Understanding Barriers to Home Safety Assessment Adoption in Older Adults: Qualitative Human-Centered Design Study
Notice bibliographique
Résumé
Background: Falls are the leading cause of injury-related death among adults aged 65 and older. The fear of falling can further limit older adults' independence by contributing to activity restriction, social isolation, and physical decline-ironically increasing the risk of mechanical falls. Although home safety assessments have been shown to reduce fall risk by up to 36% and decrease serious injuries such as hip fractures, their adoption remains low. Understanding the barriers to implementing these assessments is critical to improving their uptake and effectiveness. Objective: This study aimed to (1) identify specific barriers perceived by older adults in implementing home safety assessments and modifications to reduce the risk of mechanical falls, (2) explore the attitudes of health care professionals and other stakeholders toward these assessments, and (3) identify novel design opportunities to guide the development and implementation of more effective home safety assessment techniques and practices to reduce mechanical fall risk. Methods: This explanatory qualitative study drew on the "inspiration" phase of the human-centered design (HCD) research process. We conducted 35 interviews (28 initial and 7 follow-up) with 28 purposefully sampled participants in the San Francisco Bay Area between February and June 2021. Participants included community-dwelling older adults (n=3), geriatricians (n=4), therapists (n=6), product developers (n=2), older health researchers (n=8), and community program leaders (n=5). Interview notes were analyzed inductively by the research team to extract themes and generate insight statements and design opportunities. Results: Analysis yielded three key insights: (1) older adults often experience a conflict between maintaining independence and implementing safety modifications. One participant described living with a "repeating mantra in my head throughout the day saying 'above all, don't fall.'" (2) aesthetic and privacy concerns frequently override safety benefits. Participants rejected modifications that made their homes feel "institutional." (3) access to occupational therapy services-already limited in rural areas-was further constrained by the COVID-19 pandemic, with some providers reporting that travel time "took up the majority of their day just assessing one home." These barriers help explain the low adoption of home safety assessments despite strong supporting evidence. The study identified design opportunities to address these challenges, including customizable, user-friendly safety solutions, dignity-preserving approaches to assessment, and technology-enabled remote alternatives. Conclusions: This study identified specific emotional, aesthetic, logistical, and access-related barriers to the adoption of home safety assessments among older adults. The proposed design solutions offer promising directions to increase uptake, improve user experience, and enhance safety. However, further validation through co-design with a larger and more diverse group of older adults is needed. Future research should pilot test these ideas across varied contexts and evaluate their implementation and impact.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,035 | 0,027 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,006 | 0,006 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».