Factors associated with the accuracy of physicians' predictions of patient adherence

L. Alison Phillips, Elaine A. Leventhal, Howard Leventhal

Research output: Contribution to journalArticlepeer-review

24 Scopus citations


Objective: Physicians are inaccurate in predicting non-adherence in patients, a problem that interferes with physicians': (1) appropriate prescribing decisions and (2) effective prevention/intervention of non-adherence. The purpose of the current study is to investigate potential reasons for the poor accuracy of physicians' adherence-predictions and conditions under which their predictions may be more accurate. Methods: After the medical encounter, predictions of patient-adherence and other ratings from primary-care physicians (n= 24) regarding patient-factors that may have influenced their predictions were collected. Patients (n= 288) rated their agreement regarding the prescribed treatment after the encounter and reported adherence 1 month later. Results: Several factors were related to physicians' adherence-predictions, including physicians' perceptions of patient-agreement regarding treatment. However, some factors were not related to adherence and agreement-perceptions were inaccurate overall, potentially contributing to the poor accuracy of adherence-predictions. The degree to which physicians discussed treatment-specifics with the patient moderated agreement-perception accuracy but not adherence-prediction accuracy. Conclusions: Training providers to discuss certain treatment-specifics with patients may improve their ability to perceive patient-agreement regarding treatment and may directly improve patient-adherence. Practice implications: Discussing treatment-specifics with patients may directly improve adherence, but providers should not rely on these discussions to give them accurate estimates of the patients' likely adherence.

Original languageEnglish (US)
Pages (from-to)461-467
Number of pages7
JournalPatient Education and Counseling
Issue number3
StatePublished - Dec 2011

All Science Journal Classification (ASJC) codes

  • Medicine(all)


  • Patient adherence
  • Patient beliefs
  • Perceived agreement
  • Physician predictions


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