Implementing Systematic Screening and Structured Care for Distressed Callers Using Cancer Council’s Telephone Services: Protocol for a Randomized Stepped-Wedge Trial
Notice bibliographique
Résumé
BACKGROUND: Structured distress management, comprised a 2-stage screening and referral model, can direct supportive care resources toward individuals who are most likely to benefit. This structured approach has yet to be trialed in Australian community-based services such as Cancer Council New South Wales (NSW) and Victoria Cancer Information and Support (CIS) 13 11 20 lines who care for a large community of cancer patients and caregivers. OBJECTIVE: The aim of this study was to evaluate the effectiveness of structured screening and referral in (1) increasing the proportion of distressed CIS callers who accept supportive care referrals and (2) reducing distress levels at 6-month follow-up. METHODS: In this stepped-wedge trial, Cancer Council NSW and Victoria CIS consultants are randomized to deliver structured care during inbound 13 11 20 calls in accordance with 3 intervention periods. Eligible callers are patients or caregivers who score 4 or more on the Distress Thermometer; NSW or Victorian residents; aged 18 years or older; and English proficient. Study data are collected via computer-assisted telephone interviews (CATIs) at 3- and 6-month follow-up and CIS record audit. CATIs include demographic and service use items and the General Health Questionnaire (GHQ-28) to assess distress. An economic analysis of the structured care model will be completed. RESULTS: The structured care model was developed by guideline review and identification of service characteristics to guide mapping decisions; place-card methodology; and clinical vignettes with think-aloud methodology to confirm referral appropriateness. The model includes an additional screening tool (Patient Health Questionnaire-4) and a referral model with 16-20 CIS services. Descriptive statistics will be used to assess referral uptake rates. Differences between GHQ-28 scores for structured and usual care callers will be tested using a generalized linear mixed model with fixed effects for intervention and each time period. The trial will recruit 1512 callers. The sample size will provide the study with approximately 80% power to detect a difference of 0.3 SD in the mean score of the GHQ-28 at an alpha level of .05 and assuming an intra-cluster correlation of .04. A random sample of recorded calls will be reviewed to assess intervention fidelity and contamination. To date, 1835 distressed callers have been invited to participate with 60.71% (1114/1835) enrolled in the study. A total of 692 participants have completed 6-month CATIs. Recruitment is anticipated to end in late 2019. CONCLUSIONS: This trial is among the first to rigorously test the outcomes of a community-based structured approach to distress management. The model is evidence-informed, practice-ready, and trialed in a real-world setting. The study outcomes will advance the understanding of distress management internationally for both patients and caregivers. TRIAL REGISTRATION: Australian New Zealand Clinical Trial Registry ACTRN12617000352303; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=372105&isReview=true (Archived by WebCite on http://www.webcitation.org/78AW0Ba09). INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/12473.
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 | 0,045 | 0,038 |
| Méta-épidémiologie (sens strict) | 0,007 | 0,004 |
| Méta-épidémiologie (sens large) | 0,011 | 0,005 |
| Bibliométrie | 0,003 | 0,004 |
| Études des sciences et des technologies | 0,003 | 0,004 |
| Communication savante | 0,004 | 0,004 |
| Science ouverte | 0,004 | 0,003 |
| Intégrité de la recherche | 0,008 | 0,009 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,068 | 0,012 |
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 ».