The Influence of Social and Individual Factors on Medicine Use in Older Adults

Abstract

Objective: To quantitatively explore the social and individual factors (including beliefs, experiences, and health literacy) that may affect medicine use in older adults. Design: A descriptive research approach with quantitative-based methods was used. Individual structured interviews were completed for each participant where they were questioned on any health conditions, medicines, and healthcare utilisation. The following validated questionnaires were implemented in the interview; Beliefs about Medicines Questionnaire, Health Literacy Questionnaire, EQ-5D-5L scale, Barthel Activities of Daily Living Index, Perceived Sensitivity to Medicines Scale, Patients Attitudes Towards Deprescribing, Medication Related Burden Quality of Life, and Adherence to Refills and Medication Scale. Descriptive statistics were calculated using SPSS software. Setting: People ≥65 years living in the community in Australia. Main Outcome Measures: Suboptimal prescribing, including polypharmacy, potentially inappropriate medicines use, and adherence. Results: Twenty-four participants completed the study and reported a mean BMQ necessity score of 11/25, mean specific concerns score of 19/25, mean general overuse score of 12/20 and suggest general harm score of 16/20. Most participants believed that medicines do more harm than good and physicians are overprescribing medicines. The highest scoring HLQ domain was ‘Navigating the healthcare system’, while the lowest scoring domains were ‘social support’ and ‘having sufficient information to manage my health’. Additionally, individual experience was found to be an important factor in participants’ medication attitudes and participants who trusted their prescriber were more likely to adhere to their medication regimen. Conclusion: The influence of beliefs, experiences, and health literacy on medicine use in older adults remains unclear, and future studies will investigate the effects of these factors on a larger sample size.