ArticlePloS one2018
The number of repeated observations needed to estimate the habitual physical activity of an individual to a given level of precision.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06169020 (Design of an Intelligent Wearable to Assess Physical Activity and Health Related Outcomes - the DIWAH Study), which is not on this map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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.
Design of an Intelligent Wearable to Assess Physical Activity and Health Related Outcomes - the DIWAH Study
Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Objectively measuring the association between the built environment and physical activity: a systematic review and reporting framework.The international journal of behavioral nutrition and physical activity · 2022Pooled it
- Trial
- Development of a proposed guide to identify, screen and appraise self-report and device-based measures of habitual physical activity in systematic reviews: a methodological protocol.Discover public health · 2026Article
- Absolute and relative physical activity intensity thresholds across diverse fitness levels: a cross-sectional study in middle-aged women.Frontiers in sports and active living · 2026Article
- Passive Measures of Physical Activity and Cadence as Early Indicators of Cognitive Impairment: Observational Study.Journal of medical Internet research · 2025Observational
- Fitness-related physical activity intensity explains most of the association between accelerometer data and cardiometabolic health in persons 50-64 years old.British journal of sports medicine · 2024Article
- Determining critical monitoring periods for accurate wearable step counts in patients with degenerative spine disorders.Scientific reports · 2024Article
- Supporting Behavior Change in Sedentary Adults via Real-time Multidimensional Physical Activity Feedback: Mixed Methods Randomized Controlled Trial.JMIR formative research · 2022Article
- The interrelationship between physical activity intensity, cardiorespiratory fitness, and executive function in middle-aged adults: An observational study of office workers.Frontiers in public health · 2022Observational
- Repeatability of gaseous measurements across consecutive days in sheep using portable accumulation chambers.Journal of animal science · 2021Article
- Characterisation of Temporal Patterns in Step Count Behaviour from Smartphone App Data: An Unsupervised Machine Learning Approach.International journal of environmental research and public health · 2021Article
- Test-retest reliability of physical activity questionnaires in Parkinson's disease.BMC neurology · 2021Article
- Utility of wearable physical activity monitors in cardiovascular disease: a systematic review of 11 464 patients and recommendations for optimal use.European heart journal. Digital health · 2021Review
- Influence of the Duration and Timing of Data Collection on Accelerometer-Measured Physical Activity, Sedentary Time and Associated Insulin Resistance.International journal of environmental research and public health · 2021Article
- No one accelerometer-based physical activity data collection protocol can fit all research questions.BMC medical research methodology · 2020Article
- Stronger Association between High Intensity Physical Activity and Cardiometabolic Health with Improved Assessment of the Full Intensity Range Using Accelerometry.Sensors (Basel, Switzerland) · 2020Article
- Time Series Visualizations of Mobile Phone-Based Daily Diary Reports of Stress, Physical Activity, and Diet Quality in Mostly Ethnic Minority Mothers: Feasibility Study.JMIR formative research · 2018Article
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Physical activity behavior varies naturally from day to day, from week to week and even across seasons. In order to assess the habitual level of physical activity of a person, the person must be monitored for long enough so that the level can be identified, taking into account this natural within-person variation. An important question, and one whose answer has implications for study- and survey design, epidemiological research and population surveillance, is, for how long does an individual need to be monitored before such a habitual level or pattern can be identified to a desired level of precision? The aim of this study was to estimate the number of repeated observations needed to identify the habitual physical activity behaviour of an individual to a given degree of precision. A convenience sample of 50 Swedish adults wore accelerometers during four consecutive weeks. The number of days needed to come within 5-50% of an individual's usual physical activity 95% of the time was calculated. To get an idea of the uncertainty of the estimates all statistical estimates were bootstrapped 2000 times. The mean number of days of measurement needed for the observation to, with 95% confidence, be within 20% of the habitual physical activity of an individual is highest for vigorous physical activity, for which 182 days are needed. For sedentary behaviour the equivalent number of days is 2.4. To capture 80% of the sample to within ±20% of their habitual level of physical activity, 3.4 days is needed if sedentary behavior is the outcome of interest, and 34.8 days for MVPA. The present study shows that for analyses requiring accurate data at the individual level a longer measurement collection period than the traditional 7-day protocol should be used. In addition, the amount of MVPA was negatively associated with the number of days required to identify the habitual physical activity level indicating that the least active are also those whose habitual physical activity level is the most difficult to identify. These results could have important implications for researchers whose aim is to analyse data on an individual level. Before recommendations regarding an appropriate monitoring protocol are updated, the present study should be replicated in different populations.
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