title: A cohort study of possible risk factors for over-reporting of antihypertensive adherence.
abstract: BACKGROUND
  The identification of poor medicinal adherence is difficult because direct observation of medication use is usually impractical. Up to 50% of individuals on chronic therapies may not be taking their medication as prescribed. This study is one of the first to explore possible risk factors for over-reporting of antihypertensive adherence using electronic medication monitoring.
  
  
  METHODS
  The adherence of 286 individuals on single-drug antihypertensive therapy in a large managed care organization was electronically monitored for approximately three months. Questionnaires on socioeconomic background, adherence to therapy, health beliefs, and social support before and after adherence monitoring were completed. Over-reporting of antihypertensive adherence was assessed by comparing the self-reported frequency of noncompliance with that determined from electronic dosing records. Risk factors for over-reporting were identified by contingency table analysis and step-wise logistic regression.
  
  
  RESULTS
  Although only 21% of participants acknowledged missing doses on one or more days per week, electronic monitoring documented nonadherence at this or a higher level in 42% of participants. The following variables were associated with over-reporting: >1 versus 1 daily dose (OR = 2.58; 95% CI = 1.50-4.41; p =.0006), lower perceived health risk from nonadherence (OR = 1.35; 95% CI = 1.10-1.64; p =.0035), and annual household income of <15,000 dollars versus >30,000 dollars (OR = 2.64; 95% CI = 1.13-6.18; p =.025).
  
  
  CONCLUSIONS
  Over-reporting of adherence may be affected by factors related to dosing frequency, health beliefs and socioeconomic status. This topic deserves further investigation in other patient populations to elucidate possible underlying behavioral explanations.
authors.affiliation: Channing Laboratory, Department of Medicine, Brigham and Women's' Hospital, Harvard Medical School, Boston, MA, USA. peter.choo@channing.harvard.edu
authors.forename: P W
authors.initials: PW
authors.lastname: Choo
authors.forename: C S
authors.initials: CS
authors.lastname: Rand
authors.forename: T S
authors.initials: TS
authors.lastname: Inui
authors.forename: M L
authors.initials: ML
authors.lastname: Lee
authors.forename: C
authors.initials: C
authors.lastname: Canning
authors.forename: R
authors.initials: R
authors.lastname: Platt
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000959:Antihypertensive Agents / Q000008:administration & dosage; D001294:Attitude to Health; D015331:Cohort Studies; D005260:Female; D006801:Humans; D016013:Likelihood Functions; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D010349:Patient Compliance / Q000706:statistics & numerical data*; D012307:Risk Factors; D012959:Socioeconomic Factors; D011795:Surveys and Questionnaires; D016312:Treatment Refusal / Q000706:statistics & numerical data*
chemical_list: D000959:Antihypertensive Agents