App Development Research Articles

MAD-Onto: an ontology design for mobile app development

IntroductionMobile app development has rapidly evolved into a crucial aspect of modern technology, driving innovation across various industries and transforming user experiences globally. The dynamic nature of mobile technology requires developers to navigate a complex landscape of platforms, devices, and user requirements. Effective management and sharing of knowledge are essential to address these challenges, ensuring streamlined development processes and enhanced collaboration among stakeholders.MethodsTo this end, ontologies have emerged as powerful tools for structuring and standardizing domain-specific knowledge. This paper introduces MAD-onto, a comprehensive ontology designed specifically for the mobile app development domain. The ontology is constructed by identifying key concepts, defining classes and their hierarchies, establishing class properties, and creating instances relevant to mobile app development. To ensure robustness, the ontology is evaluated using a multi-criteria evaluation metric, focusing on consistency, completeness, conciseness, expandability, and sensitiveness. Additionally, SWRL rules are applied to validate and enforce logical constraints within the ontology.ResultsThrough these rigorous evaluation methods, MAD-onto demonstrates its utility in providing a structured framework for the mobile app development lifecycle, facilitating better decision-making, collaboration, and efficiency.DiscussionThe findings highlight the significance of ontology-driven approaches in addressing the complexities of mobile app development and set a foundation for future research and advancements in this field.

Advancing African American and hispanic health literacy with a bilingual, personalized, prevention smartphone application.

Many online health information sources are generic and difficult to understand, but consumers want information to be personalized and understandable. Smartphone health applications (apps) offer personalized information to support health goals and reduce preventable chronic conditions. This study aimed to determine how the HealthyMe/MiSalud personalized app (1) engaged English-speaking African American and Spanish-speaking Hispanic adults, and (2) motivated them to set goals and follow preventive recommendations. Our study adds to the literature on digital health, health information seeking, and prevention. We used a multi-method approach, including community and participatory design principles, to learn about potential African American and Hispanic adult health app users and evaluate the app in two usability tests and a 12-month field test. Ninety-six African American and Hispanic adults downloaded the HealthyMe/MiSalud app and used it for a minimum of 36 weeks. We found they wanted personalized information on core prevention topics, and their health histories and goals affected how they rated topic relevance. African American females ages 18-34 were more likely to save an article aligned with family health history, and African American females aged 35-49, males age 50-64, and African American males overall were more likely to save an article aligned with their health goals. Our study revealed that a prevention app with personalized recommendations can support health information seeking and health literacy. These findings can help app developers, public health practitioners, and researchers when designing apps for groups of varying identities.

User-centred design of ChestCare: mHealth app for pulmonary rehabilitation for patients with COPD; a mixed-methods sequential approach.

The increasing prevalence and burden of chronic obstructive pulmonary disorder (COPD), the challenges in implementing pulmonary rehabilitation (PR) programs and the limited availability of alternatives and supportive programs to serve patients with COPD necessitate the development of pulmonary telerehabilitation (PTR) systems to provide patients with COPD with PR programs. This study aimed to design and develop the ChestCare mobile Health app using user-centred design (UCD) approach. Thus, it provided PTR for patients with COPD, enhancing their self-management of symptoms and improving their compliance with PR programs. In this mixed-methods sequential research, we deployed the UCD iterative design through the prototype app design and development sequence. The first phase was built based on the results of a previous needs assessment study and an analysis of related apps. This produced the initial mock-up, the foundation for the focus group discussions with physiotherapists and patients. Six physiotherapists with cardiorespiratory specialisation evaluated each app module and item of the latest mock-up using the content validity index (CVI) document. The I-CVI (S-CVI/Ave) and (S-CVI/UA) were computed. Qualitative and quantitative data were integrated, and decisions were made by comparing their results. The UCD iterative design through sequential MMR has generated four mock-up app versions. The latest version identified 13 modules through 150 items validated by six experts using a CVI document. The I-CVI calculation of 145 items was 1, while 0.83 for the remaining items, was within accepted values. The S-CVI scored 99.4, indicating an overall validity of the ChestCare app as a PTR system for patients with COPD. The development and validation of the ChestCare app resulted from conducting UCD iterative design and sequential MMR, which identified 13 functionalities, including symptom assessment, tracking lung volume, functional capacity test, action plan, intervention program, COPD education, COPD community, monitoring and reminders.

Effect of a Nurse-Led Support Program Using Mobile Application Versus Nurse Phone Advice on Patients at Risk of Coronary Artery Disease: A Randomized Controlled Trial.

Coronary artery disease (CAD) is a major health problem of atherosclerotic cardiovascular (CV) disease and early intervention is regarded important. Given the proven effect of a lifestyle intervention with nursing telephone counselling and mHealth use in health care, yet the comparisons of both support are lacking, this study is proposed. This study aimed to compare the effects of a coronary artery disease (CAD) support program using a mobile application versus nurse phone advice on exercise amount and physical and psychological outcomes for clients at risk of CAD. A prospective randomized controlled trial was conducted. Ethical approval was obtained. Two-hundred and twenty-six clients were screened, and a total of 168 clients who were at risk of CAD and routinely used smartphones were randomized into the app support group (App group) or the nurse phone advice (NPA) group. Although all participants received the same health talk delivered by a cardiac nurse at the community center, the App group received additional CAD app support, whereas the NPA group received nurse phone advice for 20 min monthly. The app content comprised (1) CAD knowledge in 10 modules, (2) individual exercise records with their own goals and health measures, and (3) a chest pain action list. The intervention lasted for 3 months. Health outcome data were collected at baseline (T0) and after 1 (T1) and 3 (T2) months. The outcomes were the total amount of exercise (primary outcome), self-efficacy in illness management, perceived stress, and CAD risk profile (body weight, body mass index, and lipid concentration). Generalized estimating equation models were used to assess differential changes in all outcomes within 3 months. The attrition rates at 3 months were 3.49% and 9.30% for the App and NPA groups, respectively. The App support group was superior to the NPA group in significantly increasing total exercise amount and reducing body weight, waist circumference, triglycerides, and increased self-efficacy in illness management. The result provides further insights of app development to support health promotion programs for community-dwelling adults at risk of CAD.

A Comprehensive Review on Machine Learning Approaches for Smartphone Addiction Prediction

Smartphone addiction has become a pressing public health concern, with far-reaching implications for mental health, social interactions, and overall well-being. This study proposes an unsupervised machine learning framework to predict smartphone addiction by analyzing user behavior data, such as screen time, application usage patterns, and psychological factors. The research leverages unsupervised learning techniques to identify patterns and commonalities in unlabelled data, aiming to classify individuals at risk of addiction without predefined categories. Using advanced machine learning libraries like TensorFlow and OpenCV, the system incorporates a robust pipeline involving data collection, preprocessing, and training/testing with high-performance models. The findings highlight excessive social media use and notification frequency as significant predictors, with applications ranging from personalized intervention programs and mental health monitoring to enhanced parental control systems. With a focus on scalable and adaptive methodologies, this framework not only addresses the challenges of smartphone addiction but also offers valuable insights for researchers, policymakers, and app developers to design effective solutions for healthier technology use in an increasingly digital society Key Words: Smartphone addiction, machine learning, user behavior analysis, mental health, unsupervised learning.

Developing a Mobile App to Prevent Suicide Based on a Software Development Life Cycle: Application of Ecological Momentary Assessment and Interventions.

To improve mental health, diverse mobile applications (apps) have been developed to target those who actively use smartphones and in-phone apps. In this vein, this study developed a mobile app, eRAPPORT, to prevent suicide using ecological momentary assessment and intervention. A brief literature review and mobile app market search were conducted to determine the app's content and modality. The design and contents of eRAPPORT were developed through consulting with contextual and methodological experts for end-users' need assessment and technician review. For implementation, an experienced mobile app developer collaborated with the research team to create the app, which includes a safety plan, a feature to track suicidal risk and mental health status, evidence-based information from international and national authorised organisations, an outreach service with online/offline counselling and pop-ups displaying emergency contacts. Twenty-five general adults participated in the feasibility study. After using eRAPPORT for a month, they completed a self-reported questionnaire, followed by an in-depth interview of functionality, acceptability and safety. Both quantitative and qualitative evaluations assured the moderate level of usability and acceptability due to some features that should be improved before applying those with a high risk of suicide. No critical adverse event was reported. Thus, this eRAPPORT feasibility study provides fundamental information to describe the patient-centred processes on how to develop a mobile app for suicide prevention. Further study will be conducted to test the app's effectiveness and determine the application in clinical practice for monitoring and preventing suicide risk by collecting real-time and longitudinal data.

Mobile application-based monitoring in post-breast reconstruction surgery: current trends and future directions

Mobile apps are frequently utilized in various medical fields for postoperative care, yet there is limited research concerning their application among breast reconstruction patients. This paper examines the development of mobile apps for postoperative care and discusses key considerations for their design and implementation in the context of breast reconstruction patients. Mobile apps provide a holistic approach to recovery, featuring personalized recovery plans, wound monitoring, pain tracking, medication management, virtual consultations, and emotional support. These functionalities improve patient outcomes, facilitate communication between patients and healthcare providers, and enhance engagement with the recovery process. Advanced digital healthcare technologies are revolutionizing patient care, particularly in home settings, by improving monitoring capabilities and telemedicine, thus increasing access and efficiency. For mobile apps to be successfully adopted in postoperative care, it is crucial to address regulatory, financial, and engagement challenges to ensure they deliver sustained value to both patients and healthcare providers. Future research should aim to extend these solutions to plastic surgery and other medical disciplines to improve recovery outcomes for a broad range of patient populations.

The impact of security and privacy perceptions on cryptocurrency app evaluations by users: A text mining study

This study examines how perceived security and privacy influence user ratings of cryptocurrency applications, which are critical for adoption and satisfaction amid the growing popularity of blockchain technologies and rising concerns over information security in online platforms and mobile apps. The study focuses on mobile applications from the Android app market. It used text mining methods to investigate over 64 thousand text-based user reviews and star ratings of over 140 cryptocurrency-related mobile applications available in the Google Play store. Using a partially supervised machine learning approach, this study first identified reviewer sentiment related to privacy and security, then employed ordinal regression analysis to examine the data to reveal the relationship between perceived security threats, privacy concerns, and app ratings. This study found that crypto apps average 3.84 out of 55 stars, which is higher than Productivity apps (3.46) but lower than FinTech (4.29) and Banking (4.25) apps. Ordinal regression analysis revealed security and privacy threats negatively impact ratings, while robust security measures improve them, with a model Pseudo R² of 0.25. These results have implications for both cryptocurrency app developers and platform managers, offering insights for enhancing user experiences and informing future research endeavors in this domain. It contributes to the literature by integrating the Protection Motivation Theory with sentiment analysis and provides a structured framework for developing an understanding of user behavior in the context of cryptocurrency apps.

DLCDroid an android apps analysis framework to analyse the dynamically loaded code

To combat dynamically loaded code in anti-emulated environments, DLCDroid is an Android app analysis framework. DL-CDroid uses the reflection API to effectively identify information leaks due to dynamically loaded code within malicious apps, incorporating static and dynamic analysis techniques. The Dynamically Loaded Code (DLC) technique employs Java features to allow Android apps to dynamically expand their functionality at runtime. Unfortunately, malicious app developers often exploit DLC techniques to transform seemingly benign apps into malware once installed on real devices. Even the most sophisticated static analysis tools struggle to detect data breaches caused by DLC. Our analysis demonstrates that conventional tools areill-equipped to handle DLC. DLCDroid leverages dynamic code interposition techniques for API hooking to expose concealed malicious behavior without requiring modifications to the Android framework. DLCDroid can unveil suspicious behavior that remains hidden when relying solely on static analysis. We evaluate DLCDroid’s performance using a dataset comprising real-world benign and malware apps from reputed repositories like VirusShare and the Google Play Store. Compared to state-of-the-art approaches, the results indicate a significant improvement in detecting sensitive information leaks, more than 95.6% caused by reflection API. Furthermore, we enhance DLCDroid’s functionality by integrating it with an event-based trigger solution, making the framework more scalable and fully automated in its analysis process.

A pilot study on diabetes detection using handheld fundus camera and mobile app development

BackgroundDiabetes, affecting more than 500 million individuals worldwide, is the most widespread non-communicable disease, globally. The early identification and effective management of diabetes are crucial for controlling its spread. Currently, the HbA1c test is the gold standard for the detection of diabetes with high confidence. But this is an invasive, expensive pathology test. Therefore, alternative non-invasive and inexpensive methods have been proposed in the literature for the early detection of diabetes.MethodsIn this pilot study, we used a handheld fundus camera that simplifies the accessibility issue for doctors and patients in underprivileged communities, remote areas, enabling a quick and reasonably accurate diabetes diagnosis process. We invited participants from the community to share their demographic information, history of diabetes, and captured their retinal fundus images using the oDocs Nun IR handheld non-mydriatic fundus camera in a non-invasive manner (no dilation is required). Subsequently, we developed a deep learning model for early diagnosis of diabetes based on fundus image only. Moreover, we created an Android-based mobile application, DMPred, which utilizes the fundus images to predict the onset of diabetes.ResultsThe proposed model achieved an 86.4% accuracy rate in diabetes detection showing that handheld cameras can be effective and provide comparable results like tabletop cameras in the early diagnosis of diabetes. We also provide a comprehensive guideline, including necessary steps for transforming deep learning models into Android-based mobile applications for tech transfer.ConclusionsTo the best of our knowledge, this article is the first demonstration of diabetes diagnosis using handheld fundus camera and mobile app. We believe that this pilot study and the proposed tech solution will support the larger community with limited clinical facilities and enhance the accessibility of technology for diabetes detection.

Exploring the Application of a Co-Creation Model in Archaeological Tourism: Two Case Studies developed under TURARQ's project within the frame of Link Me Up - 1000 ideas project

This paper discusses two projects that revolve around the conceptualization of tourism products within the framework of interpreting and understanding archaeological sites through a sustainable approach as part of TURARQ's initiative. The primary objective was to explore the application of a co-creation model, specifically the Project Based Learning methodology of "Demola" with the support of the "Link me Up" project, in the field of archaeological tourism. The first project, Show Me the Past, involved the development of a mobile app that utilized an agile requirement analysis to create a prototype. The second project, Showcasing Prehistory, focused on entrepreneurship, inclusion, heritage, and sustainability, using a diagnosis of the social issues affecting the Mação territory. The outcomes of the first project included the creation of a Mobile Augmented Reality (MAR) application, which allows users to visualize virtual objects in the real environment of discovery. In the second project, empathy maps were developed, encompassing archaeotourism, the local community, theme parks, and special needs. The findings indicated that these programs generated high levels of participant satisfaction and positively impacted competency development. However, further studies are required to ascertain the number of participants who have transitioned into entrepreneurs because of their involvement in these projects.

A User-Centered Design Approach for a Screening App for People With Cognitive Impairment (digiDEM-SCREEN): Development and Usability Study.

Dementia is a widespread syndrome that currently affects more than 55 million people worldwide. Digital screening instruments are one way to increase diagnosis rates. Developing an app for older adults presents several challenges, both technical and social. In order to make the app user-friendly, feedback from potential future end users is crucial during this development process. This study aimed to establish a user-centered design process for the development of digiDEM-SCREEN, a user-friendly app to support early identification of persons with slight symptoms of dementia. This research used qualitative and quantitative methods and involved 3 key stakeholder groups: the digiDEM research team, the software development team, and the target user group (older adults ≥65 years with and without cognitive impairments). The development of the screening app was based on an already existing and scientifically analyzed screening test (Self-Administered Tasks Uncovering Risk of Neurodegeneration; SATURN). An initial prototype was developed based on the recommendations for mobile health apps and the teams' experiences. The prototype was tested in several iterations by various end users and continuously improved. The app's usability was evaluated using the System Usability Scale (SUS), and verbal feedback by the end users was obtained using the think-aloud method. The translation process during test development took linguistic and cultural aspects into account. The texts were also adapted to the German-speaking context. Additional instructions were developed and supplemented. The test was administered using different randomization options to minimize learning effects. digiDEM-SCREEN was developed as a tablet and smartphone app. In the first focus group discussion, the developers identified and corrected the most significant criticism in the next version. Based on the iterative improvement process, only minor issues needed to be addressed after the final focus group discussion. The SUS score increased with each version (score of 72.5 for V1 vs 82.4 for V2), while the verbal feedback from end users also improved. The development of digiDEM-SCREEN serves as an excellent example of the importance of involving experts and potential end users in the design and development process of health apps. Close collaboration with end users leads to products that not only meet current standards but also address the actual needs and expectations of users. This is also a crucial step toward promoting broader adoption of such digital tools. This research highlights the significance of a user-centered design approach, allowing content, text, and design to be optimally tailored to the needs of the target audience. From these findings, it can be concluded that future projects in the field of health apps would also benefit from a similar approach.

Attitudes of German General Practitioners Toward eHealth Apps for Dementia Risk Reduction: Qualitative Interview Study.

eHealth interventions constitute a promising approach to disease prevention, particularly because of their ability to facilitate lifestyle changes. Although a rather recent development, eHealth interventions might be able to promote brain health and reduce dementia risk in older adults. This study aimed to explore the perspective of general practitioners (GPs) on the potentials and barriers of eHealth interventions for brain health. Understanding the perspective of GPs allows us to identify chances and challenges for implementing eHealth apps for dementia risk reduction. We conducted semistructured expert interviews with 9 GPs working in an outpatient setting in and near Leipzig, Germany. Data were fully transcribed and analyzed using a process model of qualitative content analysis with codes and categories being constructed inductively and deductively. We found generally favorable but balanced views of eHealth apps for brain health. Eight themes were identified and elaborated on in the data as follows: "addressing dementia," "knowledge about dementia," "need for information," "potential for prevention," "chances for apps for prevention," "development of apps for prevention," and "barriers of apps for prevention." GPs talked mostly about how and when to address dementia and the requirements for their use of eHealth apps for dementia prevention. GPs stated that they only addressed dementia once abnormalities were already present or less frequently when a patient or relative expressed a direct wish, while individual dementia risk or standardized diagnostic during routine check-ups were mentioned much less frequently. According to GPs, knowledge about dementia in patients was low; therefore, patients expressed little need for information on dementia risk factors and prevention in GP practices. Most patients wished for quick information regarding diagnostics, treatment options, and progression of the disease. GPs mentioned a lack of overview of the available eHealth apps and their content. They also expressed a fear of inducing health anxiety when talking to patients about risk factors and prevention. GPs want patients to receive relevant and individualized information. Prerequisites for the use of eHealth apps for dementia prevention were app characteristics related to design and content. GPs need to address dementia more routinely, assess relevant risk factors, and aid patients in a preventive role. Concerns were expressed over limited effectiveness, overwhelming patients, limited use in clinical practice, and only targeting patients with an already low risk of dementia.

Reflections of Foster Youth Engaging in the Co-Design of Digital Mental Health Technology: Duoethnography Study.

Current research on digital applications to support the mental health and well-being of foster youth is limited to theoretical applications for transition-aged foster youth and support platforms developed without intentional input from foster youth themselves. Centering the lived expertise of foster youth in digital solutions is crucial to dismantling barriers to care, leading to an increase in service access and improving mental health outcomes. Co-design centers the intended end users during the design process, creating a direct relationship between potential users and developers. This methodology holds promise for creating tools centered on foster youth, yet little is known about the co-design experience for foster youth. Understanding foster youth's experience with co-design is crucial to identifying best practices, knowledge of which is currently limited. The aim of this paper is to reflect on the experiences of 4 foster youth involved in the co-design of FostrSpace, a mobile app designed through a collaboration among foster youth in the San Francisco Bay Area; clinicians and academics from the Juvenile Justice Behavioral Health research team at the University of California, San Francisco; and Chorus Innovations, a rapid technology development platform specializing in participatory design practices. Key recommendations for co-designing with foster youth were generated with reference to these reflections. A duoethnography study was conducted over a 1-month period with the 4 transition-aged former foster youth co-designers of FostrSpace via written reflections and a single in-person roundtable discussion. Reflections were coded and analyzed via reflexive thematic analysis. In total, 4 main themes were identified from coding of the duoethnography reflections: power and control, resource navigation, building community and safe spaces, and identity. Themes of power and control and resource navigation highlighted the challenges FostrSpace co-designers experienced trying to access basic needs, support from caregivers, and mental health resources as foster youth and former foster youth. Discussions pertaining to building community and safe spaces highlighted the positive effect of foster youth communities on co-designers, and discussions related to identity revealed the complexities associated with understanding and embracing foster youth identity. This duoethnography study highlights the importance of centering the lived expertise of co-designers throughout the app development process. As the digital health field increasingly shifts toward using co-design methods to develop digital mental health technologies for underserved youth populations, we offer recommendations for researchers seeking to ethically and effectively engage youth co-designers. Actively reflecting throughout the co-design process, finding creative ways to engage in power-sharing practices to build community, and ensuring mutual benefit among co-designers are some of the recommended core components to address when co-designing behavioral health technologies for youth.

Influence of User Involvement on the Personal Empowerment of Participants

ABSTRACT Older adults are increasingly involved in technology developments. At the same time, little is known about the extent to which the people involved can benefit from user involvement. The aim of this study was to record the subjective experiences of older adults in user-centered app development and thus to investigate the impact of user involvement on the participants at an individual level. To this end, problem-centered individual interviews were conducted with four adults: Two volunteers and two older adults living in a nursing home. The results show that typical empowerment-related outcomes such as increased competence, recovery of existing interests and competences, a more positive attitude toward life and even encouragement for further social engagement were generated. However, there are differences between the volunteers and the older adults living in the nursing home that reinforce the context-dependency of personal empowerment. The results of this study confirm the findings of other studies that older people, including those living in nursing homes, can participate in user involvement. At the same time, the results show that it is important to recognize that people react differently to user involvement and have different needs depending on the context in which they live.

SHOPPE GAMES: HOW SHOPPE UTILIZES GAMIFICATION TO INCREASE APP UPTIME

This study examines how Shopee leverages gamification to increase user engagement, particularly by enhancing the time spent on its application. The research employs a qualitative approach with a literature review method, analyzing relevant studies on gamification in e-commerce. Findings reveal that gamification elements such as rewards, challenges, and social interaction significantly contribute to prolonged app usage. Rewards motivate users with tangible incentives, challenges create engaging experiences through progressively difficult tasks, and social interaction fosters connections through competition and collaboration. These results align with Self-Determination Theory and Flow Theory, which emphasize the role of fulfilling psychological needs and creating immersive experiences in driving engagement. The study provides practical insights for app developers, highlighting the importance of designing effective gamification strategies to enhance user retention and loyalty. However, limitations include the absence of primary empirical data, suggesting future research should explore the direct impact of gamification on diverse user demographics through quantitative or mixed-method approaches.

Divergent deceptions: comparative analysis of Deceptive Patterns in iOS and Android apps

ABSTRACT Deceptive Patterns (also known as Dark Patterns) are manipulative interface elements that can cause users to experience financial, temporal, and privacy-related losses. While Deceptive Patterns have been extensively studied in Android applications, their prevalence in iOS apps remains largely unexplored, despite significant ecosystem differences and iOS's growing popularity among younger users. Notably, Apple's tight control over its ecosystem has fostered public perception of iOS being the safer platform and as a byproduct, iOS users may be less vigilant towards app-related risks. To investigate how the prevalence of Deceptive Patterns on iOS compares to Android, we conducted a review of the same 143 mobile apps across both platforms. Our analysis reveals statistically significant differences between Deceptive Patterns on iOS and Android, with iOS apps exhibiting more instances overall (1477 vs. 1398). The findings suggest that iOS users may be more vulnerable to the risks posed by Deceptive Patterns. Furthermore, our analysis identified four specific types of Deceptive Patterns with notable discrepancies between the mobile platforms, indicating potential influences by app store guidelines and developer tools, and the rise of A/B testing Deceptive Patterns. These findings highlight the need to further explore different digital platforms and user protections on mobile devices.

Indian Millennials’ continued usage intentions toward online dating apps: the interplay between trust and perceived autonomy

Purpose This study aims to empirically examine the role of privacy, security, trust and autonomy in Millennials’ continued use of online dating applications. Emerging markets have been famous for their rapid modernization, growth and cultural shifts. Yet, consumer worries about online dating consumption need to be addressed in the literature through a better understanding of their behavioural intentions. This study examines the interplay of the underlying variables by testing a conceptual framework grounded on the theory of reasoned action (TRA), the self-determination theory (SDT) and the information systems continuance theory (ISCT) with regard to an emerging market. Design/methodology/approach A cross-sectional and quantitative research design is adopted. Using a well-designed structured questionnaire adapted from established scales, data was collected through a survey featuring 332 substantive responses from actively involved Millennial users of online dating apps in India. The data was analysed using confirmatory factor analysis (CFA) and structural equation modelling (SEM) through IBM SPSS AMOS (Analysis of Moment Structures) 24.0 to provide evidence of the reliability and validity of constructs alongside testing the hypothesis in the proposed model. Furthermore, Preacher and Hayes’ (2004) approach is used to explore mediation effects. Findings The results show that autonomy and trust positively affect the continued use of online dating apps. The study further reveals that autonomous behaviour motivates Millennials to use online dating apps, overriding their concerns for privacy and security. Furthermore, the results indicate that trust fully mediates the relationship between concern for privacy, perceived security and continued usage intention. Therefore, trust affects users’ intentions to continue using online dating apps as it bridges the effect of users’ concern for privacy and the perceived security in the online dating platform, making these dimensions relevant as a whole. Research limitations/implications This study provides critical insights into the theory and practice. The findings demonstrate that autonomy is more significant in motivating Millennials to use online dating apps than concerns about privacy and perceptions of security. In addition, trust plays a crucial role in mediating the relationship between these variables. Therefore, app developers, app marketers and app stores can use the findings to motivate Millennials to continue using their platforms by encouraging a sense of freedom and a better inner self, fostering engagement and conveying user trust. Originality/value Several studies have investigated the pre-adoption behaviour of users of online dating apps, and little attention has been paid to continuance usage. This study provides a unique theoretical research model and perspective for online dating apps that uncovers the role of concern for privacy, perceived security and trust that affect post-adoption behaviour by integrating the TRA, SDT and ISCT. This integration offers a more futuristic and refined perspective on human behaviour by considering both cognitive and motivational aspects. The study establishes that autonomy outweighs concern for privacy and perceived security.

Quickly Finding the Semantically Optimal Presentation Order for a Set of Text Artifacts

This study considers how to quickly find the order in which to present a set of text artifacts on mobile apps or websites such that those artifacts are maximally semantically separated. Semantic separation is desirable because it ensures that users experience as much novelty as possible from one item to the next, thereby improving user attention and engagement. Since an exhaustive search of all possible sequences of text items becomes increasingly infeasible as the length of the sequence grows, a new algorithm is proposed to quickly find the semantically optimal presentation order for a set of text artifacts. The performance of the proposed algorithm is evaluated using an extensive set of experiments involving three different types of text artifacts, seven different sequence lengths, and more than 600 experimental trials. The results demonstrate that the proposed algorithm can select statistically optimal sequences of text artifacts extremely quickly, regardless of the type of text artifacts being used as input or the length of the sequence. App and website developers who are seeking to hold users’ attention and improve user engagement may therefore find the proposed algorithm very attractive in comparison to an exhaustive search.

CoGames: Development of an adaptive smartphone-based and gamified monitoring tool for cognitive function in Multiple Sclerosis

AimAs part of the development of a smartphone-based app for monitoring MS disease activity and progression (dreaMS, NCT05009160), we developed six gamified tests with multiple difficulty levels as a monitoring tool for cognition. This study quantified the relative difficulty between levels and investigated their reliability, ability to depict practice effects, and user acceptance.MethodsHealthy volunteers played each game, covering five cognitive domains, twice per day for 11 consecutive days. Linear mixed models determined the relative difficulty of the levels. Spearman's correlation of the two daily repetitions measured test–retest reliability. Difficulty increased daily except for days 2, 6, and 11, when the easiest level (“Beginner”) was repeated to estimate practice effects. Participants rated enjoyment and other components of acceptance on a 5-point scale.ResultsWe included 82 participants from April to July 2023 in Basel, Switzerland, of which 76 (51 female, age: 40.3 ± 13.9 years, range 18–69) completed the study according to protocol. Generally, mean performances decreased with higher difficulty levels. Across all levels of all games, the median test–retest correlation was 0.825 (range of medians 0.55–0.9). Mean performance in level “Beginner” improved across all games. The mean enjoyment rating was 3.9 (range: 3.1–4.3).ConclusionOur study showed that the CoGames yield reliable measures across different cognitive domains and difficulty levels and were enjoyable to play. The observed practice effects must be considered, but also indicate sensitivity to change. These results support the hypothesis that adaptive gamified digital tests can serve as a reliable and well-accepted monitoring tool of cognition in PwMS.