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Record W3024815728 · doi:10.1108/ijwhm-05-2019-0079

Anatomy of an effective workplace health intervention: a comprehensive new model

2020· article· en· W3024815728 on OpenAlexaff
Sean Hennessey, Laurene Rehman

Bibliographic record

VenueInternational Journal of Workplace Health Management · 2020
Typearticle
Languageen
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPsychological interventionIntervention (counseling)Applied psychologyPsychologyFacilitationMedical educationQualitative researchHealth promotionProcess (computing)OriginalityNursingMedicineComputer scienceSocial psychologyPublic healthSociology

Abstract

fetched live from OpenAlex

Purpose This study proposes a new model, called the Integrated Human Health Model (IHHM), to improve the design and effectiveness of Workplace Health Promotion (WHP) interventions. Design/methodology/approach Eighteen participants were purposefully selected from 44 participants in a 2.5-day WHP intervention targeting multiple health behaviours (MHB). The intervention has shown to improve quality of life and health-related behaviours in rigorous studies. Qualitative data collection methods were observations, repeat semi-structured interviews and weekly e-journals collected over three months. Template analysis was used to develop the IHHM describing participants' experiences. Findings The IHHM describes the health behaviour change process using eight themes: facilitation, assessment, desired life, barriers, knowledge and skills, insights, action planning, and monitor and support. Practical implications With the paucity of evidence informing WHP intervention effectiveness, this study provides a preliminary model serving practitioners to design more effective interventions and scholars to improve evidence. Originality/value This study proposes a practical comprehensive model for practitioners and leaders to more effectively design and evaluate successful MHB WHP interventions compared to existing models.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.755
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
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 head0.039
GPT teacher head0.432
Teacher spread0.393 · 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.

Study designNot applicable
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
Published2020
Admission routes1
Has abstractyes

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