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Enregistrement W2904287081 · doi:10.1186/s40814-018-0377-2

Feasibility study of goal setting discussions between older adults and volunteers facilitated by an eHealth application: development of the Health TAPESTRY approach

2018· article· en· W2904287081 sur OpenAlexafffundabout
Dena Javadi, Larkin Lamarche, Ernie Avilla, Raied Siddiqui, Jessica Gaber, Mehreen Bhamani, Doug Oliver, Laura Cleghorn, Dee Mangin, Lisa Dolovich

Notice bibliographique

RevuePilot and Feasibility Studies · 2018
Typearticle
Langueen
DomaineHealth Professions
ThématiqueGeriatric Care and Nursing Homes
Établissements canadiensMcMaster University
Organismes subventionnairesHealth CanadaGovernment of OntarioOntario Ministry of Health and Long-Term CareMcMaster University
Mots-clésGoal Attainment ScalingGoal settingeHealthPsychologyHealth careIntervention (counseling)PopulationNursingMedical educationPsychological interventionSet (abstract data type)GerontologyMedicineFamily medicineApplied psychologyComputer science

Résumé

récupéré en direct d'OpenAlex

In keeping with the changing needs of the Canadian population, primary care systems need to become more person-focused in providing quality care to older adults. As part of Health TAPESTRY, a complex intervention to strengthen primary care for older adults, a goal setting exercise was developed and tested in an initial feasibility study, intended to foster collaboration between patients and providers. Participants—clinic clients—were recruited from the McMaster Family Health Team in Hamilton, Ontario. Five participants took part in the goal setting feasibility study phase I, which tested the functionality of a technology-enabled goal setting exercise between older adults and volunteers. Based on observations and feedback from volunteers, interprofessional team members, and older adults, the exercise was refined to include a guided survey and goals report. The goal setting survey is a list of probing questions designed based on SMART (specific, measurable, attainable, relevant, timely) goal setting strategies and goal attainment scaling (GAS). This was used in phase II, carried out with 16 participants, where the feasibility of goal setting and goal attainment with support from volunteers and interprofessional teams was tested. Volunteers carried out the goal setting survey via a tablet computer, a report of client goals was generated and sent to interprofessional teams, and client goals were discussed during clinic huddles. At 6 months of follow-up, clients self-evaluated their progress using GAS. The goal setting exercise in phase I took an average of 24:45 (SD 11:42) minutes and yielded a diverse set of life and health goals. Goals identified by older adults were primarily focused on the maintenance of a certain level of activity or health state. Phase I work resulted in important changes to the goal setting process (e.g., asking about goal setting later in conversation, changing wording of questions) and development of a summary report of goals sent to the interprofessional team. In phase II, 44 goals were set by 16 participants during an average 7:23 (SD 4:26) minute discussion. Of these goals, 43.9% were characterized as health goals while 63.4% were characterized as life goals. Under the umbrella of Life goals, productivity featured most prominently at 22.9% of all goals. Goal attainment was not measured in phase I. In phase II, clients had an average weighted goal attainment score of 51.5. Considering client preferences for one goal over another, 68.8% of clients, on average, at least partially achieved the goals they had set. Goal setting as part of the Health TAPESTRY approach was feasible and provided interprofessional teams with client narratives that helped improve care management for older adults. The overall intervention—including the refined goal setting component—is being scaled and evaluated in a pragmatic randomized controlled trial.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesÉtudes des sciences et des technologies
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,079
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0020,001
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,160
Tête enseignante GPT0,451
Écart entre enseignants0,291 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations15
Publié2018
Routes d'admission3
Résumé présentoui

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