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Record W4409125771 · doi:10.1186/s12888-025-06718-2

They just don’t get it: a qualitative study on perceptions of anticipated self-injury stigma across generations

2025· article· en· W4409125771 on OpenAlexafffund
Stephen P. Lewis, Gabrielle A Lucchese-Lavecchia, Nancy L. Heath, Rob Whitley

Bibliographic record

VenueBMC Psychiatry · 2025
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsMcGill UniversityYork UniversityUniversity of Guelph
FundersSocial Sciences and Humanities Research CouncilSocial Sciences and Humanities Research Council of Canada
KeywordsStigma (botany)Qualitative researchPsychologyPerceptionPsychiatryClinical psychologySocial psychologySociology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.147
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.072
GPT teacher head0.456
Teacher spread0.384 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2025
Admission routes2
Has abstractyes

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