DESIGN: Systematic review and regression analysis.
ELIGIBILITY: Medication adherence levels studied at primary, secondary and tertiary care settings. Self-reported measures with scoring methods were included. Studies without proxy measures were excluded.
DATA SOURCES: Using detailed searches with key concepts including questionnaires, reliability and validity, and restricted to English, MEDLINE, EMBASE, CINAHL, International Pharmaceutical Abstracts, and Cochrane Library were searched until 01 March 2022. Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 (PRISMA-2020) checklist was used.
DATA ANALYSIS: Risk of bias was assessed via COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN-2018) guidelines. Narrative synthesis aided by graphical figures and statistical analyses.
OUTCOME MEASURES: Process domains [behaviour (e.g., self-efficacy), barrier (e.g., impaired dexterity) or belief (e.g., perception)], and overall outcome domains of either intentional (I), unintentional (UI), or mixed non-adherence.
RESULTS: Paper summarises evidence from 59 studies of PROMs, validated among patients aged 18-88 years in America, the United Kingdom, Europe, Middle East, and Australasia. PROMs detected outcome domains: intentional non-adherence, n=44 (I=491 criterion items), mixed intentionality, n=13 (I=79/UI=50), and unintentional, n=2 (UI=5). Process domains detected include belief (383 criterion items), barrier (192) and behaviour (165). Criterion validity assessment used proxy measures (biomarkers, e-monitors), and scoring was ordinal, dichotomised, or used Visual Analogue Scale. Heterogeneity was revealed across psychometric properties (consistency, construct, reliability, discrimination ability). Intentionality correlated positively with negative beliefs (r(57)=0.88) and barriers (r(57)=0.59). For every belief or barrier criterion-item, PROMs' aptitude to detect intentional non-adherence increased by β=0.79 and β=0.34 units, respectively (R2=0.94). Primary care versus specialised care predicted intentional non-adherence (OR 1.9; CI 1.01 to 2.66).
CONCLUSIONS: Ten PROMs had adequate psychometric properties. Of the ten, eight PROMs were able to detect total, and two PROMs were able to detect partial intentionality to medication default. Fortification of patients' knowledge and illness perception, as opposed to daily reminders alone, is most imperative at primary care levels.
METHODS: This cross-sectional survey was conducted among community pharmacists and pharmacy technicians in the capital of Yemen, Sana'a. A total of 289 community pharmacies were randomly selected. The validated and pilot-tested questionnaire consisted of six sections: demographic data, knowledge about pharmacovigilance, experience with ADR reporting, attitudes toward ADR reporting, and the facilitators to improve ADR reporting.
RESULTS: A total of 428 pharmacy technicians and pharmacists were contacted and 179 went on to complete a questionnaire (response rate: 41.8%). Of the 179 respondents, 21 (11.7%) were pharmacists and 158 (88.3%) were pharmacy technicians, of which, 176 (98.3%) were male and 3 (1.7%) were female. The mean age of the respondents was 25.87±2.63 years. There was a significant difference between the pharmacists and pharmacy technicians in terms of knowledge scores (P<0.05). The mean knowledge scores for pharmacists was 3.33±2.852 compared to 0.15±0.666 for pharmacy technicians. With regard to attitudes toward ADR reporting, all pharmacists (100%) showed a positive attitude, while only 43% of pharmacy technicians showed a positive attitude.
CONCLUSION: Pharmacists have a significantly better knowledge than pharmacy technicians with regard to pharmacovigilance. More than half of pharmacy technicians showed a negative attitude toward ADR reporting. Therefore, educational interventions and training is very important for community pharmacists and pharmacy technicians in Yemen to increase their awareness and participation in ADR reporting.