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Swahn MH, Gittner KB, Lyons MJ, Nielsen K, Mobley K, Culbreth R, Palmier J, Johnson NE, Matte M, Nabulya A. Advancing mHealth Research in Low-Resource Settings: Young Women's Insights and Implementation Challenges with Wearable Smartwatch Devices in Uganda. SENSORS (BASEL, SWITZERLAND) 2024; 24:5591. [PMID: 39275502 PMCID: PMC11398240 DOI: 10.3390/s24175591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2024] [Revised: 08/18/2024] [Accepted: 08/25/2024] [Indexed: 09/16/2024]
Abstract
In many regions globally, including low-resource settings, there is a growing trend towards using mHealth technology, such as wearable sensors, to enhance health behaviors and outcomes. However, adoption of such devices in research conducted in low-resource settings lags behind use in high-resource areas. Moreover, there is a scarcity of research that specifically examines the user experience, readiness for and challenges of integrating wearable sensors into health research and community interventions in low-resource settings specifically. This study summarizes the reactions and experiences of young women (N = 57), ages 18 to 24 years, living in poverty in Kampala, Uganda, who wore Garmin vívoactive 3 smartwatches for five days for a research project. Data collected from the Garmins included participant location, sleep, and heart rate. Through six focus group discussions, we gathered insights about the participants' experiences and perceptions of the wearable devices. Overall, the wearable devices were met with great interest and enthusiasm by participants. The findings were organized across 10 domains to highlight reactions and experiences pertaining to device settings, challenges encountered with the device, reports of discomfort/comfort, satisfaction, changes in daily activities, changes to sleep, speculative device usage, community reactions, community dynamics and curiosity, and general device comfort. The study sheds light on the introduction of new technology in a low-resource setting and also on the complex interplay between technology and culture in Kampala's slums. We also learned some insights into how wearable devices and perceptions may influence behaviors and social dynamics. These practical insights are shared to benefit future research and applications by health practitioners and clinicians to advance and enhance the implementation and effectiveness of wearable devices in similar contexts and populations. These insights and user experiences, if incorporated, may enhance device acceptance and data quality for those conducting research in similar settings or seeking to address population-specific needs and health issues.
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Affiliation(s)
- Monica H Swahn
- Wellstar College of Health and Human Services, Kennesaw State University, Kennesaw, GA 30144, USA
| | - Kevin B Gittner
- Wellstar College of Health and Human Services, Kennesaw State University, Kennesaw, GA 30144, USA
- College of Computing and Software Engineering, Kennesaw State University, Kennesaw, GA 30144, USA
| | - Matthew J Lyons
- Wellstar College of Health and Human Services, Kennesaw State University, Kennesaw, GA 30144, USA
| | - Karen Nielsen
- School of Public Health, Georgia State University, Atlanta, GA 30303, USA
| | - Kate Mobley
- College of Computing and Software Engineering, Kennesaw State University, Kennesaw, GA 30144, USA
| | - Rachel Culbreth
- American College of Medical Toxicology, Phoenix, AZ 85028, USA
| | - Jane Palmier
- Wellstar College of Health and Human Services, Kennesaw State University, Kennesaw, GA 30144, USA
| | - Natalie E Johnson
- Division of Clinical Epidemiology, Department of Clinical Research, University Hospital and University of Basel, 4051 Basel, Switzerland
| | - Michael Matte
- Uganda Youth Development Link, Kampala P.O. Box 12659, Uganda
| | - Anna Nabulya
- Uganda Youth Development Link, Kampala P.O. Box 12659, Uganda
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2
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Boissin C, Laflamme L, Jian F, Lundin M, Fredrik H, Lee W, Nikki A, Johan L. Development and evaluation of deep learning algorithms for assessment of acute burns and the need for surgery. Sci Rep 2023; 13:1794. [PMID: 36720894 PMCID: PMC9889389 DOI: 10.1038/s41598-023-28164-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 01/13/2023] [Indexed: 02/02/2023] Open
Abstract
Assessment of burn extent and depth are critical and require very specialized diagnosis. Automated image-based algorithms could assist in performing wound detection and classification. We aimed to develop two deep-learning algorithms that respectively identify burns, and classify whether they require surgery. An additional aim assessed the performances in different Fitzpatrick skin types. Annotated burn (n = 1105) and background (n = 536) images were collected. Using a commercially available platform for deep learning algorithms, two models were trained and validated on 70% of the images and tested on the remaining 30%. Accuracy was measured for each image using the percentage of wound area correctly identified and F1 scores for the wound identifier; and area under the receiver operating characteristic (AUC) curve, sensitivity, and specificity for the wound classifier. The wound identifier algorithm detected an average of 87.2% of the wound areas accurately in the test set. For the wound classifier algorithm, the AUC was 0.885. The wound identifier algorithm was more accurate in patients with darker skin types; the wound classifier was more accurate in patients with lighter skin types. To conclude, image-based algorithms can support the assessment of acute burns with relatively good accuracy although larger and different datasets are needed.
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Affiliation(s)
- Constance Boissin
- Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden. .,Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
| | - Lucie Laflamme
- Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden.,Institute for Social and Health Sciences, University of South Africa, Johannesburg, South Africa
| | - Fransén Jian
- Department of Plastic and Maxillofacial Surgery, Burn Center, Uppsala University Hospital, Uppsala, Sweden.,Department of Surgical Sciences, Plastic Surgery, Uppsala University, Uppsala, Sweden
| | - Mikael Lundin
- Institute for Molecular Medicine Finland FIMM, Helsinki Institute for Life Science HiLIFE, University of Helsinki, Helsinki, Finland
| | - Huss Fredrik
- Department of Plastic and Maxillofacial Surgery, Burn Center, Uppsala University Hospital, Uppsala, Sweden.,Department of Surgical Sciences, Plastic Surgery, Uppsala University, Uppsala, Sweden
| | - Wallis Lee
- Division of Emergency Medicine, Faculty of Medicine and Health Sciences, Stellenbosch University, Bellville, South Africa.,Division of Emergency Medicine, University of Cape Town, Cape Town, South Africa
| | - Allorto Nikki
- Pietermaritzburg Burn Service, Department of General Surgery, University of Kwa-Zulu Natal, Pietermaritzburg, South Africa
| | - Lundin Johan
- Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden.,Institute for Molecular Medicine Finland FIMM, Helsinki Institute for Life Science HiLIFE, University of Helsinki, Helsinki, Finland
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Francese R, Attanasio P. Emotion detection for supporting depression screening. MULTIMEDIA TOOLS AND APPLICATIONS 2022; 82:12771-12795. [PMID: 36570729 PMCID: PMC9761032 DOI: 10.1007/s11042-022-14290-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 10/14/2022] [Accepted: 12/03/2022] [Indexed: 06/17/2023]
Abstract
Depression is the most prevalent mental disorder in the world. One of the most adopted tools for depression screening is the Beck Depression Inventory-II (BDI-II) questionnaire. Patients may minimize or exaggerate their answers. Thus, to further examine the patient's mood while filling in the questionnaire, we propose a mobile application that captures the BDI-II patient's responses together with their images and speech. Deep learning techniques such as Convolutional Neural Networks analyze the patient's audio and image data. The application displays the correlation between the patient's emotional scores and DBI-II scores to the clinician at the end of the questionnaire, indicating the relationship between the patient's emotional state and the depression screening score. We conducted a preliminary evaluation involving clinicians and patients to assess (i) the acceptability of proposed application for use in clinics and (ii) the patient user experience. The participants were eight clinicians who tried the tool with 21 of their patients. The results seem to confirm the acceptability of the app in clinical practice.
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Affiliation(s)
- Rita Francese
- Computer Science Department, Università degli Studi di Salerno, Via Giovanni Paolo II, 132, Fisciano, 84084 (SA) Italy
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Sekandi JN, Murray K, Berryman C, Davis-Olwell P, Hurst C, Kakaire R, Kiwanuka N, Whalen CC, Mwaka ES. Ethical, Legal and Sociocultural Issues in the Use of Mobile Technologies and Call Detail Records Data for Public Health Research in the East African Region: A Scoping Review (Preprint). Interact J Med Res 2021; 11:e35062. [PMID: 35533323 PMCID: PMC9204580 DOI: 10.2196/35062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 02/17/2022] [Accepted: 04/14/2022] [Indexed: 11/13/2022] Open
Affiliation(s)
- Juliet Nabbuye Sekandi
- Global Health Institute, College of Public Health, University of Georgia, Athens, GA, United States
- Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA, United States
| | - Kenya Murray
- Global Health Institute, College of Public Health, University of Georgia, Athens, GA, United States
- Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA, United States
| | - Corinne Berryman
- Department of Health Promotion and Behavior, College of Public Health, University of Georgia, Athens, GA, United States
| | - Paula Davis-Olwell
- Global Health Institute, College of Public Health, University of Georgia, Athens, GA, United States
- Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA, United States
| | - Caroline Hurst
- Department of Health Promotion and Behavior, College of Public Health, University of Georgia, Athens, GA, United States
| | - Robert Kakaire
- Global Health Institute, College of Public Health, University of Georgia, Athens, GA, United States
| | - Noah Kiwanuka
- Department of Epidemiology and Biostatistics, School of Public Health, Makerere University, Kampala, Uganda
| | - Christopher C Whalen
- Global Health Institute, College of Public Health, University of Georgia, Athens, GA, United States
- Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA, United States
| | - Erisa Sabakaki Mwaka
- Department of Anatomy, School of Biomedical Sciences, College of Health Sciences, Makerere University, Kampala, Uganda
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Gerhards H, Weber K, Bittner U, Fangerau H. Machine Learning Healthcare Applications (ML-HCAs) Are No Stand-Alone Systems but Part of an Ecosystem - A Broader Ethical and Health Technology Assessment Approach is Needed. THE AMERICAN JOURNAL OF BIOETHICS : AJOB 2020; 20:46-48. [PMID: 33103972 DOI: 10.1080/15265161.2020.1820104] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
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6
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Laflamme L, Wallis LA. Seven pillars for ethics in digital diagnostic assistance among clinicians: Take-homes from a multi-stakeholder and multi-country workshop. J Glob Health 2020; 10:010326. [PMID: 32509282 PMCID: PMC7244932 DOI: 10.7189/jogh.10.010326] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Affiliation(s)
- Lucie Laflamme
- Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden.,University of South Africa, Institute for Social and Health Sciences, Johannesburg, South Africa
| | - Lee Alan Wallis
- Division of Emergency Medicine, Faculty of Medicine and Health Sciences, Stellenbosch University, Bellville, South Africa.,Division of Emergency Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
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Chipps J. Clients' perceptions and experiences of targeted digital communication accessible via mobile devices for reproductive, newborn, child, and adolescent health. Res Nurs Health 2020; 43:431-434. [PMID: 32394460 DOI: 10.1002/nur.22028] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Accepted: 04/28/2020] [Indexed: 11/08/2022]
Affiliation(s)
- Jennifer Chipps
- School of Nursing, University of the Western Cape, Bellville, Western Cape, South Africa
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Vaisman A, Linder N, Lundin J, Orchanian-Cheff A, Coulibaly JT, Ephraim RK, Bogoch II. Artificial intelligence, diagnostic imaging and neglected tropical diseases: ethical implications. Bull World Health Organ 2020; 98:288-289. [PMID: 32284655 PMCID: PMC7133484 DOI: 10.2471/blt.19.237560] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2019] [Revised: 12/16/2019] [Accepted: 12/17/2019] [Indexed: 12/20/2022] Open
Affiliation(s)
- Alon Vaisman
- Division Infectious Diseases, Toronto General Hospital, University of Toronto, 14EN 209, 200 Elizabeth Street, Toronto, Ontario M5G 2C4, Canada
| | - Nina Linder
- Department of Women's and Children's Health, International Maternal and Child health, Uppsala University, Sweden
| | - Johan Lundin
- Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden
| | | | - Jean T Coulibaly
- Unité de Formation et de Recherche Biosciences, Université Félix Houphouët-Boigny, Abidjan, Côte d'Ivoire
| | - Richard Kd Ephraim
- Department of Medical Laboratory Sciences, University of Cape Coast, Cape Coast, Ghana
| | - Isaac I Bogoch
- Division Infectious Diseases, Toronto General Hospital, University of Toronto, 14EN 209, 200 Elizabeth Street, Toronto, Ontario M5G 2C4, Canada
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