Impact of a pharmacist-led intervention on prostate cancer illness perception.

Abstract

Purpose: Illness perception (IP) significantly determines illness outcomes. This study determined the impact of a pharmacist educational intervention on IP and the predictors of IP in patients with prostate cancer (PCa).

Methods: Using a brief IP questionnaire, an interventional study of patients with PCa was conducted in all cancer reference hospitals in one Nigerian state. After a pre-post assessment of patients' IP, descriptive and inferential statistical analyses were performed. The impact of pharmacists' intervention on IP was determined by paired-sample statistics and correlation analysis at the 95% CI. Relationships and predictors of IP were determined using Kendall's tau-b (τb), likelihood ratio, and F tests of equality of means, respectively. P < 0.05 was considered statistically significant.

Results: Pharmacists' educational intervention significantly improved IP (SEM, 0.13; r = 0.875; P < 0.0001) among the 200 participants. The analyses also showed a significant paired sample difference (2.662; SEM, 0.06; 95%CI, 2.536-2.788; t = 41.69; df = 199; P < 0.0001). All subscales of patients' IP significantly improved except for illness consequences (P = 0.173) and identity (mean [SD], 4.40 [3.730] in both pre- and postintervention assessments). Pre- and postintervention assessments showed a significant negative relationship of IP with age (τb = -110 [P = 0.040] and τb = -14 [P = 0.021], respectively), Gleason score (τb = -0.125 [P = 0.021] and τb = -0.124 [P=0.012], respectively), and age at diagnosis (τb = -0.103 [P = 0.036] post intervention). IP was significantly dependent on the drug therapy (df = 8; mean square [M] = 6.292; F = 2.825; P = 0.006), alcohol intake (df = 1; M = 9.608; F = 4.082; P = 0.045) and Gleason score (df = 9; M = 6.706; F = 3.068; P = 0.002).

Conclusion: Patients' IP significantly improved after pharmacists' educational intervention. Predictors of IP were drug therapies, alcohol use and Gleason score. Findings can be extrapolated in clinical settings to improve treatment outcomes.