Employers' perspective on workplace health promotion programs in British Columbia, Canada
Bibliographic record
Abstract
Introduction: In recent years, the incidence of many non-communicable diseases, along with their risk factors, has increased in Canada. The workplace represents a convenient setting to reach a large segment of the Canadian adult population with prevention and health promotion programs. Given the central role that employers play in providing these programs, it is important to explore their perspectives on important aspects of programming. Objectives: This study explores employers’ perspectives on factors affecting the implementation of workplace health promotion programs, along with their motivations for implementing such programs. This study also compares factors affecting the implementation and motivations for implementing the program between participants whose programs were identified as following promising practices relative to those programs which have not achieved these standards. Methods: Participants were recruited from attendees at the 2017 Extra Mile Awards event sponsored by the Canadian Cancer Society. Employers who have previously worked with the Society and offered a workplace health promotion program to their staff were invited to participate in this event. Qualitative data were collected using semi-structured individual interviews on topics related to the history and design of programs. Data were analyzed following the template analysis approach, using an iterative process to categorize data into matching patterns. Results: A total of 15 participants agreed to take part on this study (15/46). The factors affecting the program implementation fell into two major categories: strategic and tactical. Motivations were related to improving the employees’ health and taking advantage of the associated benefits of this improvement to the business. There were no differences between programs that followed promising practices relative to those that did not in terms of factors affecting the implementation nor in the motivations for offering the program. Conclusions: The results of this study corroborated those found in previous literature on promising factors affecting workplace health promotion program implementation. Companies in BC are aware of the positive benefits that these programs have for both employees and businesses. However, there is a need for dissemination of information considered effective for workplace health promotion programs implementation and encouragement of the incorporation of this knowledge into practice.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.029 | 0.003 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".