bluuebunny/crossref_metadata_2025_split huggingface dataset:
Promoting Collaborative Goal Setting for Cancer Prevention Among Primary Care Patients Through mHealth: Mixed Methods Evaluation of a New App
Authors: Resnick Daniel , Schapira Marilyn M , Smith Jazmine M , Bautista Allison , Xu Chang , Jones Liz , Aysola Jaya 
Published: May 2021

Background
Many newly diagnosed cancers are associated with modifiable lifestyle behaviors, such as diet, exercise, smoking cessation, and maintaining a healthy weight. However, primary care providers rarely discuss cancer prevention behaviors with their patients.

Objective
This study aims to assess the usability, acceptability, and user engagement of the Healthier Together mobile app, which is designed to promote cancer prevention behaviors among non-Hispanic Black primary care patients, by using social networks and goal-setting theories of behavior change.

Methods
In an 8-week pilot study, we enrolled primary care patients (N=41) and provided them with a cancer prevention mobile app that allowed them to select, track, and share progress on cancer prevention goals with other users. App usability was assessed using the System Usability Scale. We assessed the app’s acceptability by qualitatively analyzing open-ended responses regarding participants’ overall experience with the app. We assessed participants’ engagement by analyzing the built-in data capture device, which included the number of times participants checked in (out of a maximum of 8) during the study.

Results
The mean age of the 41 participants was 51 years (SD 12), and 76% (31/41) were women. App use data were captured from all participants, and 83% (34/41) completed the exit survey and interview. The mean System Usability Scale score was 87 (SD 12; median 90; IQR 78-95). The analysis of open-ended responses revealed several key themes, and participants complemented the app’s ease of use and health behavior–promoting features while also commenting on the need for more feedback and social interactions through the app. On average, participants checked in 5.7 times (SD 2.7) out of 8 possible opportunities. Of the 41 participants, 76% (31/41) checked in during at least 4 of the 8 weeks. Secondary analyses revealed that participants often accomplished their set goals (mean 5.1, SD 2.7) for each week. The qualitative analysis of comments given by participants within the app after each weekly check-in revealed several themes on how the app assisted participants in behavioral change, highlighting that some participants created exercise programs, ate healthier foods, lost a significant amount of weight, and stopped smoking during this study.

Conclusions
The implementation of a mobile cancer prevention goal–setting app in a primary care setting was feasible, and the app achieved high usability, acceptability, and engagement among participants. User feedback revealed an influence on health behaviors. These findings suggest the promise of the Healthier Together app in facilitating behavioral change to reduce cancer risk among non-Hispanic Black primary care patients.
Addressing Biodisaster X Threats With Artificial Intelligence and 6G Technologies: Literature Review and Critical Insights
Authors: Su Zhaohui , McDonnell Dean , Bentley Barry L , He Jiguang , Shi Feng , Cheshmehzangi Ali , Ahmad Junaid , Jia Peng 
Published: May 2021

BackgroundWith advances in science and technology, biotechnology is becoming more accessible to people of all demographics. These advances inevitably hold the promise to improve personal and population well-being and welfare substantially. It is paradoxical that while greater access to biotechnology on a population level has many advantages, it may also increase the likelihood and frequency of biodisasters due to accidental or malicious use. Similar to “Disease X” (describing unknown naturally emerging pathogenic diseases with a pandemic potential), we term this unknown risk from biotechnologies “Biodisaster X.” To date, no studies have examined the potential role of information technologies in preventing and mitigating Biodisaster X.ObjectiveThis study aimed to explore (1) what Biodisaster X might entail and (2) solutions that use artificial intelligence (AI) and emerging 6G technologies to help monitor and manage Biodisaster X threats.MethodsA review of the literature on applying AI and 6G technologies for monitoring and managing biodisasters was conducted on PubMed, using articles published from database inception through to November 16, 2020.ResultsOur findings show that Biodisaster X has the potential to upend lives and livelihoods and destroy economies, essentially posing a looming risk for civilizations worldwide. To shed light on Biodisaster X threats, we detailed effective AI and 6G-enabled strategies, ranging from natural language processing to deep learning–based image analysis to address issues ranging from early Biodisaster X detection (eg, identification of suspicious behaviors), remote design and development of pharmaceuticals (eg, treatment development), and public health interventions (eg, reactive shelter-at-home mandate enforcement), as well as disaster recovery (eg, sentiment analysis of social media posts to shed light on the public’s feelings and readiness for recovery building).ConclusionsBiodisaster X is a looming but avoidable catastrophe. Considering the potential human and economic consequences Biodisaster X could cause, actions that can effectively monitor and manage Biodisaster X threats must be taken promptly and proactively. Rather than solely depending on overstretched professional attention of health experts and government officials, it is perhaps more cost-effective and practical to deploy technology-based solutions to prevent and control Biodisaster X threats. This study discusses what Biodisaster X could entail and emphasizes the importance of monitoring and managing Biodisaster X threats by AI techniques and 6G technologies. Future studies could explore how the convergence of AI and 6G systems may further advance the preparedness for high-impact, less likely events beyond Biodisaster X.
Predicting Kidney Graft Survival Using Machine Learning Methods: Prediction Model Development and Feature Significance Analysis Study
Authors: Naqvi Syed Asil Ali , Tennankore Karthik , Vinson Amanda , Roy Patrice C , Abidi Syed Sibte Raza 
Published: May 2021

Background
Kidney transplantation is the optimal treatment for patients with end-stage renal disease. Short- and long-term kidney graft survival is influenced by a number of donor and recipient factors. Predicting the success of kidney transplantation is important for optimizing kidney allocation.

Objective
The aim of this study was to predict the risk of kidney graft failure across three temporal cohorts (within 1 year, within 5 years, and after 5 years following a transplant) based on donor and recipient characteristics. We analyzed a large data set comprising over 50,000 kidney transplants covering an approximate 20-year period.

Methods
We applied machine learning–based classification algorithms to develop prediction models for the risk of graft failure for three different temporal cohorts. Deep learning–based autoencoders were applied for data dimensionality reduction, which improved the prediction performance. The influence of features on graft survival for each cohort was studied by investigating a new nonoverlapping patient stratification approach.

Results
Our models predicted graft survival with area under the curve scores of 82% within 1 year, 69% within 5 years, and 81% within 17 years. The feature importance analysis elucidated the varying influence of clinical features on graft survival across the three different temporal cohorts.

Conclusions
In this study, we applied machine learning to develop risk prediction models for graft failure that demonstrated a high level of prediction performance. Acknowledging that these models performed better than those reported in the literature for existing risk prediction tools, future studies will focus on how best to incorporate these prediction models into clinical care algorithms to optimize the long-term health of kidney recipients.
Mobile Health in Chronic Disease Management and Patient Empowerment: Exploratory Qualitative Investigation Into Patient-Physician Consultations
Authors: Stampe Kathrine , Kishik Sharon , Müller Sune Dueholm 
Published: May 2021

Background
Chronic diseases often present severe consequences for those affected. The management and treatment of chronic diseases largely depend on patients’ lifestyle choices and how they cope with the disease in their everyday lives. Accordingly, the ability of patients to self-manage diseases is a highly relevant topic. In relation to self-management, studies refer to patient empowerment as strengthening patients’ voices and enabling them to assert control over their health and treatment. Mobile health (mHealth) provides cost-efficient means to support self-management and foster empowerment.

Objective
There is a scarcity of research investigating how mHealth affects patient empowerment during patient-physician consultations. The objective of this study is to address this knowledge gap by investigating how mHealth affects consultations and patient empowerment.

Methods
We relied on data from an ethnographic field study of 6 children and adolescents diagnosed with juvenile idiopathic arthritis. We analyzed 6 patient-physician consultations and drew on Michel Foucault’s concepts of power and power technology.

Results
Our results suggest that the use of mHealth constitutes practices that structure the consultations around deviations and noncompliant patient behavior. Our analysis shows how mHealth is used to discipline patients and correct their behavior. We argue that the use of mHealth during consultations may unintentionally lead to relevant aspects of patients’ lives related to the disease being ignored; thus, inadvertently, patients’ voices may be silenced.

Conclusions
Our results show that concrete uses of mHealth may conflict with extant literature on empowerment, which emphasizes the importance of strengthening the patients’ voices and enabling patients to take more control of their health and treatment. We contribute to the state-of-the-art knowledge by showing that the use of mHealth may have unintended consequences that do not lead to empowerment. Our analysis underscores the need for further research to investigate how mHealth impacts patient empowerment during consultations.
Machine Learning Analysis to Identify Digital Behavioral Phenotypes for Engagement and Health Outcome Efficacy of an mHealth Intervention for Obesity: Randomized Controlled Trial
Authors: Kim Meelim , Yang Jaeyeong , Ahn Woo-Young , Choi Hyung Jin 
Published: May 2021

Background
The digital health care community has been urged to enhance engagement and clinical outcomes by analyzing multidimensional digital phenotypes.

Objective
This study aims to use a machine learning approach to investigate the performance of multivariate phenotypes in predicting the engagement rate and health outcomes of digital cognitive behavioral therapy.

Methods
We leveraged both conventional phenotypes assessed by validated psychological questionnaires and multidimensional digital phenotypes within time-series data from a mobile app of 45 participants undergoing digital cognitive behavioral therapy for 8 weeks. We conducted a machine learning analysis to discriminate the important characteristics.

Results
A higher engagement rate was associated with higher weight loss at 8 weeks (r=−0.59; P<.001) and 24 weeks (r=−0.52; P=.001). Applying the machine learning approach, lower self-esteem on the conventional phenotype and higher in-app motivational measures on digital phenotypes commonly accounted for both engagement and health outcomes. In addition, 16 types of digital phenotypes (ie, lower intake of high-calorie food and evening snacks and higher interaction frequency with mentors) predicted engagement rates (mean R2 0.416, SD 0.006). The prediction of short-term weight change (mean R2 0.382, SD 0.015) was associated with 13 different digital phenotypes (ie, lower intake of high-calorie food and carbohydrate and higher intake of low-calorie food). Finally, 8 measures of digital phenotypes (ie, lower intake of carbohydrate and evening snacks and higher motivation) were associated with a long-term weight change (mean R2 0.590, SD 0.011).

Conclusions
Our findings successfully demonstrated how multiple psychological constructs, such as emotional, cognitive, behavioral, and motivational phenotypes, elucidate the mechanisms and clinical efficacy of a digital intervention using the machine learning method. Accordingly, our study designed an interpretable digital phenotype model, including multiple aspects of motivation before and during the intervention, predicting both engagement and clinical efficacy. This line of research may shed light on the development of advanced prevention and personalized digital therapeutics.

Trial Registration
ClinicalTrials.gov NCT03465306; https://clinicaltrials.gov/ct2/show/NCT03465306
Characteristics of Citizens and Their Use of Teleconsultations in Primary Care in the Catalan Public Health System Before and During the COVID-19 Pandemic: Retrospective Descriptive Cross-sectional Study
Authors: Solans Oscar , Vidal-Alaball Josep , Roig Cabo Pasqual , Mora Núria , Coma Ermengol , Bonet Simó Josep Maria , Hermosilla Pérez Eduardo , Saigí-Rubió Francesc , Olmos Domínguez Carmen , Piera-Jiménez Jordi , Abizanda González Mercè , López Seguí Francesc 
Published: May 2021

Background
eConsulta—that is, asynchronous, two-way teleconsultation in primary care—is one of the most important telemedicine developments in the Catalan public health system, a service that has been heavily boosted by the onset of the COVID-19 pandemic. It is vital to know the characteristics of its users in order to be able to meet their needs and understand the coverage of this service in a context where there is reduced accessibility to the health system.

Objective
This study aims to analyze the profile of the citizens who use the eConsulta tool and the reasons for their use, as well as to gain an understanding of the elements that characterize their decision to use it while distinguishing between those who used it before and those who have used it since the onset of the COVID-19 pandemic.

Methods
A descriptive, observational study based on administrative data was performed. This study differentiates between the COVID-19 pandemic era and the period preceding it, considering the day the state of emergency was declared in Spain (ie, March 12, 2020) as the cut-off point. It also differentiates between eConsulta users who send messages and those who only receive them.

Results
During the pandemic, the number of unique users of this teleconsultation service had almost tripled, with up to 33.10 visits per 1000 inhabitants per month reported in the first three months. For the two user profiles analyzed, most users since the start of the COVID-19 outbreak were predominantly female, systematically younger, more actively employed, and with less complex pathologies. Furthermore, eConsulta users received more messages proactively from the health professionals. There was also a relative decrease in the number of conversations initiated by higher-income urban users and an increase in conversations initiated by users in rural areas.

Conclusions
The COVID-19 pandemic has helped to generalize the use of telemedicine as a tool to compensate, to some extent, for the decline in face-to-face visits, especially among younger citizens in Catalonia. Telemedicine has made it possible to maintain contact between citizens and the health care system in the context of maximum complexity.
Regulación y victimización del homoerotismo entre hombres en contextos de conflicto armado en Colombia
Authors: Giraldo Aguirre Sebastián , Gallego Montes Gabriel 
Published: May 2021

El objetivo del artículo es presentar los procesos de regulación y victimización del homoerotismo entre hombres en contextos de conflicto armado en Colombia. En términos metodológicos, la investigación se planteó desde una perspectiva de memoria social, la cual establece una centralidad del testimonio de las víctimas y de los diferentes relatos que se tejen alrededor de ellas. En general, se revela que los escenarios armados configuran unos dispositivos de género y sexuales ambivalentes en los cuales se articulan la eliminación y la persecución, a la vez que la convivencia y el ejercicio de la sexualidad entre hombres.
Palabras clave: masculinidad, homoerotismo, conflicto armado, Colombia.
Somos guapas, somos listas, somos putas feministas: encarnando prácticas disidentes con las Putas Indignadas de Barcelona
Authors: Motterle Livia 
Published: May 2021

El objetivo principal de este texto es analizar la complejidad del trabajo sexual a partir de prácticas de agencia, protesta y empoderamiento de trabajadoras sexuales de Barcelona, frente a la violencia institucional que dificulta, hasta impedir, su profesión. A partir de mi postura feminista pro derechos, nacida gracias a una larga colaboración con el colectivo Prostitutas Indignadas en el Raval de Barcelona, me propongo desmontar ciertos tópicos sobre el trabajo sexual y trazar una resonancia entre cuerpos, calles, feminismos y protesta. Por otro lado, poniendo el énfasis en uno de los debates más candentes del feminismo actual, quiero evidenciar, a partir de mi trabajo de campo y desde una mirada etnográfica, la inconsistencia de ciertos discursos abolicionistas, así como la importancia de poner en el centro de esta disputa a las voces y las experiencias encarnadas de cuantas ejercen el trabajo sexual.
Palabras clave: Trabajo sexual; Cuerpo; Etnografía feminista; Agencia; Movimientos sociales
Seguridad alimentaria, Covid-19 y crisis: una aplicación del modelo de regresión logística binomial para su estudio
Authors: Mazuera-Arias Rina , Albornoz-Arias Neida , Briceño-León Roberto 
Published: May 2021

<div class="page" title="Page 1"><div class="layoutArea"><div class="column"><p><span>La pandemia por Covid-19 ha generado impactos de serias consecuencias, y si bien en el caso venezolano resultan agravantes, es especialmente importante en el ámbito de la seguridad alimentaria. La investigación descriptiva cuantitativa tuvo por objetivo estudiar la percepción e identificación de indicadores sobre el estado de seguridad alimentaria venezolana, aportando conocimiento para definir o reorientar las políticas públicas dirigidas a las personas más vulnerables. Se aplicaron 507 encuestas a personas residentes en el municipio Fernández Feo, estado Táchira, próximo a la frontera con Colombia. El modelo de análisis empleado fue el de Regresión Logística Binaria, con SPSS</span><span>®</span><span>, identificándose nueve hallazgos, explicativos y predictivos, que determinaron la presencia o </span>ausencia de determinadas características en los programas sociales de alimentación del Estado venezolano, así como grupos con mayor o menos posibilidades de acceso a tales programas. Se concluyó —dejando nuevas perspectivas para investigaciones más específicas— cómo una emergencia sanitaria por pandemia incide exponencialmente en la demanda de grupos poblacionales de escasos recursos económicos, de ayudas sociales, de carácter público o privado, para satisfacer, en lo posible, sus necesidades vitales de alimentación.</p></div></div></div>
Estrategias para el desarrollo de la competencia lectora: Una propuesta metodológica
Authors: Pérez Medina María Elena Michael , Lozoya Meza Esperanza 
Published: May 2021

El propósito de este artículo es presentar una propuesta de estrategias metodológicas que contribuyan al desarrollo de la competencia lectora, basadas en la educación Ciencia, Tecnología, Ingeniería, Artes y Matemáticas (CTIAM), para la formación de lectores en el contexto educativo mexicano. Es un estudio de tipo cualitativo en el que se realiza una revisión bibliográfica sobre la competencia lectora y la educación CTIAM. Se presenta una propuesta metodológica que tiene como elementos centrales la interdisciplinariedad, la contextualización, la actitud crítica y la lectura digital. Se señala, además, la posibilidad de diversificar las estrategias de enseñanza de la competencia lectora mediante su relación con otros campos formativos. A partir de los resultados obtenidos, se aporta una estructura de estrategias como alternativa para la formación de lectores competentes en aras de una alfabetización funcional.
Prevalencia de biotipos gingivales según el somatotipo en estudiantes de la UCSG semestre A-2017
Authors: Pio Proaño Cristina Paulette , Guim Martínez Carlos Andrés 
Published: May 2021

Introducción: el biotipo gingival tiene un impacto importante en la supervivencia de los diferentes tratamientos odontológicos. Varios autores aseguran que cada biotipo gingival tiene una respuesta diferente ante fuerzas externas. Por ello debemos tener una comprensión clara del comportamiento del mismo, para que en investigaciones posteriores se pueda conocer adecuadamente su manejo. Además, para tener un diagnóstico preciso se debe de analizar también el somatotipo del sujeto, este puede ser ectomorfo, mesomorfo y endomorfo, según sus características clínicas. Objetivo: observar la relación que existe entre el biotipo gingival y el somatotipo. Metodología: el estudio analítico es de tipo transversal se realizó en 107 estudiantes de odontología de la UCSG, seleccionados al azar según los criterios de inclusión y exclusión. Se determinó el biotipo gingival mediante el método de translucidez de la sonda en los dientes 11, 12, 13. El somatotipo se lo determino mediante el método fotográfico de sheldon, con una fotografía de cuerpo entero. Resultados: fueron analizados 107 sujetos, 72 mujeres y 35 hombres. El 57% del total de los sujetos tuvieron biotipo grueso, el 43% mostró biotipo delgado. Un 39% mostró somatotipo ectomorfo, el 38% somatotipo mesomorfo y el 22% somatotipo endomorfo. Al relacionar las dos variables, de somatotipo ectomorfo un 90% =biotipo delgado, 10%= biotipo grueso, de somatotipo endomorfo un 100%= biotipo grueso, de somatotipo mesomorfo un 80%= biotipo grueso y un 20% biotipo delgado. Conclusión: el somatotipo más prevalente fue ectomorfo, y el biotipo más encontrado fue el grueso. Concluyendo de esta manera que no hay una relación clara entre el somatotipo y el biotipo gingival.