Self-awareness and nonattachment as internal resources for well-being among lesbian, gay, bisexual, transgender, queer, and other gender and sexually diverse individuals.
Bibliographic record
Abstract
Previous studies showed inconsistent findings on the association between self-awareness and well-being among lesbian, gay, bisexual, transgender, queer, and other gender and sexually diverse (LGBTQ+) individuals. The present study examined the mediating effects of self-stigma and negative emotional responses to oppression in the relationship between self-awareness and well-being, as well as the protective role of nonattachment on the relationship. A total of 1,050 LGBTQ+ individuals were included in the study. They completed measures of nonattachment, self-awareness, self-stigma, negative emotional responses to oppression, and well-being. Results showed that self-awareness was positively associated with well-being via its effect on reduced self-stigma and negatively associated with well-being via its effect on increased negative emotional responses to oppression. For LGBTQ+ individuals with higher levels of nonattachment, the positive association between self-awareness and negative emotional responses to oppression was nonsignificant, and the negative association between self-awareness and self-stigma was strengthened. The study unravels the underlying psychological mechanisms through which self-awareness showed its positive and negative indirect effects on well-being among LGBTQ+ individuals. The results suggest that nonattachment, together with self-awareness, could be vital internal resources for the well-being of LGBTQ+ individuals. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
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 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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".