Psychological need satisfaction across work and personal life: an empirical test of a comprehensive typology
Bibliographic record
Abstract
Introduction A comprehensive typology of the satisfaction of psychological needs at work and in personal life was developed and tested. The typology proposes five scenarios (Enriched, Middling, Impoverished, Work-Fulfilled, and Personal Life-Fulfilled) accounting for various profiles of employees showing distinct configurations of global and specific levels of need satisfaction at work and in personal life. Methods The scenarios were tested in a sample of 1,024 employees. Results Using latent profile analysis, five profiles were identified that were consistent with four or the five scenarios, either aligned (Globally Satisfied, Globally Unsatisfied) or misaligned (Globally Satisfied at Work with High Relatedness, Globally Satisfied in Personal Life with High Autonomy, and Globally Satisfied in Personal Life with Low Autonomy) across domains. No profile corresponding to the Middling scenario was observed. Discussion The results indicate that perceived job and individual characteristics predicted membership in distinct profiles. More importantly, unlike the profile Globally Unsatisfied, the profile Globally Satisfied contributed substantially to higher well-being (vitality and lower psychological distress), and to more favorable job attitudes (job satisfaction and lower turnover intentions) and behaviors (self-rated job performance and lower absenteeism, presenteeism, and work injuries). Furthermore, two of the misaligned profiles were also substantially associated with highly desirable outcome levels.
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 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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".