Bender, JL;
Babinski, S;
Wong, G;
Tricco, AC;
Englesakis, M;
Cyr, AB;
Potts, H;
... Witteman, H; + view all
(2021)
Establishing best practices in cancer online support groups: protocol for a realist review.
BMJ Open
, 11
(11)
, Article e053916. 10.1136/bmjopen-2021-053916.
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Abstract
INTRODUCTION: Considerable observational evidence suggests that cancer online support groups reduce feelings of isolation, depression and anxiety, enhance coping and self-management, and lead to better informed patients. Other studies indicate that cancer online support groups can increase distress. Yet no studies theorise the complex, context-dependent mechanisms by which cancer online support groups generate their-sometimes contrasting-outcomes. METHODS AND ANALYSIS: Guided by an integrated knowledge translation approach and the strategy for patient-oriented research, we will conduct a realist review of cancer online support groups in partnership with stakeholders. We will follow Pawson's five steps and existing quality standards to develop a program theory that explains how cancer online support groups work, for whom and in what circumstances. The specific research questions will be: what positive and negative outcomes have been reported on cancer online support groups? What are the mechanisms that are associated with these outcomes, in which contexts and for whom? Through a rigorous review of relevant scientific and grey literature, as well as ongoing dialogue with stakeholders, a program theory will be developed to explain who benefits from cancer online support groups and who does not, what benefits they derive (or do not), and the factors that affect these outcomes. ETHICS AND DISSEMINATION: The use of secondary data for this review precludes the need for ethical approval. Dissemination will be informed by the knowledge-to-action framework and will consist of tailored knowledge products that are conceived of collaboratively with stakeholders. These will include peer-reviewed publications on how cancer online support groups can be optimised and best practice recommendations to maximise the benefits experienced by people with cancer. These traditional scientific outputs, along with their respective evidence summaries, will be amplified through strategic social media events hosted and promoted by knowledge users. PROSPERO REGISTRATION NUMBER: CRD42021250046.
| Type: | Article |
|---|---|
| Title: | Establishing best practices in cancer online support groups: protocol for a realist review |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1136/bmjopen-2021-053916 |
| Publisher version: | https://doi.org/10.1136/bmjopen-2021-053916 |
| Language: | English |
| Additional information: | This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/. |
| Keywords: | Health informatics, health services administration & management, oncology |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Epidemiology and Health UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Epidemiology and Health > Behavioural Science and Health UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics > CHIME |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10137896 |
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