Effect of a participative action intervention program on reducing mental retirement
Bibliographic record
Abstract
BACKGROUND: The present study aimed to investigate the effects of a stepwise, bottom-up participatory program with a tailor-made intervention process addressing the level of mental retirement in a sample of Dutch employees. Mental retirement refers to feelings of being disconnected from your work and your organization. Prevention of mental retirement is important since sustainable employability is becoming more important in today's society due to the ageing of the working population and the changes in skills demands. METHODS: This prospective cohort study with a one-year follow-up employs a sample of 683 employees of three organizations in The Netherlands, who filled out two questionnaires: at baseline and 1 year later. The dependent measure was mental retirement, which consists of three sub-concepts: developmental pro-activity, work engagement and perceived appreciation. RESULTS: Multilevel analysis (N = 466) showed that employees who more actively participated in the intervention(s) had a small but statistically significant larger decrease in mental retirement at follow-up. CONCLUSIONS: The stepwise, bottom-up participatory program with a tailor-made intervention process shows a tendency to decrease the level of mental retirement in Dutch employees. However, the implementation of interventions could be further improved since it turned out to be very challenging to keep up participants' commitment to the program. Future research should study the effectiveness of this program further with an improved study design (control group, multiple follow-ups, several data sources).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".