Perceived control moderates the internalized stigma model of seeking mental health services in distressed older adults.
Bibliographic record
Abstract
Older adults are especially unlikely to seek mental health services, and internalized stigma is a key reason why. However, little research has investigated which older adults are particularly likely to have stigma influence help-seeking. To address this, we tested whether perceived control (PC) moderates an internalized stigma model in which public stigma is internalized as self-stigma, which negatively predicts help-seeking attitudes and help-seeking intentions. We employed moderated mediation analysis of cross-sectional, secondary data from 348 psychologically distressed Canadian adults aged 65 years and older. Participants completed an online survey that included measures of public stigma of help-seeking, self-stigma of help-seeking, help-seeking attitudes, conditional help-seeking intentions, psychological distress, and PC. PC emerged as a moderator of the internalized stigma model. Those lower in PC were more likely to have public stigma negatively predict help-seeking intentions through the serial mediation of (a) self-stigma and (b) help-seeking attitudes. Further, those lower in PC were more likely to have public stigma internalized as self-stigma and more likely to have negative help-seeking attitudes predict lower help-seeking intentions. Finally, those lower in PC also had lower help-seeking intentions in the face of low levels of self-stigma. These results contribute to a nuanced understanding of which older adults are unlikely to seek help. Identifying PC as a moderator of the internalized stigma model suggests that interventions that enhance PC should protect against public stigma's internalization and improve help-seeking behaviors for older adults who need such help. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".