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Record W3009361405 · doi:10.1186/s12966-020-00938-3

A comparison of self-reported and device measured sedentary behaviour in adults: a systematic review and meta-analysis

2020· review· en· W3009361405 on OpenAlexafffund
Stéphanie A. Prince, Luca Cardilli, Jennifer L. Reed, Travis J. Saunders, Chris Kite, Kevin Douillette, Karine Fournier, John Buckley

Bibliographic record

VenueInternational Journal of Behavioral Nutrition and Physical Activity · 2020
Typereview
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsUniversity of Prince Edward IslandPublic Health Agency of CanadaUniversity of Ottawa
FundersCanadian Institutes of Health ResearchPublic Health AgencyPublic Health Agency of Canada
KeywordsMeta-analysisMedicineSelf-report studySystematic reviewReliability (semiconductor)Physical therapyMEDLINEDemographyClinical psychologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Sedentary behaviour (SB) is a risk factor for chronic disease and premature mortality. While many individual studies have examined the reliability and validity of various self-report measures for assessing SB, it is not clear, in general, how self-reported SB (e.g., questionnaires, logs, ecological momentary assessments (EMAs)) compares to device measures (e.g., accelerometers, inclinometers). OBJECTIVE: The primary objective of this systematic review was to compare self-report versus device measures of SB in adults. METHODS: Six bibliographic databases were searched to identify all studies which included a comparable self-report and device measure of SB in adults. Risk of bias within and across studies was assessed. Results were synthesized using meta-analyses. RESULTS: The review included 185 unique studies. A total of 123 studies comprising 173 comparisons and data from 55,199 participants were used to examine general criterion validity. The average mean difference was -105.19 minutes/day (95% CI: -127.21, -83.17); self-report underestimated sedentary time by ~1.74 hours/day compared to device measures. Self-reported time spent sedentary at work was ~40 minutes higher than when assessed by devices. Single item measures performed more poorly than multi-item questionnaires, EMAs and logs/diaries. On average, when compared to inclinometers, multi-item questionnaires, EMAs and logs/diaries were not significantly different, but had substantial amount of variability (up to 6 hours/day within individual studies) with approximately half over-reporting and half under-reporting. A total of 54 studies provided an assessment of reliability of a self-report measure, on average the reliability was good (ICC = 0.66). CONCLUSIONS: Evidence from this review suggests that single-item self-report measures generally underestimate sedentary time when compared to device measures. For accuracy, multi-item questionnaires, EMAs and logs/diaries with a shorter recall period should be encouraged above single item questions and longer recall periods if sedentary time is a primary outcome of study. Users should also be aware of the high degree of variability between and within tools. Studies should exert caution when comparing associations between different self-report and device measures with health outcomes. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42019118755.

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)0.015
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.023
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.041
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0230.034
Bibliometrics0.0100.010
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.221
GPT teacher head0.482
Teacher spread0.261 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations513
Published2020
Admission routes2
Has abstractyes

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