Abstract
Objective: This study aimed to develop and validate a self-reporting adherence tool termed as General Medication Adherence Scale (GMAS) in Urdu language for measuring adherence toward medication use among Pakistani patients with a chronic disease.Methods: A month-long study (December 2017) was conducted in three tertiary health care settings of Karachi, Pakistan. The tool underwent content and face validity as well as factor analyses, i.e., exploratory, partial confirmatory and confirmatory factor analyses. Random sampling was conducted, and sample size was calculated using item response theory. The item-to-respondent ratio was 1:15. Fit indices namely normed fit index (NFI), Tucker Lewis index (TLI), comparative fit index (CFI), goodness of fit index (GFI), absolute goodness of fit (AGFI), parsimony goodness of fit index (PGFI), root mean square error of approximation (RMSEA), and standard root mean square residual (SRMR) were calculated. Additionally, estimation of the convergent, discriminant and known group validities, was conducted. Internal consistency was analyzed by test-retest reliability, McDonald’s and Pearson correlation coefficient. The factor analyses were conducted using IBM SPSS version 22 and IBM SPSS AMOS version 25.Results: Content validity index (CVI) was reported at 0.8 (SD 0.147) and the tool was content validated with three hypothetical constructs. Factor analyses highlighted a 3-factor structure. The fit indices were calculated with satisfactory results, i.e., PGFI, GFI, AGFI, NFI, TLI, and CFI were greater than 0.9 and PGFI > 0.5. The values of RMSEA and SRMR were less than 0.07. A Cronbach’s alpha value of 0.84 was obtained in reliability analysis. The test-retest Pearson’s correlation coefficient value was reported at 0.996 (p-value < 0.01). Convergent and discriminant validities for all constructs and, known group validity for two constructs, were established. A high response rate of 91% was achieved in respondents. Patients without insurance coverage appeared to be low adherent compared to those with insurance coverage (p-value < 0.05). Non-comorbid patients were more likely to be highly adherent as compared to comorbid patients (p-value < 0.01).Conclusion: A novel tool GMAS was developed in Urdu language and was subsequently validated in patients with chronic diseases.
Highlights
Patient adherence to medications is a challenging issue faced by the healthcare providers around the globe
Non-adherence to medication therapy may increase the likelihood of suffering from adverse treatment outcomes
Every chronic illness patient visiting out-patient departments (OPDs) and out-patient pharmacy, with a medical record number (MRN) ending with an odd number, was invited to participate in the study
Summary
Patient adherence to medications is a challenging issue faced by the healthcare providers around the globe. Non-adherence to medication therapy may increase the likelihood of suffering from adverse treatment outcomes This could result in increased hospital admissions and financial costs that are incurred on patients as well as the healthcare system (Iuga and McGuire, 2014). Around 3–10% of avoidable healthcare cost in United States has been reported to be linked to non-adherence (Benjamin, 2012; Iuga and McGuire, 2014) This cost varies with diseases, patient traits and insurance coverage. Measuring adherence to medications is essential to monitor treatment goals and understand patient psyche This may be affected by patient behavior in response to factors such as comorbidity, additional pill burden, regime complexity and financial barriers (Martin et al, 2005; Viana et al, 2014). It may be difficult to predict these factors with conventional techniques
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