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1.
Multimedia | Multimedia Resources | ID: multimedia-9944

ABSTRACT


Subject(s)
Mobile Applications , Mentoring
2.
Multimedia | Multimedia Resources | ID: multimedia-9945

ABSTRACT


Subject(s)
Mobile Applications , Mentoring
3.
Multimedia | Multimedia Resources | ID: multimedia-9947

ABSTRACT


Subject(s)
Mobile Applications , Mentoring
4.
Medicine (Baltimore) ; 101(35): e30260, 2022 Sep 02.
Article in English | MEDLINE | ID: mdl-36107583

ABSTRACT

BACKGROUND: Employee stress and well-being affect organizational efficiency and productivity, as well as physical and psychological health of employees. Mindfulness is believed to reduce stress, prevent diseases, and promote well-being. Mindfulness has been used as the main component of various smartphone-based healthcare applications. Previous studies have suggested that mindfulness applications have a positive effect on employee stress and mental health. However, relatively few randomized controlled trials have examined the effectiveness of mindfulness applications on employees. This study aims to evaluate whether mobile mindfulness training (MMT) as a stress self-management tool improves employees' perceived stress, subjective well-being, and Mibyeong, a condition that is not a disease but shows obvious health abnormalities. METHODS: Participants were recruited through advertisements displayed at 3 workplaces, including a patent attorney's office, a construction company, and a public relations firm. A total of 45 employees were randomly assigned to 1 of 2 groups: the MMT group (Group A) receiving smartphone application-based mindfulness training, and a wait-list control (WLC) group (Group B), who received no intervention. Group A employees conducted MMT following daily and event guidelines for 4 weeks. In contrast, Group B employees did not receive any intervention in that time. The outcome variables were perceived stress, subjective well-being, and Mibyeong. Surveys were conducted at baseline, post-intervention, and follow-up (fourth week post-intervention). RESULTS: Demographic characteristics and baseline assessments were not significantly different between the 2 groups. The results of this study revealed that subjective well-being and Mibyeong were significantly improved in the MMT group compared with the WLC group. Moreover, this improvement was maintained up to at least 4 weeks later. However, perceived stress was not significantly reduced in the MMT group compared to the WLC group. CONCLUSION: Four weeks of MMT improved the subjective well-being and Mibyeong of employees. However, further studies are required to investigate the effect of MMT on other areas of mental health.


Subject(s)
Mindfulness , Mobile Applications , Humans , Mental Health , Mindfulness/methods , Organometallic Compounds , Pilot Projects , Randomized Controlled Trials as Topic
5.
J Med Syst ; 46(11): 70, 2022 Sep 16.
Article in English | MEDLINE | ID: mdl-36109423

ABSTRACT

The use of mobile health apps to improve diet and nutrition behaviors has increased in recent years. Several studies have described the benefits and advantages of this technology as a complement to interventions for improving nutrition behaviors and nutrition-related health outcomes, including obesity indices and clinical parameters. Few of these works have developed clinical mobile health apps for children, and although parents play a critical role in children's nutrition behaviors, work targeting parents is scarce. The work presented in this paper describes the development of the PersuHabit app, a stand-alone mobile health app targeting parents to promote the intake of fruits and vegetables (FVs) and reduce the intake of ultra-processed foods (UPF) in children aged 6 to 10 years. The paper also presents the execution of an exploratory pilot study to assess the feasibility, acceptability, and preliminary effects of the PersuHabit app. The results are presented and discussed, and actions for further improvement of the PersuHabit app are identified.


Subject(s)
Mobile Applications , Telemedicine , Child , Feasibility Studies , Feeding Behavior , Humans , Parents , Pilot Projects , Telemedicine/methods
6.
BMJ Open ; 12(9): e062121, 2022 09 14.
Article in English | MEDLINE | ID: mdl-36104122

ABSTRACT

OBJECTIVES: We evaluated an online Sleep Health and Wellness (SHAW) programme paired with dayzz, a personalised sleep training programme deployed via smartphone application (dayzz app) that promotes healthy sleep and treatment for sleep disorders, among employees at a large healthcare organisation. DESIGN: Open-label, randomised, parallel-group controlled trial. SETTING: A healthcare employer in the USA. PARTICIPANTS: 1355 daytime workers. INTERVENTION: Participants were randomised to intervention (n=794) or control (n=561) on consent. Intervention participants received the SHAW educational programme at baseline plus access to the personalised dayzz app for up to 9 months. The control condition received the intervention at month 10. PRIMARY AND SECONDARY OUTCOME MEASURES: Our primary outcome measures were sleep-related behavioural changes (eg, consistent sleep schedule); sleep behaviour tracked on an electronic sleep diary and sleep quality. Our secondary outcome measures included employee absenteeism, performance and productivity; stress, mood, alertness and energy; and adverse health and safety outcomes (eg, accidents). RESULTS: At follow-up, employees in the intervention condition were more likely to report increased sleep duration on work (7.20 vs 6.99, p=0.01) and on free (8.26 vs 8.04, p=0.03) nights. At follow-up, the prevalence of poor sleep quality was lower in the intervention (n=160 of 321, 50%) compared with control (n=184 of 327, 56%) (p=0.04). The mean total dollars lost per person per month due to reduced workplace performance (presenteeism) was less in the intervention condition (US$1090 vs US$1321, p=0.001). Employees in the intervention reported fewer mental health visits (RR 0.72, 95% CI 0.56 to 0.94, p=0.01) and lower healthcare utilisation over the study interval (RR 0.81, 95% CI 0.67 to 0.98, p=0.03). We did not observe differences in stress (4.7 (95% CI 4.6 to 4.8) vs 4.7 (95% CI 4.6 to 4.8)), mood (4.5 (95% CI 4.4 to 4.6) vs 4.6 (95% CI 4.5 to 4.7)), alertness (4.9 (95% CI 4.8 to 5.0) vs 5.0 (95% CI 4.9 to 5.1)) or adverse health and safety outcomes (motor vehicle crashes: OR 0.82 (95% CI 0.34 to 1.9); near-miss crashes: OR=0.89 (95% CI 0.5 to 1.5) and injuries: 0.9 (95% CI 0.6 to 1.3)); energy was higher at follow-up in the intervention group (4.3 vs 4.5; p=0.03). CONCLUSIONS: Results from this trial demonstrate that a SHAW programme followed by access to the digital dayzz app can be beneficial to both the employee and employer. TRIAL REGISTRATION NUMBER: NCT04224285.


Subject(s)
Mobile Applications , Health Promotion , Humans , Patient Acceptance of Health Care , Sleep , Smartphone
7.
PLoS One ; 17(9): e0272235, 2022.
Article in English | MEDLINE | ID: mdl-36107954

ABSTRACT

BACKGROUND: Mobile health applications (apps) are increasing in interest to enhance patient self-management. Few apps are actually used by patients and have been developed for patients with inflammatory arthritis (IA) treated with disease-modifying anti-rheumatic drugs which use entails risk of adverse effects such as infections. OBJECTIVE: To develop Hiboot, a self-management mobile app for patients with IA, by using a user-centred step-by-step approach and assess its real-life use. METHODS: The app development included first a qualitative study with semi-guided audiotaped interviews of 21 patients to identify the impact of IA on daily life and patient treatments practices and an online cross-sectional survey of 344 patients to assess their health apps use in general and potential user needs. A multidisciplinary team developed the first version of the app via five face-to-face meetings. After app launch, a second qualitative study of 21 patients and a users' test of 13 patients and 3 rheumatologists led to the app's current version. The number of app installations, current users and comments were collected from the Google Play store and the Apple store. RESULTS: The qualitative study revealed needs for counselling, patient-health professional partnership, and skills to cope with risk situations; 86.8% participants would be ready to use an app primarily on their rheumatologist's recommendation. Six functionalities were implemented: a safety checklist before treatment administration, aids in daily life situations based on the French academic recommendations, treatment reminders, global well-being self-assessment, periodic counselling messages, and a diary. The Hiboot app was installed 20,500 times from September 2017 to October 2020, with 4300 regular current users. Scores were 4.4/5 stars at Android and iOS stores. CONCLUSION: Hiboot is a free self-management app for patients with IA developed by a step-by-step process including patients and health professionals. Further evaluation of the Hiboot benefit is needed.


Subject(s)
Antirheumatic Agents , Arthritis , Mobile Applications , Self-Management , Cross-Sectional Studies , Humans , Smartphone
8.
BMC Cancer ; 22(1): 989, 2022 Sep 17.
Article in English | MEDLINE | ID: mdl-36115962

ABSTRACT

BACKGROUND: Radiotherapy of head-and-neck cancer (SCCHN) is often associated with acute toxicity. In a previous trial, daily reminders by staff members to perform skin care resulted in less dermatitis. This randomized trial investigated whether a mobile application can replace these reminders. METHODS: Patients were stratified according to tumor site, treatment and center. Fifty-three patients were eligible for per-protocol-set (25 with, 28 without app). Primary endpoint was grade ≥ 2 dermatitis until 60 Gy. Secondary endpoints included dermatitis grade ≥ 2 until end of radiotherapy (EOT), dermatitis grade ≥ 3, and mucositis grade ≥ 2 and ≥ 3. RESULTS: After an interim analysis, the study was terminated (delayed and slow accrual). Until 60 Gy, grade ≥ 2 dermatitis rates were 72% with vs. 82% without app (p = 0.38), grade ≥ 3 dermatitis rates 20% vs. 11% (p = 0.45). Until EOT, grade ≥ 2 and ≥ 3 dermatitis rates were 72% vs. 86% (p = 0.22) and 24% vs. 18% (p = 0.58). Until 60 Gy, grade ≥ 2 and ≥ 3 mucositis rates were 76% vs. 82% (p = 0.58) and 20% vs. 36% (p = 0.20). Until EOT, corresponding mucositis rates were 76% vs. 82% (p = 0.58) and 28% vs. 43% (p = 0.26). CONCLUSION: Given the limitations of this trial, the reminder app led to non-significant reduction of grade ≥ 2 dermatitis, grade ≥ 2 mucositis and ≥ 3 mucositis. Additional studies are required to define the value of reminder apps during radiotherapy for SCCHN.


Subject(s)
Head and Neck Neoplasms , Mobile Applications , Mucositis , Radiation Injuries , Radiodermatitis , Head and Neck Neoplasms/radiotherapy , Humans , Radiodermatitis/etiology
9.
Comput Intell Neurosci ; 2022: 4115767, 2022.
Article in English | MEDLINE | ID: mdl-36105641

ABSTRACT

Advances in deep learning significantly affect reinforcement learning, which results in the emergence of Deep RL (DRL). DRL does not need a data set and has the potential beyond the performance of human experts, resulting in significant developments in the field of artificial intelligence. However, because a DRL agent has to interact with the environment a lot while it is trained, it is difficult to be trained directly in the real environment due to the long training time, high cost, and possible material damage. Therefore, most or all of the training of DRL agents for real-world applications is conducted in virtual environments. This study focused on the difficulty in a mobile robot to reach its target by making a path plan in a real-world environment. The Minimalistic Gridworld virtual environment has been used for training the DRL agent, and to our knowledge, we have implemented the first real-world implementation for this environment. A DRL algorithm with higher performance than the classical Deep Q-network algorithm was created with the expanded environment. A mobile robot was designed for use in a real-world application. To match the virtual environment with the real environment, algorithms that can detect the position of the mobile robot and the target, as well as the rotation of the mobile robot, were created. As a result, a DRL-based mobile robot was developed that uses only the top view of the environment and can reach its target regardless of its initial position and rotation.


Subject(s)
Mobile Applications , Robotics , Algorithms , Artificial Intelligence , Humans , Reinforcement, Psychology , Robotics/methods
10.
JMIR Mhealth Uhealth ; 10(9): e40576, 2022 Sep 14.
Article in English | MEDLINE | ID: mdl-36103226

ABSTRACT

BACKGROUND: Persuasive technology is an umbrella term that encompasses software (eg, mobile apps) or hardware (eg, smartwatches) designed to influence users to perform preferable behavior once or on a long-term basis. Considering the ubiquitous nature of mobile devices across all socioeconomic groups, user behavior modification thrives under the personalized care that persuasive technology can offer. However, there is no guidance for developing personalized persuasive technologies based on the psychological characteristics of users. OBJECTIVE: This study examined the role that psychological characteristics play in interpreted mobile health (mHealth) screen perceived persuasiveness. In addition, this study aims to explore how users' psychological characteristics drive the perceived persuasiveness of digital health technologies in an effort to assist developers and researchers of digital health technologies by creating more engaging solutions. METHODS: An experiment was designed to evaluate how psychological characteristics (self-efficacy, health consciousness, health motivation, and the Big Five personality traits) affect the perceived persuasiveness of digital health technologies, using the persuasive system design framework. Participants (n=262) were recruited by Qualtrics International, Inc, using the web-based survey system of the XM Research Service. This experiment involved a survey-based design with a series of 25 mHealth app screens that featured the use of persuasive principles, with a focus on physical activity. Exploratory factor analysis and linear regression were used to evaluate the multifaceted needs of digital health users based on their psychological characteristics. RESULTS: The results imply that an individual user's psychological characteristics (self-efficacy, health consciousness, health motivation, and extraversion) affect interpreted mHealth screen perceived persuasiveness, and combinations of persuasive principles and psychological characteristics lead to greater perceived persuasiveness. The F test (ie, ANOVA) for model 1 was significant (F9,6540=191.806; P<.001), with an adjusted R2 of 0.208, indicating that the demographic variables explained 20.8% of the variance in perceived persuasiveness. Gender was a significant predictor, with women having higher perceived persuasiveness (P=.008) relative to men. Age was a significant predictor of perceived persuasiveness with individuals aged 40 to 59 years (P<.001) and ≥60 years (P<.001). Model 2 was significant (F13,6536=341.035; P<.001), with an adjusted R2 of 0.403, indicating that the demographic variables self-efficacy, health consciousness, health motivation, and extraversion together explained 40.3% of the variance in perceived persuasiveness. CONCLUSIONS: This study evaluates the role that psychological characteristics play in interpreted mHealth screen perceived persuasiveness. Findings indicate that self-efficacy, health consciousness, health motivation, extraversion, gender, age, and education significantly influence the perceived persuasiveness of digital health technologies. Moreover, this study showed that varying combinations of psychological characteristics and demographic variables affected the perceived persuasiveness of the primary persuasive technology category.


Subject(s)
Mobile Applications , Telemedicine , Female , Humans , Male , Motivation , Persuasive Communication , Self Efficacy
11.
J Orthop Surg Res ; 17(1): 417, 2022 Sep 14.
Article in English | MEDLINE | ID: mdl-36104792

ABSTRACT

OBJECTIVE: Primary purpose of this study was to determine the validity and reliability of the OneStep smartphone application in healthy adults. Secondary purpose was to determine the feasibility of measuring gait dysfunction, limitation in spatiotemporal characteristics, longitudinally in patients following total hip or knee arthroplasty. METHODS: First objective, 20 healthy adults (mean age, 42.3 ± 19.7 years; 60% males; mean body mass index, 29.0 ± 5.2 kg/m2) underwent gait analysis under four gait conditions (self-selected gait speed, fixed gait speed at 0.8 m/s, fixed gait speed at 2.0 m/s and self-selected gait speed with dual task) for the validity and reliability of the smartphone to the motion laboratory. Reliability was determined by intraclass correlation coefficients. Validity was determined by Pearson correlations. Agreement was assessed by the Bland-Altman method. Second objective, 12 additional patients with total hip or knee arthroplasty (mean age, 58.7 ± 6.5 years; 58% males; mean body mass index, 28.9 ± 5.8 kg/m2) were measured at 2- and 10 weeks postoperatively. The smartphone application was used to evaluate change in gait dysfunction over time within the patients' own environment using paired t test. RESULTS: The smartphone application demonstrated moderate-to-excellent intraclass correlation coefficients for reliability between-system (ICC range, 0.56-0.99), -limb (ICC range, 0.62-0.99) and -device (ICC range, 0.61-0.96) for gait analysis of healthy adults. Pearson correlations were low-to-very high between methods (r range, 0.45-0.99). Bland-Altman analysis revealed relative underestimation of spatiotemporal variables by the smartphone application compared to the motion system. For patients following total hip or knee arthroplasty, gait analysis using the OneStep application demonstrated significant improvement (p < 0.001, Cohen's d > 0.95) in gait dysfunction between 2- and 10 weeks postoperatively. CONCLUSION: The smartphone application can be a valid, reliable and feasible alternative to motion laboratories in evaluating deficits in gait dysfunction in various environments and clinical settings.


Subject(s)
Mobile Applications , Smartphone , Adult , Aged , Feasibility Studies , Female , Gait , Humans , Male , Middle Aged , Reproducibility of Results , Young Adult
13.
Article in English | MEDLINE | ID: mdl-36078395

ABSTRACT

This study examines fitness app use patterns and their correlates among Chinese users from the perspectives of uses and gratification theory and self-determination theory. Our sample comprised 632 users of WeRun, the fitness plugin of WeChat, the largest Chinese mobile social networking app; participants completed an online survey and provided self-tracked physical activity data, which were subjected to latent class analysis. Based on the four-class latent class model (which yielded the best model fit and the most interpretable results), 30.5%, 27.5%, 24.7%, and 17.3% of the users were categorized as light users, reward-oriented users, lifestyle-oriented users, and interaction-oriented users, respectively. Moreover, class membership was associated with gender, age, education, income, life satisfaction, autonomy, and platform-based motivations. There is a significant heterogeneity in fitness app use and exercise behaviors. Platform-based motivations and autonomy are important classification factors, as users are looking for specific kinds of gratification from their use of fitness apps. Demographics and individual characteristics are also explanatory factors for class membership. The study findings suggest that fitness app designers should segment users based on motivation and gratification.


Subject(s)
Mobile Applications , China , Exercise , Humans , Latent Class Analysis , Surveys and Questionnaires
14.
Article in English | MEDLINE | ID: mdl-36078523

ABSTRACT

The COVID-19 pandemic has changed the fitness-related field. More people started working out at home, and the use of fitness mobile apps that can measure the amount of exercise through a scientific method has increased compared to before the COVID-19 pandemic. This phenomenon is likely to continue even after the COVID-19 pandemic, and therefore this study aimed to investigate the importance of and satisfaction with a fitness app's functions according to consumers while using the fitness mobile app. Through this study, we intended to provide data for creating an environment where users can use fitness mobile apps consistently. A total of 420 questionnaires were distributed through Google Survey for about 3 months, from 13 September to 20 November 2020, and a total of 399 complete questionnaires were analyzed in this study. Regarding the data processing methods, frequency analysis, exploratory factor analysis, reliability analysis, descriptive statistical analysis, and IPA were used. The results are as follows. First, the first quadrant of the IPA matrix indicated the high importance of and satisfaction with the fitness mobile app, and included five attributes: cost-effectiveness, easy-to-understand information, ease of use and application, privacy protection, and compatibility with other devices. Second, the second quadrant of the matrix indicated relatively low satisfaction in association to high importance and included five attributes: accurate exercise information provision, design efficiency, daily exercise amount setting, convenient icons and interface, and provision of images and videos in appropriate proportions. Third, the third quadrant of the matrix, indicating low importance and low satisfaction, included five attributes: not sharing personal information, overall design composition and color, customer service, reliable security level, and providing information on goal achievement after exercising. Fourth, in the quadrant of the matrix, indicating low importance and high satisfaction, five attributes were included: exercise notification function, continuous service provision, step count and heart rate information, individual exercise recommendation, and individual body type analysis information.


Subject(s)
COVID-19 , Mobile Applications , COVID-19/epidemiology , Exercise , Humans , Pandemics , Reproducibility of Results
15.
Article in English | MEDLINE | ID: mdl-36078567

ABSTRACT

In Liberia, female genital mutilation/cutting (FGM/C) is a legally allowed initiation ritual in the secret Sande society. Due to the secrecy, Liberian healthcare providers receive little education on FGM/C and its health consequences. As mobile learning approaches proved to efficiently increase providers' knowledge and skills, a mobile application ('app') was designed to support self-learning, decision-making, and the follow-up of FGM/C survivors' health. The 'app' was introduced in a capacity-building project in 2019 and evaluated through this qualitative study to assess healthcare provider's needs and acceptance. We conducted 22 semi-structured interviews and eight focus group discussions with 42 adult healthcare providers in three Liberian counties. A thematic approach grounded in descriptive phenomenology guided data analysis and led to three main themes: the 'app', mobile learning and health education, and personal impression. Healthcare providers judge the 'app' useful to broaden their knowledge and skills, which might lead to better FGM/C detection and management. The 'app' might further facilitate patient and community education about the negative health consequences of FMG/C, possibly contributing to a reduction of FGM/C prevalence.


Subject(s)
Circumcision, Female , Mobile Applications , Adult , Delivery of Health Care , Female , Health Knowledge, Attitudes, Practice , Humans , Liberia , Smartphone , Survivors
16.
BMC Health Serv Res ; 22(1): 1120, 2022 Sep 04.
Article in English | MEDLINE | ID: mdl-36057715

ABSTRACT

BACKGROUND: Regular physical activity (PA), healthy habits, and an appropriate diet are recommended guidelines to maintain a healthy lifestyle. A healthy lifestyle can help to avoid chronic diseases and long-term illnesses. A monitoring and automatic personalized lifestyle recommendation system (i.e., automatic electronic coach or eCoach) with considering clinical and ethical guidelines, individual health status, condition, and preferences may successfully help participants to follow recommendations to maintain a healthy lifestyle. As a prerequisite for the prototype design of such a helpful eCoach system, it is essential to involve the end-users and subject-matter experts throughout the iterative design process. METHODS: We used an iterative user-centered design (UCD) approach to understend context of use and to collect qualitative data to develop a roadmap for self-management with eCoaching. We involved researchers, non-technical and technical, health professionals, subject-matter experts, and potential end-users in design process. We designed and developed the eCoach prototype in two stages, adopting different phases of the iterative design process. In design workshop 1, we focused on identifying end-users, understanding the user's context, specifying user requirements, designing and developing an initial low-fidelity eCoach prototype. In design workshop 2, we focused on maturing the low-fidelity solution design and development for the visualization of continuous and discrete data, artificial intelligence (AI)-based interval forecasting, personalized recommendations, and activity goals. RESULTS: The iterative design process helped to develop a working prototype of eCoach system that meets end-user's requirements and expectations towards an effective recommendation visualization, considering diversity in culture, quality of life, and human values. The design provides an early version of the solution, consisting of wearable technology, a mobile app following the "Google Material Design" guidelines, and web content for self-monitoring, goal setting, and lifestyle recommendations in an engaging manner between the eCoach app and end-users. CONCLUSIONS: The adopted iterative design process brings in a design focus on the user and their needs at each phase. Throughout the design process, users have been involved at the heart of the design to create a working research prototype to improve the fit between technology, end-user, and researchers. Furthermore, we performed a technological readiness study of ProHealth eCoach against standard levels set by European Union (EU).


Subject(s)
Mobile Applications , Artificial Intelligence , Healthy Lifestyle , Humans , Quality of Life , User-Centered Design
17.
Sensors (Basel) ; 22(17)2022 Aug 31.
Article in English | MEDLINE | ID: mdl-36081021

ABSTRACT

The widespread usage of mobile devices and their seamless adaptation to each user's needs through useful applications (apps) makes them a prime target for malware developers. Malware is software built to harm the user, e.g., to access sensitive user data, such as banking details, or to hold data hostage and block user access. These apps are distributed in marketplaces that host millions and therefore have their forms of automated malware detection in place to deter malware developers and keep their app store (and reputation) trustworthy. Nevertheless, a non-negligible number of apps can bypass these detectors and remain available in the marketplace for any user to download and install on their device. Current malware detection strategies rely on using static or dynamic app extracted features (or a combination of both) to scale the detection and cover the growing number of apps submitted to the marketplace. In this paper, the main focus is on the apps that bypass the malware detectors and stay in the marketplace long enough to receive user feedback. This paper uses real-world data provided by an app store. The quantitative ratings and potential alert flags assigned to the apps by the users were used as features to train machine learning classifiers that successfully classify malware that evaded previous detection attempts. These results present reasonable accuracy and thus work to help to maintain a user-safe environment.


Subject(s)
Mobile Applications , Data Collection , Feedback , Machine Learning
18.
JMIR Mhealth Uhealth ; 10(9): e33247, 2022 Sep 09.
Article in English | MEDLINE | ID: mdl-36083606

ABSTRACT

BACKGROUND: The popularization of mobile health (mHealth) apps for public health or medical care purposes has transformed human life substantially, improving lifestyle behaviors and chronic condition management. OBJECTIVE: This review aimed to identify behavior change techniques (BCTs) commonly used in mHealth, assess their effectiveness based on the evidence reported in interventions and reviews to highlight the most appropriate techniques to design an optimal strategy to improve adherence to data reporting, and provide recommendations for future interventions and research. METHODS: We performed a systematic review of studies published between 2010 and 2021 in relevant scientific databases to identify and analyze mHealth interventions using BCTs that evaluated their effectiveness in terms of user adherence. Search terms included a mix of general (eg, data, information, and adherence), computer science (eg, mHealth and BCTs), and medicine (eg, personalized medicine) terms. RESULTS: This systematic review included 24 studies and revealed that the most frequently used BCTs in the studies were feedback and monitoring (n=20), goals and planning (n=14), associations (n=14), shaping knowledge (n=12), and personalization (n=7). However, we found mixed effectiveness of the techniques in mHealth outcomes, having more effective than ineffective outcomes in the evaluation of apps implementing techniques from the feedback and monitoring, goals and planning, associations, and personalization categories, but we could not infer causality with the results and suggest that there is still a need to improve the use of these and many common BCTs for better outcomes. CONCLUSIONS: Personalization, associations, and goals and planning techniques were the most used BCTs in effective trials regarding adherence to mHealth apps. However, they are not necessarily the most effective since there are studies that use these techniques and do not report significant results in the proposed objectives; there is a notable overlap of BCTs within implemented app components, suggesting a need to better understand best practices for applying (a combination of) such techniques and to obtain details on the specific BCTs used in mHealth interventions. Future research should focus on studies with longer follow-up periods to determine the effectiveness of mHealth interventions on behavior change to overcome the limited evidence in the current literature, which has mostly small-sized and single-arm experiments with a short follow-up period.


Subject(s)
Mobile Applications , Telemedicine , Behavior Therapy/methods , Humans , Precision Medicine , Self Report , Telemedicine/methods
19.
Addict Sci Clin Pract ; 17(1): 50, 2022 Sep 09.
Article in English | MEDLINE | ID: mdl-36085078

ABSTRACT

BACKGROUND: People with opioid use disorder (OUD) face barriers to entering and remaining in life-saving treatment (e.g., stigma, detrimental interactions with health care, and privacy concerns). Telehealth and related technology can reduce barriers to entering and staying in care. Patient feedback is critical to the development of these newer treatment approaches to ensure they are usable and do not inadvertently recreate treatment barriers. PURPOSE: Evaluate the perceived usability of existing and planned features of a mobile application (app) that facilitates delivery of OUD treatment via telehealth. METHODS: People with current or prior experience with OUD treatment were eligible for the study. Participants (n = 31; 55% women) provided feedback on an interactive prototype demonstration via individual qualitative interviews and completed a quantitative survey on the app's perceived usability. Descriptive statistics summarized the usability survey. We analyzed qualitative interview transcripts to elicit common themes. RESULTS: Participants were primarily white (77%) with a mean age of 42.2 years (range 22-69). Participants rated the six major features of the current app as helpful (median response 5 out of 5) and appreciated the flexibility of conducting a visit from a place of their choosing. Participants regarded the five proposed components of the app, such as daily affirmations and medication treatment-related reminders (e.g., pick up medication at pharmacy, medication schedule), as useful features with medians 5 out of 5, and reported they would recommend the app to others for OUD care. Participant qualitative interviews provided additional information on perceived usability of existing and proposed app features. CONCLUSION: Our study suggests that an appealing, easy-to-use app-with tools and features that effectively support care-could circumvent existing barriers and foster sustained recovery.


Subject(s)
Mobile Applications , Opioid-Related Disorders , Telemedicine , Adult , Aged , Female , Humans , Male , Middle Aged , Opioid-Related Disorders/drug therapy , Smartphone , Social Stigma , Young Adult
20.
Annu Int Conf IEEE Eng Med Biol Soc ; 2022: 3657-3660, 2022 Jul.
Article in English | MEDLINE | ID: mdl-36085635

ABSTRACT

We have developed a real-time system which can estimate and display chronic stress levels determined from a long-term physiological data. It consists of wearable sensors that measure physiological data, a smartphone application that receives data from the sensors and displays chronic stress levels, and a cloud system that estimates them on the basis of received data. To operate it, we have to treat irregularly uploaded user-physiological-data of varying sizes, calculate chronic stress levels from long-term features without delay on a daily basis, and display them in real-time on the smartphone application. For this purpose, we have developed a system that requires relatively little memory and processing time with one six-hundredth of maximum memory usage and one twentieth of processing time as compared to conventional method by subdividing uploaded physiological data, calculating features from them, and creating long-term features by combining the subdivided features.


Subject(s)
Computer Systems , Mobile Applications
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