Assessing stressor exposure, chemsex use, and adjustment disorder in a sample of men who have sex with men
Bibliographic record
Abstract
Background: Evidence suggests that men who have sex with men (MSM) experience heightened risk for stressor-related mental health issues. This may be exacerbated among those who engage in chemsex; recreational substance use during sex. Valid assessment of adjustment difficulties, and risk factors associated with these, is needed to better understand these wellbeing risks. The present study aimed to validate a novel screening tool for Adjustment Disorder (AjD) in this population.Method: A sample of MSM (N = 503) completed an online survey of stressful life experiences. Among those who reported exposure to a stressor (n = 376), the factorial structure of the International Adjustment Disorder Questionnaire (IADQ) was assessed using Confirmatory Factor Analysis. Probable diagnostic status was assessed using established criteria. Associations with stressor exposure and chemsex participation were examined using between-group comparisons.Results: A unidimensional model representing a single latent AjD factor best fit these data. AjD symptomatology was commonly reported, with screening results indicating that 36.44% of participants met criteria for a probable AjD diagnosis. Small effect sizes were found for associations between positive AjD screening status, chemsex participation, and a range of stressors including problems related to health, relationships, finances, work, and housing. A medium effect size was found for the association between multiple stressor exposure and probable AjD diagnosis.Conclusions: Findings support the use of the IADQ as a brief and valid measure of AjD among men who have sex with men. Various stressful life experiences and chemsex participation may constitute risk factors for AjD, with exposure to multiple stressor types representing a particularly salient risk factor. Screening for stressful life experiences, chemsex practice, and AjD may identify those at risk for adverse health and wellbeing outcomes in this population.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".