Objective <p>Self-reported medication adherence may be influenced by socially desirable answers and untruthful reporting. Misreporting of adherence behavior can bias estimations of treatment (cost)effectiveness. This study investigated how to induce truthful self-reported medication adherence and evaluated how self-reported (truth-induced vs. regularly reported) medication adherence and treatment preferences were associated.</p> Methods <p>Medication adherence was measured after a discrete choice experiment eliciting stated preferences for Multiple Sclerosis (MS)-treatments. Data was collected among MS-patients in three Western countries. Half of the sample was randomized to ‘choice-matching’, a novel mechanism which induces truthfulness. It financially compensates respondents based on their self-reported adherence and guesses about other respondents’ adherence. To investigate the impact of truth-incentivized adherence reporting on preference heterogeneity, interaction effects between medication adherence and treatment preferences were tested separately within the choice-matching and the ‘standard’ group.</p> Results <p>The sample comprised 380 MS-patients (mean age 41y, 69% female). Respondents in the choice-matching group reported a lower medication adherence compared to the standard group (always adherent: 39.3% vs. 46.6%). Mixed logit models showed significant interaction effects: in the choice-matching group, higher medication adherence resulted in lower utility for pills twice/day compared to injections three times/week (<i>p</i> = 0.019), while in the standard group, respondents with higher medication adherence preferred pills once/day compared to injections three times/week (<i>p</i> = 0.005).</p> Conclusion <p>Choice-matching likely encouraged respondents to report their true medication adherence. Linking truthful behavior to patients’ preferences allows for a better understanding of preference heterogeneity and helping to make decisions that fit patients’ true preferences.</p>

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Association of medication adherence with treatment preferences: incentivizing truthful self-reporting

  • Carina Oedingen,
  • Raf van Gestel,
  • Samare P. I. Huls,
  • Georg Granic,
  • Esther W. de Bekker-Grob,
  • Jorien Veldwijk

摘要

Objective

Self-reported medication adherence may be influenced by socially desirable answers and untruthful reporting. Misreporting of adherence behavior can bias estimations of treatment (cost)effectiveness. This study investigated how to induce truthful self-reported medication adherence and evaluated how self-reported (truth-induced vs. regularly reported) medication adherence and treatment preferences were associated.

Methods

Medication adherence was measured after a discrete choice experiment eliciting stated preferences for Multiple Sclerosis (MS)-treatments. Data was collected among MS-patients in three Western countries. Half of the sample was randomized to ‘choice-matching’, a novel mechanism which induces truthfulness. It financially compensates respondents based on their self-reported adherence and guesses about other respondents’ adherence. To investigate the impact of truth-incentivized adherence reporting on preference heterogeneity, interaction effects between medication adherence and treatment preferences were tested separately within the choice-matching and the ‘standard’ group.

Results

The sample comprised 380 MS-patients (mean age 41y, 69% female). Respondents in the choice-matching group reported a lower medication adherence compared to the standard group (always adherent: 39.3% vs. 46.6%). Mixed logit models showed significant interaction effects: in the choice-matching group, higher medication adherence resulted in lower utility for pills twice/day compared to injections three times/week (p = 0.019), while in the standard group, respondents with higher medication adherence preferred pills once/day compared to injections three times/week (p = 0.005).

Conclusion

Choice-matching likely encouraged respondents to report their true medication adherence. Linking truthful behavior to patients’ preferences allows for a better understanding of preference heterogeneity and helping to make decisions that fit patients’ true preferences.