Community (dis)connectedness and identity among LGBTQIA+ people during the COVID-19 pandemic: a qualitative cross-sectional and longitudinal trajectory study
Bibliographic record
Abstract
The coronavirus (COVID-19) pandemic and associated shelter-in-place ordinances rapidly limited access to in-person social interactions, raising concerns of diminishing social support and community cohesion while psychological stressors increased. For LGBTQIA+ people, connectedness to the LGBTQIA+ community buffers against the harmful effects of stressors and decreases risks for poor psychological and behavioural health outcomes. The current study uses qualitative cross-sectional (between-person) and trajectory (within-person) analysis methods to characterise how LGBTQIA+ people’s perceptions of community connectedness shifted during the first year of the pandemic. A convenience sample of LGBTQIA+ people in the U.S. completed an initial online survey in September 2020 (n = 298 and a follow-up survey in September 2021; n = 129). The survey included questions about changes in connectedness to the LGBTQIA+ community since the pandemic’s beginning. Eight cross-cutting themes (related to identity shifts/exploration, disconnection, online connections, and increased awareness of social justice issues) were identified and then organised within each level of the LGBTQIA+ Social-Ecological Model (i.e. the individual-, couple-, interpersonal-, organisational-, community-, and chronosystem- level). Given the importance of social support for LGBTQIA+ wellbeing, more longitudinal research is needed to determine whether these changes persist after the resolution of the acute phase of the pandemic.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".