Exploratory attitude survey of homeless persons regarding telecare services in shelters providing mid- and long-term accommodation: The importance of trust

Győrffy, Zsuzsa; Békási, Sándor; Döbrössy, Bence; Bognár, Virág Katalin; Radó, Nóra; Morva, Emília; Zsigri, Szabolcs; Tari, Péter; Girasek, Edmond

doi:10.1371/journal.pone.0261145

Cited by 11 publications

(11 citation statements)

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“…Such disparities lower life expectancy and strengthen social exclusion. To mitigate health inequalities among homeless populations, digital technology [ 12 ], a new health determinant, can be considered on a broader scale. In a previous study by the Digital Health Research Group [ 12 ] at Semmelweis University that examined the attitudes and openness of homeless individuals regarding telecare in a Hungarian sample, a significant fraction of people experiencing homelessness with mid- or long-term residency in homeless shelters was open to the use of telecare via live web-based video consultation.…”

Section: Discussionmentioning

confidence: 99%

“…To mitigate health inequalities among homeless populations, digital technology [ 12 ], a new health determinant, can be considered on a broader scale. In a previous study by the Digital Health Research Group [ 12 ] at Semmelweis University that examined the attitudes and openness of homeless individuals regarding telecare in a Hungarian sample, a significant fraction of people experiencing homelessness with mid- or long-term residency in homeless shelters was open to the use of telecare via live web-based video consultation. As a step forward in assessing the feasibility of launching a comprehensive telehealth project and disseminating other well-being programs, the research team conducted this survey assessing existing access to digital platforms (smartphones and internet) and barriers in both physical and educational spaces among homeless populations.…”

Section: Discussionmentioning

confidence: 99%

“…Physical barriers in the form of lack of access to technological equipment, as well as educational barriers in being unable to use the technology, may contribute to the inaccessibility of services and resources, further depriving a segment of the population that is already marginalized. This very possibility would negatively impact behaviors and stressors and might further contribute to poorer health outcomes for those who are digitally excluded, widening the already existent digital inequality landscape [ 11 , 12 ].…”

Section: Introductionmentioning

confidence: 99%

“…This study fits into a broader set of research undertaken by the joint action of the Digital Health Research Group at Semmelweis University and the Hungarian Charity Service of the Order of Malta (HCSOM), aiming to analyze the relationship between digital health and homeless populations in Hungary. Previous research has studied the attitudes of homeless individuals toward telecare services, with the main finding being that trust in the general health care system leads to trust in digital health solutions [ 12 ]. This study also served as an assessment tool for analyzing the viability of a telecare system planned to be launched by the HCSOM.…”

Section: Introductionmentioning

confidence: 99%

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Digital Technology Access and Health-Related Internet Use Among People Experiencing Homelessness in Hungary: Quantitative Survey

Radó¹,

Girasek²,

Békási³

et al. 2022

J Med Internet Res

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Background In recent years, there has been an increase in the use of digital technology for personal health and well-being. Previous research has revealed that these technologies might provide vulnerable populations, including those who are homeless, better access to health services and thus a greater chance of more personalized care. Objective However, little is known about the relationship between technology and health among people experiencing homelessness in Central and Eastern Europe. This study is part of a series of studies by the Digital Health Research Group at Semmelweis University (Budapest, Hungary) in cooperation with the Hungarian Charity Service of the Order of Malta; it aims to assess the existing technological resources available for the homeless population and their health-related internet use characteristics to set the ground for potential health policy interventions, enabling better access to health services by strengthening the digital components of the existing health care system. Methods Between April 19, 2021, and August 11, 2021, a total of 662 people from 28 institutions providing social services for people experiencing homelessness in Budapest, Hungary, were surveyed about their access to digital tools and internet use patterns. For selected questions, the responses of a representative sample of the Hungarian population were used for comparison as the reference group. Chi-square tests and logistic regression analyses were performed to identify variables affecting internet use for health-related reasons. Results The results demonstrated a considerable level of internet use in the homeless population; 52.9% (350/662) of the respondents used the internet frequently compared with 81.3% (1220/1500) of the respondents in the reference group. Among the homeless group, 69.6% (461/662) of the respondents reported mobile phone ownership, and 39.9% (264/662) of the respondents added that it had a smartphone function. Moreover, 11.2% (70/662) of the respondents had already used a health mobile app, and 34.6% (229/662) of the respondents had used the internet for medical purposes. On the basis of these characteristics, we were able to identify a broadly defined, digitally engaged group among people experiencing homelessness (129/662, 19.5%). This subpopulation was inclined to benefit from digitalization related to their personal health. Multivariate analysis demonstrated that internet use for health reasons was more significant for younger respondents, women, those with higher levels of education, and those with no chronic conditions. Conclusions Although compared with the general population, health-related internet use statistics are lower, our results show that the idea of involving homeless populations in the digital health ecosystem is viable, especially if barriers to access are systematically reduced. The results show that digital health services have great promise as another tool in the hands of community shelters for keeping homeless populations well ingrained in the social infrastructure as well as for disease prevention purposes.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Digital Technology Access and Health-Related Internet Use Among People Experiencing Homelessness in Hungary: Quantitative Survey

Radó¹,

Girasek²,

Békási³

et al. 2022

J Med Internet Res

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“…The "Health Unit Clinics" (Health Units that constitute Primary Health Care) are defined by their commitment to health promotion and protection, disease prevention, diagnosis, treatment, rehabilitation, harm reduction, and health maintenance on an individual and collective level, to provide comprehensive care that has a positive impact on the health status of communities [13]. They provide primary care services across the board, including the evaluation and diagnosis of acute illnesses and ongoing treatment for patients with chronic conditions [14].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Machine Learning Algorithms for Early Diagnosis of Deep Venous Thrombosis

Contreras-Luján

García-Guerrero

López-Bonilla

et al. 2022

MCA

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Deep venous thrombosis (DVT) is a disease that must be diagnosed quickly, as it can trigger the death of patients. Nowadays, one can find different ways to determine it, including clinical scoring, D-dimer, ultrasonography, etc. Recently, scientists have focused efforts on using machine learning (ML) and neural networks for disease diagnosis, progressively increasing the accuracy and efficacy. Patients with suspected DVT have no apparent symptoms. Using pattern recognition techniques, aiding good timely diagnosis, as well as well-trained ML models help to make good decisions and validation. The aim of this paper is to propose several ML models for a more efficient and reliable DVT diagnosis through its implementation on an edge device for the development of instruments that are smart, portable, reliable, and cost-effective. The dataset was obtained from a state-of-the-art article. It is divided into 85% for training and cross-validation and 15% for testing. The input data in this study are the Wells criteria, the patient’s age, and the patient’s gender. The output data correspond to the patient’s diagnosis. This study includes the evaluation of several classifiers such as Decision Trees (DT), Extra Trees (ET), K-Nearest Neighbor (KNN), Multi-Layer Perceptron Neural Network (MLP-NN), Random Forest (RF), and Support Vector Machine (SVM). Finally, the implementation of these ML models on a high-performance embedded system is proposed to develop an intelligent system for early DVT diagnosis. It is reliable, portable, open source, and low cost. The performance of different ML algorithms was evaluated, where KNN achieved the highest accuracy of 90.4% and specificity of 80.66% implemented on personal computer (PC) and Raspberry Pi 4 (RPi4). The accuracy of all trained models on PC and Raspberry Pi 4 is greater than 85%, while the area under the curve (AUC) values are between 0.81 and 0.86. In conclusion, as compared to traditional methods, the best ML classifiers are effective at predicting DVT in an early and efficient manner.

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Factors Influencing the Implementation of Evidence-Based Interventions with Street-Connected Children and Youth: Two Case Studies from Eldoret, Kenya

Embleton

Murphy

Kirwa

et al. 2023

Glob Implement Res Appl

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Exploratory attitude survey of homeless persons regarding telecare services in shelters providing mid- and long-term accommodation: The importance of trust

Cited by 11 publications

References 27 publications

Digital Technology Access and Health-Related Internet Use Among People Experiencing Homelessness in Hungary: Quantitative Survey

Digital Technology Access and Health-Related Internet Use Among People Experiencing Homelessness in Hungary: Quantitative Survey

Evaluation of Machine Learning Algorithms for Early Diagnosis of Deep Venous Thrombosis

Factors Influencing the Implementation of Evidence-Based Interventions with Street-Connected Children and Youth: Two Case Studies from Eldoret, Kenya

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