Needs and Expectations Associated With an e–Mental Health Intervention for Reducing Somatoform, Anxiety, and Depressive Symptoms in Sexual and Gender Minority Adults: Qualitative Participative Study
Bibliographic record
Abstract
BACKGROUND: Sexual and gender minority individuals experience heightened risks of mental health disorders due to marginalization, discrimination, and inadequacies in health care. OBJECTIVE: This study aims to identify the needs and expectations concerning an e-mental health intervention designed for people who are lesbian, gay, bisexual, transgender, queer or questioning, intersex, asexual, or have other sexual orientation and gender identities (LGBTQIA+) to reduce somatoform, anxiety and depressive (SAD) symptoms. METHODS: A qualitative participative study was conducted, involving semistructured interviews (face-to-face and online) with 10 sexual and gender minority individuals experiencing SAD symptoms. Telephone interviews were conducted with 10 health care professionals (HCPs). This study was part of a participatory project, emphasizing cooperation with the LGBTQIA+ community. Data were analyzed through a deductive-inductive content analysis to derive categories of needs and expectations relevant for the development of an e-mental health intervention. RESULTS: Participants expressed a strong desire for the intervention to be inclusive, validating, and sensitive to the unique challenges faced by LGBTQIA+ people. Key themes included the need for information on the relationship between being queer and mental health; representation through case stories; psychoeducation; and exercises tailored to address minority stress, identity affirmation, and coping strategies. HCPs emphasized the importance of addressing the coming-out process, managing rejection, fostering self-acceptance, and including content on minority stress and its impact on mental health. Results of both interview groups highlighted the need for direct interaction with therapists or peer support, including both synchronous and asynchronous elements (eg, video calls and chat) based on nonheteronormative, sensitive therapeutic support, for example, avoiding preassumptions, using sensitive language, and reflecting possible trigger points. CONCLUSIONS: This study underscores the need for e-mental health interventions tailored to a queer-sensitive and participatory approach. Interventions should incorporate comprehensive psychoeducation, interactive elements, content reflecting the lived experiences of LGBTQIA+ individuals with SAD symptoms, and the possibility to connect and exchange experiences with others facing similar challenges. Engaging with both LGBTQIA+ people and HCPs in the development process is essential to ensure the intervention's relevance, effectiveness, and acceptability.
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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 | 0.015 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".