Physical and mental well-being during the COVID-19 pandemic is typically assessed via surveys, which might make it difficult to conduct longitudinal studies and might lead to data suffering from ...recall bias. Ecological momentary assessment (EMA) driven smartphone apps can help alleviate such issues, allowing for in situ recordings. Implementing such an app is not trivial, necessitates strict regulatory and legal requirements, and requires short development cycles to appropriately react to abrupt changes in the pandemic. Based on an existing app framework, we developed Corona Health, an app that serves as a platform for deploying questionnaire-based studies in combination with recordings of mobile sensors. In this paper, we present the technical details of Corona Health and provide first insights into the collected data. Through collaborative efforts from experts from public health, medicine, psychology, and computer science, we released Corona Health publicly on Google Play and the Apple App Store (in July 2020) in eight languages and attracted 7290 installations so far. Currently, five studies related to physical and mental well-being are deployed and 17,241 questionnaires have been filled out. Corona Health proves to be a viable tool for conducting research related to the COVID-19 pandemic and can serve as a blueprint for future EMA-based studies. The data we collected will substantially improve our knowledge on mental and physical health states, traits and trajectories as well as its risk and protective factors over the course of the COVID-19 pandemic and its diverse prevention measures.
In the last decade, there has been a proliferation of mobile apps claiming to support the needs of people living with depression. However, it is unclear what functionality is actually provided by ...apps for depression, or for whom they are intended.
This paper aimed to explore the key features of top-rated apps for depression, including descriptive characteristics, functionality, and ethical concerns, to better inform the design of apps for depression.
We reviewed top-rated iPhone OS (iOS) and Android mobile apps for depression retrieved from app marketplaces in spring 2019. We applied a systematic analysis to review the selected apps, for which data were gathered from the 2 marketplaces and through direct use of the apps. We report an in-depth analysis of app functionality, namely, screening, tracking, and provision of interventions. Of the initially identified 482 apps, 29 apps met the criteria for inclusion in this review. Apps were included if they remained accessible at the moment of evaluation, were offered in mental health-relevant categories, received a review score greater than 4.0 out of 5.0 by more than 100 reviewers, and had depression as a primary target.
The analysis revealed that a majority of apps specify the evidence base for their intervention (18/29, 62%), whereas a smaller proportion describes receiving clinical input into their design (12/29, 41%). All the selected apps are rated as suitable for children and adolescents on the marketplace, but 83% (24/29) do not provide a privacy policy consistent with their rating. The findings also show that most apps provide multiple functions. The most commonly implemented functions include provision of interventions (24/29, 83%) either as a digitalized therapeutic intervention or as support for mood expression; tracking (19/29, 66%) of moods, thoughts, or behaviors for supporting the intervention; and screening (9/29, 31%) to inform the decision to use the app and its intervention. Some apps include overtly negative content.
Currently available top-ranked apps for depression on the major marketplaces provide diverse functionality to benefit users across a range of age groups; however, guidelines and frameworks are still needed to ensure users' privacy and safety while using them. Suggestions include clearly defining the age of the target population and explicit disclosure of the sharing of users' sensitive data with third parties. In addition, we found an opportunity for apps to better leverage digital affordances for mitigating harm, for personalizing interventions, and for tracking multimodal content. The study further demonstrated the need to consider potential risks while using depression apps, including the use of nonvalidated screening tools, tracking negative moods or thinking patterns, and exposing users to negative emotional expression content.
Leveraging artificial intelligence (AI)-driven apps for health education and promotion can help in the accomplishment of several United Nations sustainable development goals. SnehAI, developed by the ...Population Foundation of India, is the first Hinglish (Hindi + English) AI chatbot, deliberately designed for social and behavioral changes in India. It provides a private, nonjudgmental, and safe space to spur conversations about taboo topics (such as safe sex and family planning) and offers accurate, relatable, and trustworthy information and resources.
This study aims to use the Gibson theory of affordances to examine SnehAI and offer scholarly guidance on how AI chatbots can be used to educate adolescents and young adults, promote sexual and reproductive health, and advocate for the health entitlements of women and girls in India.
We adopted an instrumental case study approach that allowed us to explore SnehAI from the perspectives of technology design, program implementation, and user engagement. We also used a mix of qualitative insights and quantitative analytics data to triangulate our findings.
SnehAI demonstrated strong evidence across fifteen functional affordances: accessibility, multimodality, nonlinearity, compellability, queriosity, editability, visibility, interactivity, customizability, trackability, scalability, glocalizability, inclusivity, connectivity, and actionability. SnehAI also effectively engaged its users, especially young men, with 8.2 million messages exchanged across a 5-month period. Almost half of the incoming user messages were texts of deeply personal questions and concerns about sexual and reproductive health, as well as allied topics. Overall, SnehAI successfully presented itself as a trusted friend and mentor; the curated content was both entertaining and educational, and the natural language processing system worked effectively to personalize the chatbot response and optimize user experience.
SnehAI represents an innovative, engaging, and educational intervention that enables vulnerable and hard-to-reach population groups to talk and learn about sensitive and important issues. SnehAI is a powerful testimonial of the vital potential that lies in AI technologies for social good.
Purpose
Competitor analysis is a key component in operations management. Most business decisions are rooted in the analysis of rival products inferred from market structure. Relative to more ...traditional competitor analysis methods, the purpose of this paper is to provide operations managers with an innovative tool to monitor a firm’s market position and competitors in real time at higher resolution and lower cost than more traditional competitor analysis methods.
Design/methodology/approach
The authors combine the techniques of Web Crawler, Natural Language Processing and Machine Learning algorithms with data visualization to develop a big data competitor-analysis system that informs operations managers about competitors and meaningful relationships among them. The authors illustrate the approach using the fitness mobile app business.
Findings
The study shows that the system supports operational decision making both descriptively and prescriptively. In particular, the innovative probabilistic topic modeling algorithm combined with conventional multidimensional scaling, product feature comparison and market structure analyses reveal an app’s position in relation to its peers. The authors also develop a user segment overlapping index based on user’s social media data. The authors combine this new index with the product functionality similarity index to map indirect and direct competitors with and without user lock-in.
Originality/value
The approach improves on previous approaches by fully automating information extraction from multiple online sources. The authors believe this is the first system of its kind. With limited human intervention, the methodology can easily be adapted to different settings, giving quicker, more reliable real-time results. The approach is also cost effective for market analysis projects covering different data sources.
With increased access to technology and the internet, there are many opportunities for utilizing electronic health (eHealth), internet, or technology-delivered health services and information for the ...prevention and management of chronic diseases.
The aim of this paper was to explore (1) the differences in technology use, (2) Web-based health information seeking and use behaviors, (3) attitudes toward seeking health information on the Web, and (4) the level of eHealth literacy between adults aged 18 and 64 years with and without chronic disease.
A cross-sectional internet survey was conducted in March 2017 with 401 US adults. Participant responses were examined to understand associations between chronic disease status and eHealth behaviors such as internet health-seeking behaviors and Web-based behaviors related to health, tracking health indicators with a mobile app, patient portal use, and preferences for health information.
About 1 in 3 (252/401, 37.2%) participants reported at least 1 chronic disease diagnosis. Seventy-five percent (301/401) of all participants reported having ever searched for health information on the Web. Participants with a chronic disease reported significantly higher instances of visiting and talking to a health care provider based on health information found on the Web (40.0% 48/120 vs 25.8% 46/178, χ
=6.7; P=.01; 43.3% 52/120 vs 27.9% 50/179; χ
=7.6; P=.006). The uses of health information found on the Web also significantly differed between participants with and without chronic diseases in affecting a decision about how to treat an illness or condition (49.2% 59/120 vs 35.0% 63/180, χ
=6.7; P=.04), changing the way they cope with a chronic condition or manage pain (40.8% 49/120 vs 19.4% 35/180, χ
=16.3; P<.001), and leading them to ask a doctor new questions or get a second opinion (37.5% 45/120 vs 19.6% 35/179, χ
=11.8; P<.001). Chronic disease participants were significantly more likely to be tracking health indicators (43.9% 65/148 vs 28.3%, 71/251 χ
=10.4; P=.006). In addition, participants with chronic disease diagnosis reported significantly higher rates of patient portal access (55.0% 82/149 vs 42.1% 106/252, χ
=6.3; P=.01) and use (40.9% 61/149 vs 21.0% 53/252, χ
=18.2; P<.001). Finally, both groups reported similar perceived skills in using the internet for health information on the eHealth Literacy Scale (eHEALS). The majority of participants responded positively when asked about the usefulness of health information and importance of accessing health resources on the Web.
The high rates of reported information seeking and use of internet-based health technology among participants with chronic disease may reflect the uptake in eHealth to help manage chronic disease conditions. Health care providers and educators should continue to seek ways to interact and support patients in their management of chronic disease through eHealth platforms, including capitalizing on Web-based resources, patient portals, and mobile phone apps for disease education and monitoring.
Abstract
Background
Shifts in treatment strategies for rheumatoid arthritis (RA) have made ambulatory care more labour-intensive. These developments have prompted innovative care models, including ...mobile health (mHealth) applications. This study aimed to explore the perceptions of mHealth-inexperienced stakeholders concerning these applications in RA care.
Methods
We performed a qualitative study by focus group interviews of stakeholders including RA patients, nurses specialised in RA care and rheumatologists. The qualitative analysis guide of Leuven (QUAGOL), which is based on grounded theory principles, was used to thematically analyse the data. In addition, the Persuasive Systems Design (PSD) model was used to structure recommended app-features.
Results
In total, 2 focus groups with nurses (total
n
= 16), 2 with patients (
n
= 17) and 2 with rheumatologists (
n
= 25) took place. Six overarching themes emerged from the analysis. Efficiency of care and enabling patient empowerment were the two themes considered as expected benefits of mHealth-use in practice by the stakeholders. In contrast, 4 themes emerged as possible barriers of mHealth-use: the burden of chronic app-use, motivational aspects, target group aspects, and legal and organisational requirements. Additionally, recommendations for an ideal mHealth-app could be structured into 4 domains (Primary Task Support, Dialogue Support, Social Support and System Credibility) according to the PSD-framework. Most recommended features were related to improving ease of use (Task Support) and System Credibility.
Conclusions
Although mHealth-apps were expected to improve care efficiency and stimulate patient empowerment, stakeholders were concerned that mHealth-app use could reinforce negative illness behaviour. For mHealth-apps to be successful in practice, challenges according to stakeholders were avoiding long-term poor compliance, finding the target audience and tailoring a legal and organisational framework. Finally, the ideal mHealth-application should above all be trustworthy and easy to use.
The small retail sector in India, which employs millions of people, faces continuous threats from the emergence of modern retail and e-commerce. There is an urgent need to become more efficient and ...competitive. Increased use of technology can address many of the challenges, and in the last few years, many tech start-ups have come up with low-cost technology solutions for small retailers. The article attempts to map the emergence of these low-cost technologies and draw out the themes that could help increase the adoption and help the small retailer become more competitive.
Recent years have seen a significant increase in the availability of smartphone apps for mental health problems. Despite their proliferation, few apps have been specifically developed for young ...people, and almost none have been subject to any form of evaluation.
This study aimed to undertake a preliminary evaluation of a smartphone app (BlueIce), coproduced with young people and designed to help young people manage distress and urges to self-harm. We aimed to assess the acceptability, safety, and use of BlueIce and to explore the effects on the primary outcome of self-harm and the secondary outcomes of psychological functioning.
We undertook an open trial where we recruited young people aged 12 to 17 years attending specialist child and adolescent mental health services (CAMHS) who were currently self-harming or had a history of self-harm. Eligible participants were assessed at baseline and then given BlueIce. They were assessed 2 weeks later (post familiarization) and again at 12 weeks (post use). A behavior-screening questionnaire (Strengths and Difficulties Questionnaire) was completed along with standardized measures of depression (Mood and Feelings Questionnaire or MFQ) and anxiety (Revised Child Anxiety and Depression Scale or RCADS), taking into account self-reports of self-harm, app helpfulness, and safety.
All core CAMHS professional groups referred at least 1 young person. Out of 40 young people recruited, 37 (93%) elected to use BlueIce after familiarization, with 29 out of 33 (88%) wanting to keep it at the end of the study. No young person called the emergency numbers during the 12-week trial, and no one was withdrawn by his or her clinician due to increased risk of suicide. Almost three-quarters (73%) of those who had recently self-harmed reported reductions in self-harm after using BlueIce for 12 weeks. There was a statistically significant mean difference of 4.91 (t
=2.11; P=.04; 95% CI 0.17-9.64) on postuse symptoms of depression (MFQ) and 13.53 on symptoms of anxiety (RCADS) (t
=3.76; P=.001; 95% CI 6.17-20.90), which was evident across all anxiety subscales. Ratings of app acceptability and usefulness were high.
Our study has a number of methodological limitations, particularly the absence of a comparison group and a prospective way of assessing self-harm. Nonetheless, our findings are encouraging and suggest that BlueIce, used alongside a traditional CAMHS face-to-face intervention, can help young people manage their emotional distress and urges to self-harm.
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