MétaCan
Menu
Back to cohort
Record W2911834817

ENHANCING EMPLOYEES’ HEALTH AND WELLBEING: DEVELOPING A SUCCESSFUL HOLISTIC WELLNESS CHALLENGE

2019· article· en· W2911834817 on OpenAlexaboutno aff
T. Andrews, Ginny Crosby, Rebecca Carrigan, Casey Fewell, Sandy Ly, Monique Papworth, Katelynne Santos, Asha Timilsina, Tam Truong Donnelly

Bibliographic record

VenueInternational journal of nursing · 2019
Typearticle
Languageen
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsnot available
Fundersnot available
KeywordsHealth promotionWorkplace health promotionWork (physics)Mental healthPromotion (chess)NursingPublic relationsPsychologyMedical educationMedicinePublic healthPolitical scienceEngineering
DOInot available

Abstract

fetched live from OpenAlex

Improving the overall health and wellness of employees is an important focus of many organizations. Healthy employees experience more job satisfaction and productivity. The University of Calgary offers programs and services that promote healthy living, a healthy work environment, and respect the employees’ lives outside of work as well as their work life. Collaborating with the university’s WellBeing and Work Life department, the purpose of our community health promotion project was to develop and provide recommendations for the implementation of a successful holistic wellness challenge for faculty and staff. Drawing on the Population Health Promotion Model, the Community as Partner model, and the nursing process, a windshield survey, key informant interviews, a focused review of literature, and an environmental scan of 15 Canadian universities (U15) and Vanderbilt University (well-known for its excellent occupational health program).  The information gained was used to create then pilot a holistic evidence-based challenge that aims to improve employees’ physical activity, exercise, mental health, social health, financial health, and nutrition. To increase community members’ awareness and participation in the wellness challenge, we developed brochures detail the health benefits to be gained and offer suggestions for implementing each component. Because our evidence-based recommendations are feasible and flexible with clear marketing strategies, they are more likely to be adopted by organizations and their employees.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.323
Threshold uncertainty score0.673

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.055
GPT teacher head0.437
Teacher spread0.382 · 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 teacher head, 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

Citations1
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueInternational journal of nursingSame topicWorkplace Health and Well-beingFrench-language works237,207