Embedded motivational interviewing combined with a smartphone application to increase physical activity in people with sub-acute low back pain: a cluster randomised controlled trial.

BACKGROUND: Moderately vigorous physical activity (PA) may be beneficial for people with sub-acute low back pain (LBP), but may initially be painful for patients and challenging for physical therapists to facilitate. OBJECTIVES: This study investigated motivational interviewing (MI) delivered by physical therapists and a smartphone app for increasing PA in people with LBP. METHODS: A mixed methods cluster randomised controlled trial involving 46 adults with LBP in Melbourne, Australia. Participants attended weekly 30-min physical therapy consultations for 6 weeks. Experimental group physical therapists were taught to embed MI into consultations and patients were provided with a self-directed app. The primary outcome was accelerometer-derived moderately vigorous PA. Secondary outcomes were LBP disability (Oswestry Disability Index), functional capacity (Patient Specific Functional Scale), and self-efficacy (Pain Self-Efficacy Questionnaire). Between-group differences were analysed by ANCOVA post-intervention. RESULTS: There was no statistically significant difference between the experimental group and control group for PA. Between-group differences in LBP disability (MD= 19.4 units, 95% CI: 8.5, 30.3), functional capacity (primary MD= -4.1 units, 95% CI: -6.9, -1.3; average MD= -3.1, 95% CI: -4.9, -1.2) and self-efficacy (MD -11.3 units, 95%CI -20.2, -2.5) favoured the control group with small to moderate effect sizes. There were low levels of overall engagement with the app. CONCLUSION: The embedded MI intervention was no more beneficial than physical therapy alone for PA and was associated with poorer LBP disability, function, and self-efficacy. The effectiveness of embedding MI and a smartphone app into usual care for LBP was not supported.

Improve the satisfaction of medical staff on the use of home nursing mobile APP by using a hybrid multi-standard decision model.

OBJECTIVE: To identify critical satisfaction gaps in a home nursing mobile application (APP) using a systematic decision-making model. METHODS: Initially, the decision-making trial and evaluation laboratory method was used to analyze the relationship structure and corresponding weights among the indicators. The Importance-Performance Analysis (IPA) method was used to identify the categories of all indicators and their corresponding strategic directions. Twenty-six home nursing specialists currently providing home nursing services were recruited for this study. RESULTS: The IPA results revealed that "Assurance," "Reliability," and "Personal security protection" are critical satisfaction gaps. From the influence network and weight results, "information quality" and "system quality" were the critical quality factors in the home nursing mobile APP. The influence of the network relationship structure and weight demonstrated a 98.12% significance level, indicating good stability. CONCLUSION: Continuous improvement in information and system quality is recommended to optimize the overall quality of the home nursing mobile APP. Additionally, user demands should be considered, and personal safety guarantee functions should be developed and integrated into the system to ensure the safety of home nursing workers.

What's in a name? A systematic review and meta-analysis to assess the effectiveness of non-medical amplification devices in adults with mild and moderate hearing losses.

OBJECTIVE: To assess non-medical amplification devices in adults with mild-to-moderate hearing loss, and the impact of device features on outcomes. DESIGN: A prospectively registered systematic review. STUDY SAMPLE: Ten studies evaluating personal sound amplification products (PSAPs), and four evaluating smartphone amplification applications (or apps). Devices were classified as "premium" or "basic" based on the number of compression channels (≥16 or <16, respectively). RESULTS: Meta-analyses showed that premium PSAPs improved speech intelligibility in noise performance compared to unaided, whereas basic PSAPs and smartphone apps did not. Premium PSAPs performed better than basic hearing aids. Premium hearing aids performed better than premium and basic PSAPs, smartphone apps, and basic hearing aids. Although data could not be pooled, similar findings were also found for quality of life, listening ability, cognition, feasibility, and adverse effects. CONCLUSIONS: Premium PSAPs appear to be an effective non-medical amplification device for adults with mild-to-moderate hearing loss. Given the overlap in features available, it may be that this is a key consideration when drawing comparisons between devices, rather than the device being named a PSAP or hearing aid. Nevertheless, the extent to which PSAPs are effective without audiological input remains to be determined.

Corrigendum: Implementation of a patient-centered remote wound monitoring system for management of diabetic foot ulcers.

[This corrects the article DOI: 10.3389/fendo.2023.1157518.].

Study protocol for a randomized trial of a supportive care mobile application to improve symptoms, coping, and quality of life in patients with advanced non-small cell lung cancer.

Patients with advanced non-small cell lung cancer (NSCLC) often experience burdensome symptoms, emotional distress, and poor quality of life (QOL). While national guidelines recommend early palliative care to address these supportive care needs, most patients with advanced NSCLC lack access to such comprehensive care. Our aim in the current study is to test a novel model of palliative care delivery and use of innovative technology to evaluate the feasibility, acceptability, and preliminary efficacy of a supportive care mobile application (app) for improving symptom management and adaptive coping in patients with advanced NSCLC. We will enroll 120 patients with unresectable Stage III or IV NSCLC diagnosed within the past 12 weeks receiving care with palliative intent at a major academic comprehensive cancer center and its community affiliates. The study will take place in two phases, the first of which will be dedicated to adapting an evidence-based, early palliative care treatment guide and prior supportive care mobile app intervention to address the specific symptom management and coping needs of patients with advanced NSCLC. The second phase of the study will be a two-group, randomized controlled trial. Study patients will complete baseline self-report measures of symptoms, mood, coping skills, and QOL, after which they will be randomized to receive either the mobile app intervention combined with usual oncology care or usual oncology care alone. Intervention patients will use a tablet computer to self-administer the mobile app, which consists of six modules that teach evidence-based skills for managing burdensome symptoms and coping effectively with advanced cancer and its treatment. At 12 weeks follow up, patients in both groups will repeat the same self-report measures. We will use descriptive statistics to determine feasibility metrics of enrollment and retention rates. For secondary self-report measures, we will use linear regression controlling for baseline values. The results of the present study will contribute to a growing body of evidence regarding the supportive care needs of patients with advanced cancer and will have implications for how best to use innovative technology to widely disseminate comprehensive supportive care services to all patients who may benefit. Clinical Trial Registration: [www.ClinicalTrials.gov], identifier[NCT04629300].

Mobile heath applications for self-management in chronic lung disease: a systematic review.

Integration of mobile health (mHealth) applications (apps) into chronic lung disease management is becoming increasingly popular. MHealth apps may support adoption of self-management behaviors to assist people in symptoms control and quality of life enhancement. However, mHealth apps' designs, features, and content are inconsistently reported, making it difficult to determine which were the effective components. Therefore, this review aims to summarize the characteristics and features of published mHealth apps for chronic lung diseases. A structured search strategy across five databases (CINAHL, Medline, Embase, Scopus and Cochrane) was performed. Randomized controlled trials investigating interactive mHealth apps in adults with chronic lung disease were included. Screening and full-text reviews were completed by three reviewers using Research Screener and Covidence. Data extraction followed the mHealth Index and Navigation Database (MIND) Evaluation Framework (https://mindapps.org/), a tool designed to help clinicians determine the best mHealth apps to address patients' needs. Over 90,000 articles were screened, with 16 papers included. Fifteen distinct apps were identified, 8 for chronic obstructive pulmonary disease (53%) and 7 for asthma (46%) self-management. Different resources informed app design approaches, accompanied with varying qualities and features across studies. Common reported features included symptom tracking, medication reminders, education, and clinical support. There was insufficient information to answer MIND questions regarding security and privacy, and only five apps had additional publications to support their clinical foundation. Current studies reported designs and features of self-management apps differently. These app design variations create challenges in determining their effectiveness and suitability for chronic lung disease self-management. Registration: PROSPERO (CRD42021260205). Supplementary Information: The online version contains supplementary material available at 10.1007/s13721-023-00419-0.

Implementation of a patient-centered remote wound monitoring system for management of diabetic foot ulcers.

Background: Regular clinical assessment is critical to optimize lower extremity wound healing. However, family and work obligations, socioeconomic, transportation, and time barriers often limit patient follow-up. We assessed the feasibility of a novel, patient-centered, remote wound management system (Healthy.io Minuteful for Wound Digital Management System) for the surveillance of lower extremity wounds. Methods: We enrolled 25 patients from our outpatient multidisciplinary limb preservation clinic with a diabetic foot ulcer, who had undergone revascularization and podiatric interventions prior to enrollment. Patients and their caregivers were instructed on how to use the digital management system and asked to perform one at-home wound scan per week for a total of 8 weeks using a smartphone application. We collected prospective data on patient engagement, smartphone app useability, and patient satisfaction. Results: Twenty-five patients (mean age 65.5 ± 13.7 years, 60.0% male, 52.0% Black) were enrolled over 3 months. Mean baseline wound area was 18.0 ± 15.2 cm2, 24.0% of patients were recovering from osteomyelitis, and post-surgical WiFi stage was 1 in 24.0%, 2 in 40.0%, 3 in 28.0%, and 4 in 8.00% of patients. We provided a smartphone to 28.0% of patients who did not have access to one that was compatible with the technology. Wound scans were obtained by patients (40.0%) and caregivers (60.0%). Overall, 179 wound scans were submitted through the app. The mean number of wound scans acquired per patient was 0.72 ± 0.63 per week, for a total mean of 5.80 ± 5.30 scans over the course of 8 weeks. Use of the digital wound management system triggered an early change in wound management for 36.0% of patients. Patient satisfaction was high; 94.0% of patients reported the system was useful. Conclusion: The Healthy.io Minuteful for Wound Digital Management System is a feasible means of remote wound monitoring for use by patients and/or their caregivers.

Guiding protein design choices by per-residue energy breakdown analysis with an interactive web application.

Recent developments in machine learning have greatly facilitated the design of proteins with improved properties. However, accurately assessing the contributions of an individual or multiple amino acid mutations to overall protein stability to select the most promising mutants remains a challenge. Knowing the specific types of amino acid interactions that improve energetic stability is crucial for finding favorable combinations of mutations and deciding which mutants to test experimentally. In this work, we present an interactive workflow for assessing the energetic contributions of single and multi-mutant designs of proteins. The energy breakdown guided protein design (ENDURE) workflow includes several key algorithms, including per-residue energy analysis and the sum of interaction energies calculations, which are performed using the Rosetta energy function, as well as a residue depth analysis, which enables tracking the energetic contributions of mutations occurring in different spatial layers of the protein structure. ENDURE is available as a web application that integrates easy-to-read summary reports and interactive visualizations of the automated energy calculations and helps users selecting protein mutants for further experimental characterization. We demonstrate the effectiveness of the tool in identifying the mutations in a designed polyethylene terephthalate (PET)-degrading enzyme that add up to an improved thermodynamic stability. We expect that ENDURE can be a valuable resource for researchers and practitioners working in the field of protein design and optimization. ENDURE is freely available for academic use at: http://endure.kuenzelab.org.

Challenges and opportunities faced by nurse scientists in integrating data and technology in research to promote health equity.

Advances in technologies including omics, apps, imaging, sensors, and big data are increasingly being integrated into research by nurse scientists, but the impact on improving health equity is still unclear. In this article, nursing research faculty from one institution discuss challenges and opportunities experienced when integrating various technologies into their research aimed at promoting health equity. Using exemplars from faculty experiences, a three-pronged approach to keeping patients and communities and the goal of health equity central in research while incorporating advancing technologies is described. This approach includes establishing long-term engagement with populations underrepresented in research, adopting strategies to increase diversity in study participant recruitment, and training and collaboration among a diverse workforce of educators, clinicians, and researchers. Training nurse scientists in integrating data and technology for advancing the science on health equity will shift the culture of how we understand, collaborate, and grow with the communities in which we train and practice as nurse scientists.

Systematic assessment of the quality and integrity of popular mental health smartphone apps using the American Psychiatric Association's app evaluation model.

Mobile phones are playing an increasingly important role in supporting mental health, by providing confidential, accessible and scalable support for individuals who may not seek or have means of accessing professional help. There are concerns, however, that many apps claiming to support mental health do not meet professional, ethical or evidence-based standards. App store search algorithms favour popularity (reviews and downloads) and commercial factors (in-app purchases), with what appears to be low prioritisation of safety or effectiveness features. In this paper, the most visible 100 apps for "depression", "anxiety" and/or "mood" on the Google Play and Apple App stores were selected for assessment using the American Psychiatric Association App Evaluation model. This model systematically assesses apps across five broad steps: accessibility, integrity, clinical and research evidence base, user engagement and interoperability. Assessment is hierarchical, with the most fundamental requirements of apps assessed first, with apps excluded at each step if they do not meet the criteria. The relationship between app quality and app store visibility was first analysed. App quality was also compared across four different app function types: mental health promotion or psychoeducation; monitoring or tracking; assessment or prevention; and intervention or treatment. Of the 92 apps assessed (after eight failed to meet inclusion criteria), half failed to meet the first criterion step of accessibility, and a further 20% of the remaining apps failed to meet the second criterion step of security and privacy. Only three of the 10 apps most visible on app stores met the criteria for research/clinical base and engagement/ease of use, and only one app fulfilled all five criterion steps of the evaluation model. Quality did not differ significantly across app function type. There was no significant correlation between app quality and app store visibility, which presents a potential risk to vulnerable consumers. The findings of this review highlight the need for greater accountability of app developers to meet, and report, at least minimum quality and integrity standards for their apps. Recommendations are also provided to assist users and clinicians to make informed choices in their selection of reputable and effective mental health apps.

Study Design and Protocol of a Randomized Controlled Trial of the Efficacy of a Smartphone-Based Therapy of Migraine (SMARTGEM).

Background: Digitalization and electronic health (eHealth) offer new treatment approaches for patients with migraine. Current smartphone applications (apps) for migraine patients include a wide spectrum of functions ranging from digital headache diaries to app-based headache treatment by, among others, analysis of the possible triggers, behavioral therapy approaches and prophylactic non-drug treatment methods with relaxation therapy or endurance sport. Additional possibilities arise through the use of modern, location-independent communication methods, such as online consultations. However, there is currently insufficient evidence regarding the benefits and/or risks of these electronic tools for patients. To date, only few randomized controlled trials have assessed eHealth applications. Methods: SMARTGEM is a randomized controlled trial assessing whether the provision of a new digital integrated form of care consisting of the migraine app M-sense in combination with a communication platform (with online consultations and medically moderated patient forum) leads to a reduction in headache frequency in migraine patients, improving quality of life, reducing medical costs and work absenteeism (DRKS-ID: DRKS00016328). Discussion: SMARTGEM constitutes a new integrated approach for migraine treatment, which aims to offer an effective, location-independent, time-saving and cost-saving treatment. The design of the study is an example of how to gather high quality evidence in eHealth. Results are expected to provide insightful information on the efficacy of the use of electronic health technology in improving the quality of life in patients suffering from migraine and reducing resource consumption.

Engaging with EPIO, a digital pain self-management program: a qualitative study.

BACKGROUND: Chronic pain conditions entail significant personal and societal burdens and improved outreach of evidence-based pain self-management programs are needed. Digital cognitive-behavioral self-management interventions have shown promise. However, evidence is still scarce and several challenges with such interventions for chronic pain exist. Exploring patients' experiences and engagement with digital interventions may be an essential step towards developing meaningful digital self-management interventions for those living with chronic pain. OBJECTIVES: This study aimed to gain insight into the experiences of people with chronic pain when engaging with EPIO, an application (app)-based cognitive-behavioral pain self-management intervention program. METHODS: Participants (N = 50) living with chronic pain received access to the EPIO intervention in a feasibility pilot-study for 3 months. During this time, all participants received a follow-up phone call at 2-3 weeks, and a subsample (n = 15) also participated in individual semi-structured interviews after 3 months. A qualitative design was used and thematic analysis was employed aiming to capture participants' experiences when engaging with the EPIO intervention program. RESULTS: Findings identifying program-related experiences and engagement were organized into three main topics, each with three sub-themes: (1) Engaging with EPIO; motivation to learn, fostering joy and enthusiasm, and helpful reminders and personalization, (2) Coping with pain in everyday life; awareness, practice and using EPIO in everyday life, and (3) The value of engaging with the EPIO program; EPIO - a friend, making peace with the presence of pain, and fostering communication and social support. CONCLUSIONS: This qualitative study explored participants' experiences and engagement with EPIO, a digital self-management intervention program for people living with chronic pain. Findings identified valued aspects related to motivation for engagement, and showed how such a program may be incorporated into daily life, and encourage a sense of acceptance, social support and relatedness. The findings highlight vital components for facilitating digital program engagement and use in support of self-management for people living with chronic pain. TRIAL REGISTRATION: ClinicalTrials.gov NCT03705104 .

LaminaRGeneVis: A Tool to Visualize Gene Expression Across the Laminar Architecture of the Human Neocortex.

The application of RNA sequencing has enabled the characterization of genome-wide gene expression in the human brain, including distinct layers of the neocortex. Neuroanatomically, the molecular patterns that underlie the laminar organization of the neocortex can help link structure to circuitry and function. To advance our understanding of cortical architecture, we created LaminaRGeneVis, a web application that displays across-layer cortical gene expression from multiple datasets. These datasets were collected using bulk, single-nucleus, and spatial RNA sequencing methodologies and were normalized to facilitate comparisons between datasets. The online resource performs single- and multi-gene analyses to provide figures and statistics for user-friendly assessment of laminar gene expression patterns in the adult human neocortex. The web application is available at https://ethanhkim.shinyapps.io/laminargenevis/.

Assessing the effectiveness of an app-based child unintentional injury prevention intervention for caregivers of rural Chinese preschoolers: protocol for a cluster randomized controlled trial.

BACKGROUND: Compared to urban children, children living in rural areas of most countries, including China, are at higher risk of suffering unintentional injuries. Most proven injury prevention interventions, however, are rarely implemented in rural China due to lack of resources. Mobile health interventions are low-cost and easy-to-implement, facilitating implementing injury prevention in resource-limited areas (e.g., rural areas). This study is designed and implemented to examine the effectiveness of an app-based intervention for unintentional injury prevention among rural preschoolers in China. METHODS: A single-blind, 18-month, parallel-group cluster randomized controlled trial with 1:1 allocation ratio will be implemented in 2 rural areas of China (Yang County, Shaanxi Province, and Shicheng County, Jiangxi Province). In total, at least 3508 rural caregivers of preschoolers aged 3-6 years old who own a smartphone will be recruited from 24 preschools. Clusters will be randomized at the preschool level and allocated to the control group (receiving routine school-based education plus app-based parenting education excluding unintentional injury prevention) or the intervention group (receiving routine school-based education plus app-based parenting education including unintentional injury prevention). External support strategies will be adopted by local partners to minimize user fatigue, non-compliance, and attrition. Data collection will be conducted at baseline and then every 3 months during the 18-month follow-up time period. Intention-to-treat data analysis will be implemented. Missing values will be imputed by using the Expectation Maximization algorithm. Generalized estimating equation will test the overall effectiveness of the app-based intervention. A per-protocol sensitivity analysis will be conducted to test the robustness of results. Subgroup analyses will follow the strategies for primary analyses. The primary outcome measure is the incidence rate of unintentional injury among preschoolers during the study period. Secondary outcome measures comprise longitudinal changes in caregiver's attitudes, caregiver-reported supervision behaviors, and caregiver-assessed home environment safety surrounding child unintentional injury prevention in the last week using a standardized audit instrument. DISCUSSION: The app-based intervention is expected to be feasible and effective over the 18-month intervention period. If the app is demonstrated effective as hypothesized, we will initiate processes to generalize and popularize it broadly to rural child caregivers across China. TRIAL REGISTRATION: ChiCTR2000037606 , registered on August 29, 2020.

What Makes for a Successful Digital Health Integrated Program of Work? Lessons Learnt and Recommendations From the Melbourne Children's Campus.

Embedding digital technologies in healthcare has the potential to streamline and personalize medical care. However, healthcare systems are often fragmented, and therefore achieving a truly integrated digital health program can be challenging. To promote a streamlined, evidence-based approach to implementing digital health solutions in a healthcare system, the Murdoch Children's Research Institute (MCRI) established the Digital Health Translation and Implementation Program (DHTI) bringing together clinicians, researchers and digital health experts. From the program commencement, frontline clinical innovators have collaborated with DHTI team members to develop and implement digital solutions to address pain-points in the healthcare system. Throughout this program, important lessons have been learnt relating to the development, evaluation and implementation of digital solutions in the healthcare system. This paper explores these lessons and makes recommendations for the successful implementation of digital health solutions in healthcare systems under five main categories: (1) design and usability, (2) stakeholder engagement and uptake, (3) project management and resourcing, (4) process and implementation, and (5) evaluation. Recommendations suggested here are designed to support future healthcare-based digital health programs to maximize the impact digital solutions can have on the healthcare system and patients.

User-centred iterative design to develop an evidence-based communication application for maternity care.

A record number of immigrants, many Arabic speaking, arrived in Sweden during the years 2015/2016. Immigrant women have a higher risk of pregnancy complications than native European women and cultural and communicative problems have been identified as a cause of such disparities. Maternity services are under pressure because of language and cultural barriers. Language translation programmes are sometimes used but these are not evidence-based so are not considered safe for use in maternity care. The aim of this research was to create an evidence-based app for communication with Arabic-speaking women in maternity care. User-centred iterative design was used to develop an evidence-based, fit-for-purpose app. Data were collected from midwives in a focus group interview, field observations and workshops. The iterative approach resulted in an evidence-based prototype that is currently being tested in the field.

Urology at your fingertips: the development of a urology m-learning app for medical students.

BACKGROUND: Surgical education has embraced advancing technology with an emphasis on e-learning in recent years. Smartphones are a useful tool for medical teaching and learning with increasing use by medical students to access e-books, medical calculators, podcasts, and medical applications (apps). Our aim was to develop a dedicated urology app for medical students as an adjunct to traditional teaching. METHODS: We published an e-book: Urology Handbook for Medical Students in 2017 based on the core urology curriculum for medical students. Subsequently, we developed a concise, simple and user-friendly smartphone app for medical students called "Urology Med", available for download on App Store and Google Play. RESULTS: This app is an introduction to urology for medical students but may also be useful for interns and surgical trainees. The app encompasses core urology topics subdivided into common urological presentations, urological examination, urological diseases, and urological devices. To make the app interactive, it includes 5 clinical cases that complement the reading material and six quizzes for self-assessment. A comprehensive checklist of 31 "must see" and "good to see" urology experiences is included. Within one month of launch, the app was downloaded 435 times in five countries across three continents. It has a 5-star rating on the Apple store. CONCLUSIONS: High educational standards with relevant content make e-learning a valuable learning tool for surgical education. The Urology Med app facilitates easy access to urology and is ideal for quick reading while working or revising.

Deep learning for species identification of bolete mushrooms with two-dimensional correlation spectral (2DCOS) images.

Bolete is well-known and widely consumed mushroom in the world. However, its medicinal properties and nutritional are completely different from one species to another. Therefore, the consumers need a fast and effective detection method to discriminate their species. A new method using directly digital images of two-dimensional correlation spectroscopy (2DCOS) for the species discrimination with deep learning is proposed in this paper. In our study, a total of 2054 fruiting bodies of 21 wild-grown bolete species were collected in 52 regions from 2011 to 2014. Firstly, we intercepted 1750-400 cm-1 fingerprint regions of each species from their mid-infrared (MIR) spectra, and converted them to 2DCOS spectra with matlab2017b. At the same time, we developed a specific method for the calculation of the 2DCOS spectra. Secondly, we established a deep residual convolutional neural network (Resnet) with 1848 (90%) 2DCOS spectral images. Therein, the discrimination of the bolete species using directly 2DCOS spectral images instead of data matric from the spectra was first to be reported. The results displayed that the respective identification accuracy of these samples was 100% in the training set and 99.76% in the test set. Then, 203 samples were accurately discriminated in 206 (10%) samples of external validation set. Thirdly, we employed t-SNE method to visualize and evaluate the spectral dataset. The result indicated that most samples can be clustered according to different species. Finally, a smartphone applications (APP) was developed based on the established 2DCOS spectral images strategy, which can make the discrimination of bolete mushrooms more easily in practice. In conclusion, deep learning method by using directly 2DCOS spectral image was considered to be an innovative and feasible way for the species discrimination of bolete mushrooms. Moreover, this method may be generalized to other edible mushrooms, food, herb and agricultural products in the further research.

Assessment of the Quality of Mobile Applications (Apps) for Management of Low Back Pain Using the Mobile App Rating Scale (MARS).

Digital health interventions may improve different behaviours. However, the rapid proliferation of technological solutions often does not allow for a correct assessment of the quality of the tools. This study aims to review and assess the quality of the available mobile applications (apps) related to interventions for low back pain. Two reviewers search the official stores of Android (Play Store) and iOS (App Store) for localisation in Spain and the United Kingdom, in September 2019, searching for apps related to interventions for low back pain. Seventeen apps finally are included. The quality of the apps is measured using the Mobile App Rating Scale (MARS). The scores of each section and the final score of the apps are retrieved and the mean and standard deviation obtained. The average quality ranges between 2.83 and 4.57 (mean 3.82) on a scale from 1 (inadequate) to 5 (excellent). The best scores are found in functionality (4.7), followed by aesthetic content (mean 4.1). Information (2.93) and engagement (3.58) are the worst rated items. Apps generally have good overall quality, especially in terms of functionality and aesthetics. Engagement and information should be improved in most of the apps. Moreover, scientific evidence is necessary to support the use of applied health tools.

MindHike, a Digital Coaching Application to Promote Self-Control: Rationale, Content, and Study Protocol.

This protocol describes a study that will test the effectiveness of a 7-week non-clinical digital coaching intervention to promote self-control. The goal of the coaching is to support and guide people who are willing and motivated to improve their self-control with the help of the smartphone application MindHike. The coaching is based on a process model of self-control and aims to target five groups of self-control strategies. The goal of the study is to examine the effectiveness of the digital coaching intervention. A single-arm study design with pre-test, post-test and 2-month follow-up assessments and process assessments will be used to evaluate the 7-week digital coaching intervention. The digital coaching includes 49 daily lessons that are organized along 7 weekly core themes. Study participants will be at least 150 adults aged 18 years and older who are willing and motivated to improve their self-control using the MindHike application. This is the first study testing the effectiveness of a digital coaching intervention to promote self-control. Given that this approach proves effective, it could be easily implemented in various non-clinical settings such as education, health, relationship, and work, and in clinical settings. Due to its digital low-threshold character, it could also reach large numbers of people.