Community Members’ Perceptions of a Resource-Rich Well-Being Website in California During the COVID-19 Pandemic: Qualitative Thematic Analysis
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,016 | 0,017 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,003 | 0,004 |
| Études des sciences et des technologies | 0,012 | 0,009 |
| Communication savante | 0,005 | 0,004 |
| Science ouverte | 0,003 | 0,005 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».