Community Members’ Perceptions of a Resource-Rich Well-Being Website in California During the COVID-19 Pandemic: Qualitative Thematic Analysis
Bibliographic record
Abstract
BACKGROUND: To address needs for emotional well-being resources for Californians during the COVID-19 pandemic, the Together for Wellness/Juntos por Nuestro Bienestar (T4W/Juntos) website was developed in collaboration with multiple community partners across California, funded by the California Department of Health Care Services Behavioral Health Division federal emergency response. OBJECTIVE: This qualitative study was designed to explore and describe the perspectives of participants affiliated with California organizations on the T4W/Juntos website, understand their needs for web-based emotional health resources, and inform iterative website development. METHODS: After providing informed consent and reviewing the website, telephone interviews were conducted with 29 participants (n=21, 72% in English and n=8, 28% in Spanish) recruited by partnering community agencies (October 2021-February 2022). A 6-phase thematic analysis was conducted, enhanced using grounded theory techniques. The investigators wrote reflexive memos and performed line-by-line coding of 12 transcripts. Comparative analyses led to the identification of 15 overarching codes. The ATLAS.ti Web software (ATLAS.ti Scientific Software Development GmbH) was used to mark all 29 transcripts using these codes. After examining the data grouped by codes, comparative analyses led to the identification of main themes, each with a central organizing concept. RESULTS: Four main themes were identified: (1) having to change my coping due to the pandemic, (2) confronting a context of shifting perceptions of mental health stigma among diverse groups, (3) "Feels like home"-experiencing a sense of inclusivity and belonging in T4W/Juntos, and (4) "It's a one-stop-shop"-judging T4W/Juntos to be a desirable and useful website. Overall, the T4W/Juntos website communicated support and community to this sample during the pandemic. Participants shared suggestions for website improvement, including adding a back button and a drop-down menu to improve functionality as well as resources tailored to the needs of groups such as older adults; adolescents; the lesbian, gay, bisexual, transgender, and queer community; police officers; and veterans. CONCLUSIONS: The qualitative findings from telephone interviews with this sample of community members and service providers in California suggest that, during the COVID-19 pandemic, the T4W/Juntos website was well received as a useful, accessible tool, with some concerns noted such as language sometimes being too "professional" or "clinical." The look, feel, and content of the website were described as welcoming due to pictures, animations, and videos that showcased resources in a personal, colorful, and inviting way. Furthermore, the content was perceived as lacking the stigma typically attached to mental health, reflecting the commitment of the T4W/Juntos team. Unique features and diverse resources, including multiple languages, made the T4W/Juntos website a valuable resource, potentially informing dissemination. Future efforts to develop mental health websites should consider engaging a diverse sample of potential users to understand how to tailor messages to specific communities and help reduce stigma.
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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 | 0.016 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.012 | 0.009 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".