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In recent years, we have seen many examples of software products unintentionally causing demonstrable harm. Many guidelines for ethical and responsible computing have been developed in response. Dominant approaches typically attribute liability and blame to individual companies or actors, rather than understanding how the working practices, norms, and cultural understandings in the software industry contribute to such outcomes. In this paper, we propose an understanding of responsibility that is infrastructural, relational, and cultural; thus, providing a foundation to better enable responsible software engineering into the future. Our approach draws on Young's (2006) social connection model of responsibility and Star and Ruhleder's (1994) concept of infrastructure. By bringing these theories together we introduce a concept called infrastructural injustice, which offers a new way for software engineers to consider their opportunities for responsible action with respect to society and the planet. We illustrate the utility of this approach by applying it to an Open-Source software communities’ development of Deepfake technology, to find key leverage points of responsibility that are relevant to both Deepfake technology and software engineering more broadly.

BackgroundRetaining participants in clinical trials is an established challenge. Currently, the industry is moving to a technology-mediated, decentralized model for running trials. The shift presents an opportunity for technology design to aid the participant experience and promote retention; however, there are many open questions regarding how this can be best supported. We advocate the adoption of a stronger theoretical position to improve the quality of design decisions for clinical trial technology to promote participant engagement. ObjectiveThis study aimed to identify and analyze the types of retention strategies used in published clinical trials that successfully retain participants. MethodsA systematic scoping review was carried out on 6 electronic databases for articles published from 1990 to September 2020, namely CINAHL, The Cochrane Library, EBSCO, Embase, PsycINFO, and PubMed, using the concepts “retention,” “strategy,” “clinal trial,” and “clinical research.” This was followed by an analysis of the included articles through the lens of self-determination theory, an evidence-based theory of human motivation. ResultsA total of 26 articles were included in this review. The motivational strategies identified in the clinical trials in our sample were categorized into 8 themes: autonomy; competence; relatedness; controlled motivation; branding, communication material, and marketing literature; contact, tracking, and scheduling methods and data collection; convenience to contribute to data collection; and organizational competence. The trials used a wide range of motivational strategies. Notably, the trials often relied on controlled motivation interventions and underused strategies to support intrinsic motivation. Moreover, traditional clinical trials relied heavily on human interaction and “relatedness” to support motivation and retention, which may cause problems in the move to technology-led decentralized trials. We found inconsistency in the data-reporting methods and that motivational theory–based approaches were not evident in strategy design. ConclusionsThis study offers direction and a framework to guide digital technology design decisions for future decentralized clinical trials to enhance participant retention during clinical trials. This research defines previous clinical trial retention strategies in terms of participant motivation, identifies motivational strategies, and offers a rationale for selecting strategies that will improve retention. It emphasizes the benefits of using theoretical frameworks to analyze strategic approaches and aid decision-making to improve the quality of technology design decisions.

Conspiracy beliefs have become a topic of increasing interest among behavioural researchers. While holding conspiracy beliefs has been associated with several detrimental social, personal, and health consequences, little research has been dedicated to systematically reviewing the methods that could reduce conspiracy beliefs. We conducted a systematic review to identify and assess interventions that have sought to counter conspiracy beliefs. Out of 25 studies (total N = 7179), we found that while the majority of interventions were ineffective in terms of changing conspiracy beliefs, several interventions were particularly effective. Interventions that fostered an analytical mindset or taught critical thinking skills were found to be the most effective in terms of changing conspiracy beliefs. Our findings are important as we develop future research to combat conspiracy beliefs.

There are growing concerns about the potential for deepfake technology to spread misinformation and distort memories, though many also highlight creative applications such as recasting movies using other actors, or younger versions of the same actor. In the current mixed-methods study, we presented participants (N = 436) with deepfake videos of fictitious movie remakes (such as Will Smith staring as Neo in The Matrix). We observed an average false memory rate of 49%, with many participants remembering the fake remake as better than the original film. However, deepfakes were no more effective than simple text descriptions at distorting memory. Though our findings suggest that deepfake technology is not uniquely placed to distort movie memories, our qualitative data suggested most participants were uncomfortable with deepfake recasting. Common concerns were disrespecting artistic integrity, disrupting the shared social experience of films, and a discomfort at the control and options this technology would afford.

Deepfakes are a form of multi-modal media generated using deep-learning technology. Many academics have expressed fears that deepfakes present a severe threat to the veracity of news and political communication, and an epistemic crisis for video evidence. These commentaries have often been hypothetical, with few real-world cases of deepfake's political and epistemological harm. The Russo-Ukrainian war presents the first real-life example of deepfakes being used in warfare, with a number of incidents involving deepfakes of Russian and Ukrainian government officials being used for misinformation and entertainment. This study uses a thematic analysis on tweets relating to deepfakes and the Russo-Ukrainian war to explore how people react to deepfake content online, and to uncover evidence of previously theorised harms of deepfakes on trust. We extracted 4869 relevant tweets using the Twitter API over the first seven months of 2022. We found that much of the misinformation in our dataset came from labelling real media as deepfakes. Novel findings about deepfake scepticism emerged, including a connection between deepfakes and conspiratorial beliefs that world leaders were dead and/or replaced by deepfakes. This research has numerous implications for future research, societal media platforms, news media and governments. The lack of deepfake literacy in our dataset led to significant misunderstandings of what constitutes a deepfake, showing the need to encourage literacy in these new forms of media. However, our evidence demonstrates that efforts to raise awareness around deepfakes may undermine trust in legitimate videos. Consequentially, news media and governmental agencies need to weigh the benefits of educational deepfakes and pre-bunking against the risks of undermining truth. Similarly, news companies and media should be careful in how they label suspected deepfakes in case they cause suspicion for real media.

Abstract Background Digital harm-reduction interventions typically focus on people with severe drug-use problems, yet these interventions have moderate effectiveness on drug-users with lower levels of risk of harm. The difference in effectiveness may be explained by differences in behavioural patterns between the two groupings. Harnessing behavioural theories to understand what is at the core of drug-use behaviours and mapping the content of new interventions, may improve upon the effectiveness of interventions for lower-risk drug-users. To the best of our knowledge, this is the first study to systematically apply the Behaviour Change Wheel (BCW) approach to understand the components, influencing capabilities, opportunities, and motivations (COM-B) of higher education students to change their drug-use behaviors. It is also the first study which identifies specific patterns of behaviours that are more responsive to harm reduction practices through the use of the Theoretical Domain Framework (TDF). Methods We employed an explanatory sequential mix-method design. We first conducted an on-line survey and a Delphi exercise to understand the factors influencing COM-B components of higher education students to change their drug-use. Subsequently, we mapped all evidence onto the COM-B components and the TDF domains to identify clusters of behaviours to target for change, using a pattern-based discourse analysis. Finally, a series of multidisciplinary group meetings identified the intervention functions—the means by which the intervention change targeted behaviours and the Behavioural Change Techniques (BCTs) involved using the behaviour change technique taxonomy (v.1). Results Twenty-nine BCTs relevant to harm-reduction practices were identified and mapped across five intervention functions (education, modelling, persuasion, incentivization, and training) and five policy categories (communication/marketing, guidelines, regulation, service provision, and environmental/social planning). These BCTs were distributed across eight identified saturated clusters of behaviours MyUSE intervention attempts to change. Conclusions The BCTs, identified, will inform the development of a digitally delivered behaviour change intervention that focuses on increasing mindful decision-making with respect to drug-use and promotes alternatives to drug-use activities. The findings can also inform implementation scientists in applying context-specific harm-reduction practices in higher education. We present examples of how the eight identified clusters of target behaviours are mapped across the COM-B components and the TDF, along with suggestions of implementation practices for harm reduction at student population level.

Instagram is an increasingly popular photography-based social networking platform. Recent studies that seek to understand the impact of engaging with Instagram on the behaviour and wellbeing of users have generated surprisingly conflicting evidence. We argue that in much of the existing research, “using Instagram” is considered a standardised, homogenous, experience, much like watching a TV show or film. The reality is that Instagram supports a wide range of possible experiences for users, who have some agency in shaping that experience. The aim of this study is to better understand the various ways in which Instagram users actively participate, or not, in the shaping and curation of their own Instagram experience. There were 17 participants in this study, 10 females and seven males, with an age range of 18–39 years old, who were recruited through a university mailing list. Semi-structured interviews were conducted and a combination of inductive and deductive thematic analysis was carried out to identify and organise patterns of meaning in the data. Specifically, open-coded interview transcripts were deductively analysed, following Bandura's (2001) framework for classifying the experience of agency, using the organising concepts of; intentionality, forethought, self-reactiveness, and reflection. Our findings, firstly, describe a unique set of aims, motivations, and strategies that participants employed to shape and curate a personal Instagram experience. Secondly, findings suggest that Bandura's framework provides some explanation for the variation in experience reported by our participants. Specifically, while some participants were active agents in their use of Instagram, others were less capable of commanding their experience. Thirdly, agentic practices were not necessarily stable; some participants were active in some areas of Instagram use and passive in others. Their engagement changed with context and mood, and their manner of Instagram use developed considerably over time. Finally, there were observable differences between usage patterns and agentic practices between the older and the younger participants. Our findings indicate that Instagram use is idiosyncratic, complex, and changeable, providing some explanation for why previous studies on the impact of Instagram on wellbeing have often been contradictory.

Abstract Background Illicit substance misuse is a growing public health problem, with misuse peaking among 18–25 year-olds, and attendance at third-level education identified as a risk factor. Illicit substance misuse has the potential to harm mental and physical health, social relationships, and impact on academic achievements and future career prospects. Digital interventions have been identified as a vehicle for reaching large student populations and circumventing the limited capacity of student health services for delivering face-to-face interventions. Digital interventions have been developed in the area of alcohol and tobacco harm reduction, reporting some effectiveness, but the evidence for the effectiveness of digital interventions targeting illicit substance misuse is lacking. This review aims to systematically identify and critically appraise studies examining the effectiveness of digital interventions for illicit substance misuse harm reduction in third-level students. Methods We systematically searched ten databases in April 2018 using keywords and database specific terms under the pillars of “mHealth,” “substance misuse,” and “student.” To be eligible for inclusion, papers had to present a measure of illicit substance misuse harm reduction. Included articles were critically appraised and included in the qualitative synthesis regardless of quality. Results A total of eight studies were included in the qualitative synthesis. Studies reported harm reduction in terms of substance misuse or initiation, as consequences or problems associated with substance misuse, or as correction of perceived social norms. Overall, five out of the eight studies reported at least one positive outcome for harm reduction. The critical appraisal indicated that the study quality was generally weak, predominantly due to a lack of blinding of study participants, and the use of self-reported substance misuse measures. However, results suggest that digital interventions may produce a modest reduction in harm from illicit substance misuse. Conclusions The results of this review are positive, and support the need for further high-quality research in this area, particularly given the success of digital interventions for alcohol and tobacco harm reduction. However, very few studies focused solely on illicit substances, and those that did targeted only marijuana. This suggests the need for further research on the effectiveness of this type of intervention for other illicit substances. Trial registration This review is registered on PROSPERO, ID number: CRD42018097203.

Standard mindfulness-based interventions have significant at-home assignments of formal mindfulness practice as a key component. Engagement with formal home practice has been correlated with treatment outcomes, but participants often complete less than the assigned amounts. Here, we explore the requirements for technology tools that can support and encourage home practice, in a way that is appropriate and consistent with the core principles of mindfulness-based interventions. Interviews were held with a group of five highly experienced mindfulness teachers and a group of five participants who had previously completed an eight-week course. Data was subjected to thematic analysis. A key finding was that providing teachers with information on how students practice could support communication around difficulties with home practice. We also identified questions around the appropriateness of adapting the course in response to participant difficulties and participant preferences. Both teachers and students made numerous suggestions for ways to augment their training using technology, such as via practice reminders and provision of teacher-specific content. Finally, a major design issue for technology developers is how to support participants in reflecting on their experiences of mindfulness practice, and subsequent learning, but not to critically evaluate their practice.

Objective The aim of this study is to review the evidence for tailored eHealth weight-loss interventions, describing in detail: 1. how tailoring was implemented in these studies and 2. whether these tailored approaches were effective in producing weight loss compared with generic or inactive controls. Methods A systematic review was carried out. Five databases were searched up until 15 March, 2018, including: EBSCO, Science Direct, Pubmed, EMBASE and Web of Science, using combinations of the concepts ‘tailoring’, ‘eHealth’ and ‘overweight’. Results Eight articles relating to six interventions were accepted. Tailoring was carried out in a number of ways, based on, for example, anthropometric data, health-related behaviours (e.g. dietary intake, physical activity), goals (e.g. weight goal), theoretical determinants (e.g. confidence/willingness to change behaviours), psychosocial factors (e.g. social support) and participant location. Systems acquired data using strategies that ranged from online questionnaire administration, to the dynamic gathering of data from web-based diaries, websites, mobile applications and SMS messaging. Tailored interventions were more effective in supporting weight loss than generic or waitlist controls in four of the six articles. Effect sizes were very small to moderate, with evidence for fluctuations in effect sizes and differences of effect between tailoring and non-tailoring interventions, and between tailoring types, over time. Conclusions We contribute an enhanced understanding of the variety of methods used for the tailoring of eHealth interventions for weight loss and propose a model for categorising tailoring approaches.