Observational studyJMIR mHealth and uHealth2025
Comparison of ActiGraph CentrePoint Insight Watch Placement on Dominant and Nondominant Wrists in Young Adults in Free-Living Conditions: Observational Validation Study.
Observational study in JMIR mHealth and uHealth, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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.
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Who cites it
2 citing papers in PubMed.
- Association between 24-h activity patterns and inhibitory control in community-dwelling older adults: a cross-sectional study based on chronic disease status.Frontiers in public health · 2026Article
- Evening preference with evening-type rest-activity rhythm: a risk for poor quality of life.Health and quality of life outcomes · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: With the continuous evolution of technology, wearable accelerometers have become one of the most popular means of measuring daily physical activity (PA) levels. Despite the conventional use of the nondominant wrist as a device placement in numerous PA studies, the impact of wrist-worn accelerometer placement on PA data outcomes remains uncertain. Objective: This study aimed to examine the degree of agreement between accelerometry data collected from CentrePoint Insight Watches (CPIWs; ActiGraph) worn on the dominant and nondominant wrists of young adults in free-living conditions. Methods: Twenty-nine participants (mean age 20.2, SD 1.6 years; 23 females) simultaneously wore an ActiGraph CPIW on both dominant and nondominant wrists for 7 consecutive days during waking hours. A sampling frequency of 32 Hz and Montoye 2020 cut-points were used to categorize activity intensity based on counts per minute. Data validity criteria included (1) ≥600 minutes per day of monitor wear time for both wrists, (2) a daily wear time difference of <1% of the average wear time between the dominant and nondominant wrists, and (3) a minimum of 3 valid days of monitor wear for both wrists. Bland-Altman plots and intraclass correlation coefficient (ICC) analyses were performed to compare the accelerometry data between the two device placements. Results: Average daily monitor wear time was 789.6 (SD 86.1) minutes per day for the dominant wrist and 793.0 (SD 91.8) minutes per day for the nondominant wrist. All accelerometer variables, including sedentary time (ST), light PA, moderate-to-vigorous PA (MVPA), steps, triaxial counts, and vector magnitude (VM), showed good-to-excellent levels of reliability between the two measurements (ICC >0.88 for all; P<.001). Bland-Altman analysis calculated mean bias and SD between the two device placements as follows: ST (-18.8, SD 27.6 min/d), light PA (2.7, SD 15.9 min/d), MVPA (12.7, SD 26.7 min/d), steps (218.1, SD 476.6 counts/d), x-axis (99.4, SD 188.8 counts/min), y-axis (73.9, SD 147.0 counts/min), z-axis (107.6, SD 183.5 counts/min), and VM (161.2, SD 273.4 counts/min). Bland-Altman plots revealed that the upper and lower limits of agreement across most variables were considerably wide. Conclusions: Our findings partially align with previous research, demonstrating higher MVPA and step counts on the dominant wrist, while the nondominant wrist produced a higher level of ST. Despite the acceptable level of reliability between the two placements based on ICC analyses, the dominant wrist tended to produce greater outcomes as the intensity of PA increased, highlighting the need for careful consideration when determining the wear location of CPIWs and interpreting data outcomes.
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