Faculty Bibliography

Although there is a large amount of user-generated content about urological health issues on social media, much of this content has not been vetted for information accuracy. In this article, we review the literature on the quality and balance of information on urological health conditions on social networks. Across a wide range of benign and malignant urological conditions, studies show a substantial amount of commercial, biased and/or inaccurate information present on popular social networking sites. The healthcare community should take proactive steps to improve the quality of medical information on social networks. PATIENT SUMMARY: In this review, we examined the spread of misinformation about urological health conditions on social media. We found that a significant amount of the circulating information is commercial, biased or misinformative.

BACKGROUND:Little is known about the key composition of a successful tweet in urology. OBJECTIVE:To investigate for predictors of engagement with urology content on Twitter. DESIGN, SETTING, AND PARTICIPANTS/METHODS:This was a cross-sectional study based on 2-wk Twitter data surrounding a major international urology conference. INTERVENTION/METHODS:We examined the engagement for all original tweets containing the hashtags for the European Association of Urology conference ("#EAU19" and/or "#EAU2019"). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS/UNASSIGNED:Study outcomes included engagement with tweets, as measured by the number of "likes" and "retweets." Tweet- and Twitter user-related parameters of each individual tweet were recorded. Multiple linear regression analyses were performed to investigate for predictors of likes and retweets. RESULTS AND LIMITATIONS/CONCLUSIONS:From March 9 to 22, 2019, there were a total of 37 222 tweets. Among them, 3534 were "original tweets" that had 31 889 likes and 10 031 retweets. On multivariable analysis, the word count, number of mentions, and presence of a photo were predictors of likes and retweets. An increasing number of hashtags were associated with fewer likes. The number of "followings" and "followers" of the contributor, and their time since joining Twitter did not have any associations with the number of likes or retweets. The major limitation of the study is the lack of assessment about the quality of the tweet content. CONCLUSIONS:Based on the Twitter data from a urology conference, we concluded that the word count, number of mentions, and presence of a photo within the tweet were associated with audience engagement. PATIENT SUMMARY/UNASSIGNED:We could engage the audience more successfully by increasing the number of words and mentions, and including a photo within a tweet. The results formulated the basic principles in creating successful tweets for sharing urological knowledge.

PURPOSE OF REVIEW/OBJECTIVE:This review summarizes the most recent and innovative implementation strategies for hypertension control in low- and middle-income countries (LMICs). RECENT FINDINGS/RESULTS:Implementation strategies from Latin America, Africa, and Asia were organized across three levels: community, health system, and policy/population. Multicomponent interventions involving task-shifting strategies, with or without mobile health tools, had the most supporting evidence, with policy or population-level interventions having the least, focused only on salt reduction with mixed results. More research is needed to better understand how context affects intervention implementation. There is an emerging evidence base for implementation strategies for hypertension control and CVD risk reduction in LMICs at the community and health system levels, but further research is needed to determine the most effective policy and population-level strategies. How to best account for local context in adapting and implementing these evidence-based interventions in LMICs still remains largely unknown. Accelerating the translation of this implementation research into policy and practice is imperative to improve health and save lives globally.

BACKGROUND:Non-communicable disease (NCD) care in Sub-Saharan Africa is challenging due to barriers including poverty and insufficient health system resources. Local culture and context can impact the success of interventions and should be integrated early in intervention design. Human-centered design (HCD) is a methodology that can be used to engage stakeholders in intervention design and evaluation to tailor-make interventions to meet their specific needs. METHODS:We created a Design Team of health professionals, patients, microfinance officers, community health workers, and village leaders. Over 6 weeks, the Design Team utilized a four-step approach of synthesis, idea generation, prototyping, and creation to develop an integrated microfinance-group medical visit model for NCD. We tested the intervention with a 6-month pilot and conducted a feasibility evaluation using focus group discussions with pilot participants and community members. RESULTS:Using human-centered design methodology, we designed a model for NCD delivery that consisted of microfinance coupled with monthly group medical visits led by a community health educator and a rural clinician. Benefits of the intervention included medication availability, financial resources, peer support, and reduced caregiver burden. Critical concerns elicited through iterative feedback informed subsequent modifications that resulted in an intervention model tailored to the local context. CONCLUSIONS:Contextualized interventions are important in settings with multiple barriers to care. We demonstrate the use of HCD to guide the development and evaluation of an innovative care delivery model for NCDs in rural Kenya. HCD can be used as a framework to engage local stakeholders to optimize intervention design and implementation. This approach can facilitate the development of contextually relevant interventions in other low-resource settings. TRIAL REGISTRATION/BACKGROUND:Clinicaltrials.gov, NCT02501746, registration date: July 17, 2015.

Increasing urbanization is having a profound effect on infectious disease risk, posing significant challenges for governments to allocate limited resources for their optimal control at a sub-city scale. With recent advances in data collection practices, empirical evidence about the efficacy of highly localized containment and intervention activities, which can lead to optimal deployment of resources, is possible. However, there are several challenges in analyzing data from such real-world observational settings. Using data on 3.9 million instances of seven dengue vector containment activities collected between 2012 and 2017, here we develop and assess two frameworks for understanding how the generation of new dengue cases changes in space and time with respect to application of different types of containment activities. Accounting for the non-random deployment of each containment activity in relation to dengue cases and other types of containment activities, as well as deployment of activities in different epidemiological contexts, results from both frameworks reinforce existing knowledge about the efficacy of containment activities aimed at the adult phase of the mosquito lifecycle. Results show a 10% (95% CI: 1-19%) and 20% reduction (95% CI: 4-34%) reduction in probability of a case occurring in 50 meters and 30 days of cases which had Indoor Residual Spraying (IRS) and fogging performed in the immediate vicinity, respectively, compared to cases of similar epidemiological context and which had no containment in their vicinity. Simultaneously, limitations due to the real-world nature of activity deployment are used to guide recommendations for future deployment of resources during outbreaks as well as data collection practices. Conclusions from this study will enable more robust and comprehensive analyses of localized containment activities in resource-scarce urban settings and lead to improved allocation of resources of government in an outbreak setting.

BACKGROUND:The seminal Dietary Approaches to Stopping Hypertension (DASH) study demonstrated the effectiveness of diet to control hypertension; however, the effective implementation and dissemination of its principles have been limited. OBJECTIVE:This study aimed to determine the feasibility and effectiveness of a DASH mobile health intervention. We hypothesized that combining Bluetooth-enabled data collection, social networks, and a human coach with a smartphone DASH app (DASH Mobile) would be an effective medium for the delivery of the DASH program. METHODS:We conducted a single-arm pilot study from August 2015 through August 2016, using a pre-post evaluation design to evaluate the feasibility and preliminary effectiveness of a smartphone version of DASH that incorporated a human health coach. Participants were recruited both online and offline. RESULTS:A total of 17 patients participated in this study; they had a mean age of 59 years (SD 6) and 10 (60%) were women. Participants were engaged with the app; in the 120 days of the study, the mean number of logged blood pressure measurements was 63 (SD 46), the mean number of recorded weight measurements was 52 (SD 45), and participants recorded a mean of 55 step counts (SD 36). Coaching phone calls had a high completion rate (74/102, 73%). The mean number of servings documented per patient for the dietary assessment was 709 (SD 541), and patients set a mean number of 5 (SD 2) goals. Mean systolic and diastolic blood pressure, heart rate, weight, body mass index, and step count did not significantly change over time (P>.10 for all parameters). CONCLUSIONS:In this pilot study, we found that participants were engaged with an interactive mobile app that promoted healthy behaviors to treat hypertension. We did not find a difference in the physiological outcomes, but were underpowered to identify such changes.

Background: Due to underreporting, a major challenge associated with drug use surveys is obtaining precise estimates of drug use.Objective: This study examined reliability of self-reported lifetime marijuana use among electronic dance music (EDM) party attendees - a high-risk population for drug use.Methods: 794 adults (35.1% female) entering EDM parties were intercept-surveyed. Participants were asked about lifetime marijuana use early in the survey. Those not reporting use were asked 5-10 min later if their earlier response was correct. Participants reporting their original response was not correct were asked to check off a reason why they did not originally report use. Participants were also asked at the end of the survey how honestly they responded throughout the survey. Prevalence of lifetime marijuana use with and without corrected responses was compared and risk factors for underreporting were examined using a Poisson generalized linear model.Results: Among those not reporting marijuana use, 31.2% subsequently reported use when asked again. Prevalence of use increased from 73.7% to 81.9% after correcting responses, an 8.2% absolute increase and a 10.0% relative increase. Reporting lifetime use of ecstasy and/or LSD was associated with lower risk for underreporting marijuana use. Compared to those reporting that they answered all questions honestly, those who reportedly answered most or no questions honestly were at higher risk for underreporting.Conclusion: Asking participants to confirm previous responses can help detect underreporting of drug use on intercept surveys. Results can inform survey methods when participants are believed to be at risk for underreporting.

OBJECTIVE:Protected bike lanes separated from the roadway by physical barriers are relatively new in the United States. This study examined the risk of collisions or falls leading to emergency department visits associated with bicycle facilities (e.g., protected bike lanes, conventional bike lanes demarcated by painted lines, sharrows) and other roadway characteristics in three U.S. cities. METHODS:We prospectively recruited 604 patients from emergency departments in Washington, DC; New York City; and Portland, Oregon during 2015-2017 who fell or crashed while cycling. We used a case-crossover design and conditional logistic regression to compare each fall or crash site with a randomly selected control location along the route leading to the incident. We validated the presence of site characteristics described by participants using Google Street View and city GIS inventories of bicycle facilities and other roadway features. RESULTS:Compared with cycling on lanes of major roads without bicycle facilities, the risk of crashing or falling was lower on conventional bike lanes (adjusted OR = 0.53; 95 % CI = 0.33, 0.86) and local roads with (adjusted OR = 0.31; 95 % CI = 0.13, 0.75) or without bicycle facilities or traffic calming (adjusted OR = 0.39; 95 % CI = 0.23, 0.65). Protected bike lanes with heavy separation (tall, continuous barriers or grade and horizontal separation) were associated with lower risk (adjusted OR = 0.10; 95 % CI = 0.01, 0.95), but those with lighter separation (e.g., parked cars, posts, low curb) had similar risk to major roads when one way (adjusted OR = 1.19; 95 % CI = 0.46, 3.10) and higher risk when they were two way (adjusted OR = 11.38; 95 % CI = 1.40, 92.57); this risk increase was primarily driven by one lane in Washington. Risk increased in the presence of streetcar or train tracks relative to their absence (adjusted OR = 26.65; 95 % CI = 3.23, 220.17), on downhill relative to flat grades (adjusted OR = 1.92; 95 % CI = 1.38, 2.66), and when temporary features like construction or parked cars blocked the cyclist's path relative to when they did not (adjusted OR = 2.23; 95 % CI = 1.46, 3.39). CONCLUSIONS:Certain bicycle facilities are safer for cyclists than riding on major roads. Protected bike lanes vary in how well they shield riders from crashes and falls. Heavier separation, less frequent intersections with roads and driveways, and less complexity appear to contribute to reduced risk in protected bike lanes. Future research should systematically examine the characteristics that reduce risk in protected lanes to guide design. Planners should minimize conflict points when choosing where to place protected bike lanes and should implement countermeasures to increase visibility at these locations when they are unavoidable.

Algorithms are regularly used to identify persons living with diagnosed HIV (PLWDH) in the Medicaid data. To the authors knowledge, there are no published reports of an HIV algorithm from claims codes that have been compared to an HIV surveillance system to assess its sensitivity, specificity, positive predictive value and negative predictive value in identifying PLWDH. The aims of this study were to: 1) develop an algorithm that could identify PLWDH in New York Medicaid data from 2006-2014; and 2) validate this algorithm using the New York HIV surveillance system. Classification and regression tree analysis identified 16 nodes that were combined to create a case-finding algorithm with five criteria. This algorithm identified 86,930 presumed PLWDH, of which 88.0% were verified by matching to the surveillance system. The algorithm yielded a sensitivity of 94.5%, a specificity of 94.5%, a positive predictive value of 88.0%, and a negative predictive value of 97.6%. This validated algorithm has the potential to improve the utility of the Medicaid data for assessing health outcomes and programmatic interventions.