Effectiveness of a Nurse-Led Mobile-Based Health Coaching Program for Patients With Prostate Cancer at High Risk of Metabolic Syndrome: Randomized Waitlist Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: Androgen deprivation therapy (ADT), a standard treatment for prostate cancer (PC), causes many physical side effects. In particular, it causes metabolic changes such as fasting glucose abnormalities or accumulation of body fat, and its continuation can lead to metabolic syndrome (MetS), which is closely related to diabetes and cardiovascular disease. Therefore, it is important to maintain and practice a healthy lifestyle in patients with PC. OBJECTIVE: This study aims to evaluate the effectiveness of a nurse-led mobile-based program that aims to promote a healthy lifestyle in patients with PC undergoing ADT with MetS risk factors. METHODS: This was a single-blind, randomized, waitlist control interventional study. A total of 48 patients were randomly assigned to the experimental and waitlist control groups at the urology cancer clinic of a tertiary general hospital in South Korea. The inclusion criteria were patients who had undergone ADT for >6 months, had at least 1 of the 5 MetS components in the abnormal range, and could access a mobile-based education program. The experimental group attended a 4-week mobile-based program on exercise and diet that included counseling and encouragement to maintain a healthy lifestyle, whereas the control group was placed on a waitlist and received usual care during the follow-up period, followed by the intervention. The primary outcome was a change in the lifestyle score. The secondary outcomes were changes in 5 MetS components, body composition, and health-related quality of life. The outcomes were measured at 6 weeks and 12 weeks after the initiation of the intervention. Each participant was assigned to each group in a sequential order of enrollment in a 4×4 permuted block design randomization table generated in the SAS (SAS Institute) statistical program. A linear mixed model was used for statistical analysis. RESULTS: A total of 24 participants were randomly assigned to each group; however, 2 participants in the experimental group dropped out for personal reasons before starting the intervention. Finally, 46 participants were included in the intention-to-treat analysis. The experimental group showed more positive changes in the healthy lifestyle score (β=29.23; P≤.001), level of each MetS component (fasting blood sugar: β=-12.0; P=.05 and abdominal circumference: β=-2.49; P=.049), body composition (body weight: β=-1.52; P<.001 and BMI: β=-0.55; P<.001), and the urinary irritative and obstructive domain of health-related quality of life (β=14.63; P<.001) over time than the waitlist control group. CONCLUSIONS: Lifestyle changes through nurse-led education can improve level of each MetS components, body composition, and ADT side effects. Nurses can induce positive changes in patients' lifestyles and improve the self-management of patients starting ADT through this program. TRIAL REGISTRATION: Clinical Research Information Service KCT0006560; http://tinyurl.com/yhvj4vwh.
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,002 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,001 |
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 ».