Relationship between self-esteem and employment in people with severe mental illness: A systematic review and meta-analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Results from past research on the association between work outcomes and self-esteem were inconsistent. OBJECTIVE: This study aimed to review and quantify the correlation between employment variables and self-esteem in people with severe mental illness. METHOD: The first electronic database search was performed between November 5 and November 12, 2021. A second search update was completed in September 2023. Studies that reported a correlation between at least one employment-related variable and self-esteem were subsequently verified. Pooled effect sizes were calculated with random-effects models by aggregating Fisher’s Z-to-Pearson r transformed correlations. RESULTS: The database search generated 3,547 reports. Thirteen and seven reports were included in the qualitative review and the meta-analyses, respectively. Meta-analyses results based on data from 1,065 participants suggested a positive albeit small correlation between employment variables and self-esteem in people with severe mental illness (r = 0.26, p = .002 for global self-esteem; r = 0.21, p < 0.001 for total self-esteem). It was found through systematic review that greater confidence in personal capacity, more opportunities on novel activities, and positive affirmation from coworkers were some potential mechanisms underlying self-esteem improvement following work. CONCLUSION: Future research on employment in severe mental illness would benefit from including adapted self-esteem measures and can build on this work by examining the relationships between specific employment variables (e.g., job acquisition, job tenure) and self-esteem.
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.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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 it