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Record W4310359339 · doi:10.21203/rs.3.rs-2303406/v1

Mental Illness Stigma and Microaggressions: An Experimental Study of Familiarity and Relationship Quality

2022· preprint· en· W4310359339 on OpenAlexaff
Arianna M. Gibson, Brittany L. Lindsay, Andrew C. H. Szeto

Bibliographic record

VenueResearch Square · 2022
Typepreprint
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPsychologyVignetteClosenessSocial psychologyStigma (botany)Mental illnessTraitClinical psychologyDevelopmental psychologyMental healthPsychotherapistPsychiatry

Abstract

fetched live from OpenAlex

Abstract Purpose: Familiarity (i.e., relationship closeness) and relationship quality (i.e., the degree of negativity/positivity) have been suggested as critical components affecting stigmatizing attitudes towards those with mental illnesses. The current study experimentally tested components of, and expanded upon, a recent theoretical framework by Corrigan and Nieweglowski (2019), which proposes a convex (u-shaped) curvilinear relationship between familiarity and stigma (i.e., people hold the most stigma towards others at the lowest andhighest levels of familiarity) rather than a linear one (i.e., stigma simply decreases as familiarity increases). By examining how both familiarity and relationship quality affect public stigma broadly, as well as microaggressions specifically, this research adds to the growing body of literature on mental illness stigma. Methods: Undergraduate students (N = 242) were randomly assigned to read one of six vignettes via a 2(quality: positive vs. negative) x 3(familiarity: co-worker, cousin, romantic partner) between-subjects factorial design. Following, participants completed measures assessing stigmatizing attitudes and microaggression endorsement towards the vignette character. Results: There was a significant main effect of relationship quality on stigmatizing attitudes only; on average, those in the three negative conditions had significantly higher stigmatizing attitudes than those in the positive conditions. Conversely, familiarity only had a significant main effect on microaggressions, wherein higher familiarity groups demonstrated higher microaggression endorsement. No significant interactions were found for either variable. Conclusion: These results suggest that stigmatizing attitudes and microaggressions may be functionally different, and further research is required to clarify current theoretical frameworks in understanding how relational contexts impact these negative attitudes.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.307
GPT teacher head0.586
Teacher spread0.279 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2022
Admission routes1
Has abstractyes

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