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Record W2810159300 · doi:10.2196/formative.9343

Assessing the Feasibility and Pre-Post Impact Evaluation of the Beta (Test) Version of the BeUpstanding Champion Toolkit in Reducing Workplace Sitting: Pilot Study

2018· article· en· W2810159300 on OpenAlexvenueno aff
Geneviève N. Healy, Elizabeth Eakin, Elisabeth Winkler, Nyssa Hadgraft, David W. Dunstan, Nicholas D. Gilson, Ana D. Goode

Bibliographic record

VenueJMIR Formative Research · 2018
Typearticle
Languageen
FieldPsychology
TopicFacilities and Workplace Management
Canadian institutionsnot available
Fundersnot available
KeywordsChampionDeskTest (biology)SittingMedical educationWork (physics)PsychologyMedicineEngineeringPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: The Web-based, evidence-informed BeUpstanding Champion Toolkit was developed to provide employers (via a "train-the-champion approach") with resources and support to help in reducing prolonged sitting in their own desk-based workplace. As part of a five-phase research-to-dissemination process, this study reports on the evaluation of the beta (test) version of this toolkit (Phase 2). OBJECTIVE: The objective of our study was to evaluate (1) the implementation of the toolkit by workplace champions and (2) the impact of the toolkit on sitting (primary outcome), standing, and moving; use of activity-promoting strategies; knowledge and attitudes; and indicators of health and work performance. METHODS: An implementation study using a pre-post design was conducted in 7 desk-based workplaces in Australia (September 2015 to May 2016), with work teams (one per workplace) purposively recruited to ensure representation across a range of sectors (white- or blue-collar), organizational sizes (small or medium or large), and locations (metropolitan or regional). All staff within participating teams were invited to participate in the relevant toolkit activities. Implementation outcomes (time commitment required by champions and toolkit activities completed) were collected from each champion via telephone interviews. Changes in impact outcomes, measured via a Web-based questionnaire completed by employees at baseline and 3 months postimplementation, were assessed using mixed models, correcting for clustering. RESULTS: Champions reported a 30-60 minutes per week time commitment to the toolkit activities. All teams formed a wellbeing committee and sent the staff surveys at both time points; most champions held a staff consultation workshop (6/7), identified team-level strategies within that workshop (5/7), used the communication resources provided within the toolkit (emails, posters; 6/7), and completed the action plan (5/7). In total, 52% (315 of ≈600) employees participated in at least one survey and 97 (16%) participated in both. At follow-up, there was a significant (P<.05) reduction in self-reported workplace sitting time compared to baseline (-6.3%, 95% CI -10.1 to -2.5; n=85) equating to ≈30 minutes per workday. Significant benefits were also observed for the use of activity-promoting strategies, with small, nonsignificant changes observed for knowledge and attitudes and indicators of health and work performance. CONCLUSIONS: The beta version of the BeUpstanding Champion Toolkit was feasible to implement and effective in reducing self-reported workplace sitting across a broad range of desk-based workplaces. The next phase (Phase 3) will build on these findings to optimize the toolkit for wider-scale implementation and longer term evaluation.

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)0.021
metaresearch head score (Gemma)0.035
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.035
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.179
GPT teacher head0.498
Teacher spread0.319 · 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

Citations23
Published2018
Admission routes1
Has abstractyes

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