0870 Shift Work Disorder Prevalence and Associated Characteristics Using the Mobile Application SLEEP by Cleveland Clinic™ Article Swipe

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Sikawat Thanaviratananich , James C. Johnson , James Bena , Nancy Foldvary‐Schaefer ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.1093/sleep/zsaf090.0870

Introduction Shift Work Disorder (SWD) arises from recurring work schedules overlapping typical sleep times. SWD is associated with increased risks of medical and psychiatric disorders with estimated prevalence of 2-5%, likely to be underestimated. We studied the prevalence and associated characteristics of SWD using a mobile application developed to estimate sleep disorder risk in adults. Methods SLEEP by Cleveland Clinic™ is a free iOS/Android mobile application that evaluates sleep disorder risk including Cleveland Clinic Sleep Apnea Probability Score (Katzan, Sleep Med 2016), Insomnia Severity Index (ISI; Morin, Sleep 2011), 24-hr sleep duration, and SWD (Barger, Sleep 2012). Demographic, comorbidity and sleep disorder risks were compared between high-risk (HR) and low-risk (LR) SWD groups using Pearson chi-square and t-tests, where appropriate. Results There were 5,217 unique user downloads Nov 2019-Dec 2024. Of these 3,515 provided geographic information and 2,149 (61%) were Ohio residents. Among 445 users who completed SWD screening, 198 (44.5%) were HR and 247 (55.5%) LR. HR SWD users were younger (40 + 13 vs 44 + 14 yrs) and more likely to be female (69 vs 57%), both p=0.009, work full time (85 vs 71%; p< 0.001), work nights/rotating shifts (80 vs 67%; p=0.006) and work longer shifts (p< 0.001) without difference in race or BMI. HR SWD was associated with higher mental health disorder diagnoses (66% vs 38%, p=0.001), more alcoholic drinks/week (0.0 (0.0,2.0) vs 1.0(0.0,3.0; p=0.032)), and more sleep aid use (53 vs 40%; p=0.035), but were similar on caffeine and tobacco use. ISI was higher in HR SWD (18(14,21) vs 13(9,17); p< 0.001)) but habitual sleep duration was comparable. LR SWD had higher probability of OSA and moderate-severe OSA 57(23,80)/15(6,9) vs 36(11,72)/9(3,23; p=0.002). Conclusion Among users of a sleep screening mobile application who completed SWD screening, nearly half classified as HR SWD were more likely to work nights/rotating shifts, use alcohol and sleep aids, have mental health disorders and have higher insomnia severity, but lower risk of OSA. The application provides immediate accessibly to sleep disorder risk that can help identify SWD, insomnia and OSA among adults with smartphones. Support (if any)

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Shift work Sleep (system call) Gerontology Medicine Psychiatry Psychology Clinical psychology Computer science Operating system

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Type: article
Language: en
Landing Page: https://doi.org/10.1093/sleep/zsaf090.0870
PDF: https://academic.oup.com/sleep/article-pdf/48/Supplement_1/A378/63222466/zsaf090.0870.pdf
OA Status: bronze
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OpenAlex ID: https://openalex.org/W4410502812

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DOI: https://doi.org/10.1093/sleep/zsaf090.0870

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Title: 0870 Shift Work Disorder Prevalence and Associated Characteristics Using the Mobile Application SLEEP by Cleveland Clinic™

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Language: en

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Publication year: 2025

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Publication date: 2025-05-01

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Authors: Sikawat Thanaviratananich, James C. Johnson, James Bena, Nancy Foldvary‐Schaefer

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Landing page: https://doi.org/10.1093/sleep/zsaf090.0870

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Concepts: Shift work, Sleep (system call), Gerontology, Medicine, Psychiatry, Psychology, Clinical psychology, Computer science, Operating system

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abstract_inverted_index.Insomnia	83
abstract_inverted_index.Severity	84
abstract_inverted_index.caffeine	244
abstract_inverted_index.compared	105
abstract_inverted_index.disorder	52, 70, 102, 217, 331
abstract_inverted_index.duration	262
abstract_inverted_index.estimate	50
abstract_inverted_index.habitual	260
abstract_inverted_index.identify	336
abstract_inverted_index.insomnia	317, 338
abstract_inverted_index.low-risk	110
abstract_inverted_index.p=0.006)	196
abstract_inverted_index.p=0.009,	181
abstract_inverted_index.provided	134
abstract_inverted_index.provides	326
abstract_inverted_index.t-tests,	118
abstract_inverted_index.(0.0,2.0)	227
abstract_inverted_index.13(9,17);	256
abstract_inverted_index.Cleveland	59, 73
abstract_inverted_index.Clinic™	60
abstract_inverted_index.alcoholic	224
abstract_inverted_index.completed	147, 289
abstract_inverted_index.developed	48
abstract_inverted_index.diagnoses	218
abstract_inverted_index.disorders	25, 313
abstract_inverted_index.downloads	127
abstract_inverted_index.duration,	92
abstract_inverted_index.estimated	27
abstract_inverted_index.evaluates	68
abstract_inverted_index.high-risk	107
abstract_inverted_index.immediate	327
abstract_inverted_index.including	72
abstract_inverted_index.increased	19
abstract_inverted_index.p&lt;	188, 257
abstract_inverted_index.p=0.001),	222
abstract_inverted_index.p=0.002).	278
abstract_inverted_index.p=0.035),	239
abstract_inverted_index.recurring	8
abstract_inverted_index.schedules	10
abstract_inverted_index.screening	285
abstract_inverted_index.severity,	318
abstract_inverted_index.(18(14,21)	254
abstract_inverted_index.(p&lt;	201
abstract_inverted_index.Conclusion	279
abstract_inverted_index.accessibly	328
abstract_inverted_index.associated	17, 40, 212
abstract_inverted_index.chi-square	116
abstract_inverted_index.classified	294
abstract_inverted_index.difference	204
abstract_inverted_index.geographic	135
abstract_inverted_index.p=0.032)),	230
abstract_inverted_index.prevalence	28, 38
abstract_inverted_index.residents.	142
abstract_inverted_index.screening,	149, 291
abstract_inverted_index.Probability	77
abstract_inverted_index.application	47, 66, 287, 325
abstract_inverted_index.comorbidity	99
abstract_inverted_index.comparable.	264
abstract_inverted_index.drinks/week	225
abstract_inverted_index.iOS/Android	64
abstract_inverted_index.information	136
abstract_inverted_index.overlapping	11
abstract_inverted_index.probability	269
abstract_inverted_index.psychiatric	24
abstract_inverted_index.1.0(0.0,3.0;	229
abstract_inverted_index.Demographic,	98
abstract_inverted_index.Introduction	1
abstract_inverted_index.appropriate.	120
abstract_inverted_index.smartphones.	344
abstract_inverted_index.characteristics	41
abstract_inverted_index.moderate-severe	273
abstract_inverted_index.nights/rotating	191, 303
abstract_inverted_index.underestimated.	34
abstract_inverted_index.36(11,72)/9(3,23;	277
abstract_inverted_index.57(23,80)/15(6,9)	275
cited_by_percentile_year
countries_distinct_count	1
institutions_distinct_count	4
citation_normalized_percentile.value	0.19428571
citation_normalized_percentile.is_in_top_1_percent	False
citation_normalized_percentile.is_in_top_10_percent	True