Designing for Sustained Motivation: A Review of Self-Determination Theory in Behaviour Change Technologies

Recent years have seen a surge in applications and technologies aimed at motivating users to achieve personal goals and improve their wellbeing. However, these often fail to promote long-term behaviour change, and sometimes even backfire. We consider how self-determination theory (SDT), a metatheory of human motivation and wellbeing, can help explain why such technologies fail, and how they may better help users internalise the motivation behind their goals and make enduring changes in their behaviour. In this work, we systematically reviewed 15 papers in the ACM Digital Library that apply SDT to the design of behaviour change technologies (BCTs). We identified 50 suggestions for design features in BCTs, grounded in SDT, that researchers have applied to enhance user motivation. However, we find that SDT is often leveraged to optimise engagement with the technology itself rather than with the targeted behaviour change per se. When interpreted through the lens of SDT, the implication is that BCTs may fail to cultivate sustained changes in behaviour, as users' motivation depends on their enjoyment of the intervention, which may wane over time. An underexplored opportunity remains for designers to leverage SDT to support users to internalise the ultimate goals and value of certain behaviour changes, enhancing their motivation to sustain these changes in the long term.Comment: Submitted to the Interacting with Computers (IwC) special issue on self-determination theory in HC

Third Party Tracking in the Mobile Ecosystem

Third party tracking allows companies to identify users and track their behaviour across multiple digital services. This paper presents an empirical study of the prevalence of third-party trackers on 959,000 apps from the US and UK Google Play stores. We find that most apps contain third party tracking, and the distribution of trackers is long-tailed with several highly dominant trackers accounting for a large portion of the coverage. The extent of tracking also differs between categories of apps; in particular, news apps and apps targeted at children appear to be amongst the worst in terms of the number of third party trackers associated with them. Third party tracking is also revealed to be a highly trans-national phenomenon, with many trackers operating in jurisdictions outside the EU. Based on these findings, we draw out some significant legal compliance challenges facing the tracking industry.Comment: Corrected missing company info (Linkedin owned by Microsoft). Figures for Microsoft and Linkedin re-calculated and added to Table

Computers as Bad Social Actors: Dark Patterns and Anti-Patterns in Interfaces that Act Socially

Technologies increasingly mimic human-like social behaviours. Beyond prototypical conversational agents like chatbots, this also applies to basic automated systems like app notifications or self-checkout machines that address or 'talk to' users in everyday situations. Whilst early evidence suggests social cues may enhance user experience, we lack a good understanding of when, and why, their use may be inappropriate. Building on a survey of English-speaking smartphone users (n=80), we conducted experience sampling, interview, and workshop studies (n=11) to elicit people's attitudes and preferences regarding how automated systems talk to them. We thematically analysed examples of phrasings/conduct participants disliked, the reasons they gave, and what they would prefer instead. One category of inappropriate behaviour we identified regards the use of social cues as tools for manipulation. We describe four unwanted tactics interfaces use: agents playing on users' emotions (e.g., guilt-tripping or coaxing them), being pushy, `mothering' users, or being passive-aggressive. Another category regards pragmatics: personal or situational factors that can make a seemingly friendly or helpful utterance come across as rude, tactless, or invasive. These include failing to account for relevant contextual particulars (e.g., embarrassing users in public); expressing obviously false personalised care; or treating a user in ways that they find inappropriate for the system's role or the nature of their relationship. We discuss these behaviours in terms of an emerging 'social' class of dark and anti-patterns. Drawing from participant recommendations, we offer suggestions for improving how interfaces treat people in interactions, including broader normative reflections on treating users respectfully.Comment: Accepted paper for the 2024 ACM SIGCHI Conference on Computer-Supported Cooperative Work & Social Computing (CSCW

Further Exploring Communal Technology Use in Smart Homes: Social Expectations

Device use in smart homes is becoming increasingly communal, requiring cohabitants to navigate a complex social and technological context. In this paper, we report findings from an exploratory survey grounded in our prior work on communal technology use in the home [4]. The findings highlight the importance of considering qualities of social relationships and technology in understanding expectations and intentions of communal technology use. We propose a design perspective of social expectations, and we suggest existing designs can be expanded using already available information such as location, and considering additional information, such as levels of trust and reliability.Comment: to appear in CHI '20 Extended Abstracts, April 25--30, 2020, Honolulu, HI, US

Self-Control in Cyberspace: Applying Dual Systems Theory to a Review of Digital Self-Control Tools

Many people struggle to control their use of digital devices. However, our understanding of the design mechanisms that support user self-control remains limited. In this paper, we make two contributions to HCI research in this space: first, we analyse 367 apps and browser extensions from the Google Play, Chrome Web, and Apple App stores to identify common core design features and intervention strategies afforded by current tools for digital self-control. Second, we adapt and apply an integrative dual systems model of self-regulation as a framework for organising and evaluating the design features found. Our analysis aims to help the design of better tools in two ways: (i) by identifying how, through a well-established model of self-regulation, current tools overlap and differ in how they support self-control; and (ii) by using the model to reveal underexplored cognitive mechanisms that could aid the design of new tools.Comment: 11.5 pages (excl. references), 6 figures, 1 tabl

“I finally felt i had the tools to control these urges”: empowering students to achieve their device use goals with the reduce digital distraction workshop

Digital self-control tools (DSCTs) help people control their time and attention on digital devices, using interventions like distraction blocking or usage tracking. Most studies of DSCTs’ effectiveness have focused on whether a single intervention reduces time spent on a single device. In reality, people may require combinations of DSCTs to achieve more subjective goals across multiple devices. We studied how DSCTs can address individual needs of university students (n = 280), using a workshop where students reflect on their goals before exploring relevant tools. At 1-3 month follow-ups, 95% of respondents still used at least one type of DSCT, typically applied across multiple devices, and there was substantial variation in the tool combinations chosen. We observed a large increase in self reported digital self-control, suggesting that providing a space to articulate goals and self-select appropriate DSCTs is a powerful way to support people who struggle to self-regulate digital device use

Hearing in Color: How Expectations Distort Perception of Skin Tone

Abstract from publication: Previous research has found that the perceived brightness of a face can be distorted by the social category of race. Thus, Levin & Banaji (2006) found in a US sample that faces of identical brightness were perceived to be lighter if they had stereotypical White American features than if they had Black American features. Here, we present two experiments conducted in Natal, Brazil, that extend this line of research. Experiment 1 tested if the brightness distortion effect would generalize to a Brazilian population. Experiment 2 tested if speech accent would have a similar effect on brightness perception. In Experiment 1, we found that the brightness distortion effect clearly replicated in the Brazilian sample: faces with Black racial features were perceived to be darker than faces with White racial features, even though their objective brightness was identical. In Experiment 2, we found that speech accent influenced brightness perception in a similar manner: faces were perceived to be darker when paired with an accent associated with low socio-economic status than when they were paired with an accent associated with high socio-economic status. Whereas racial concepts in Brazil are often claimed to be much more fluid compared to the US, our findings suggest that the populations are quite similar with respect to associations between facial features and skin tone. Our findings also demonstrate speech accent as an additional source of category-information that perceptual cognition can take into account when modelling the world

Self-Control in Cyberspace: Applying Dual Systems Theory to Digital Self-Control Tools

Supplementary materials for Lyngs, Lukoff, Slovak, Binns, Slack, Inzlicht, Van Kleek, and Shadbolt. 2019. Self-Control in Cyberspace: Applying Dual Systems Theory to a Review of Digital Self-Control Tools. In CHI Conference on Human Factors in Computing Systems Proceedings, https://doi.org/10.1145/3290605.3300361 To recreate the paper, click 'OSF Storage', 'Download as zip', open 'cog-design-space.Rproj' in RStudio, then open 'main.Rmd' and click the 'Knit' button. If you get an error, try reinstalling the package versions (as per October 8th 2020, where Ulrik Lyngs recompiled this paper) using the `renv` package (the file **renv.lock** notes which ones these are). To do this, install the `renv` package by running `remotes::install_github("rstudio/renv")` in an R console, followed by `renv::restore()`. (Documentation for the `renv` package is available at https://rstudio.github.io/renv/