Understanding Design Approaches and Evaluation Methods in mHealth applications Targeting Substance Use: Protocol for a Systematic Review (Preprint)

BACKGROUND Substance use and use disorders in the US have had significant and devastating impacts on individuals and communities, and the escalating substance use crisis calls for urgent and innovative solutions to effectively detect and provide interventions for individuals in times of need. Recent mHealth-based approaches offer promising new opportunities to address these issues through ubiquitous devices. However, the design rationale, theoretical framing, and the mechanisms through which users' perspectives and experiences guide the design and deployment of such systems have not been analyzed in any prior systematic reviews. OBJECTIVE In this paper, we systematically review these approaches and applications for their feasibility, efficacy, and usability. Further, we evaluate whether human-centered research principles and techniques guide the design and development of these systems, and examine how the current state-of-art systems apply to real-world contexts. In an effort to gauge the applicability of these systems, we also investigate whether these approaches consider the effects of stigma and the privacy concerns related to collecting data on substance use. Lastly, we examine persistent challenges in the design and large-scale adoption of substance use intervention applications and draw inspiration from other domains of mHealth to suggest actionable reforms into the design and deployment of these applications. METHODS Four databases (PubMed, IEEE, JMIR and ACM DL) were searched over a five-year period (2016 - 2021) for articles evaluating connected mHealth approaches for substance use (alcohol use, marijuana use, opioid use, tobacco use, and substance co-use). Articles that will be included describe an mHealth detection or intervention targeting substance use and provided outcomes data and a discussion of design techniques and user perspectives. Independent evaluation will be conducted by one author, followed by secondary reviewer(s) who will check and validate themes and data. RESULTS This is a protocol for a systematic review, therefore results are not yet available. We are currently in the process of selecting the studies for inclusion in the final analysis. CONCLUSIONS To the best of our knowledge, this is the first systematic review to assess real-world applicability, scalability, and use of human-centered design and evaluation techniques in mHealth approaches targeting substance use. This study is expected to identify gaps in current substance use detection and intervention mHealth technologies and inform and motivate future development of such systems.

User perspectives on critical factors for collaborative playlists

Today, collaborative playlists (CPs) translate long-standing social practices around music consumption to enable people to curate and listen to music together over streaming platforms. Yet despite the critical role of CPs in digitally connecting people through music, we still understand very little about the needs and desires of real-world users, and how CPs might be designed to best serve them. To bridge this gap in knowledge, we conducted a survey with CP users, collecting open-ended text responses on what aspects of CPs they consider most important and useful, and what they viewed as missing or desired. Using thematic analysis, we derived from these responses the Codebook of Critical CP Factors, which comprises eight categories. We gained insights into which aspects of CPs are particularly useful—for instance, the ability for multiple collaborators to edit a single playlist—and which are absent and desired—such as the ability for collaborators to communicate about a CP or the music contained therein. From these findings we propose design implications to inform further design of CP functionalities and platforms, and highlight potential benefits and challenges related to their adoption in current music services.

Assessment of Antipsychotic Medications on Social Media: Machine Learning Study

Background: Antipsychotic medications are the first-line treatment for schizophrenia. However, non-adherence is frequent despite its negative impact on the course of the illness. In response, we aimed to investigate social media posts about antipsychotics to better understand the online environment in this regard.Methods: We collected tweets containing mentions of antipsychotic medications posted between January 1st 2019 and October 31st 2020. The content of each tweet and the characteristics of the users were analyzed as well as the number of retweets and likes generated.Results: Twitter users, especially those identified as patients, showed an interest in antipsychotic medications, mainly focusing on the topics of sexual dysfunction and sedation. Interestingly, paliperidone, despite being among one of the newest antipsychotics, accounted for a low number of tweets and did not generate much interest. Conversely, retweet and like ratios were higher in those tweets asking for or offering help, in those posted by institutions and in those mentioning cognitive complaints. Moreover, health professionals did not have a strong presence in tweet postings, nor did medical institutions. Finally, trivialization was frequently observed.Conclusion: This analysis of tweets about antipsychotic medications provides insights into experiences and opinions related to this treatment. Twitter user perspectives therefore constitute a valuable input that may help to improve clinicians' knowledge of antipsychotic medications and their communication with patients regarding this treatment.

Practitioner and Service User Perspectives on the Rapid Shift to Teletherapy for Individuals on the Autism Spectrum as a Result of COVID-19

Prior to COVID-19, research into teletherapy models for individuals on the autism spectrum was slowly progressing. Following the onset of COVID-19, teletherapy became a necessity for continuity of services, however, research was still emerging for how to translate best practice autism support to the online environment. The aim of this research was to gain insight into the rapid shift to teletherapy for practitioner and service users and the implications for the broader disability sector. Survey responses were collected from 141 allied health practitioners (speech pathologists, occupational therapists, psychologists, educators, and social workers) from four Australian states and territories. A total of 806 responses were collected from service users following an individual teletherapy session. Five themes were identified during the qualitative analysis; (1) technology—love it or hate it; (2) teletherapy as a “new normal”; (3) short term pain, for long term gain; (4) the shape of service delivery has changed; (5) is teletherapy always an option? Data from the quantitative analysis provided further insights into the first two themes. While COVID-19 has brought forward significant advances in telehealth models of practice, what is needed now is to delve further into what works, for who, and in which context, and explore the potentiality, efficiencies, and scalability of a post-pandemic hybrid approach. This will inform practice guidelines and training, as well as information for service users on what to expect.

Rút bài vì sử dụng dữ liệu trái phép

SSHPA (30-09-2021) — Tạp chí International Journal of Older People Nursing đã ra quyết định rút bài báo “Co-designing technology with people with dementia and their carers: Exploring user perspectives when co-creating a mobile health application” vì lý do khá đặc biệt: Tác giả duy nhất của bài sử dụng dữ liệu không được phép, và không ghi nhận vai trò của các nhà nghiên cứu và nguồn tài trợ khác [1,2].

Datafication research: Mapping the field for a future agenda

A growing body of research centers around the concept of “datafication” suggesting a buzz around data studies and, perhaps, the emergence of a research field. This article analyzes and discusses the current state of datafication research. Our dataset comprises 463 publications on datafication identified through a systematic literature search in Web of Science and Scopus, an explorative network analysis of keyword co-occurrences and a content analysis of these publications. We map datafication research interests in various research fields, find that the majority of studies are theoretically oriented, whereas empirical analyses largely apply qualitative approaches and rarely make use of data-driven methods. We suggest studies on datafication can be devised into categories reflecting research interests in either user understandings and practices or in infrastructure and technological processes of datafication. The latter strand is particularly sparse in empirical anchoring, and needs empirical and methodological attention. We conclude by outlining three paths for future datafication research to cross-pollinate infrastructural and user perspectives, highlighting the bridging role of communication research in such an endeavor.