Mood and Stress Evaluation of Adult Patients With Moyamoya Disease in Korea: Ecological Momentary Assessment Method Using a Mobile Phone App
Notice bibliographique
Résumé
BACKGROUND: Moyamoya disease (MMD) is a known progressive obstructive cerebrovascular disorder. Monitoring and managing mood and stress are critical for patients with MMD, as they affect clinical outcomes. The ecological momentary assessment (EMA) method is a longitudinal study design by which multiple variable assessments can be performed over time to detect momentary fluctuations and changes in psychological dimensions such as mood and stress over time. OBJECTIVE: This study aimed to identify predicting factors associated with momentary mood and stress at both the within-person and between-person levels and to examine individual fluctuation of mood over time in the short term using an EMA method combined with a mobile phone app. METHODS: Participants aged older than 18 years were recruited from a tertiary hospital in Seoul, Korea, between July 2018 and January 2019. The PsyMate scale for negative affect (NA) and positive affect (PA) and the Trier Inventory for Chronic Stress Scale were uploaded on patient mobile phones. Using a mobile app, data were collected four times a day for 7 days. Pearson correlations and mixed modeling were used to predict relationships between repeatedly measured variables at both the between-person and within-person levels. RESULTS: The mean age of the 93 participants was 40.59 (SD 10.06) years, 66 (71%) were female, and 71 (76%) were married. Participants provided 1929 responses out of a possible 2604 responses (1929/2604, 74.08%). The mean momentary NA and PA values were 2.15 (SD 1.12) and 4.70 (SD 1.31) out of 7, respectively. The momentary stress value was 2.03 (SD 0.98) out of 5. Momentary NA, PA, and stress were correlated (P<.001) and varied over time in relation to momentary variables. Common momentary variables associated with momentary mood and stress at both the within-person (level 1) and between-person (level 2) levels were identified. Momentary NA increased when being alone and being at the hospital at both levels, whereas momentary PA increased when eating or drinking, resting, being at a café, restaurant or a public place but decreased when being alone at both levels. Momentary stress increased when being at the office, at a public place, or as the time of the day went by but decreased when resting or during the weekend. Different factors affecting mood and stress at different levels were identified. Fluctuations in individual momentary mood over time at the within-person level were captured. CONCLUSIONS: The EMA method using a mobile phone app demonstrated its ability to capture changes in mood and stress in various environmental contexts in patients with MMD. The results could provide baseline information for developing interventions to manage negative mood and stress of patients with MMD based on the identified predictors affecting mood and stress at two different levels.
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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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».