End-user development in social psychology research:Factors for adoption

Psychology researchers employ the Experience Sampling Method (ESM) to capture thoughts and behaviours of participants within their everyday lives. Smartphone-based ESM apps are increasingly used in such research. However, the diversity of researchers' app requirements, coupled with cost and complexity of their implementation, has prompted end-user development (EUD) approaches. In addition, limited evaluation of such environments beyond lab-based usability studies precludes discovery of factors pertaining to real-world EUD adoption.We first describe the extension of Jeeves, our visual programming environment for ESM app creation, in which we implemented additional functional requirements, derived from a survey and analysis of previous work. We further describe interviews with psychology researchers to understand their practical considerations for employing this extended environment in their work practices. Results of our analysis are presented as factors pertaining to the adoption of EUD activities within and between communities of practice.Postprin

TAPping into mental models with blocks

Trigger-Action Programming (TAP) has been shown to support end-users' rule-based mental models of context-aware applications. However, when desired behaviours increase in complexity, this can lead to ambiguity that confuses events, states, and how they can be combined in meaningful ways. Blocks programming could provide a solution, through constrained editing of visual triggers, conditions and actions. We observed slips and mistakes by users performing TAP with Jeeves, our domain-specific blocks environment, and propose solutions.Postprin

Jeeves - A visual programming environment for mobile experience sampling

The Experience Sampling Method (ESM) captures participants’ thoughts and feelings in their everyday environments. Mobile and wearable technologies afford us opportunities to reach people using ESM in varying contexts. However, a lack of programming knowledge often hinders researchers in creating ESM applications. In practice, they rely on specialised tools for app creation. Our initial review of these tools indicates that most are expensive commercial services, and none utilise the full potential of sensors for creating context-aware applications. We present “Jeeves”, a visual language to facilitate ESM application creation. Inspired by successful visual languages in literature, our block-based notation enables researchers to visually construct ESM study specifications. We demonstrate its applicability by replicating existing ESM studies found in medical and psychology literature. Our preliminary study with 20 participants demonstrates that both non-programmers and programmers are able to successfully utilise Jeeves. We discuss future work in extending Jeeves with alternative mobile technologies.PostprintPeer reviewe

Overcoming mental blocks:A blocks-based approach to experience sampling studies

Experience Sampling Method (ESM) studies repeatedly survey participants on their behaviours and experiences as they go about their everyday lives. Smartphones afford an ideal platform for ESM study applications as devices seldom leave their users, and can automatically sense surrounding context to augment subjective survey responses. ESM studies are employed in fields such as psychology and social science where researchers are not necessarily programmers and require tools for application creation. Previous tools using web forms, text files, or flowchart paradigms are either insufficient to model the potential complexity of study protocols, or fail to provide a low threshold to entry. We demonstrate that blocks programming simultaneously lowers the barriers to creating simple study protocols, while enabling the creation of increasingly sophisticated protocols. We discuss the design of Jeeves, our blocks-based environment for ESM studies, and explain advantages that blocks afford in ESM study design.Postprin

Jeeves - an Experience Sampling study creation tool

Ubiquitous mobile technology affords clinicians new opportunities to enhance personalised, patient-centric care remotely, easing the burden on both patient and clinician. The Experience Sampling Method (ESM) involves the repeated assessment of patients on their symptoms or behaviours, and their external contexts, as they go about their everyday lives, enhancing ecological validity and minimising recall bias. While previously conducted with paper diaries, ESM smartphone applications are now being employed, that have a range of benefits over paper-based methods including the ability to scale to many more patients. However, development of such applications is time-consuming and requires considerable programming knowledge. This has prompted the development of ESM creation tools that alleviate a researcher from the burden of programming an ESM application from scratch. This paper presents our work on Jeeves, a visual environment for creating secure ESM Android applications, and a usability evaluation we conducted with health psychology students.Postprin

End-User Development of Experience Sampling Smartphone Apps - Recommendations and Requirements

Professional programmers are significantly outnumbered by end-users of software, making it problematic to predict the diverse, dynamic needs of these users in advance. An end-user development (EUD) approach, supporting the creation and modification of software independent of professional developers, is one potential solution. EUD activities are applicable to the work practices of psychology researchers and clinicians, who increasingly rely on software for assessment of participants and patients, but must also depend on developers to realise their requirements. In practice, however, the adoption of EUD technology by these two end-user groups is contingent on various contextual factors that are not well understood. In this paper, we therefore establish recommendations for the design of EUD tools allowing non-programmers to develop apps to collect data from participants in their everyday lives, known as "experience sampling" apps. We first present interviews conducted with psychology researchers and practising clinicians on their current working practices and motivation to adopt EUD tools. We then describe our observation of a chronic disease management clinic. Finally, we describe three case studies of psychology researchers using our EUD tool Jeeves to undertake experience sampling studies, and synthesise recommendations and requirements for tools allowing the EUD of experience sampling apps

Barriers to and Facilitators of Using eHealth to Support Gestational Diabetes Mellitus Self-management:Systematic Literature Review of Perceptions of Health Care Professionals and Women With Gestational Diabetes Mellitus

BACKGROUND: Gestational diabetes mellitus (GDM) is one of the most common medical complications during pregnancy. eHealth technologies are proving to be successful in supporting the self-management of medical conditions. Digital technologies have the potential to improve GDM self-management. OBJECTIVE: The primary objective of this systematic literature review was to identify the views of health professionals (HPs) and women with GDM regarding the use of eHealth for GDM self-management. The secondary objective was to investigate the usability and user satisfaction levels when using these technologies. METHODS: Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) approach, the search included primary papers in English on the evaluation of technology to support self-management of GDM from January 2008 to September 2021 using MEDLINE, CINAHL, Embase, ACM, and IEEE databases. The lists of references from previous systematic literature reviews, which were related to technology and GDM, were also examined for primary studies. Papers with qualitative, quantitative, and mixed methodologies were included and evaluated. The selected papers were assessed for quality using the Cochrane Collaboration tool, National Institute for Health and Care Excellence clinical guidelines, Critical Appraisal Skills Programme Qualitative Checklist, and McGill University Mixed Methods Appraisal Tool. NVivo (QSR International) was used to extract qualitative data, which were subjected to thematic analysis. Narrative synthesis was used to analyze the quantitative data. RESULTS: A total of 26 papers were included in the review. Of these, 19% (5/26) of studies used quantitative research methodologies, 19% (5/26) used qualitative methods, and 62% (16/26) used mixed methods. In all, 4 themes were identified from the qualitative data: the benefits of using technology, engagement with people via technology, the usability of technology, and discouragement factors for the use of technology. The thematic analysis revealed a vast scope of challenges and facilitators in the use of GDM self-management systems. The challenges included usability aspects of the system, technical problems, data privacy, lack of emotional support, the accuracy of reported data, and adoption of the system by HPs. Convenience, improved GDM self-management, peer support, increased motivation, increased independence, and consistent monitoring were facilitators to use these technologies. Quantitative data showed that there is potential for improving the usability of the GDM self-management systems. It also showed that convenience, usefulness, increasing motivation for GDM self-management, helping with GDM self-management, and being monitored by HPs were facilitators to use the GDM self-management systems. CONCLUSIONS: This novel systematic literature review shows that HPs and women with GDM encountered some challenges in using GDM self-management systems. The usability of GDM systems was the primary challenge derived from qualitative and quantitative results, with convenience, consistent monitoring, and optimization of GDM self-management emerging as important facilitators

Commonshare:a new approach to social reputation for online collaborative communities

Reputation systems are a popular feature of web-based platforms for ensuring that their users abide by platform rules and regulations and are incentivized to demonstrate honest, trustworthy conduct. Accrual of “reputation” in these platforms, most prominently those in the e-commerce domain, is motivated by self-interested goals such as acquiring an advantage over competing platform users. Therefore, in community-oriented platforms, where the goals are to foster collaboration and cooperation among community members, such reputation systems are inappropriate and indeed contrary to the intended ethos of the community and actions of its members. In this article, we argue for a new form of reputation system that encourages cooperation rather than competition, derived from conceptualizing platform communities as a networked assemblage of users and their created content. In doing so, we use techniques from social network analysis to conceive a form of reputation that represents members’ community involvement over a period of time rather than a sum of direct ratings from other members. We describe the design and implementation of our reputation system prototype called “commonshare” and preliminary results of its use within a Digital Social Innovation platform. Further, we discuss its potential to generate insight into other networked communities for their administrators and encourage cooperation between their users