Academic information on Twitter: A user survey

Although counts of tweets citing academic papers are used as an informal indicator of interest, little is known about who tweets academic papers and who uses Twitter to find scholarly information. Without knowing this, it is difficult to draw useful conclusions from a publication being frequently tweeted. This study surveyed 1,912 users that have tweeted journal articles to ask about their scholarly-related Twitter uses. Almost half of the respondents (45%) did not work in academia, despite the sample probably being biased towards academics. Twitter was used most by people with a social science or humanities background. People tend to leverage social ties on Twitter to find information rather than searching for relevant tweets. Twitter is used in academia to acquire and share real-time information and to develop connections with others. Motivations for using Twitter vary by discipline, occupation, and employment sector, but not much by gender. These factors also influence the sharing of different types of academic information. This study provides evidence that Twitter plays a significant role in the discovery of scholarly information and cross-disciplinary knowledge spreading. Most importantly, the large numbers of non-academic users support the claims of those using tweet counts as evidence for the non-academic impacts of scholarly researc

Change in health literacy over a decade in a prospective cohort of community-dwelling older adults

BACKGROUND: Health literacy is often viewed as a static trait in longitudinal studies, which may over or underestimate an individual’s ability to manage one’s health. OBJECTIVES: We sought to examine health literacy over time among older adults using three widely used measures. DESIGN: A prospective cohort study. PARTICIPANTS: Community-dwelling adults ages 55 to 74 at baseline with at least one follow-up visit (N = 656) recruited from one academic internal medicine clinic and six community health centers in Chicago, IL. MEASURES: Health literacy was measured using the Test of Functional Health Literacy in Adults (TOFHLA), Newest Vital Sign (NVS), and Rapid Estimate of Adult Literacy in Medicine (REALM) at baseline and up to three follow-up time points. RESULTS: In unadjusted analyses, significant changes since baseline were found beginning at the second follow-up (mean (M) = 6.0 years, SD = 0.6) for the TOFHLA (M = − 0.9, SD = 0.95, p = 0.049) and the REALM (M = 0.3, SD = 2.5, p = 0.004) and at the last follow-up (M = 8.6 years, SD = 0.5) for the NVS (M = − 0.2, SD = 1.4, p = 0.02). There were non-linear effects of baseline age on TOFHLA and NVS scores over time (piecewise cubic spline p = 0.01 and p < 0.001, respectively) and no effect on REALM scores (B = 0.02, 95% CI − 0.01 to 0.04, p = 0.17) using multivariable mixed-effects linear regression models, controlling for race, education, income, and comorbidity. CONCLUSION: We found a negative relationship between age and health literacy over time as measured by the TOFHLA and NVS. Health literacy barriers appear to be more prevalent among individuals in later life, when self-care demands are similarly increasing. Clinicians might consider strategies to assess and respond to limited health literacy, particularly among patients 70 and older. REALM performance remained stable over 10 years of follow-up. This questions whether health literacy tools measure the same attribute. Prospective health literacy studies should carefully consider what measures to use, depending on their objective

The electronic medication complete communication (EMC2) study: Rationale and methods for a randomized controlled trial of a strategy to promote medication safety in ambulatory care

AbstractBackgroundAdverse drug events (ADEs) affect millions of patients annually and place a significant burden on the healthcare system. The Food and Drug Administration (FDA) has developed patient safety information for high-risk medications that pose serious public health concerns. However, there are currently few assurances that patients receive this information or are able to identify or respond correctly to ADEs.ObjectiveTo evaluate the effectiveness of the Electronic Medication Complete Communication (EMC2) Strategy to promote safe medication use and reporting of ADEs in comparison to usual care.MethodsThe automated EMC2 Strategy consists of: 1) provider alerts to counsel patients on medication risks, 2) the delivery of patient-friendly medication information via the electronic health record, and 3) an automated telephone assessment to identify potential medication concerns or ADEs. The study will take place in two community health centers in Chicago, IL. Adult, English or Spanish-speaking patients (N=1200) who have been prescribed a high-risk medication will be enrolled and randomized to the intervention arm or usual care based upon practice location. The primary outcomes of the study are medication knowledge, proper medication use, and reporting of ADEs; these will be measured at baseline, 4weeks, and three months. Intervention fidelity as well as barriers and costs of implementation will be evaluated.ConclusionsThe EMC2 Strategy automates a patient-friendly risk communication and surveillance process to promote safe medication use while minimizing clinic burden. This trial seeks to evaluate the effectiveness and feasibility of this strategy in comparison to usual care

Cut points on the Patient Health Questionnaire (PHQ-9) that predict response to cognitive-behavioral treatments for depression

Objective: Monitoring depressive symptoms during treatment can guide clinical decision making and improve outcomes. The aim of this study was to explore values on the Patient Health Questionnaire (PHQ-9) that could predict response to treatment. Method: Data came from two independent trials, including three treatment modalities of cognitive–behavioral treatment for depression. Four hundred eighty-seven participants who either met the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition criteria for major depressive disorder or had PHQ-9 scores consistent with a diagnosis of depression were included in our analyses. Participants either received 18 weeks of telephone or face-to-face (n= 279) or 8 weeks of Web-delivered (n= 208) cognitive–behavioral therapy. Depressive symptoms, evaluated using the PHQ-9, were reported every 4 weeks in the telephone and face-to-face trial and weekly in the Web-delivered intervention trial. Results: Optimal cut points for predicting end-of-treatment response were consistent in both trials. Our results suggested using cut points of a PHQ-9 ≥ 17 at Week 4, and PHQ-9 ≥ 13 at Week 9 and PHQ-9 ≥ 9 at Week 14. Conclusions: Consistent cut points were found within the included trials. These cut points may be valuable for algorithms to support clinical decision making.6 page(s