Just-in-time adaptive intervention (JITAI) has gained attention recently and previous studies have indicated that it is an effective strategy in the field of mobile healthcare intervention. Identifying the right moment for the intervention is a crucial component. In this paper the reinforcement learning (RL) technique has been used in a smartphone exercise application to promote physical activity. This RL model determines the ‘right’ time to deliver a restricted number of notifications adaptively, with respect to users’ temporary context information (i.e., time and calendar). A four-week trial study was conducted to examine the feasibility of our model with real target users. JITAI reminders were sent by the RL model in the fourth week of the intervention, while the participants could only access the app’s other functionalities during the first 3 weeks. Eleven target users registered for this study, and the data from 7 participants using the application for 4 weeks and receiving the intervening reminders were analyzed. Not only were the reaction behaviors of users after receiving the reminders analyzed from the application data, but the user experience with the reminders was also explored in a questionnaire and exit interviews. The results show that 83.3% reminders sent at adaptive moments were able to elicit user reaction within 50 min, and 66.7% of physical activities in the intervention week were performed within 5 h of the delivery of a reminder. Our findings indicated the usability of the RL model, while the timing of the moments to deliver reminders can be further improved based on lessons learned.
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Background: The immunization uptake rates in Pakistan are much lower than desired. Major reasons include lack of awareness, parental forgetfulness regarding schedules, and misinformation regarding vaccines. In light of the COVID-19 pandemic and distancing measures, routine childhood immunization (RCI) coverage has been adversely affected, as caregivers avoid tertiary care hospitals or primary health centers. Innovative and cost-effective measures must be taken to understand and deal with the issue of low immunization rates. However, only a few smartphone-based interventions have been carried out in low- and middle-income countries (LMICs) to improve RCI. Objective: The primary objectives of this study are to evaluate whether a personalized mobile app can improve children’s on-time visits at 10 and 14 weeks of age for RCI as compared with standard care and to determine whether an artificial intelligence model can be incorporated into the app. Secondary objectives are to determine the perceptions and attitudes of caregivers regarding childhood vaccinations and to understand the factors that might influence the effect of a mobile phone–based app on vaccination improvement. Methods: A mixed methods randomized controlled trial was designed with intervention and control arms. The study will be conducted at the Aga Khan University Hospital vaccination center. Caregivers of newborns or infants visiting the center for their children’s 6-week vaccination will be recruited. The intervention arm will have access to a smartphone app with text, voice, video, and pictorial messages regarding RCI. This app will be developed based on the findings of the pretrial qualitative component of the study, in addition to no-show study findings, which will explore caregivers’ perceptions about RCI and a mobile phone–based app in improving RCI coverage. Results: Pretrial qualitative in-depth interviews were conducted in February 2020. Enrollment of study participants for the randomized controlled trial is in process. Study exit interviews will be conducted at the 14-week immunization visits, provided the caregivers visit the immunization facility at that time, or over the phone when the children are 18 weeks of age. Conclusions: This study will generate useful insights into the feasibility, acceptability, and usability of an Android-based smartphone app for improving RCI in Pakistan and in LMICs.
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Background: Home-based exercise is an important part of physical therapy treatment for patients with low back pain. However, treatment effectiveness depends heavily on patient adherence to home-based exercise recommendations. Smartphone apps designed to support home-based exercise have the potential to support adherence to exercise recommendations and possibly improve treatment effects. A better understanding of patient perspectives regarding the use of smartphone apps to support home-based exercise during physical therapy treatment can assist physical therapists with optimal use and implementation of these apps in clinical practice. Objective: The aim of this study was to investigate patient perspectives on the acceptability, satisfaction, and performance of a smartphone app to support home-based exercise following recommendations from a physical therapist. Methods: Using an interpretivist phenomenology approach, 9 patients (4 males and 5 females; aged 20-71 years) with nonspecific low back pain recruited from 2 primary care physical therapy practices were interviewed within 2 weeks after treatment ended. An interview guide was used for the interviews to ensure that different aspects of the patients’ perspectives were discussed. The Physitrack smartphone app was used to support home-based exercise as part of treatment for all patients. Data were analyzed using the “Framework Method” to assist with interpretation of the data. Results: Data analysis revealed 11 categories distributed among the 3 themes “acceptability,” “satisfaction,” and “performance.” Patients were willing to accept the app as part of treatment when it was easy to use, when it benefited the patient, and when the physical therapist instructed the patient in its use. Satisfaction with the app was determined by users’ perceived support from the app when exercising at home and the perceived increase in adherence. The video and text instructions, reminder functions, and self-monitor functions were considered the most important aspects for performance during treatment. The patients did not view the Physitrack app as a replacement for the physical therapist and relied on their therapist for instructions and support when needed. Conclusions: Patients who use an app to support home-based exercise as part of treatment are accepting of the app when it is easy to use, when it benefits the patient, and when the therapist instructs the patient in its use. Physical therapists using an app to support home-based exercise can use the findings from this study to effectively support their patients when exercising at home during treatment.
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Background: Home-based exercise is an important part of physical therapy treatment for patients with low back pain. However, treatment effectiveness depends heavily on patient adherence to home-based exercise recommendations. Smartphone apps designed to support home-based exercise have the potential to support adherence to exercise recommendations and possibly improve treatment effects. A better understanding of patient perspectives regarding the use of smartphone apps to support home-based exercise during physical therapy treatment can assist physical therapists with optimal use and implementation of these apps in clinical practice. Objective: The aim of this study was to investigate patient perspectives on the acceptability, satisfaction, and performance of a smartphone app to support home-based exercise following recommendations from a physical therapist. Methods: Using an interpretivist phenomenology approach, 9 patients (4 males and 5 females; aged 20-71 years) with nonspecific low back pain recruited from 2 primary care physical therapy practices were interviewed within 2 weeks after treatment ended. An interview guide was used for the interviews to ensure that different aspects of the patients' perspectives were discussed. The Physitrack smartphone app was used to support home-based exercise as part of treatment for all patients. Data were analyzed using the "Framework Method" to assist with interpretation of the data. Results: Data analysis revealed 11 categories distributed among the 3 themes "acceptability," "satisfaction," and "performance." Patients were willing to accept the app as part of treatment when it was easy to use, when it benefited the patient, and when the physical therapist instructed the patient in its use. Satisfaction with the app was determined by users' perceived support from the app when exercising at home and the perceived increase in adherence. The video and text instructions, reminder functions, and self-monitor functions were considered the most important aspects for performance during treatment. The patients did not view the Physitrack app as a replacement for the physical therapist and relied on their therapist for instructions and support when needed. Conclusions: Patients who use an app to support home-based exercise as part of treatment are accepting of the app when it is easy to use, when it benefits the patient, and when the therapist instructs the patient in its use. Physical therapists using an app to support home-based exercise can use the findings from this study to effectively support their patients when exercising at home during treatment.
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In BMC Oral Health verscheen het volgende artikel van Inholland-docente en promovenda Janneke Scheerman (en collega’s). Background: Adolescents with fixed orthodontic appliances are at high risk of developing dental caries. To date, new smartphone technologies have seldom been used to support them in the preventive behavior that can help prevent dental caries. After an intervention-mapping process, we developed a smartphone application (the WhiteTeeth app) for preventing dental caries through improved oral-health behavior and oral hygiene. The app, which is intended to be used at home, will help adolescents with fixed orthodontic appliances perform their oral self-care behavior. The app is based on the Health Action Process Approach (HAPA) theory, and incorporates several behavior-change techniques that target the psychosocial factors of oral-health behavior. This article describes the protocol of a randomized controlled trial (RCT) to evaluate the effects of the WhiteTeeth app on oral-health behavior and oral-hygiene outcomes (presence of dental plaque and gingival bleeding) compared with those of care as usual, in patients aged 12–16 with fixed orthodontic appliances.
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Background: Major surgery is associated with negative postoperative outcomes such as complications and delayed or poor recovery. Multimodal prehabilitation can help to reduce the negative effects of major surgery. Offering prehabilitation by means of mobile health (mHealth) could be an effective new approach. Objective: The objectives of this pilot study were to (1) evaluate the usability of the Be Prepared mHealth app prototype for people undergoing major surgery, (2) explore whether the app was capable of bringing about a change in risk behaviors, and (3) estimate a preliminary effect of the app on functional recovery after major surgery. Methods: A mixed-methods pilot randomized controlled trial was conducted in two Dutch academic hospitals. In total, 86 people undergoing major surgery participated. Participants in the intervention group received access to the Be Prepared app, a smartphone app using behavior change techniques to address risk behavior prior to surgery. Both groups received care as usual. Usability (System Usability Scale), change in risk behaviors 3 days prior to surgery, and functional recovery 30 days after discharge from hospital (Patient-Reported Outcomes Measurement Information System physical functioning 8-item short form) were assessed using online questionnaires. Quantitative data were analyzed using descriptive statistics, chi-square tests, and multivariable linear regression. Semistructured interviews about the usability of the app were conducted with 12 participants in the intervention group. Thematic analysis was used to analyze qualitative data. Results: Seventy-nine people—40 in the intervention group and 39 in the control group—were available for further analysis. Participants had a median age of 61 (interquartile range 51.0-68.0) years. The System Usability Scale showed that patients considered the Be Prepared app to have acceptable usability (mean 68.2 [SD 18.4]). Interviews supported the usability of the app. The major point of improvement identified was further personalization of the app. Compared with the control group, the intervention group showed an increase in self-reported physical activity and muscle strengthening activities prior to surgery. Also, 2 of 2 frequent alcohol users in the intervention group versus 1 of 9 in the control group drank less alcohol in the run-up to surgery. No difference was found in change of smoking cessation. Between-group analysis showed no meaningful differences in functional recovery after correction for baseline values (β=–2.4 [95% CI –5.9 to 1.1]). Conclusions: The Be Prepared app prototype shows potential in terms of usability and changing risk behavior prior to major surgery. No preliminary effect of the app on functional recovery was found. Points of improvement have been identified with which the app and future research can be optimized.
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Introduction: Many adults do not reach the recommended physical activity (PA) guidelines, which can lead to serious health problems. A promising method to increase PA is the use of smartphone PA applications. However, despite the development and evaluation of multiple PA apps, it remains unclear how to develop and design engaging and effective PA apps. Furthermore, little is known on ways to harness the potential of artificial intelligence for developing personalized apps. In this paper, we describe the design and development of the Playful data-driven Active Urban Living (PAUL): a personalized PA application.Methods: The two-phased development process of the PAUL apps rests on principles from the behavior change model; the Integrate, Design, Assess, and Share (IDEAS) framework; and the behavioral intervention technology (BIT) model. During the first phase, we explored whether location-specific information on performing PA in the built environment is an enhancement to a PA app. During the second phase, the other modules of the app were developed. To this end, we first build the theoretical foundation for the PAUL intervention by performing a literature study. Next, a focus group study was performed to translate the theoretical foundations and the needs and wishes in a set of user requirements. Since the participants indicated the need for reminders at a for-them-relevant moment, we developed a self-learning module for the timing of the reminders. To initialize this module, a data-mining study was performed with historical running data to determine good situations for running.Results: The results of these studies informed the design of a personalized mobile health (mHealth) application for running, walking, and performing strength exercises. The app is implemented as a set of modules based on the persuasive strategies “monitoring of behavior,” “feedback,” “goal setting,” “reminders,” “rewards,” and “providing instruction.” An architecture was set up consisting of a smartphone app for the user, a back-end server for storage and adaptivity, and a research portal to provide access to the research team.Conclusions: The interdisciplinary research encompassing psychology, human movement sciences, computer science, and artificial intelligence has led to a theoretically and empirically driven leisure time PA application. In the current phase, the feasibility of the PAUL app is being assessed.
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Background: Major surgery is associated with negative postoperative outcomes such as complications and delayed or poor recovery. Multimodal prehabilitation can help to reduce the negative effects of major surgery. Offering prehabilitation by means of mobile health (mHealth) could be an effective new approach. Objective: The objectives of this pilot study were to (1) evaluate the usability of the Be Prepared mHealth app prototype for people undergoing major surgery, (2) explore whether the app was capable of bringing about a change in risk behaviors, and (3) estimate a preliminary effect of the app on functional recovery after major surgery. Methods: A mixed-methods pilot randomized controlled trial was conducted in two Dutch academic hospitals. In total, 86 people undergoing major surgery participated. Participants in the intervention group received access to the Be Prepared app, a smartphone app using behavior change techniques to address risk behavior prior to surgery. Both groups received care as usual. Usability (System Usability Scale), change in risk behaviors 3 days prior to surgery, and functional recovery 30 days after discharge from hospital (Patient-Reported Outcomes Measurement Information System physical functioning 8-item short form) were assessed using online questionnaires. Quantitative data were analyzed using descriptive statistics, chi-square tests, and multivariable linear regression. Semistructured interviews about the usability of the app were conducted with 12 participants in the intervention group. Thematic analysis was used to analyze qualitative data. Results: Seventy-nine people-40 in the intervention group and 39 in the control group-were available for further analysis. Participants had a median age of 61 (interquartile range 51.0-68.0) years. The System Usability Scale showed that patients considered the Be Prepared app to have acceptable usability (mean 68.2 [SD 18.4]). Interviews supported the usability of the app. The major point of improvement identified was further personalization of the app. Compared with the control group, the intervention group showed an increase in self-reported physical activity and muscle strengthening activities prior to surgery. Also, 2 of 2 frequent alcohol users in the intervention group versus 1 of 9 in the control group drank less alcohol in the run-up to surgery. No difference was found in change of smoking cessation. Between-group analysis showed no meaningful differences in functional recovery after correction for baseline values (β=-2.4 [95% CI -5.9 to 1.1]). Conclusions: The Be Prepared app prototype shows potential in terms of usability and changing risk behavior prior to major surgery. No preliminary effect of the app on functional recovery was found. Points of improvement have been identified with which the app and future research can be optimized. Trial Registration: Netherlands Trial Registry NL8623; https://www.trialregister.nl/trial/8623.
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Non-professional runners make extensive use of consumer-available wearable devices and smartphone apps to monitor training sessions, health, and physical performance. Despite the popularity of these products, they usually neglect subjective factors, such as psychosocial stress, unexpected daily physical (in)activity, sleep quality perception, and/or previous injuries. Consequently, the implementation of these products may lead to underperformance, reduced motivation, and running-related injuries. This paper investigates how the integration of subjective training, off-training, and contextual factors from a 24/7 perspective might lead to better individual screening and health protection methods for recreational runners. Using an online-based Ecological Momentary Assessment survey, a seven-day cohort study was conducted. Twenty participants answered daily surveys three times a day regarding subjective off-training and contextual data; e.g., health, sleep, stress, training, environment, physiology, and lifestyle factors. The results show that daily habits of people are unstructured, unlikely predictable, and influenced by factors, such as the demands of work, social life, leisure time, or sleep. By merging these factors with sensor-based data, running-related systems would be able to better assess the individual workload of recreational runners and support them to reduce their risk of suffering from running-related injuries
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Light profoundly impacts many aspects of human physiology and behaviour, including the synchronization of the circadian clock, the production of melatonin, and cognition. These effects of light, termed the non-visual effects of light, have been primarily investigated in laboratory settings, where light intensity, spectrum and timing can be carefully controlled to draw associations with physiological outcomes of interest. Recently, the increasing availability of wearable light loggers has opened the possibility of studying personal light exposure in free-living conditions where people engage in activities of daily living, yielding findings associating aspects of light exposure and health outcomes, supporting the importance of adequate light exposure at appropriate times for human health. However, comprehensive protocols capturing environmental (e.g., geographical location, season, climate, photoperiod) and individual factors (e.g., culture, personal habits, behaviour, commute type, profession) contributing to the measured light exposure are currently lacking. Here, we present a protocol that combines smartphone-based experience sampling (experience sampling implementing Karolinska Sleepiness Scale, KSS ratings) and high-quality light exposure data collection at three body sites (near-corneal plane between the two eyes mounted on spectacle, neck-worn pendant/badge, and wrist-worn watch-like design) to capture daily factors related to individuals’ light exposure. We will implement the protocol in an international multi-centre study to investigate the environmental and socio-cultural factors influencing light exposure patterns in Germany, Ghana, Netherlands, Spain, Sweden, and Turkey (minimum n = 15, target n = 30 per site, minimum n = 90, target n = 180 across all sites). With the resulting dataset, lifestyle and context-specific factors that contribute to healthy light exposure will be identified. This information is essential in designing effective public health interventions.
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