Smart Speaker-Based Applications to Support Social Connectedness in Older Adult Residents in Affordable Housing: A User-Centered Design Study (Preprint)
Notice bibliographique
Résumé
Background: Older adults in affordable housing face heightened risks of social isolation and loneliness due to limited social networks, transportation barriers, chronic conditions, and inadequate technology access. Smart speakers offer potential for enhancing social connectedness in this underserved population, yet technology interventions are rarely designed with meaningful input from older adults themselves. User-centered design (UCD) approaches can address this gap by engaging end users throughout the development process to ensure technology solutions align with their needs and living contexts. Objective: This study aimed to engage older adults in affordable housing in an iterative UCD process to develop prototype scenarios for smart speaker-based applications that promote social connectedness while addressing safety, community-building, and wellness needs. Methods: We conducted a 3-stage UCD study with 29 older adults (mean age 70, SD 6.8 years; 23/29, 79% African American; 20/29, 69% high school education or less) living alone in affordable housing between April 2021 and April 2022. Stage 1 included 5 focus groups (n=25) combining needs assessment discussions with rapid brainstorming activities. Stage 2 involved research team synthesis of focus group transcripts and brainstorming data to create a Design Strategies Map, development of initial prototype scenarios, 5 evaluation focus groups (n=18) to gather feedback, and iterative scenario refinement. Stage 3 comprised 4 validation focus groups (n=17) to assess refined scenarios and identify implementation recommendations. Participants included both smart speaker users (n=13) and nonusers (n=16). Data were analyzed using thematic analysis for needs assessment, content analysis for brainstorming ideas and feedback, and matrix analysis for systematic comparison across scenarios. Results: Participants generated 153 ideas for smart speaker use, with Health and Safety and Daily Assistance being the most frequent categories. Analysis revealed that social connection needs were inseparable from safety concerns related to living alone. Through iterative co-design, we developed 7 prototype scenarios across 4 functional categories: Checking-In (peer and management safety verification with privacy controls), Social Companion (conversational artificial intelligence-based companionship and emotional support), Community Involvement (virtual bulletin boards and activity coordination), and Wellness Check (system-initiated monitoring of activity and behavioral patterns as health indicators with user-controlled interventions). Participants emphasized requirements for personalization, opt-in/opt-out controls, "Do-Not-Disturb" functionality, and safeguards preventing replacement of human connection. Conclusions: Older adults in affordable housing engaged in technology design and provided valuable insights that challenge assumptions about their needs and preferences. The prototype scenarios addressed the dual imperatives of social connection and safety while living alone, offering a foundation for developing technology-based applications tailored to underserved populations. Implementation should prioritize user control, privacy protection, and human-in-the-loop design ensuring that technology facilitates rather than replaces human connection and community programming, alongside consideration of user characteristics to build trust and ensure effective, sustained use of the intended technology platform.
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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 | 0,004 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
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 ».