bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Unstructured Supplementary Service Data System for Daily Tracking of Patient Samples and Diagnostic Results in a Diagnostic Network in Malawi: System Development and Field Trial
Authors: Killian Daniel , Gibson Emma , Kachule Mphatso , Palamountain Kara , Bangoh Joseph Bitilinyu , Deo Sarang , Jonasson Jonas Oddur 
Published: July 2021

Background
Diagnostics in many low- and middle-income countries are conducted through centralized laboratory networks. Samples are collected from patients at remote point-of-care health facilities, and diagnostic tests are performed at centralized laboratories. Sample transportation systems that deliver diagnostic samples and test results are crucial for timely diagnosis and treatment in such diagnostic networks. However, they often lack the timely and accurate data (eg, the quantity and location of samples prepared for collection) required for efficient operation.

Objective
This study aims to demonstrate the feasibility, adoption, and accuracy of a distributed data collection system that leverages basic mobile phone technology to gather reports on the quantity and location of patient samples and test results prepared for delivery in the diagnostic network of Malawi.

Methods
We designed a system that leverages unstructured supplementary service data (USSD) technology to enable health workers to submit daily reports describing the quantity of transportation-ready diagnostic samples and test results at specific health care facilities, free of charge with any mobile phone, and aggregate these data for sample transportation administrators. We then conducted a year-long field trial of this system in 51 health facilities serving 3 districts in Malawi. Between July 2019 and July 2020, the participants submitted daily reports containing the number of patient samples or test results designated for viral load, early infant diagnosis, and tuberculosis testing at each facility. We monitored daily participation and compared the submitted USSD reports with program data to assess system feasibility, adoption, and accuracy.

Results
The participating facilities submitted 37,771 reports over the duration of the field trial. Daily facility participation increased from an average of 50% (26/51) in the first 2 weeks of the trial to approximately 80% (41/51) by the midpoint of the trial and remained at or above 80% (41/51) until the conclusion of the trial. On average, more than 80% of the reports submitted by a facility for a specific type of sample matched the actual number of patient samples collected from that facility by a courier.

Conclusions
Our findings suggest that a USSD-based system is a feasible, adoptable, and accurate solution to the challenges of untimely, inaccurate, or incomplete data in diagnostic networks. Certain design characteristics of our system, such as the use of USSD, and implementation characteristics, such as the supportive role of the field team, were necessary to ensure high participation and accuracy rates without any explicit financial incentives.
Efficacy of a Just-in-Time Adaptive Intervention to Promote HIV Risk Reduction Behaviors Among Young Adults Experiencing Homelessness: Pilot Randomized Controlled Trial
Authors: Santa Maria Diane , Padhye Nikhil , Businelle Michael , Yang Yijiong , Jones Jennifer , Sims Alexis , Lightfoot Marguerita 
Published: July 2021

BackgroundPeople experiencing homelessness have higher rates of HIV than those who are stably housed. Mental health needs, substance use problems, and issues unique to homelessness such as lack of shelter and transiency need to be considered with regard to HIV prevention. To date, HIV prevention interventions for young adults experiencing homelessness have not specifically addressed modifiable real-time factors such as stress, sexual or drug use urge, or substance use, or been delivered at the time of heightened risk. Real-time, personalized HIV prevention messages may reduce HIV risk behaviors.ObjectiveThis pilot study tested the initial efficacy of an innovative, smartphone-based, just-in-time adaptive intervention that assessed predictors of HIV risk behaviors in real time and automatically provided behavioral feedback and goal attainment information.MethodsA randomized attention control design was used among young adults experiencing homelessness, aged 18-25 years, recruited from shelters and drop-in centers in May 2019. Participants were randomized to either a control or an intervention group. The intervention (called MY-RID [Motivating Youth to Reduce Infection and Disconnection]) consisted of brief messages delivered via smartphone over 6 weeks in response to preidentified predictors that were assessed using ecological momentary assessments. Bayesian hierarchical regression models were used to assess intervention effects on sexual activity, drug use, alcohol use, and their corresponding urges.ResultsParticipants (N=97) were predominantly youth (mean age 21.2, SD 2.1 years) who identified as heterosexual (n=51, 52%), male (n=56, 57%), and African American (n=56, 57%). Reports of sexual activity, drug use, alcohol use, stress, and all urges (ie, sexual, drug, alcohol) reduced over time in both groups. Daily drug use reduced by a factor of 13.8 times over 6 weeks in the intervention group relative to the control group (Multimedia Appendix 4). Lower urges for sex were found in the intervention group relative to the control group over the duration of the study. Finally, there was a statistically significant reduction in reports of feeling stressed the day before between the intervention and control conditions (P=.03).ConclusionsFindings indicate promising intervention effects on drug use, stress, and urges for sex in a hard-to-reach, high-risk population. The MY-RID intervention should be further tested in a larger randomized controlled trial to further investigate its efficacy and impact on sexual risk behaviors.Trial RegistrationClinicalTrials.gov NCT03911024; https://clinicaltrials.gov/ct2/show/NCT03911024
An Electronic Registry for Improving the Quality of Antenatal Care in Rural Bangladesh (eRegMat): Protocol for a Cluster Randomized Controlled Trial
Authors: Rahman Anisur , Friberg Ingrid K , Dolphyne Akuba , Fjeldheim Ingvild , Khatun Fatema , O'Donnell Brian , Pervin Jesmin , Rahman Monjur , Rahman A M Qaiyum , Nu U Tin , Sarker Bidhan Krishna , Venkateswaran Mahima , Frøen J Frederik 
Published: July 2021

Background
Digital health interventions (DHIs) can alleviate several barriers to achieving better maternal and child health. The World Health Organization’s guideline recommendations for DHIs emphasize the need to integrate multiple DHIs for maximizing impact. The complex health system of Bangladesh provides a unique setting for evaluating and understanding the role of an electronic registry (eRegistry) for antenatal care, with multiple integrated DHIs for strengthening the health system as well as improving the quality and utilization of the public health care system.

Objective
The aim of this study is to assess the effect of an eRegistry with DHIs compared with a simple digital data entry tool without DHIs in the community and frontline health facilities.

Methods
The eRegMat is a cluster-randomized controlled trial conducted in the Matlab North and Matlab South subdistricts in the Chandpur district, Bangladesh, where health facilities are currently using the eRegistry for digital tracking of the health status of pregnant women longitudinally. The intervention arm received 3 superimposed data-driven DHIs: health worker clinical decision support, health worker feedback dashboards with action items, and targeted client communication to pregnant women. The primary outcomes are appropriate screening as well as management of hypertension during pregnancy and timely antenatal care attendance. The secondary outcomes include morbidity and mortality in the perinatal period as well as timely first antenatal care visit; successful referrals for anemia, diabetes, or hypertension during pregnancy; and facility delivery.

Results
The eRegistry and DHIs were co-designed with end users between 2016 and 2018. The eRegistry was implemented in the study area in July 2018. Recruitment for the trial started in October 2018 and ended in June 2020, followed by an 8-month follow-up period to capture outcome data until February 2021. Trial results will be available for publication in June 2021.

Conclusions
This trial allows the simultaneous assessment of multiple integrated DHIs for strengthening the health system and aims to provide evidence for its implementation. The study design and outcomes are geared toward informing the living review process of the guidelines for implementing DHIs.

Trial Registration
ISRCTN Registry ISRCTN69491836; https://www.isrctn.com/ISRCTN69491836

International Registered Report Identifier (IRRID)
DERR1-10.2196/26918
The Mediating Influence of the Unified Theory of Acceptance and Use of Technology on the Relationship Between Internal Health Locus of Control and Mobile Health Adoption: Cross-sectional Study
Authors: Ahadzadeh Ashraf Sadat , Wu Shin Ling , Ong Fon Sim , Deng Ruolan 
Published: July 2021

Background
Mobile health (mHealth) as an innovative form of information and communications technology can efficiently deliver high-quality health care by enhancing communication and health management, reducing costs, and increasing access to health services. An individual’s internal health locus of control (HLOC) is found to be associated with the behavioral intent to adopt mHealth. However, little is known about the underlying mechanism of this association.

Objective
The primary objective of this study was to test the mediation influence of the Unified Theory of Acceptance and Use of Technology (UTAUT) on the relationship between internal HLOC and the behavioral intention to use mHealth.

Methods
A total of 374 responses were collected from Malaysian adult users of mHealth, using convenience and snowball sampling methods. Partial least squares structural equation modeling was used to analyze the data. Data were collected for variables, including demographics, internal HLOC, and modified UTAUT constructs (ie, performance expectancy, effort expectancy, and social influence).

Results
The results showed that there was no direct relationship between internal HLOC and the behavioral intention to use mHealth (β=−0.039, P=.32). The indirect relationship between internal HLOC and the intent to adopt mHealth was supported, indicating that the UTAUT constructs performance expectancy (β=0.104, P<.001), effort expectancy (β=0.056, P=.02), and social influence (β=0.057, P=.002) mediated this relationship. The results showed full mediation, with total variance explained at 47.2%.

Conclusions
This study developed an integrative model, where a health-related disposition (internal HLOC), mHealth-related beliefs (performance expectancy and effort expectancy), and normative pressure (social influence) were combined to explain the underlying mechanism of the behavioral intent to adopt mHealth. The results showed that the intention to adopt mHealth is mediated by the influence of UTAUT factors, while HLOC has no direct effect on adoption intention. The findings provide insights into augmenting mHealth adoption among the public by enhancing the perceived benefits of mHealth, helping design more effective and user-friendly mHealth tools, and capitalizing on social normative influence to adopt mHealth. This study utilized the constructs of the UTAUT model to determine the intention to use mHealth. Future research should focus on other health- and technology-related theories to ascertain other possible factors influencing the behavioral intent of mHealth adoption.
Using Artificial Intelligence With Natural Language Processing to Combine Electronic Health Record’s Structured and Free Text Data to Identify Nonvalvular Atrial Fibrillation to Decrease Strokes and Death: Evaluation and Case-Control Study
Authors: Elkin Peter L , Mullin Sarah , Mardekian Jack , Crowner Christopher , Sakilay Sylvester , Sinha Shyamashree , Brady Gary , Wright Marcia , Nolen Kimberly , Trainer JoAnn , Koppel Ross , Schlegel Daniel , Kaushik Sashank , Zhao Jane , Song Buer , Anand Edwin 
Published: July 2021

Background
Nonvalvular atrial fibrillation (NVAF) affects almost 6 million Americans and is a major contributor to stroke but is significantly undiagnosed and undertreated despite explicit guidelines for oral anticoagulation.

Objective
The aim of this study is to investigate whether the use of semisupervised natural language processing (NLP) of electronic health record’s (EHR) free-text information combined with structured EHR data improves NVAF discovery and treatment and perhaps offers a method to prevent thousands of deaths and save billions of dollars.

Methods
We abstracted 96,681 participants from the University of Buffalo faculty practice’s EHR. NLP was used to index the notes and compare the ability to identify NVAF, congestive heart failure, hypertension, age ≥75 years, diabetes mellitus, stroke or transient ischemic attack, vascular disease, age 65 to 74 years, sex category (CHA2DS2-VASc), and Hypertension, Abnormal liver/renal function, Stroke history, Bleeding history or predisposition, Labile INR, Elderly, Drug/alcohol usage (HAS-BLED) scores using unstructured data (International Classification of Diseases codes) versus structured and unstructured data from clinical notes. In addition, we analyzed data from 63,296,120 participants in the Optum and Truven databases to determine the NVAF frequency, rates of CHA2DS2‑VASc ≥2, and no contraindications to oral anticoagulants, rates of stroke and death in the untreated population, and first year’s costs after stroke.

Results
The structured-plus-unstructured method would have identified 3,976,056 additional true NVAF cases (P<.001) and improved sensitivity for CHA2DS2-VASc and HAS-BLED scores compared with the structured data alone (P=.002 and P<.001, respectively), causing a 32.1% improvement. For the United States, this method would prevent an estimated 176,537 strokes, save 10,575 lives, and save >US $13.5 billion.

Conclusions
Artificial intelligence–informed bio-surveillance combining NLP of free-text information with structured EHR data improves data completeness, prevents thousands of strokes, and saves lives and funds. This method is applicable to many disorders with profound public health consequences.
Sources of Health Information, Technology Access, and Use Among Non–English-Speaking Immigrant Women: Descriptive Correlational Study
Authors: Chae Steve , Lee Yoon-Jae , Han Hae-Ra 
Published: July 2021

Background
As the world is becoming increasingly connected by the World Wide Web, the internet is becoming the main source of health information. With the novel COVID-19 pandemic, ubiquitous use of the internet has changed the daily lives of individuals, from working from home to seeking and meeting with health care providers through web-based sites. Such heavy reliance on internet-based technologies raises concerns regarding the accessibility of the internet for minority populations who are likely to already face barriers when seeking health information.

Objective
This study aims to examine the level of technology access and common modes of technology used by Korean American women and to investigate how key psychosocial determinants of health such as age, education, English proficiency, and health literacy are correlated with sources of health information used by Korean American women and by their use of the internet.

Methods
We used data from a subsample of Korean American women (N=157) who participated in a community-based randomized trial designed to test a health literacy–focused cancer screening intervention. In addition to descriptive statistics to summarize Korean American women’s internet access and common modes of technology use, we conducted backward stepwise logistic regression analyses to substantiate the association between the psychosocial determinants of health and internet use.

Results
Approximately two-thirds (103/157, 65.6%) of the sample had access to the internet, and nearly all had access to a mobile phone. The internet was the most commonly used channel to obtain health information 63% (99/157), and 70% (110/157) of the sample used text messaging. Nevertheless, only approximately 38.8% (40/103) of the sample were very confident in using the internet, and only 29.9% (47/157) were very confident in using text messaging. Multivariate analyses revealed that older age (>50 years) was associated with 79% lower odds of using the internet to seek health information (adjusted odds ratio [AOR] 0.21, 95% CI 0.10-0.46). The higher health literacy group (19+ on Rapid Estimate of Adult Literacy in Medicine) had 56% lower odds of using the internet to acquire health information (AOR 0.44, 95% CI 1.13-11.18). Higher education (college+) was associated with both internet use (AOR 4.42, 95% CI 1.88-9.21) and text messaging (AOR 3.42, 95% CI 1.55-7.54). Finally, English proficiency was associated with text messaging (AOR 4.20, 95% CI 1.44-12.24).

Conclusions
The differences in modes of technology access, use, and confidence by some of the key psychosocial determinants, as observed in our study sample, have important implications when health care teams develop dissemination plans.
Self-Focused and Other-Focused Health Concerns as Predictors of the Uptake of Corona Contact Tracing Apps: Empirical Study
Authors: große Deters Fenne , Meier Tabea , Milek Anne , Horn Andrea B 
Published: July 2021

BackgroundCorona contact tracing apps are a novel and promising measure to reduce the spread of COVID-19. They can help to balance the need to maintain normal life and economic activities as much as possible while still avoiding exponentially growing case numbers. However, a majority of citizens need to be willing to install such an app for it to be effective. Hence, knowledge about drivers for app uptake is crucial.ObjectiveThis study aimed to add to our understanding of underlying psychological factors motivating app uptake. More specifically, we investigated the role of concern for one’s own health and concern to unknowingly infect others.MethodsA two-wave survey with 346 German-speaking participants from Switzerland and Germany was conducted. We measured the uptake of two decentralized contact tracing apps officially launched by governments (Corona-Warn-App, Germany; SwissCovid, Switzerland), as well as concerns regarding COVID-19 and control variables.ResultsControlling for demographic variables and general attitudes toward the government and the pandemic, logistic regression analysis showed a significant effect of self-focused concerns (odds ratio [OR] 1.64, P=.002). Meanwhile, concern of unknowingly infecting others did not contribute significantly to the prediction of app uptake over and above concern for one’s own health (OR 1.01, P=.92). Longitudinal analyses replicated this pattern and showed no support for the possibility that app uptake provokes changes in levels of concern. Testing for a curvilinear relationship, there was no evidence that “too much” concern leads to defensive reactions and reduces app uptake.ConclusionsAs one of the first studies to assess the installation of already launched corona tracing apps, this study extends our knowledge of the motivational landscape of app uptake. Based on this, practical implications for communication strategies and app design are discussed.
Empowering Anxious Parents to Manage Child Avoidance Behaviors: Randomized Control Trial of a Single-Session Intervention for Parental Accommodation
Authors: Sung Jenna Y , Mumper Emma , Schleider Jessica Lee 
Published: July 2021

Background
A majority of youth who need anxiety treatment never access support. This disparity reflects a need for more accessible, scalable interventions—particularly those that may prevent anxiety in high-risk children, mitigating future need for higher-intensity care. Self-guided single-session interventions (SSIs) may offer a promising path toward this goal, given their demonstrated clinical utility, potential for disseminability, and low cost. However, existing self-guided SSIs have been designed for completion by adolescents already experiencing symptoms, and their potential for preventing anxiety in children—for instance, by mitigating known anxiety risk factors—remains unexplored.

Objective
This trial evaluated the acceptability and proximal effects of project EMPOWER: a web-based, self-guided SSI designed to reduce parental accommodation, a parenting behavior known to increase the risk of anxiety in offspring.

Methods
In total, 301 parents who reported elevated anxiety symptoms with children aged 4-10 years received either project EMPOWER or an informational control (containing psychoeducational materials and resources); parents self-reported their accommodation of child anxiety and overall distress tolerance at baseline and 2-week follow-up.

Results
Relative to control-group parents, those who received the intervention outlined in project EMPOWER reported significant reductions in their accommodation of child anxiety (ds=0.61; P<.001) and significant increases in their distress tolerance (ds=0.43; P<.001) from baseline to 2-week follow-up. Additionally, parents rated project EMPOWER as highly acceptable (ie, easy to use, helpful, and engaging) in accordance with preregistered benchmarks.

Conclusions
Project EMPOWER is an acceptable self-guided SSI for parents of children at-risk for anxiety, which yields proximal reductions in clinically relevant targets.

Trial Registration
ClinicalTrials.gov NCT04453865; https://tinyurl.com/4h84j8t9