Self-management toolkit and delivery strategy for end-of-life pain: the mixed-methods feasibility study
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Résumé
BACKGROUND: Pain affects most people approaching the end of life and can be severe for some. Opioid analgesia is effective, but evidence is needed about how best to support patients in managing these medicines. OBJECTIVES: To develop a self-management support toolkit (SMST) and delivery strategy and to test the feasibility of evaluating this intervention in a future definitive trial. DESIGN: Phase I - evidence synthesis and qualitative interviews with patients and carers. Phase II - qualitative semistructured focus groups and interviews with patients, carers and specialist palliative care health professionals. Phase III - multicentre mixed-methods single-arm pre-post observational feasibility study. PARTICIPANTS: Phase I - six patients and carers. Phase II - 15 patients, four carers and 19 professionals. Phase III - 19 patients recruited to intervention that experienced pain, living at home and were treated with strong opioid analgesia. Process evaluation interviews with 13 patients, seven carers and 11 study nurses. INTERVENTION: Self-Management of Analgesia and Related Treatments at the end of life (SMART) intervention comprising a SMST and a four-step educational delivery approach by clinical nurse specialists in palliative care over 6 weeks. MAIN OUTCOME MEASURES: Recruitment rate, treatment fidelity, treatment acceptability, patient-reported outcomes (such as scores on the Brief Pain Inventory, Self-Efficacy for Managing Chronic Disease Scale, Edmonton Symptom Assessment Scale, EuroQol-5 Dimensions, Satisfaction with Information about Medicines Scale, and feasibility of collecting data on health-care resource use for economic evaluation). RESULTS: Phase I - key themes on supported self-management were identified from evidence synthesis and qualitative interviews. Phase II - the SMST was developed and refined. The delivery approach was nested within a nurse-patient consultation. Phase III - intervention was delivered to 17 (89%) patients, follow-up data at 6 weeks were available on 15 patients. Overall, the intervention was viewed as acceptable and valued. Descriptive analysis of patient-reported outcomes suggested that interference from pain and self-efficacy were likely to be candidates for primary outcomes in a future trial. No adverse events related to the intervention were reported. The health economic analysis suggested that SMART could be cost-effective. We identified key limitations and considerations for a future trial: improve recruitment through widening eligibility criteria, refine the SMST resources content, enhance fidelity of intervention delivery, secure research nurse support at recruiting sites, refine trial procedures (including withdrawal process and data collection frequency), and consider a cluster randomised design with nurse as cluster unit. LIMITATIONS: (1) The recruitment rate was lower than anticipated. (2) The content of the intervention was focused on strong opioids only. (3) The fidelity of intervention delivery was limited by the need for ongoing training and support. (4) Recruitment sites where clinical research nurse support was not secured had lower recruitment rates. (5) The process for recording withdrawal was not sufficiently detailed. (6) The number of follow-up visits was considered burdensome for some participants. (7) The feasibility trial did not have a control arm or assess randomisation processes. CONCLUSIONS: A future randomised controlled trial is feasible and acceptable. STUDY AND TRIAL REGISTRATION: This study is registered as PROSPERO CRD42014013572; Current Controlled Trials ISRCTN35327119; and National Institute for Health Research (NIHR) Portfolio registration 162114. FUNDING: The NIHR Health Technology Assessment programme.
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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) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 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) | 0,000 | 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 découle