ObjectivesThe disease burden of type 2 diabetes mellitus (T2DM) is rising due to suboptimal glycaemic control leading to vascular complications. Medication adherence (MA) directly influences glycaemic control and clinical consequences. This study aimed to assess the MA of patients with T2DM and identify associated factors.DesignAnalysis of data from a cross-sectional survey and electronic medical records.SettingPrimary care outpatient clinic in Singapore.ParticipantsAdult patients with T2DM.Main outcome measuresMA to each prescribed oral hypoglycaemic agent (OHA) was measured using the five-question Medication Adherence Report Scale (MARS-5). Low MA is defined as a MARS-R score of <25. Demographic data, clinical characteristics and investigation results were collected to identify factors that are associated with low MA.ResultsThe study population comprised 382 patients with a slight female predominance (53.4%) and a mean±SD age of 62.0±10.4 years. 57.1% of the patients had low MA to at least one OHA. Univariate analysis showed that patients who were younger, of Chinese ethnicity, married or widowed, self-administering their medications or taking fewer (four or less) daily medications tended to have low MA to OHA. Logistic regression revealed that younger age (OR 0.97; 95% CI 0.95 to0.99), Chinese ethnicity (OR 2.80; 95% CI 1.53 to5.15) and poorer glycaemic control (HbA1c level) (OR 1.27; 95% CI 1.06 to1.51) were associated with low MA to OHA.ConclusionsYounger patients with T2DM and of Chinese ethnicity were susceptible to low MA to OHA, which was associated with poorer glycaemic control. Polytherapy was not associated with low MA.

Abstract Background Potentially inappropriate prescribing (PIP) may not have received as much attention in primary care settings (compared to tertiary hospital and nursing home settings), due to uncertainty about its prevalence in this healthcare setting. We conducted a systematic review with meta-analysis to summarise the prevalence of PIP specific to primary care settings and computed the population attributable risk (PAR) to estimate the impact of PIP in primary care. Method We searched PubMed, Embase, CINAHL, Web of Science, Scopus, PsycINFO and previous review articles for studies related to ‘older persons’, ‘primary care’ and ‘inappropriate prescribing’. Two reviewers selected eligible articles, extracted data and evaluated risk of bias. Multilevel meta-analysis was conducted to pool the prevalence estimates across the included studies, while meta-regression was conducted to investigate the sources of heterogeneity. Results Of the 4,259 articles identified, we included 67 articles with 111 prevalence estimates and a total of 5,054,975 participants. Overall, PIP had a pooled prevalence of 33.3% (95% CI 29.7–37.0%). Based on population attributable risks, PIP explained 7.7–17.3% of adverse outcomes related to older persons in primary care. If current PIP prevalence is halved, 37–79 cases of adverse outcomes may potentially be prevented (per 1,000 adverse outcomes). Conclusions The findings demonstrate the relevance and potential impact of PIP specific to primary care settings. Given the increasingly central role that primary care plays in coordinating healthcare, the findings highlight the need to prioritise PIP intervention in primary care as a key strategy to reduce iatrogenic medication-related harm among older persons in current healthcare system.

PURPOSE Potentially inappropriate prescribing (PIP) is a common yet preventable medical error among older persons in primary care. It is uncertain whether PIP produces adverse outcomes in this population, however. We conducted a systematic review with meta-analysis to pool the adverse outcomes of PIP specific to primary care. METHOD We searched PubMed, Embase, CINAHL, Web of Science, Scopus, PsycINFO, and previous review articles for studies related to "older persons," "primary care," and "inappropriate prescribing." Two reviewers selected eligible articles, extracted data, and evaluated the risk of bias. Meta-analysis was conducted to pool studies with similar PIP criteria and outcome measures. RESULTS Of the 2,804 articles identified, we included 8 articles with a total of 77,624 participants. All included studies had cohort design and low risk of bias. Although PIP did not affect mortality (risk ratio [RR] 0.98; 95% CI, 0.93-1.05), it was significantly associated with the other available outcomes, including emergency room visits (RR 1.63; 95% CI, 1.32-2.00), adverse drug events (RR 1.34; 95% CI, 1.09-1.66), functional decline (RR 1.53; 95% CI, 1.08-2.18), health-related quality of life (standardized mean difference-0.26; 95% CI,-0.36 to-0.16), and hospitalizations (RR 1.25; 95% CI, 1.09-1.44). A majority of the pooled estimates had negligible heterogeneity. CONCLUSIONS This meta-analysis provides consolidated evidence on the wideranging impact of PIP among older persons in primary care. It highlights the need to identify PIP in primary care, calls for further research on PIP interventions in primary care, and points to the need to consider potential implications when deciding on the operational criteria of PIP.

Background Although COVID-19 vaccines have recently become available, efforts in global mass vaccination can be hampered by the widespread issue of vaccine hesitancy. Objective The aim of this study was to use social media data to capture close-to-real-time public perspectives and sentiments regarding COVID-19 vaccines, with the intention to understand the key issues that have captured public attention, as well as the barriers and facilitators to successful COVID-19 vaccination. Methods Twitter was searched for tweets related to “COVID-19” and “vaccine” over an 11-week period after November 18, 2020, following a press release regarding the first effective vaccine. An unsupervised machine learning approach (ie, structural topic modeling) was used to identify topics from tweets, with each topic further grouped into themes using manually conducted thematic analysis as well as guided by the theoretical framework of the COM-B (capability, opportunity, and motivation components of behavior) model. Sentiment analysis of the tweets was also performed using the rule-based machine learning model VADER (Valence Aware Dictionary and Sentiment Reasoner). Results Tweets related to COVID-19 vaccines were posted by individuals around the world (N=672,133). Six overarching themes were identified: (1) emotional reactions related to COVID-19 vaccines (19.3%), (2) public concerns related to COVID-19 vaccines (19.6%), (3) discussions about news items related to COVID-19 vaccines (13.3%), (4) public health communications about COVID-19 vaccines (10.3%), (5) discussions about approaches to COVID-19 vaccination drives (17.1%), and (6) discussions about the distribution of COVID-19 vaccines (20.3%). Tweets with negative sentiments largely fell within the themes of emotional reactions and public concerns related to COVID-19 vaccines. Tweets related to facilitators of vaccination showed temporal variations over time, while tweets related to barriers remained largely constant throughout the study period. Conclusions The findings from this study may facilitate the formulation of comprehensive strategies to improve COVID-19 vaccine uptake; they highlight the key processes that require attention in the planning of COVID-19 vaccination and provide feedback on evolving barriers and facilitators in ongoing vaccination drives to allow for further policy tweaks. The findings also illustrate three key roles of social media in COVID-19 vaccination, as follows: surveillance and monitoring, a communication platform, and evaluation of government responses.

Although interventions for caregiver depression in dementia are effective in general, the different components of interventions may not share the same efficacy and acceptability. In implementing interventions, policymakers may consider addressing CC first, introducing CN in a graded manner, and providing ES only when indicated. Future studies may also consider using network meta-analysis to gain additional insights on how to implement multicomponent interventions in geriatric care.