How does family face relate to intention to seek therapist-guided and digital self-guided psychological interventions? mediating effects of interdependent stigma and help-seeking attitudes
Bibliographic record
Abstract
PURPOSE: The present study aimed to investigate the association between family face concern and help-seeking intention for therapist-guided and digital self-guided psychological interventions in four cultures, with possible mediation of interdependent stigma of help-seeking and attitudes towards seeking help. METHODS: Using online questionnaires, six-hundred and forty-five responses (Mean age = 21.25, SD = 4.65; 70% women) were collected from college students in four regions, including Canada (n = 172), United Kingdom (n = 158), India (n = 160), and Hong Kong (n = 155). Levels of family face concern (adapted from the Face Concern Scale), interdependent stigma of help-seeking (Interdependent Stigma of Seeking Help Scale), attitudes towards therapist-guided and digital self-guided psychological intervention (adapted Face-to-Face Counselling Attitude Scale), intention to seek these interventions (items adapted to measure intention to seek help), and depressive symptoms (Patient Health Questionnaire-9) were assessed. RESULTS: Using R (version 4.4.1) to conduct the path analysis, results showed that after controlling for depressive symptoms, family face concern was negatively associated with the intention to seek therapist-guided psychological intervention through the perception of higher social stigma on family members and negative attitudes towards the intervention. However, such a mediating effect was not significant for the intention to seek digital self-guided psychological intervention. CONCLUSIONS: The present study highlighted the potential negative influence of family face concern on one's intention to seek psychological help. It also highlighted that digital self-guided psychological intervention may be less subject to the influence of family face concern and stigma.
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 | 0.013 |
| 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) | 0.002 | 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".