Factors Associated with Participation, Active Refusals and Reasons for Not Taking Part in a Mortality Followback Survey Evaluating End-of-Life Care
نویسندگان
چکیده
BACKGROUND Examination of factors independently associated with participation in mortality followback surveys is rare, even though these surveys are frequently used to evaluate end-of-life care. We aimed to identify factors associated with 1) participation versus non-participation and 2) provision of an active refusal versus a silent refusal; and systematically examine reasons for refusal in a population-based mortality followback survey. METHODS Postal survey about the end-of-life care received by 1516 people who died from cancer (aged ≥18), identified through death registrations in London, England (response rate 39.3%). The informant of death (a relative in 95.3% of cases) was contacted 4-10 months after the patient died. We used multivariate logistic regression to identify factors associated with participation/active refusals and content analysis to examine refusal reasons provided by 205 nonparticipants. FINDINGS The odds of partaking were higher for patients aged 90+ (AOR 3.48, 95%CI: 1.52-8.00, ref: 20-49yrs) and female informants (AOR 1.70, 95%CI: 1.33-2.16). Odds were lower for hospital deaths (AOR 0.62, 95%CI: 0.46-0.84, ref: home) and proxies other than spouses/partners (AORs 0.28 to 0.57). Proxies of patients born overseas were less likely to provide an active refusal (AOR 0.49; 95% CI: 0.32-0.77). Refusal reasons were often multidimensional, most commonly study-related (36.0%), proxy-related and grief-related (25.1% each). One limitation of this analysis is the large number of nonparticipants who did not provide reasons for refusal (715/920). CONCLUSIONS Our survey better reached proxies of older patients while those dying in hospitals were underrepresented. Proxy characteristics played a role, with higher participation from women and spouses/partners. More information is needed about the care received by underrepresented groups. Study design improvements may guide future questionnaire development and help develop strategies to increase response rates.
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