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Record W7045284713

Analysis of sleep and sleep hygiene in relation to the 2020 24-Hr Canadian Movement Guidelines among adults with intellectual and developmental disabilities: A Pilot Study

2023· dissertation· en· W7045284713 on OpenAlexaboutno aff

Bibliographic record

VenueUVic’s Research and Learning Repository (University of Victoria) · 2023
Typedissertation
Languageen
FieldMedicine
TopicDown syndrome and intellectual disability research
Canadian institutionsnot available
Fundersnot available
KeywordsSleep hygieneSleep (system call)SmartwatchDuration (music)ActigraphySleep debtPhysical activitySleep diary
DOInot available

Abstract

fetched live from OpenAlex

Background: A variety of physiological and behavioural factors contribute to adults with Intellectual and Developmental Disabilities (IDD) being at high risk of problems with sleep duration and sleep quality. Sleep problems in this demographic may have been exacerbated by changes and restrictions in place due to the COVID-19 pandemic. Objective: The objective of this pilot study was to determine if collecting field data using smartwatch technology and sleep and physical activity diaries was feasible in this population. Utilizing these methodologies, the main goal was to monitor the sleep duration and sleep quality of adults with IDD and to compare those findings to the recommendations in the Canadian 24-Hour Movement Guidelines. Additionally, sleep hygiene behaviours and daily activities were recorded to further understand relationships between sleep and these variables. Methods: Participants (n = 15) were invited to wear a Polar Ignite smartwatch for a 9-day period and instructed how to complete a sleep and physical activity diary. Total sleep, actual sleep, sleep disturbances, and physical activity were recorded quantitatively using actigraphy. Behaviours were assessed using the sleep and physical activity diary. Results: Participants were able to consistently wear the smartwatch and report information in the sleep and physical activity diary. The majority of participants did not meet sleep duration guidelines based on their weekly average, with 9 out of 15 participants outside the guideline recommendations and only 1 participant meeting the guidelines every night. Participants regularly reported problems with their sleep and smartwatches recorded an average of 35:40 minutes (SD = 10:50) of sleep disturbances each night. Screen time before bed was the most common adverse sleep hygiene behaviour. Screen time was negatively, but not significantly correlated with total sleep (r = -0.34, p > 0.1) and actual sleep (r = -0.33, p > 0.1). Average moderate-vigorous physical activity (MVPA) was significantly correlated with sleep disturbances. This relationship was negative and moderately strong (r = -0.57, p < 0.05). Conclusions: This pilot study highlights that participants were able to provide seven days of sleep data and adhere to reporting their daily behaviours via a sleep and physical activity diary. Additionally, sleep duration and quality were not adequate in most participants. It is also likely that before-bed screentime had an adverse effect on sleep duration. Physical activity, on the other hand, had a positive effect on reducing sleep disturbances. These results suggest fruitful lines of enquiry, and future research with larger samples of adults with IDD are recommended to understand these relationships further. Researchers should have an ultimate objective of optimizing sleep, which in turn, would improve the health status of adults with IDD.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.478
Threshold uncertainty score0.961

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.043
GPT teacher head0.302
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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