Older Adult Peer Support Specialists’ Age-Related Contributions to an Integrated Medical and Psychiatric Self-Management Intervention: Qualitative Study of Text Message Exchanges
Notice bibliographique
Résumé
BACKGROUND: Middle-aged and older adults with mental health conditions have a high likelihood of experiencing comorbid physical health conditions, premature nursing home admissions, and early death compared with the general population of adults aged 50 years or above. An emerging workforce of peer support specialists aged 50 years or above or "older adult peer support specialists" is increasingly using technology to deliver peer support services to address both the mental health and physical health needs of middle-aged and older adults with a diagnosis of a serious mental illness. OBJECTIVE: This exploratory qualitative study examined older adult peer support specialists' text message exchanges with middle-aged and older adults with a diagnosis of a serious mental illness and their nonmanualized age-related contributions to a standardized integrated medical and psychiatric self-management intervention. METHODS: Older adult peer support specialists exchanged text messages with middle-aged and older adults with a diagnosis of a serious mental illness as part of a 12-week standardized integrated medical and psychiatric self-management smartphone intervention. Text message exchanges between older adult peer support specialists (n=3) and people with serious mental illnesses (n=8) were examined (mean age 68.8 years, SD 4.9 years). A total of 356 text messages were sent between older adult peer support specialists and service users with a diagnosis of a serious mental illness. Older adult peer support specialists sent text messages to older participants' smartphones between 8 AM and 10 PM on weekdays and weekends. RESULTS: Five themes emerged from text message exchanges related to older adult peer support specialists' age-related contributions to integrated self-management, including (1) using technology to simultaneously manage mental health and physical health issues; (2) realizing new coping skills in late life; (3) sharing roles as parents and grandparents; (4) wisdom; and (5) sharing lived experience of difficulties with normal age-related changes (emerging). CONCLUSIONS: Older adult peer support specialists' lived experience of aging successfully with a mental health challenge may offer an age-related form of peer support that may have implications for promoting successful aging in older adults with a serious mental illness.
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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 | 0,007 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».