Patient preference attributes in eHealth interventions for cancer‐related fatigue: A scoping review. (16th November 2022)

• Record Type: Journal Article
• Authors: Beenhakker, Lian; Witteveen, Annemieke; Wijlens, Kim A. E.; Siemerink, Ester J. M.; van der Lee, Marije L.; Bode, Christina; Siesling, Sabine; Vollenbroek‐Hutten, Miriam M. R.
• Is Part Of: European journal of cancer care. Volume 31:Number 6(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-11-16
• Subjects: breast cancer -- cancer‐related fatigue -- eHealth -- interventions -- patient preference -- scoping review; Cancer -- Nursing -- Periodicals; 616.994
• DOI: 10.1111/ecc.13754
• Languages: English
• ISSNs: 0961-5423

Abstract

Abstract: Introduction: Cancer‐related fatigue (CRF) is one of the most reported long‐term effects breast cancer patients experience after diagnosis. Many interventions for CRF are effective, however, not for every individual. Therefore, intervention advice should be adjusted to patients' preferences and characteristics. Our aim was to develop an overview of eHealth interventions and their (preference sensitive) attributes. Methods: eHealth interventions were identified using a scoping review approach. Eligible studies included breast cancer patients and assessed CRF as outcome. Interventions were categorised as physical activity, mind–body, psychological, 'other' or 'combination'. Information was extracted on various (preference sensitive) attributes, like duration, intensity, peer support and costs. Results: Thirty‐five interventions were included and divided over the intervention categories. (Preference sensitive) attributes varied both within and between these categories. Duration varied from 4 weeks to 6 months, intensity from daily to own pace. Peer support was present in seven interventions and costs were known for six. Conclusion: eHealth interventions exist in various categories, additionally, there is much variation in (preference sensitive) attributes. This provides opportunities to implement our overview for personalised treatment recommendations for breast cancer patients struggling with CRF. Taking into account patients' preferences and characteristics suits the complexity of CRF and heterogeneity of patients.