The uncertainties around disease management and control measures have not only motivated clinicians to keep abreast of new evidence available in the scholarly literature, but also to be rigorously engaged in medical research, dissemination and knowledge transfer. We aimed to explore clinicians’ publication output from the Malaysian perspective. A self-report survey and bibliometric analysis was conducted. A total of 201/234 clinicians participated in the survey. Items consisted of demographics, researching habits, publication output and level of importance of journal selection metrics. Descriptive, bivariate and multivariate analyses were conducted. Bibliometric analysis using retrieved records from PubMed between 2009 and October 2019 was conducted and co-occurrence and co-authorship analyses were executed. Self-reported publication output was 16.9%. In the logistic regression model, publication output was significantly higher amongst consultants or clinical specialists (aOR = 2.5, 95% CI 1.1–10.0, p = 0.023); clinicians previously involved in research (aOR = 4.2, 95% CI 1.5–11.4, p = 0.004); clinicians who ever used reference citation managers (aOR = 3.2, 95% CI 1.3–7.7, p = 0.010); and journal publication speed (aOR = 2.9, 95% CI 1.2–7.1, p = 0.019). Most clinicians published original research papers (76.4%) in international journals (78.2%). Published papers were mostly observational studies, genetic, stroke and health services or systems research. In conclusion, socio-demographics, researching habits and journal selection metrics were significantly associated with self-reported publication output. Real outputs from bibliometrics were predominantly focused across five clusters.

Stroke has emerged as a major public health concern in Malaysia. We aimed to determine the trends and temporal associations of real-time health information-seeking behaviors (HISB) and stroke incidences in Malaysia. We conducted a countrywide ecological correlation and time series study using novel internet multi-timeline data stream of 6,282 hit searches and conventional surveillance data of 14,396 stroke cases. We searched popular search terms related to stroke in Google Trends between January 2004 and March 2019. We explored trends by comparing average relative search volumes (RSVs) by month and weather through linear regression bootstrapping methods. Geographical variations between regions and states were determined through spatial analytics. Ecological correlation analysis between RSVs and stroke incidences was determined via Pearson’s correlations. Forecasted model was yielded through exponential smoothing. HISB showed both cyclical and seasonal patterns. Average RSV was significantly higher during Northeast Monsoon when compared to Southwest Monsoon (P < 0.001). “Red alerts” were found in specific regions and states. Significant correlations existed within stroke related queries and actual stroke cases. Forecasted model showed that as HISB continue to rise, stroke incidence may decrease or reach a plateau. The results have provided valuable insights for immediate public health policy interventions.

Background and objectives: The cumulative time spent without medical intervention in acute stroke patients may affect clinical outcomes. As the onset-to-arrival time to the hospital is crucial for effective treatment interventions, this study aimed to explore the factors associated with pre-hospital delays amongst acute stroke patients. Methods: We explored 932 patients data retrieved from the National Neurology Registry of Seberang Jaya Hospital between January 2013 and December 2018. Data on patient demographics and stroke manifestations were analysed using descriptive, univariate and multivariate logistic regressions. Results: Most patients were men (62.9%) with an average age of 62 years old. In the final multivariate regression model, pre-hospital delay was significantly lower among Chinese patients (aOR=0.6, 95% CI 0.4–0.9, p=0.016) and those using hospital ambulance (aOR=0.4, 95% CI 0.3–0.7, p<0.001), but higher among patients with lacunar infarcts (aOR=2.5, 95% CI 1.4–3.3; p<0.001). Conclusions: Demographic characteristic (ethnicity) and stroke manifestations, particularly stroke subtypes, and mode of transport were mainly associated with pre-hospital delays among acute stroke patients.