Mental Health and Career Intentions Among Young Adults
Bibliographic record
Abstract
Poor mental health has been shown to influence career-related behaviours and outcomes; however, limited research has examined how young adults’ mental health is related to their career intentions. Guided by the Conservation of Resources theory, this study examined how loneliness and psychological distress relate to career aspirations and motivations to lead, and whether recovery moderates these relationships. Additionally, this study investigated whether loneliness and distress are related to intentions to pursue public sector work (e.g., military service), an area that remains underexplored in vocational research. Participants included 256 university students who completed an online survey. Results suggested that lower loneliness was associated with higher career aspirations, while psychological distress had no significant relationship with career aspirations. Results also suggested that neither loneliness nor psychological distress had a significant relationship with motivation to lead. Exploratory data analyses revealed that neither loneliness nor distress was related to public service motivation. Unexpectedly, the moderation analyses showed that recovery amplified the effects of loneliness and distress on career aspirations, as well as the relationship between loneliness and motivation to lead. These findings underscore the importance of examining how mental health can shape young adults’ career intentions and suggest that recovery may play a nuanced role in this process.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".