Real-time exposure to negative news media and suicidal ideation intensity among LGBTQ young adults in a high-stigma US state
Bibliographic record
Abstract
Abstract Background With a recent surge in anti-LGBTQ policies and associated news/media coverage worldwide, there is a crucial need to study the role of LGBTQ negative news/media on proximal risk for suicide among LGBTQ youth, especially in high-stigma contexts. Methods Using a smartphone-based protocol, participants responded to brief self-report surveys 3x per day for 28 consecutive days. LGBTQ young adults (ages 18-24 years old) residing in Tennessee with recent suicidal ideation were recruited. At each assessment, participants reported real-time exposure to negative news/media, whether the news/media was related to LGBTQ topics, expectations of anti-LGBTQ rejection, and current intensity of passive suicidal ideation, active suicidal ideation, and self-harm ideation. Statistical analyses employed multilevel path analyses with restricted maximum likelihood estimation. Results 31 participants completed 2189 assessments (90.5% median compliance). Within-person effects showed that real-time exposure to LGBTQ - but not general - negative news/media was positively associated with suicidal ideation intensity. Significant indirect effects were present from exposure to LGBTQ negative news/media to higher suicidal ideation intensity through expectations of rejection. Mediation through expectations of rejection accounted for 25% and 39% of the total effect for active and passive suicidal ideation, respectively. Conclusions Findings have important public health implications related to media reporting, policy, and clinical intervention. Interventions targeting media organizations should promote responsible reporting practices and increase awareness of the potential suicidogenic impact of negative LGBTQ news coverage. This study joins numerous others in documenting the potential mental health harms of policies that restrict LGBTQ visibility and rights. Mental health professionals play a vital role in promoting coping in the face of exposure to LGBTQ negative news/media content.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".