Development and psychometric testing of a measure of the healthcare experiences of persons with dementia and their caregivers
Notice bibliographique
Résumé
Background: Dementia affects many older adults. The Canadian Study of Health and Aging estimates that 8.0% of Canadians aged 65 years or older meet the criteria for dementia.(1) Within the subgroup of individuals aged 85 years or older, the prevalence rate increases to 34.5%.(1) While this is already a substantial proportion of the older adult Canadian population, it is only expected to increase as the Canadian population ages. Persons living with dementia and their caregivers have frequent contact with the healthcare system, yet in spite of this there is still much to be desired with regard to optimizing the healthcare experience for persons living with dementia and their caregivers. Moreover, in order to optimize the experience, it is necessary to be able to measure the experience. To date, no such measure exists. The aim of this study was to develop and test the psychometric properties of a measure of healthcare experience of persons living with dementia and their caregivers. \nMethods: The study was conducted in three phases. Phase I was a qualitative systematic review using a thematic synthesis approach. Several electronic databases were searched to identify studies of dementia healthcare experiences in primary and secondary care. Data were abstracted from included studies and analyzed using qualitative analysis software (NVivo 11). The thematic synthesis resulted in the development of a healthcare experiences model, which identified domains for development of a draft experience measure. Phase II sought the feedback of persons living with dementia and caregivers on the developed measure. Participants took part in either individual or focus group interviews (participant choice). All interviews were recorded and transcribed. Inductive content analysis of transcripts was used to identify modifications which should be made to the measure, as well as aspects of the measure that participants recommended remain unchanged. The revised measure underwent psychometric testing in Phase III. Once again, persons living with dementia and caregivers were recruited to take part. The measure underwent assessment of face validity, content validity, construct validity, internal consistency, and test-retest reliability. \nResults: Phase I resulted in a healthcare experiences model. It was hypothesized that the experiences of persons living with dementia and caregivers would be sufficiently different to warrant two different frameworks or models, however the experiences were found to have many commonalities and one model was developed. Consequently, this resulted in the development of one measure for both persons living with dementia and their caregivers. Thirteen persons living with dementia and 16 caregivers participated in individual, dyad, and focus group interviews in Phase II. Based on analysis of their feedback, several changes were made to the measure. These included addressing the topic of driving, improving the clarity of instructions, and making modifications to the wording of a few items. Following these modifications, the measure was ready for Phase III. Eighteen caregivers participated in this phase, though only three persons living with dementia could be recruited. Therefore, psychometric analyses were largely only conducted with data from the caregiver group. The measure was found to have good face validity and content validity. Correlation with a global question on the degree to which healthcare expectations were met showed good construct validity (Spearman correlation coefficient = 0.71). Internal consistency was also high (Cronbach’s α = 0.78). Test-retest reliability was found to be fair (ICC(2,1) = 0.62). \nConclusions: This three-phase study aimed to develop a measure of healthcare experiences for persons living with dementia and their caregivers. The measure was based on the literature and revised with the input of individuals with lived experience. Caregivers participated in psychometric testing with overall positive results, though further testing is required with persons living with dementia.
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 | 0,032 | 0,055 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 ».