Use of Adaptive Conjoint Analysis–Based Values Clarification in a Patient Decision Aid Is Not Associated with Better Perceived Values Clarity or Reduced Decisional Conflict but Enhances Values Congruence

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Use of Adaptive Conjoint Analysis–Based Values Clarification in a Patient Decision Aid Is Not Associated with Better Perceived Values Clarity or Reduced Decisional Conflict but Enhances Values Congruence ABSTRACT Background Evidence is lacking on the most effective values clarification methods (VCMs) in patient decision aids (PtDAs). We tested the effects of an adaptive conjoint analysis (ACA)–based VCM compared with a ranking-based VCM and no VCM on several decision-related outcomes, with the decisional conflict and its subscale “perceived values clarity” as primary outcomes. Design Online experimental study with 3 conditions: no VCM versus ranking-based VCM versus ACA-based VCM (N = 282; Mage = 63.11 y, s = 12.12), with the latter 2 conditions including attributes important for a lung cancer treatment decision. We assessed 1) decisional conflict, 2) perceived values clarity (decisional conflict subscale), 3) perceived cognitive load, 4) anticipated regret, 5) ambivalence, 6) preparedness for decision making, 7) hypothetical treatment preference, and 8) values congruence (proxy). We performed analysis of covariance and linear regression. Age and level of deliberation were included as potential moderators, and we controlled for subjective numeracy (covariate). We exploratively tested the moderating effects of subjective numeracy and health literacy (without covariates). Results We found no significant effect of type of VCM on overall decisional conflict or perceived values clarity. Age had a moderating effect: in younger participants, no VCM (v. ranking-based VCM) led to more values clarity, while in older participants, a ranking-based VCM (v. no VCM) led to more values clarity. Completing the ACA-based VCM, compared with no VCM, resulted in more values congruence. Limitations The hypothetical choice situation might have induced lower levels of cognitive/affective involvement in the decision. Conclusions This study found mixed effects of an ACA-based VCM. It did not decrease decisional conflict or increase perceived values clarity, yet it did improve values congruence. Implications Completion of an ACA-based VCM in a PtDA may increase values congruence. Highlights An adaptive conjoint analysis or a ranking-based values clarification method did not decrease analog patients’ decisional conflict nor did it increase their perceived values clarity. In younger participants, no VCM (v. ranking-based VCM) led to more values clarity, while in older participants, a ranking-based VCM (v. no VCM) led to more values clarity. An adaptive conjoint analysis task for values clarification resulted in more values congruence. To support patients in clarifying what is most important to them in treatment decision making, patient decision aids (PtDAs) often provide values clarification methods (VCMs).1,2 VCMs have been shown to help patients think about how desirable they consider characteristics of treatment options, to determine which they prefer, and to make more values-congruent choices.1–4 Rating and ranking exercises are common types of VCMs5,6 and are generally based on the assumption that patients are willing and able to deliberately evaluate and weigh characteristics of options (i.e., attributes). Rating exercises do not require tradeoffs between attributes; patients can attach equal importance to all attributes, and therefore, they likely do not provide much insight into order of importance. It has been shown that how patients fill in such rating scales does not always predict their actual health care choices.7 Ranking methods, alternatively, can provide more feedback on what matters most, but it remains questionable to what extent they contribute to values clarity and help in determining preferences. In longer lists of attributes, it is known that people rank attributes adequately at the top and at the bottom, but the middle part of the ranking is more unreliable.8 Moreover, ranking methods possibly require cognitive effort.9