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Background: A digital health check can be used to screen health behavior risks in the population, help health care professionals with standardized risk estimation for their patients, and motivate a patient to change unhealthy behaviors. Long-term unemployed individuals comprise a particular subgroup with an increased risk of lifestyle-related diseases., Objective: This study aims to investigate the clinical utility of a general digital health examination, the STAR Duodecim Health Check and Coaching Program (STAR), which was developed in Finland, in the targeted screening of long-term unemployed individuals. For this purpose, we compared health challenges identified by a digital health check with those identified by a nurse during a face-to-face health check for unemployed individuals., Methods: In this comparison study, 49 unemployed participants attending a health check were recruited from two Finnish primary health care centers. The participants used STAR and attended a nurse's health check. Data were collected by surveys with multiple-choice and open-ended questions from the participants, nurses, and a study assistant who observed the session. The nurses were asked to name the three most significant health challenges for each participant. These health challenges were categorized into health challenges corresponding to STAR and these were compared with each other. Percentages of agreement between STAR and nurses were calculated. Sensitivity and specificity, as well as Cohen κ with P values and CIs, were computed for agreement., Results: STAR identified a total of 365 health challenges, an average of 7.4 (SD 2.5) health challenges per participant (n=49). The nurses named a total of 160 health challenges (n=47). In 53% (95% CI 38.1-67.9; n=25) of cases, STAR identified all categorized health challenges named by nurses. In 64% (95% CI 48.5-77.3; n=30) of cases, STAR identified at least 2/3 of the health challenges identified by nurses. Cohen κ was 0.877 (P<.001) for alcohol, indicating almost perfect agreement, and 0.440 (P<.001) for smoking and 0.457 (P=.001) for cholesterol, indicating moderate agreement. STAR left a total of 89 health challenges, an average of 1.8 (SD 1.1) per participant, uncategorized because STAR lacked an answer to the question or questions required for the classification of a certain health challenge. The participants did not always add information on their blood pressure (n=36, 74%), cholesterol (n=22, 45%), and waist circumference (n=15, 31%)., Conclusions: In conclusion, STAR identified most of the health challenges identified by nurses but missed some essential ones. Participants did not have information on measurements, such as blood pressure and cholesterol values, which are pivotal to STAR in assessing cardiovascular risks. Using the tool for screening or as a part of a traditional health check with necessary measurements and dialog with health care professionals may improve the risk assessments and streamline the health checks of unemployed individuals., International Registered Report Identifier (irrid): RR2-10.2196/27668., (©Venla Raussi, Sari Kujala, Iiris Hörhammer, Kaisa Savolainen, Reija Autio, Tuomas Koskela. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 16.10.2024.)

Background: Despite a recent rise in adoption, telemedicine consultations retention remains challenging, and aspects around the associated experiences and outcomes remain unclear. The need to further investigate these aspects was a motivating factor for conducting this scoping review., Objective: With a focus on synchronous telemedicine consultations between patients with nonmalignant chronic illnesses and health care professionals (HCPs), this scoping review aimed to gain insights into (1) the available evidence on telemedicine consultations to improve health outcomes for patients, (2) the associated behaviors and attitudes of patients and HCPs, and (3) how supplemental technology can assist in remote consultations., Methods: PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guided the scoping review process. Inclusion criteria were (1) involving adults with nonmalignant, noncommunicable chronic conditions as the study population; (2) focusing on health outcomes and experiences of and attitudes toward synchronous telemedicine consultations between patients and HCPs; and (3) conducting empirical research. A search strategy was applied to PubMed (including MEDLINE), CINAHL Complete, APA PsycNet, Web of Science, IEEE, and ACM Digital. Screening of articles and data extraction from included articles were performed in parallel and independently by 2 researchers, who corroborated their findings and resolved any conflicts., Results: Overall, 4167 unique articles were identified from the databases searched. Following multilayer filtration, 19 (0.46%) studies fulfilled the inclusion criteria for data extraction. They investigated 6 nonmalignant chronic conditions, namely chronic obstructive pulmonary disease, diabetes, chronic kidney disease, ulcerative colitis, hypertension, and congestive heart failure, and the telemedicine consultation modality varied in each case. Most observed positive health outcomes for patients with chronic conditions using telemedicine consultations. Patients generally favored the modality's convenience, but concerns were highlighted around cost, practical logistics, and thoroughness of clinical examinations. The majority of HCPs were also in favor of the technology, but a minority experienced reduced job satisfaction. Supplemental technological assistance was identified in relation to technical considerations, improved remote workflow, and training in remote care use., Conclusions: For patients with noncommunicable chronic conditions, telemedicine consultations are generally associated with positive health outcomes that are either directly or indirectly related to their ailment, but sustained improvements remain unclear. These modalities also indicate the potential to empower such patients to better manage their condition. HCPs and patients tend to be satisfied with remote care experience, and most are receptive to the modality as an option. Assistance from supplemental technologies mostly resides in addressing technical issues, and additional modules could be integrated to address challenges relevant to patients and HCPs. However, positive outcomes and attitudes toward the modality might not apply to all cases, indicating that telemedicine consultations are more appropriate as options rather than replacements of in-person visits., (©Pranavsingh Dhunnoo, Bridie Kemp, Karen McGuigan, Bertalan Meskó, Vicky O’Rourke, Michael McCann. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 09.07.2024.)

Background: The growth in the capabilities of telehealth have made it possible to identify individuals with a higher risk of uncontrolled diabetes and provide them with targeted support and resources to help them manage their condition. Thus, predictive modeling has emerged as a valuable tool for the advancement of diabetes management., Objective: This study aimed to conceptualize and develop a novel machine learning (ML) approach to proactively identify participants enrolled in a remote diabetes monitoring program (RDMP) who were at risk of uncontrolled diabetes at 12 months in the program., Methods: Registry data from the Livongo for Diabetes RDMP were used to design separate dynamic predictive ML models to predict participant outcomes at each monthly checkpoint of the participants' program journey (month-n models) from the first day of onboarding (month-0 model) up to the 11th month (month-11 model). A participant's program journey began upon onboarding into the RDMP and monitoring their own blood glucose (BG) levels through the RDMP-provided BG meter. Each participant passed through 12 predicative models through their first year enrolled in the RDMP. Four categories of participant attributes (ie, survey data, BG data, medication fills, and health signals) were used for feature construction. The models were trained using the light gradient boosting machine and underwent hyperparameter tuning. The performance of the models was evaluated using standard metrics, including precision, recall, specificity, the area under the curve, the F 1 -score, and accuracy., Results: The ML models exhibited strong performance, accurately identifying observable at-risk participants, with recall ranging from 70% to 94% and precision from 40% to 88% across the 12-month program journey. Unobservable at-risk participants also showed promising performance, with recall ranging from 61% to 82% and precision from 42% to 61%. Overall, model performance improved as participants progressed through their program journey, demonstrating the importance of engagement data in predicting long-term clinical outcomes., Conclusions: This study explored the Livongo for Diabetes RDMP participants' temporal and static attributes, identification of diabetes management patterns and characteristics, and their relationship to predict diabetes management outcomes. Proactive targeting ML models accurately identified participants at risk of uncontrolled diabetes with a high level of precision that was generalizable through future years within the RDMP. The ability to identify participants who are at risk at various time points throughout the program journey allows for personalized interventions to improve outcomes. This approach offers significant advancements in the feasibility of large-scale implementation in remote monitoring programs and can help prevent uncontrolled glycemic levels and diabetes-related complications. Future research should include the impact of significant changes that can affect a participant's diabetes management., (©Arash Khalilnejad, Ruo-Ting Sun, Tejaswi Kompala, Stefanie Painter, Roberta James, Yajuan Wang. Originally published in JMIR Formative Research (https://formative.jmir.org), 26.04.2024.)

Background: An aging population with a growing burden of chronic complex illnesses will seriously challenge the public health care system. Consequently, novel and efficacious treatment approaches are highly warranted. Based on our experiences with concentrated treatment formats for other health challenges, we developed a highly concentrated interdisciplinary group rehabilitation approach for chronic illnesses., Objective: We aim to explore the acceptability of the intervention and describe potential changes in functional impairment at follow-up., Methods: The cornerstones of the intervention are as follows: (1) prepare the patient for change prior to treatment, (2) focus on health promoting microchoices instead of symptoms, and (3) expect the patient to integrate the changes in everyday living with limited hands-on follow-up. The intervention will be delivered to patients with highly diverse primary symptoms, namely patients with low back pain, post-COVID-19 symptoms, anxiety and depression, and type 2 diabetes., Results: Recruitment started between August 2020 and January 2021 (according to the illness category). For initial 3-month results, recruitment is expected to be completed by the end of 2021., Conclusions: If successful, this study may have a substantial impact on the treatment of low back pain, post-COVID-19 symptoms, anxiety and depression, and type 2 diabetes, which together constitute a major socioeconomic cost. Further, the study may widen the evidence base for the use of the concentrated treatment format in a diverse group of medical conditions., International Registered Report Identifier (irrid): DERR1-10.2196/32216., (©Gerd Kvale, Bente Frisk, Marte Jürgensen, Tore Børtveit, Øystein Theodor Ødegaard-Olsen, Ane Wilhelmsen-Langeland, Bernt Bøgvald Aarli, Kristina Sandnes, Sidsel Rykken, Anne Haugstvedt, Sigurd William Hystad, Eirik Søfteland. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 07.10.2021.)

Background: Lifestyle choices and socioeconomic status have a significant impact on the expected onset of diseases, age of death, and risk factors concerning long-term illnesses and morbidity. STAR is an online health examination tool, which gives users a report that includes an evaluation of their life expectancy and an estimated risk for developing common long-term illnesses based on questions about health, characteristics, lifestyle, and quality of life., Objective: The goals of this study are to (1) review the capacity of STAR to recognize morbidity risks in comparison to a traditional nurse-led health examination and patient-reported health challenges; (2) evaluate the user experience and usability of STAR; and (3) assess the potential impact of STAR on the health confidence and motivation of patients to make healthier lifestyle choices., Methods: This mixed methods validation study will consist of a quantitative part (questionnaires) and a qualitative part (phone interviews and open-ended questions from the questionnaires). The participants will include 100 long-term unemployed individuals attending a health check for the unemployed. The participants will be recruited from three Finnish public health centers in Espoo, Hämeenlinna, and Tampere. At the health centers, the participants will use STAR and attend a nurse's health check. Surveys with multiple-choice and open-ended questions will be collected from the participants, the nurse, and a study assistant. The questionnaires include questions about the participant's background and health challenges from the patient and nurse points of view, as well as questions about how well the health challenges matched the STAR report. The questionnaires also gather data about user experience, health confidence, and usability of STAR. A study assistant will fill out an observer's form containing questions about use time and possible problems encountered while using STAR. A sample of the unemployed participants will be interviewed by telephone subsequently. For the quantitative data, descriptive statistics and a reliability analysis will be performed, and mean sum scores will be computed for the study variables. Thematic analysis of the qualitative data will be performed., Results: This study was approved by the Ethics Committee of the Expert Responsibility Area of Tampere University Hospital in June 2020 (ETL Code R20067). Data collection will begin in June 2021 and will take approximately 3-6 months., Conclusions: Online health examinations can improve the effectiveness of primary prevention in health care by supporting efficient evidence-based morbidity risk estimation and motivating patients to change unhealthy behaviors. A multimethod approach is used to allow for assessment of the tool's usefulness from the points of view of both professionals and patients. This study will further provide a rich understanding of how the tool can be used as part of routine health checks, and how and why the tool may or may not motivate users for making healthier lifestyle choices., International Registered Report Identifier (irrid): PRR1-10.2196/27668., (©Henna Kuhlberg, Sari Kujala, Iiris Hörhammer, Tuomas Koskela. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 01.06.2021.)

Background: Gamification is the use of game elements and techniques in nongaming contexts. The use of gamification in health care is receiving a great deal of attention in both academic research and the industry. However, it can be noticed that many gamification apps in health care do not follow any standardized guidelines., Objective: This research aims to (1) present a set of guidelines based on the validated framework the Wheel of Sukr and (2) assess the guidelines through expert interviews and focus group sessions with developers., Methods: Expert interviews (N=6) were conducted to assess the content of the guidelines and that they reflect the Wheel of Sukr. In addition, the guidelines were assessed by developers (N=15) in 5 focus group sessions, where each group had an average of 3 developers., Results: The guidelines received support from the experts. By the end of the sixth interview, it was determined that a saturation point was reached. Experts agreed that the guidelines accurately reflect the framework the Wheel of Sukr and that developers can potentially use them to create gamified self-management apps for chronic illnesses. Moreover, the guidelines were welcomed by developers who participated in the focus group sessions. They found the guidelines to be clear, useful, and implementable. Also, they were able to suggest many ways of gamifying a nongamified self-management app when they were presented with one., Conclusions: The findings suggest that the guidelines introduced in this research are clear, useful, and ready to be implemented for the creation of self-management apps that use the notion of gamification as described in the Wheel of Sukr framework. The guidelines are now ready to be practically tested. Further practical studies of the effectiveness of each element in the guidelines are to be carried out., (©Alaa AlMarshedi, Gary Wills, Ashok Ranchhod. Originally published in JMIR Serious Games (http://games.jmir.org), 12.05.2017.)

Background: Self-management of chronic illnesses is an ongoing issue in health care research. Gamification is a concept that arose in the field of computer science and has been borrowed by many other disciplines. It is perceived by many that gamification can improve the self-management experience of people with chronic illnesses. This paper discusses the validation of a framework (called The Wheel of Sukr) that was introduced to achieve this goal., Objective: This research aims to (1) discuss a gamification framework targeting the self-management of chronic illnesses and (2) validate the framework by diabetic patients, medical professionals, and game experts., Methods: A mixed-method approach was used to validate the framework. Expert interviews (N=8) were conducted in order to validate the themes of the framework. Additionally, diabetic participants completed a questionnaire (N=42) in order to measure their attitudes toward the themes of the framework., Results: The results provide a validation of the framework. This indicates that gamification might improve the self-management of chronic illnesses, such as diabetes. Namely, the eight themes in the Wheel of Sukr (fun, esteem, socializing, self-management, self-representation, motivation, growth, sustainability) were perceived positively by 71% (30/42) of the participants with P value <.001., Conclusions: In this research, both the interviews and the questionnaire yielded positive results that validate the framework (The Wheel of Sukr). Generally, this study indicates an overall acceptance of the notion of gamification in the self-management of diabetes., Competing Interests: Conflicts of Interest: None declared.