SynthesisThe patient2025
Preferences for Telephone Cancer Information and Support in People with Cancer and Carers: Attribute and Level Selection for a Discrete Choice Experiment.
Synthesis in The patient, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
13 authors.
Funding
Abstract
BACKGROUND AND
objectiveTelephone cancer information and support services (CISS) deliver essential evidence-based resources for people living with cancer. This research aimed to describe how attributes and levels were developed for a future discrete choice experiment to elicit preferences for operational characteristics of a CISS, focusing on Cancer Council Victoria's service.
methodsUsing a mixed-methods approach guided by the ISPOR checklist for conjoint analysis in healthcare, initial attributes were developed using an artificial intelligence framework to analyse CISS calls (January 2018-December 2021), focus groups with people with cancer and carers using the CISS (July-August 2022), and a systematic literature review of qualitative studies. A four-stage descriptive process guided attribute and level development. An expert panel of researchers (n = 10), a CISS staff member, a person with lived experience of cancer and a consumer-only panel (n = 7) met monthly to prioritise, refine and finalise attributes by consensus.
resultsCall data analysis (people with cancer n = 7701; carers n = 5500), six focus groups (people with cancer n = 10; carers n = 11) and a systematic literature review of qualitative studies generated 14 candidate attributes. The expert panels selected seven final attributes, each with three levels: follow-up call, operating hours, additional technology, operator type, operator consistency, call length and service fee.
conclusionsTransparent reporting of the discrete choice experiment design process is essential for credible interpretation. The four-stage approach enhanced the comprehensibility of the experiment, as multi-modal data ensured the selected attributes and levels accurately reflect CISS caller priorities, which may be applicable to other choice-based studies.
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