and discussed during the meeting. Based on advisor input, the final study protocol incorporated several points, including support for participants undergoing oxybate washout (eg, transportation, childcare, and meal service, as needed), additional breaks between assessments, moving assessments from evening to morning to reduce participant burden, measuring fatigue separately from sleepiness, and suggestions to make participants more comfortable for overnight visits. Advisors noted the high value of reporting individualized data back to study participants—particularly PSG data, with specific interest in number of awakenings, duration of rapid eye movement sleep, and duration of slow-wave sleep. In addition to these changes, study materials were developed to help participants prepare for overnight visits, and a checklist of items to bring to these visits was created.

Conclusion
The final DUET study design incorporated patient-centric elements recommended by a patient advisory board. Implementation of these elements is anticipated to reduce participant burden, improve participant experience, enhance recruitment and retention, and facilitate collection of meaningful and comprehensive data.

Support (if any)
Jazz Pharmaceuticals
1107 Facilitating Accurate Sleep Diary Data Collection and Processing Based on Common Participant Data Entry Errors
Authors: Tully Isabelle , Suh Sooyeon , Dietch Jessica , Manber Rachel 
Published: April 2024

Abstract

Introduction
Sleep diaries are the gold-standard measure of self-reported sleep parameters; however, data utility is contingent upon accurate data entry and clarity of standardized diary terminology/calculations between participants and researchers. Informed by the RESTING study, an effectiveness-implementation RCT of cognitive-behavioral therapy for insomnia, sleep diary dataset, the current study elucidates common participant sleep diary entry errors to inform standardizable research strategies for minimizing post hoc inaccuracies.

Methods
RESTING Study participants (N=245) with insomnia disorder completed Consensus Sleep Diaries through REDCap at baseline. Embedded survey data validation prompted participants to check unexpected values (e.g., calculated TIB &gt;10 hours). Researchers reviewed diaries weekly, correcting immediately apparent errors. Post hoc data cleaning scripts flagged sleep diaries with potential inaccuracies based on: (1) 9 hours&lt; Calculated Total Sleep Time (TST)&lt; 4.5 hours, (2) Difference between calculated and self-reported TST &gt;2 hours, (3) 100%&lt; Sleep Efficiency&lt; 45%, (4) Difference between lights out (LO) and bedtime (BT)&lt; 0, or (5) Difference between rise time (RT) and wake time (WT)&lt; 0. Researchers examined internal consistency within flagged diaries and across all entries by a participant.

Results
3,382 days of sleep diary data were submitted at baseline (98% of expected). During active data collection, researchers corrected errors within 61 (1.8%) unique diaries, completed by 37 participants. Of 503 (14.9%) distinct sleep diaries (among 173 participants) flagged by post hoc scripts, 173 (5.1%) contained at least one error. Examining internal consistency across diary dates when reviewing flagged entries revealed 20 additional diaries with errors, among 2 participants. In sum, 348 errors were made among 119 participants. The most common errors were: confusion between WT and RT (n=150), confusion between BT and LO (n=45), inclusion of multiple sleep parameters within self-reported “wake after sleep onset” (n=29), unambiguous typos (n=29), and AM/PM mix-ups (n=28).

Conclusion
Despite training participants on sleep diary completion and utilizing survey data validation, 5.7% of diaries contained errors corrected post hoc. This highlights the importance of standardizing use of post hoc data cleaning scripts. Common errors identified can inform best practices for embedded sleep diary data validation and development of sensitive, precise protocols for reviewing diaries throughout data collection.

Support (if any)
1R01AG057500
1108 Prior-night Sleep Predicts Next-day Symptoms over Ten Days Among Military Personnel with Sleep Problems
Authors: Collen Jacob , Capaldi Vincent , Zhao Zhiwei , Thomas Connie , Williams Scott , Assefa Samson , Chen Shuo , Albrecht Jennifer , Wickwire Emerson 
Published: April 2024

Abstract

Introduction
Insufficient and disturbed sleep are highly prevalent and associated with adverse consequences in the U.S. military. The purpose of this study was to employ remote monitoring/ecological momentary assessment methods to test the hypothesis that prior-night sleep is associated with next-day subjective symptoms among military personnel.

Methods
Participants (N=270) with sleep problems were recruited from two military treatment facilities and completed an intensive ten-day remote monitoring assessment. Prior night sleep was measured using standardized sleep diaries and a commercial wearable sleep tracker (Fitbit Inspire 2). Next-day symptoms were measured using twice-daily symptom surveys (i.e., 20 surveys over ten days). Individual items assessed subjective cognition, energy level, and mood using an “I feel tired” format and scored from 0-4. To determine the lagged impact of prior-night sleep on next-day symptoms, a total of 40 mixed models (MMs) were developed. Individual prior-night sleep diary (total sleep time [TST], sleep efficiency [SE], and sleep quality [QUAL]) and Fitbit (TST, SE) parameters were entered as independent variables, and individual daytime symptoms (feeling alert, clear-headed, refreshed, fatigued, happy, sad, stressed, and relaxed) were entered as dependent variables. All models controlled for age and sex. The Benjamini-Hochberg procedure for correcting false discovery rate (BH-FDR) method was used to correct for multiple comparisons.

Results
Lagged MM analyses revealed that all prior-night sleep diary variables were significantly associated with next-day symptoms (all ps&lt; 0.001 with df=2081) over ten days. Specifically, prior-night sleep diary parameters (TST, SE, QUAL) were positively associated with next-day feeling alert, clear-headed, refreshed, happy, and relaxed; and negatively associated with next-day feeling fatigued, sad, and stressed. Prior-night Fitbit sleep parameters were significantly associated with most next-day symptoms (largest p=0.023 with df=1956). Specifically, Fitbit TST and SE were positively associated with next-day feeling clear-headed, refreshed, happy, and relaxed and negatively associated with next-day fatigue. Fitbit TST was negatively associated with next-day stress.

Conclusion
Among military personnel with sleep problems, prior-night sleep predicts next-day subjective cognition, energy level, and mood over ten days. Future research should employ remote monitoring approaches to predict treatment response and deliver personalized care to improve sleep and daytime symptoms.

Support (if any)
DoD W81XWH1990006 (via Medical Technology Enterprise Consortium)
1109 The Impact of Sleep Duration and Its Variability on the Human Phenome: Analysis of All of Us Wearables Data
Authors: Manetta Mason , Mazzotti Diego 
Published: April 2024

Abstract

Introduction
Epidemiological evidence indicates that short, long and variable sleep duration are associated with cardiometabolic outcomes. However, due to the ubiquitous role of sleep, one would expect to see effects on a broad range of human diseases. Using electronic health records (EHR) and wearable sleep data from the All of Us Research Program, we conducted a cross-sectional analysis of sleep duration and variability with the risk of over 3530 chronic conditions across the human phenome.

Methods
All of Us participants (≥18 years) with available EHR data and at least 90 days of continuous monitoring using Fitbit devices under a ‘bring your own device’ model were included. Average (mean) and variability (standard deviation) of sleep duration were derived based on device-generated data. Chronic conditions were determined based on mapping of International Classification of Disease 10 codes available in the EHR to phecodes, an ontology representing clinically meaningful concepts. Associations between sleep traits and phecodes were assessed using multiple test corrected logistic regression adjusted for age, sex, and race.

Results
A total of 8,256 participants with available Fitbit data were included. Participants were 89% White, 72% female, 72% college educated and had median (IQR) age of 51 (36.6-52.0) years, BMI 28.3 (24.4-33.0) kg/m2, and 1,566 (860-2307) days with sleep measurements. The median average nightly sleep duration was 6.34 (5.67-6.91) hours and the median nightly sleep variability was 1.63 (1.33-1.95) hours. In adjusted analyses, participants with greater sleep duration had significantly lower odds of obesity (OR; 95%CI = 0.85; 0.80-0.91, obstructive sleep apnea (0.74; 0.74-0.88), type 2 diabetes (0.68, CI 0.58-0.80), and essential hypertension (0.86; 0.81-0.92). Conversely, participants with greater sleep duration variability had higher odds of major depressive disorder (2.15; 1.84-2.51), anxiety disorder (1.75; 1.51-2.03), gastroesophageal reflux disease (1.61; 1.39-1.86), and abnormal electrocardiogram (1.80; 1.47-2.19).

Conclusion
Our findings suggest important associations between sleep duration patterns and chronic conditions, emphasizing the importance of sleep health in disease prevention and management. Important limitations include analysis of a selected population with access to wearable devices, which may not represent the general population enrolled in All of Us.

Support (if any)
All of Us Research Scholars Program