A Longitudinal Investigation of the Changes in Work Motivation and Employees’ Psychological Health
Bibliographic record
Abstract
Organizations strive to motivate employees to thrive at work. However, employees’ motivation is likely to vary over a short period (e.g., a few months) to cope with the routine dynamics of organizations’ activities. These motivation dynamics covary with employees’ affective, cognitive, and behavioral outcomes in the workplace. Moreover, employees’ psychological health, a multidimensional concept focused on the individual’s well/ill-being simultaneously, changes over time. Using the integrated theoretical frameworks of self-determination theory (SDT) and the hierarchical model of self-determined motivation (H-SDT), this research sought to examine the motivational changes following the dual-path model. In particular, this work sought to unpack the temporal dynamics in employees’ subjective well/ill-beings predicted by the changes in basic needs satisfaction/frustration through autonomous/controlled motivation, while considering the characteristics of people’s general causality orientations (trait-level motivation). Over four months, longitudinal field data were collected from the employees in several private small businesses in the consumer product retail industry. Latent growth modeling (LGM) results supported the positive dual relations between the changes in employees’ psychological health and basic psychological needs satisfaction/frustration, but neither the changes of autonomous/controlled work motivation nor the indirect change paths via autonomous/controlled work motivation were significant. Finally, we discussed the theoretical and practical implications of the findings. Limitations and possible future research directions to further this line of research on the dynamic of work motivation were also summarized.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".