Limitations
’, RPL, ®, chronic disease
REGRESSION, LCM, CHRONIC DISEASE
The choices patients make in real life may not always be the same as the choices they make in a hypothetical DCE. This is known as hypothetical bias and is a general limitation of DCEs.DCE is a complex method that works best through face-to-face interviews in older or less literate populations. We used a telephone survey as this was used to collect other patient-reported trial data. We tried to minimize patient burden and risk of poor recall of all variables in a telephone interview with no visualization by 1) keeping choice sets to four; 2) requesting patients to keep a pen and paper handy following recommendations from the pretest; 3) using CATI technology and trained interviewers; 4) providing detailed instruction to the interviewer in the survey before each scenario to standardize the approach and to allow for repetition before collecting the patient’s response. The self-administered online survey was not feasible due to the age and literacy level of our population. It could be interesting to explore online surveys in older populations through SMS or WhatsApp® in the future.We did not include an opt-out alternative, (e.g. patients’ current pharmacy service features), but we did not have a large enough sample size to account for the loss of preference data. Choosing an opt-out alternative does indicate the relative preference of patients who do not wish to choose between available alternatives, but an opt-out alternative may have implications as patients need to be censored in preference assessment. Hence, a large enough sample size is required for assessing preferences on attributes and levels to account for the loss of patients who choose an opt-out alternative.We could not reach the minimum sample size required according to Johnson and Orme for DCEs [The survey version used in the pretest included probabilities in the risk reduction attribute and this was not well understood which has been reported in previous research [We framed cost as WTA cost to the NHS because, in health care, WTA is more appropriate for potential “losers”, e.g. individuals that may experience loss aversion as an intrinsic feeling of loss toward a new intervention, or when the health care intervention has already completed and changes in health state may have been experienced or perceived [We did not include some patient characteristics such as interacting covariates in the regression model due to a high proportion of missing data, which would reduce the sample size. Hence, we may have missed the effect of individual heterogeneity in preferences. Yet, we assumed low heterogeneity for trial patients where inclusion criteria apply. Furthermore, although an income effect occurs in WTP because payment is constrained by income, it does not occur in WTA [We did not test alternative regression models, such as Random-Parameters Logit (RPL), Hierarchical Bayes, or Latent Class Models (LCM) to allow for unobserved heterogeneity and compare the consistency of results, as we did not have a large enough sample size [It is also likely that chronic disease patients’ perception of pharmacy services has evolved since the time this study was conducted. Community pharmacists have undertaken relevant direct patient care interventions during the pandemic in response to the extended closure of NHS face-to-face GP appointments [These limitations preclude the generalization of our findings but offer valuable lessons from a real-world trial for future DCE studies in pharmacy-based public health interventions.