Health Literacy Level and Comprehension of Prescription and Nonprescription Drug Information

Factors associated with low health literacy in unpaid caregivers of older people: a systematic review

Health literacy is a public health issue. Unpaid caregivers of older people with low health literacy may have difficulties providing care, exerting a negative impact on the care process. The aim of the present study was to perform a systematic review of the literature on factors associated with low health literacy in unpaid caregivers of older people. Searches for relevant articles were conducted in the Cochrane Library, Embase, LILACS, PubMed and Web of Science databases. A total of 1440 articles were identified, nine of which met the eligibility criteria and were included in the systematic review, which was registered in PROSPERO (CRD42024522986). A total of 2209 unpaid caregivers participated in the studies selected for this review. Most were women (67.2%). The average frequency of inadequate health literacy was 27.1%. Sociodemographic characteristics (i.e. advanced age, low educational level, the female sex), factors related to the care process (i.e. low acculturation, low empowerment, poor ability to read medication package inserts, lower care capacity, greater disease severity, hospitalization of care recipients), cognitive factors and factors related to quality of life/well-being (i.e. less social support, poorer quality of life, greater cognitive impairment, higher levels of burden) were associated with low health literacy. In conclusion, low health literacy in unpaid caregivers of older people is associated with sociodemographic, care-related and cognitive factors as well as factors related to quality of life/well-being. Low health literacy may exert a negative impact on the health of caregivers and, consequently, the quality of care provided to older people.

Validating the short-version European Health Literacy Survey Questionnaire for community-dwelling older adults in Japan

The European Health Literacy Survey Questionnaire (HLS-EU-Q47) is available in multiple languages, and shortened versions have also been developed. This study aimed to examine the reliability and validity of the short version of the questionnaire (HLS-Q12) developed for community-dwelling older adults in Japan. The HLS-Q12 was developed using 12 of the 47 items of the Japanese version of the HLS-EU-Q47. In this study, the survey was conducted by distributing self-administered questionnaires to community-dwelling individuals aged 65 years and older who consented to participate; their responses were collected by mail. The correlation between the HLS-Q12 and the HLS-EU-Q47 was tested to assess criterion validity. To test construct validity, nine novel hypotheses were proposed. We also conducted a confirmatory factor analysis of the HLS-Q12. Based on a resurvey after 5-7 days, test-retest reliability was examined using interclass correlation coefficients (ICCs) and Bland-Altman analysis. In total, 118 individuals provided valid responses to the questionnaire. The Spearman rank correlation coefficient between the HLS-Q12 and the HLS-EU-Q47 was r = 0.98 (p < 0.001), and eight of the nine hypotheses were supported. The ICC was 0.96 (p < 0.001), and the 95% limit of agreement was -0.26 ± 5.9, suggesting no systematic error. Thus, the Japanese version of the HLS-Q12 was found to be reliable with high criterion validity and reproducibility. Hence, the HLS-Q12 is a useful scale for measuring health literacy among older adults in Japan.

Trends and Patterns of Systemic Glucocorticoid Prescription in Primary Care Institutions in Southwest China, from 2018 to 2021

Purpose

The purpose of this study was to investigate the prescribing patterns and usage trends of systemic glucocorticoids in primary care institutions located in Southwest China from 2018 to 2021.

Materials and Methods

A retrospective cross-sectional analysis of systemic glucocorticoids prescriptions was conducted in 32 primary care institutions located in Southwest China between 2018 and 2021. Prescriptions of systemic glucocorticoids were classified as appropriate or inappropriate use. Inappropriate use was further classified into (1) inappropriate indications and (2) inappropriate selection of glucocorticoids. Generalized estimation equations were employed to investigate the factors associated with inappropriate utilization of systemic glucocorticoids. The seasonal autoregressive integrated moving average (SARIMA) model was employed to predict the rate of inappropriate glucocorticoids prescriptions.

Results

A total of 203,846 (92.89%) prescriptions were included, both the number of systemic glucocorticoids prescriptions and inappropriate prescriptions increased in winter. Diseases of the respiratory system (68.90%) were the most frequent targets of systemic glucocorticoids use. Of all prescriptions, 73.18% exhibited inappropriate indications, while 0.05% demonstrated inappropriate selection. The utilization of systemic glucocorticoids was deemed inappropriate for diseases of the respiratory system (94.19%), followed by diseases of the digestive system (87.75%). Physicians, who were female or younger than 33 years old, possess lower levels of education and professional titles and exhibit a higher likelihood of inappropriately prescribing systemic glucocorticoids. The phenomenon of inappropriate glucocorticoids use was commoner among male patients aged 65 years and older. After conducting model verification, it was determined that the SARIMA model could be used to predict the monthly rate of inappropriate systemic glucocorticoids prescriptions in primary care institutions in southwest China.

Conclusion

The inappropriate use of systemic glucocorticoids remains a significant concern in primary care institutions. In this regard, continuing education and professional knowledge training of physicians should be strengthened in the future.

Prevalence, associated factors and clinical implications of medication literacy linked to frailty in hemodialysis patients in China: a cross-sectional study

BACKGROUND

Maintenance hemodialysis (MHD) patients have complex medication regimens that require a high level of skill to interpret medication information. However, there is currently a lack of research evaluating the ability to read and understand medication labels in Chinese MHD patients. In addition, the relationship between frailty and medication literacy among MHD patients remains unclear. Therefore, this study aims to assess the potential factors affecting medication literacy in MHD patients and to explore the relationship between frailty and medication literacy.

METHODS

This cross-sectional study was conducted using convenience sampling in West China Hospital of Sichuan University, China. Using a general questionnaire, we collected demographic, clinical and laboratory data. Medication literacy was assessed by the Chinese Medication Literacy Scale, and frailty was assessed by the FRAIL Scale. Univariate analyses examined potential factors associated with medication literacy. An ordered logistic regression was used to analyze the relationships between medication literacy and these factors. Spearman's correlation was used to assess the association between medication literacy and frailty.

RESULTS

A total of 290 MHD patients were included in the analysis. Inadequate, marginal, and adequate medication literacy was found in 56 (19.3%), 153 (52.8%), and 81 (27.9%) patients, respectively. Ordered logistic regression revealed factors associated with inadequate medication literacy: age (OR = 0.281, 95% CI = 0.139-0.565, p < 0.001 for < 65 years); education (OR = 8.612, 95% CI = 3.524-21.046, p < 0.001 for ≤ primary school education; OR = 3.405, 95% CI = 1.683-6.887, p = 0.001 for junior high school education); presence of caregiver medication assistance (OR = 2.302, 95% CI = 1.173-4.516, p = 0.015); frailty (OR = 0.440, 95% CI = 0.216-0.893, p = 0.023 for frail patients); and high β2-microglobulin (β2-MG) (OR = 1.010, 95% CI = 1.002-1.019, p = 0.012). Spearman's analysis showed that medication literacy was negatively correlated with frailty in MHD patients (R=-0.189, p = 0.001).

CONCLUSIONS

Medication literacy levels in MHD patients needed improvement and were associated with certain patient characteristics, including age, education level, presence of caregiver support, β2-microglobulin levels, and risk of frailty. This study identified subgroups of MHD patients, such as those who were older, had lower education, had caregiver assistance, had high β2-microglobulin levels, or were frail, to have inadequate medication literacy. These findings underscore the need for routine screening and targeted interventions to improve medication literacy in this population.

Comprehension of prescription orders with and without pictograms: tool validation and comparative assessment among a sample of participants from a developing country

BACKGROUND

Medication errors can often occur due to the patient's inability to comprehend written or verbal medication orders. This study aimed to develop pictograms of selected medication orders and to validate the comprehension of prescription orders index and compare the comprehension scores with and without pictograms. In addition to determine the predictors that could be associated with a better or worse comprehension of prescription orders with pictograms versus that of their written counterparts.

METHODS

A cross-sectional study was conducted using a snowball sampling technique. Six pictograms were developed to depict specific medication orders. The comprehension of prescription orders index was constructed and validated. The study then compared the comprehension scores of prescription orders with and without pictograms, and identified the predicting factors score difference.

RESULTS

A total of 1848 participants were included in the study. The structure of the comprehension of prescription orders index was validated over a solution of four factors, with an adequate Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy of 0.711 and a significant Bartlett's test of sphericity (P < 0.001). The construct validity of the index was further confirmed by highly significant correlations between each item and the full index (P < 0.001). The study also found a significant association between the difference in comprehension scores for prescription orders with and without pictograms and several factors, including age, level of education, area of residence, number of children, and smoking status with the difference of comprehension scores (P < 0.001).

CONCLUSION

Pictogram-based instructions of medication orders were better understood by the Lebanese population than written instructions, making the incorporation of pictograms in pharmacy practice paramount to optimize medication use by the patient and thus yielding better health outcomes.

Association between health literacy and medication comprehension; attitudes toward reporting adverse events in adults using over-the-counter medicines

BACKGROUND

Self-medication using over-the-counter (OTC) medicines is one of the effective self-care measures in dealing with daily health problems. Health literacy (HL) is critical to ensuring the appropriate use of OTC medicines. The purpose of this study was to evaluate the association between HL and comprehension of medication package inserts among adults who use OTC medicines.

METHODS

We conducted a cross-sectional study using a self-administered questionnaire and interviews at 14 drugstores in the Kanto region in Japan from January to February 2020. The study participants were adults aged 20 years or older who purchased OTC medicines. HL was measured using the 14-item HL scale for Japanese adults (Japanese version of HLS-14), and comprehension of medication package inserts was evaluated using an interview survey (label comprehension study [LCS] form). The association between HL and LCS correct response rate and that between HL and attitude toward reporting adverse drug events (ADEs) were assessed using multiple linear regression and logistic regression analyses, respectively.

RESULTS

The analysis included the data of 140 adults, 50 men (35.7%) and 90 women (64.3%), with an average age of 55.2 years. The average HLS-14 score was 51.6, and the overall correct answer rate for reading comprehension was 57.5%. Multiple linear regression analysis revealed that a higher HLS-14 score was associated a higher LCS correct response rate (β = 1.01, p = 0.001). In addition, logistic regression analysis revealed that higher HL was associated with positive attitude towards reporting ADEs to health professionals (adjusted odds ratio = 1.06, p = 0.031).

CONCLUSIONS

Adults with higher HL had higher comprehension of OTC package inserts, and higher HL was associated with positive attitude toward reporting ADEs to healthcare professionals. These results indicate that optimal self-medication with OTC medicines requires improving HL among the general public through health education and effective health information provision from pharmacists and registered sales clerks at drug stores.

Using machine learning to develop a clinical prediction model for SSRI-associated bleeding: a feasibility study

INTRODUCTION

Adverse drug events (ADEs) are associated with poor outcomes and increased costs but may be prevented with prediction tools. With the National Institute of Health All of Us (AoU) database, we employed machine learning (ML) to predict selective serotonin reuptake inhibitor (SSRI)-associated bleeding.

METHODS

The AoU program, beginning in 05/2018, continues to recruit ≥ 18 years old individuals across the United States. Participants completed surveys and consented to contribute electronic health record (EHR) for research. Using the EHR, we determined participants who were exposed to SSRIs (citalopram, escitalopram, fluoxetine, fluvoxamine, paroxetine, sertraline, vortioxetine). Features (n = 88) were selected with clinicians' input and comprised sociodemographic, lifestyle, comorbidities, and medication use information. We identified bleeding events with validated EHR algorithms and applied logistic regression, decision tree, random forest, and extreme gradient boost to predict bleeding during SSRI exposure. We assessed model performance with area under the receiver operating characteristic curve statistic (AUC) and defined clinically significant features as resulting in > 0.01 decline in AUC after removal from the model, in three of four ML models.

RESULTS

There were 10,362 participants exposed to SSRIs, with 9.6% experiencing a bleeding event during SSRI exposure. For each SSRI, performance across all four ML models was relatively consistent. AUCs from the best models ranged 0.632-0.698. Clinically significant features included health literacy for escitalopram, and bleeding history and socioeconomic status for all SSRIs.

CONCLUSIONS

We demonstrated feasibility of predicting ADEs using ML. Incorporating genomic features and drug interactions with deep learning models may improve ADE prediction.