ReviewEuropean journal of cancer care2022
Systematic adaptation of the adherence improving self-management strategy to support breast cancer survivors' adherence to adjuvant endocrine therapy: An intervention mapping approach.
Review in European journal of cancer care, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.
- Integrating 'undetectable equals untransmittable' into HIV counselling in South Africa: the development of locally acceptable communication tools using intervention mapping.BMC public health · 2024Pooled it
- Identification of patient subgroups who benefit from a behavioral intervention to improve adjuvant endocrine therapy adherence: a randomized-controlled trial.Breast cancer research and treatment · 2024Trial
- Cancer patient navigation interventions improving timeliness from diagnosis to first treatment in oncology care: A scoping review.Japan journal of nursing science : JJNS · 2026Article
- Development of an Evidence-Based and Theory-Informed Self-Management Intervention for People with Lipoedema: An Intervention Mapping Study.Journal of multidisciplinary healthcare · 2025Article
- Self-management of geriatric syndromes - an observational study.BMC geriatrics · 2023Observational
- Systematic adaptation of the adherence improving self-management strategy to support breast cancer survivors' adherence to adjuvant endocrine therapy: An intervention mapping approach.European journal of cancer care · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveNon-adherence to adjuvant endocrine therapy (AET) for breast cancer leads to increased recurrence and mortality risk and healthcare costs. Evidence on feasible, effective AET adherence interventions is scarce. This paper describes the systematic adaptation of the cost-effective adherence improving self-management strategy (AIMS) for patients with HIV to AET for women after breast cancer treatment.
methodsWe followed the intervention mapping protocol for adapting interventions by conducting a needs assessment, reviewing target behaviours and determinants, reassessing behaviour change methods and adapting programme content. Therefore, we performed a literature review, consulted behavioural theory and organised nine advisory board meetings with patients and healthcare professionals.
resultsNon-adherence occurs frequently among AET users. Compared to HIV treatment, AET is less effective, and AET side effects are more burdensome. This drives AET treatment discontinuation. However, the key determinants of non-adherence are largely similar to HIV treatment (e.g. motivation, self-regulation and patient-provider relationship); therefore, most strategies in AIMS-HIV also seem suitable for AIMS-AET. Modifications were required, however, regarding supporting patients with coping with side effects and sustaining treatment motivation.
conclusionAIMS seems to be a suitable framework for adherence self-management across conditions and treatments. Intervention mapping offered a transparent, systematic approach to adapting AIMS-HIV to AET.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.