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Record W2157032834 · doi:10.12927/hcpap..16822

Workplace Prevention and Promotion Strategies

2004· article· en· W2157032834 on OpenAlexaffvenueabout
Michel Vézina, Renée Bourbonnais, Chantal Brisson, Louis Trudel

Bibliographic record

VenueA Nudge Too Far? A Nudge at All? On Paying People to Be Healthy · 2004
Typearticle
Languageen
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsInstitut universitaire en santé mentale de MontréalUniversité LavalInstitut National de Santé Publique du Québec
Fundersnot available
KeywordsPsychosocialPsychologyPsychological interventionSocial supportIntervention (counseling)Applied psychologyHealth promotionPromotion (chess)Interpersonal communicationPublic healthMedicineNursingSocial psychologyPsychiatryPolitical science

Abstract

fetched live from OpenAlex

Psychosocial factors refer to all organizational factors and interpersonal relationships in the workplace that may affect the health of the workers. Currently, two psychosocial risk models are universally recognized for producing solid scientific knowledge regarding the vital link between social or psychological phenomena at work and the development of several diseases, such as cardiovascular diseases or depression. The first is the "job demand-contro-support" model, which was defined by Karasek and to which the concept of social support has been added; the second is the "effort/reward imbalance" model defined by Siegrist. The public health perspective calls for theoretical models based on certain psychosocial attributes of the work environment for which there is empirical evidence of their pathogenic potential for exposed workers. Not only do these models reduce the complexity of the psychosocial reality of the work to components that are significant in terms of health risks, but they also facilitate the development and implementation of workplace interventions. Psychosocial risk intervention strategies currently implemented by companies are predominantly individual-oriented and aim chiefly at reducing the effects of stressful work situations by improving individual ability to adapt to the situation and manage stress. Like personal protection equipment for exposure to physical or chemical risks, these secondary prevention measures are commendable but insufficient, because they aim to reduce only the symptoms and not the cause of problems. Any intervention program for these risks should necessarily include a primary prevention component with a view to eliminating, or at least reducing, the psychosocial pathogenic agents in the workplace. Several authors have suggested that well-structured organizational approaches are most effective and should generate more important, longer-lasting effects than individual approaches. However, the evidence should be strengthened by more systematic studies to assess the models, their implementation and the outcomes for employers and employees alike. The research agenda on mental health and the workplace should have the following goals; to foster the development and evaluation of well-adapted models of interventions designed to reduce adverse psychosocial factors and their mental health effects to give a better understanding of the prevalence of work organization risk factors in Canada, how they may be changing and how they affect mental health in the long term to acquire an understanding of the effects on mental health of prominent trends in organizational practices, such as restructuring, lean production and flexible staffing (all of which result in precarious employment), that may pose special risks for women, immigrants or aging workers in Canada to collect data on the considerable direct and indirect costs to business, workers and society of work-related stress in Canada.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.264
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.055
GPT teacher head0.394
Teacher spread0.340 · 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
GenreCommentary

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

Citations69
Published2004
Admission routes3
Has abstractyes

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