Decisional Conflict and Regret | 43 2 Methods Study design This is a systematic review about DC and DR in HNC patients, reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines19. The review was registered in the International Prospective Register of Systematic Reviews (PROSPERO) database prior to starting the search (CRD42021267872). Literature search process A sensitive literature search was developed with support of a medical librarian and adapted for the following databases: MEDLINE (Ovid), Embase, PsycINFO (Ovid), and Web of Science. The search strategy, with a final search on 24 February 2023, included terms relating to HNC and DC and/or DR and consisted of both database-specific thesaurus terms (where applicable) and terms to search in the title, abstract and keywords. The simplified structure of the search was: (head and neck cancer) AND (decisional conflict OR decisional regret). See appendix A for full details of the search strategy. No restrictions on language or publication period were applied. References of the included articles were checked to identify any potentially relevant missed publications. Inclusion criteria Eligible studies were quantitative, qualitative, or mixed-methods studies addressing DC and/or DR in patients with HNC of any stage and receiving any treatment. DC and DR could be primary or secondary outcomes and be measured with any instrument, including study-specific questionnaires. Studies with subjects < 18 years old, conference abstracts, and studies on cutaneous carcinomas were excluded. Selection process After deduplication, all identified records were uploaded into Rayyan software20. Because of the high yield of our search, we used Rayyan’s Artificial Intelligence (AI) to support screening21. The Rayyan AI algorithm calculates the likelihood of eligibility for records, based on a first set of manual inclusions (training data). Potential eligibility of new records is represented on a 0-5 stars scale, with 5 stars indicating the highest likelihood for eligibility.
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