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Record W2968433830 · doi:10.1186/s12889-019-7393-x

Activate Your Health, a 3-year, multi-site, workplace healthy lifestyle promotion program: study design

2019· article· en· W2968433830 on OpenAlexafffund
Thiffya Arabi Kugathasan, François Lecot, Suzanne Laberge, Jonathan Tremblay, Marie-Eve Mathieu

Bibliographic record

VenueBMC Public Health · 2019
Typearticle
Languageen
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineUniversité de Montréal
FundersUniversité de MontréalPublic Health Agency of Canada
KeywordsMedicineHealth promotionPsychological interventionReturn on investmentCoachingPublic healthHealth careNursingEnvironmental healthGerontologyPsychologyProfit (economics)

Abstract

fetched live from OpenAlex

BACKGROUND: Workplace Health Promotion Programs (WHPP) have been shown to be an efficient way of improving workers' health. These programs can be incorporated in the worker's daily schedule and improve their productivity at work. Improving employees' health also benefits the employers by increasing their return on investment and lowering healthcare costs. The Activate Your Health program, created by Capsana in 2015, is a WHPP targeting multiple lifestyle habits for a three-year period. This WHPP includes tailored web-based interventions and the support of different health professionals throughout the years. We hypothesize that this approach will yield long-term lifestyle changes. The objective of the current paper is to describe the Activate Your Health program's design. METHODS/DESIGN: Eleven companies are taking part in this WHPP and had to choose among five different options of this program and all their employees were encouraged to participate. Each option differs by the number and type of interventions included. The limited option, which is considered the control group, only consists in completing a questionnaire regarding their health status, lifestyle habits and behaviors. On the other end, the extensive option receives a combination of multiple interventions: online menus, health challenges, support in creating a healthy work environment, coaching by health professionals (nurse, nutritionist, and kinesiologist), health screening and flexibility assessment, online resources, social health platform, and activity tracking. The remaining options are in between these options and vary by the amount of intervention. Baseline data are already gathered; two other data collection periods will take place after one and 2 years into the program. The primary outcomes of the current program are physical activity and fitness measures, nutritional data, smoking habits, stress and intention to change. DISCUSSION: The Activate Your Health program will allow us to compare which combinations of interventions are the most effective. It is expected that the extensive option will be the most advantageous to improve lifestyle habits. The results will indicate the strength and weakness of each intervention and how it could be improved. TRIAL REGISTRATION: Clinicaltrails.gov, registration number: NCT02933385 (updated on the 26th of March 2019, initially registered on the 5th of October 2016).

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)0.009
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.003
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.002
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0030.003
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0080.002

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 head0.142
GPT teacher head0.442
Teacher spread0.300 · 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 designNot applicable
Domainnot available
GenreProtocol

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

Citations7
Published2019
Admission routes2
Has abstractyes

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