Reduced Emotional Awareness and Distress Concealment: A Pathway to Loneliness for Young Men Seeking Mental Health Care
Bibliographic record
Abstract
Background: Loneliness, the painful affective state that reflects perceived deficits in social relationships, is a significant health issue requiring further understanding. Individual differences in awareness and disclosure of emotional concerns may contribute to loneliness, and may do so diversely according to gender and age. The present study examined a hypothesized mediation pathway from emotional awareness abilities to loneliness through distress concealment, with moderation by gender and age, in a sample of adults attending outpatient mental health services. Methods: In a cross-sectional study design, 244 patients attending Canadian community mental health clinics completed study assessments at the commencement of care. Conditional process modeling examined interactions between gender and age and both emotional awareness and distress concealment in mediation models predicting loneliness. Results: A significant three-way interaction between gender, age, and distress concealment was observed, along with significant conditional moderated mediation. The indirect effect of emotional awareness on loneliness through the mediating effect of distress concealment was significant for young- and mid-adulthood men, but not for women or older men. Limitations: The study was limited by exclusive use of self-report assessment, and cross-sectional design precluding representation of causal sequencing over time. Conclusion: Findings suggest the pathway to loneliness from reduced emotional awareness through distress concealment to be particularly salient for younger men. Thus, intervention targeting restricted awareness and disclosure of emotional concerns should be considered in helping young men to address the pain of loneliness.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".