Developing a Comprehensive Model for Improving Quality of Life in Individuals with Alzheimer Disease and Related Dementia and Their Informal Caregivers: Qualitative Study of AZL Forum Data
Notice bibliographique
Résumé
Background It is estimated that more than five million Americans are living with Alzheimer disease and related dementia (ADRD), and the population of people living with the disease is expected to triple by 2060. Most care for persons living with ADRD is provided by informal caregivers. However, current strategies to improve the quality of life for both people living with ADRD and their informal caregivers are not optimal, especially from a comprehensive approach. Social media and online forums have become increasingly popular tools for ADRD caregivers to manage the burden of caregiving. Objective This study was to 1) explore informal caregivers’ discussion topics by analyzing the caregiver online forum data, and 2) develop a comprehensive model based on their discussion topics, with the aim to improve quality of life for both persons living with ADRD and their informal caregivers. Methods Publicly available peer interactions of 4102 registered users, with 96% self-claimed as informal caregivers (67% as a child of a person with dementia, 13% as a partner/spouse, and 7% as a relative) on the Alzheimer’s Association ALZ Connected Caregivers Forum were extracted in January 2019 using computer programming. A total of 40,798 postings were collected. All authors agreed to use a triangular model to serve as the predetermined three major themes to categorize all codes. The three major themes were factors of caregivers, factors of individuals with ADRD, and factors of care context. Inductive coding was used to derive in vivo codes from the data, and the codes were further refined throughout the coding process. Two researchers independently coded postings until saturation was reached. Discrepancies were discussed among the two researchers to reach consensus. A third senior researcher’s opinion was referred to whenever necessary. Results For factors of caregivers, the most frequent subthemes were perceived caregiver burden, caregiver’s life balance, caregiving strategies, communication, expectations, personal health issues, poor relationship, and ineffective coping. Subthemes of factors of individuals with ADRD included changes in abilities and capacities, commodities, behaviors, health conditions, daily living function, disengagement, and ineffective coping. Lastly, for factors of care context, the most frequent themes were family support, financial support, informational support, professional support, length of care provided, living arrangement, activities and stimulation, patient health care coordination, unexpected situations, communication, and physical environment. One theme under one of the triangular factors may influence another theme under another triangular factor and vice versa. Conclusions By analyzing the discussions of informal caregivers on ALZ online forum, we found that taking care of a loved one with ADRD is challenging for informal caregivers. The challenges may affect the quality of life for both caregivers and the caregiver recipients; factors of care recipients, caregivers, and the care context interactively affect perceived challenges of caregivers. This study has identified a comprehensive model which may be used to help improve quality of life for both informal caregivers and people living with ADRD. Our next step is to use these manually determined codes to analyze all extracted postings via machine learning to improve this model.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».