Trial reportPloS one2018
Identifying bedrest using 24-h waist or wrist accelerometry in adults.
Trial report in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed, 20 citations in OpenAlex.
- Effectiveness of Smartphone-Based Dyadic Interventions to Increase Physical Activity in Romantic Couples: Microrandomized Trial.JMIR mHealth and uHealth · 2026Trial
- Effect of a Tailored eHealth Physical Activity Intervention on Physical Activity and Depression During Postpartum: Randomized Controlled Trial (The Postpartum Wellness Study).JMIR mental health · 2025Trial
- An automated image-based dietary assessment application: a pilot study.Journal of nutritional science · 2025Trial
- The growing gap: A study of sleep, encoding, and consolidation of new words in chronic traumatic brain injury.Neuropsychologia · 2023Trial
- 24-Hour movement behaviour and quality of life among Chinese caregivers of children with intellectual disabilities: a compositional analysis.Preventive medicine reports · 2026Article
- Feasibility and acceptability of longitudinal measurement of 24-hour movement profiles across pregnancy using research-grade devices paired with sleep diaries.Journal of activity, sedentary and sleep behaviors · 2026Article
- Repeated device-based measures of daily movement, sedentary behavior, and sleep at 6 months postpartum: the Pregnancy Environment and Lifestyle Study-2 cohort.Sleep advances : a journal of the Sleep Research Society · 2026Article
- Measuring 24-hour Movement Profiles During Pregnancy: Protocol for the 24MOVE Prospective Cohort Study.JMIR research protocols · 2025Article
- Utility of PLUS CYCLE to measure physical activity and sleep duration and detect postoperative sleep disturbances in hospitalized dogs.PloS one · 2025Article
- Assessment of physical activity patterns in patients with rheumatoid arthritis using the UK Biobank.PloS one · 2025Article
- A Tailored Postpartum eHealth Physical Activity Intervention for Individuals at High Risk of Postpartum Depression-the POstpartum Wellness Study (POW): Protocol and Data Overview for a Randomized Controlled Trial.JMIR research protocols · 2024Article
- Criterion validity of wrist accelerometry for assessing energy intake via the intake-balance technique.The international journal of behavioral nutrition and physical activity · 2023Article
- Article
- Simple Method for the Objective Activity Type Assessment with Preschoolers, Children and Adolescents.Children (Basel, Switzerland) · 2020Article
- Sleep/Wake Regularity Associated with Default Mode Network Structure among Healthy Adolescents and Young Adults.Scientific reports · 2020Article
- Parameterizing and validating existing algorithms for identifying out-of-bed time using hip-worn accelerometer data from older women.Physiological measurement · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
objectivesTo adapt and refine a previously-developed youth-specific algorithm to identify bedrest for use in adults. The algorithm is based on using an automated decision tree (DT) analysis of accelerometry data.
designHealthy adults (n = 141, 85 females, 19-69 years-old) wore accelerometers on the waist, with a subset also wearing accelerometers on the dominant wrist (n = 45). Participants spent ≈24-h in a whole-room indirect calorimeter equipped with a force-platform floor to detect movement.
methodsMinute-by-minute data from recordings of waist-worn or wrist-worn accelerometers were used to identify bedrest and wake periods. Participants were randomly allocated to development (n = 69 and 23) and validation (n = 72 and 22) groups for waist-worn and wrist-worn accelerometers, respectively. The optimized DT algorithm parameters were block length, threshold, bedrest-start trigger, and bedrest-end trigger. Differences between DT classification and synchronized objective classification by the room calorimeter to bedrest or wake were assessed for sensitivity, specificity, and accuracy using a Receiver Operating Characteristic (ROC) procedure applied to 1-min epochs (n = 92,543 waist; n = 30,653 wrist).
resultsThe optimal algorithm parameter values for block length were 60 and 45 min, thresholds 12.5 and 400 counts/min, bedrest-start trigger 120 and 400 counts/min, and bedrest-end trigger 1,200 and 1,500 counts/min, for the waist and wrist-worn accelerometers, respectively. Bedrest was identified correctly in the validation group with sensitivities of 0.819 and 0.912, specificities of 0.966 and 0.923, and accuracies of 0.755 and 0.859 by the waist and wrist-worn accelerometer, respectively. The DT algorithm identified bedrest/sleep with greater accuracy than a commonly used automated algorithm (Cole-Kripke) for wrist-worn accelerometers (p<0.001).
conclusionsThe adapted DT accurately identifies bedrest in data from accelerometers worn by adults on either the wrist or waist. The automated bedrest/sleep detection DT algorithm for both youth and adults is openly accessible as a package "PhysActBedRest" for the R-computer language.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.