They just don’t get it: a qualitative study on perceptions of anticipated self-injury stigma across generations
Bibliographic record
Abstract
BACKGROUND: Non-suicidal self-injury (NSSI) is a common and serious mental health concern among young adults. It is also highly stigmatised, which can impede disclosure and recovery. To advance the literature on NSSI stigma, we explored what young adults who self-injure believe different age-groups (i.e., young adults, parents, middle-aged, and older adults) think about NSSI and people who self-injure. METHOD: Participants (n = 187) with a mean age of 19.07 (SD = 1.52) took part in an online survey and answered open-ended questions about the above beliefs. Responses were examined via reflexive thematic analysis. RESULTS: Findings yielded three primary themes namely: They Just Don't Get It, Ignorance is Bliss, and Willing to Lend a Helping Hand. Overall, our results indicate that all age-groups asked about are believed to harbour stigmatising views (e.g., NSSI is selfish and attention-seeking, people who self-injure are weak and crazy). Perceptions regarding the prominence of these beliefs, however, varied across age-groups. CONCLUSION: Expectancy beliefs and differences in anticipated stigma across age groups may stem from prior experiences with others and may play a role in disclosure. The present findings thus have implications for research, anti-stigma initiatives, and supportive practices.
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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 | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".