Interpreting fitness: self-tracking with fitness apps through a postphenomenology lens

Tendencies and characteristics of public fitness behavior in the digital era: an Internet ethnography study based on the K Community in China

Introduction

The deep integration of media technologies into fitness activities in the era of digital intelligence has created a new and evolving landscape for public fitness. This transformation significantly impacts the practices and experiences of fitness.

Methods

This study employs Internet ethnography as a qualitative research methodology, focusing on the daily activities of participants in a digital fitness community known as the K-community. Through immersive observation and analysis, the research seeks to uncover the evolving patterns and characteristics of fitness practices in China during the digital era.

Results

As media technology and network culture advance, participants in digital fitness increasingly display fragmented, digitized, entertaining, ritualized, and highly socialized behaviors. These traits reflect the community's desire for varied and complex exercise experiences within the context of modern technology.

Discussion

The evolution of fitness behavior not only reflects the operational principles of contemporary media technologies but also encapsulates the essence of popular culture in the digital age. This study enhances our comprehension of fitness practices in digital environments and their wider cultural ramifications.

Identifying Behavior Change Techniques in an Artificial Intelligence-Based Fitness App: A Content Analysis

In the field of artificial intelligence-based fitness apps, the effective integration of behavior change techniques (BCTs) is critical for promoting physical activity and improving health outcomes. However, the specific BCTs employed by apps and their impact on user engagement and behavior change are not explored sufficiently. This study investigates the Freeletics fitness app through a mixed-methods approach to evaluate the use of BCTs. In the quantitative analysis, fifteen unique BCTs were identified based on the Behavior Change Technique Taxonomy (V1). In the qualitative analysis, user reviews (n=400) were examined to understand perspectives on the app's effectiveness in promoting behavior change. Goal setting, action planning, self-monitoring of behavior, and social support were among the most prevalent BCTs identified in the Freeletics app, and their effectiveness in enhancing user engagement and promoting behavior change was also highlighted by user reviews. Among the areas of improvement identified in the study were the need for simplifying personalization options and addressing user concerns regarding the specificity of feedback. The study underscores the importance of integrating BCTs effectively within AI-based fitness apps to drive user engagement and facilitate behavior change. It contributes valuable insights into the design and implementation of BCTs in fitness apps and offers recommendations for developers, emphasizing the significance of goal setting, feedback mechanisms, self-monitoring, and social support. By understanding the impact of specific BCTs on user behavior and addressing user concerns, developers can create more effective fitness apps, ultimately promoting healthier lifestyles and positive behavior change.

Infusing behavior science into large language models for activity coaching

Large language models (LLMs) have shown promise for task-oriented dialogue across a range of domains. The use of LLMs in health and fitness coaching is under-explored. Behavior science frameworks such as COM-B, which conceptualizes behavior change in terms of capability (C), Opportunity (O) and Motivation (M), can be used to architect coaching interventions in a way that promotes sustained change. Here we aim to incorporate behavior science principles into an LLM using two knowledge infusion techniques: coach message priming (where exemplar coach responses are provided as context to the LLM), and dialogue re-ranking (where the COM-B category of the LLM output is matched to the inferred user need). Simulated conversations were conducted between the primed or unprimed LLM and a member of the research team, and then evaluated by 8 human raters. Ratings for the primed conversations were significantly higher in terms of empathy and actionability. The same raters also compared a single response generated by the unprimed, primed and re-ranked models, finding a significant uplift in actionability and empathy from the re-ranking technique. This is a proof of concept of how behavior science frameworks can be infused into automated conversational agents for a more principled coaching experience.

Crowdsourced cycling data applications to estimate noise pollution exposure during urban cycling

This research demonstrates a methodology to integrate freely available datasets to understand the relationship between road traffic noise and cycling experiences in a medium sized city. An illustrative example of the methodology was drawn from data for Dublin, Ireland. We aggregate local environmental data with 81,403 Strava cycle trips, contextualised by feedback from 335 cyclists to estimate exposure levels and infer impacts on experiences and behaviours. Results demonstrate that cyclists recognise that they are subjected to increased noise levels and experience negative psychophysical consequences as a result, but they tend to downplay the impact of noise as merely a minor annoyance. Noise also impacts behaviour, most noticeably through temporal and spatial detours. Geospatial mapping was used to visualise the relationship between noise pollution and cycling activity. Estimating traffic noise levels across two cycle routes, direct vs popular detour, revealed a +10 dB(A) increase in exposure for a saving of approximately 4 min on the direct route compared to the detour. Spatial inequities in exposure levels may have serious health consequences for cyclists in a city such as Dublin. The methodology is demonstrated as suitable for policy level interventions and planning purposes.

The multistability of predictive technology in nuclear disasters

Postphenomenological studies have explored technological mediation between the human body and the world by analysing the bodily experience of the world. Applying this analytical perspective to predictive technology requires some expansions because humans cannot directly experience the future world. I conceptualize pre-spectival focus, which refers to how human attention is directed to the making-future-present process, and which features or aspects of its process are foregrounded or backgrounded. Through the concept of pre-spectival focus and actor-network theory (ANT), this article examines the case of System for the Prediction of Environmental Emergency Dose Information (SPEEDI), a Japanese technology used to simulate the atmospheric dispersion of radionuclides released from nuclear reactors. SPEEDI provides prediction maps representing radiological consequences and was expected to support evacuation decisions during nuclear emergencies. However, this was not the case with the Fukushima disaster, which led to a socio-technical controversy regarding SPEEDI's usage. Based on bibliographic surveys and several interviews, I encapsulate four multistable uses of SPEEDI: prediction as supporting advice, prediction as a tool for evacuation drills, prediction as self-protection, and prediction as a source of misunderstanding. Relevant actors perceive the predictions of a nuclear disaster in each stability depending on the diversity of their pre-spectival foci, which is also related to the forms of life nourished through their professional and daily lives. A distinct rivalry can be observed between the two actor-networks around nuclear emergency management in which SPEEDI is differently enrolled: the social control network and self-determination network. In the former, the residents are constituted as passive selves who obediently follow governmental instructions; in the latter, residents are included as autonomous subjects who can actively decide protective actions. Moreover, I discuss future postphenomenology-ANT studies on predictive technologies based on these analyses.

The Effects of Adopting Mobile Health and Fitness Apps on Hospital Visits: Quasi-Experimental Study

BACKGROUND

Overcrowding in public hospitals, a common issue in many countries, leads to a range of negative outcomes, such as insufficient access to medical services and patient dissatisfaction. Prior literature regarding solutions to reducing hospital overcrowding primarily focuses on organizational-level operational efficiency. However, few studies have investigated the strategies from the individual patient perspective. Specifically, we considered using mobile health and fitness apps to promote users' health behaviors and produce health benefits, thereby reducing hospital visits.

OBJECTIVE

This study estimated the causal effect of health and fitness app adoption on hospital visits by exploiting the staggered timing of adoption. We also investigated how the effect varied with users' socioeconomic status and digital literacy. This study provides causal evidence for the effects of health apps, extends the digital health literature, and sheds light on mobile health policies.

METHODS

This study used a data set containing health and fitness app use and hospital-related geolocation data of 267,651 Chinese mobile phone users from January to December 2019. We used the difference-in-differences and difference-in-difference-in-differences designs to estimate the causal effect. We performed a sensitivity analysis to establish the robustness of the findings. We also conducted heterogeneity analyses based on the interactions of postadoption indicators with users' consumption levels, city tiers, and digital literacy.

RESULTS

The preferred model (difference-in-difference-in-differences) showed a significant decrease in hospital visits after the adoption of health and fitness apps. App adoption led to a 5.8% (P<.001), 13.1% (P<.001), and 18.4% reduction (P<.001) in hospital visits 1, 2, and 3 months after adoption, respectively. In addition, the moderation analysis shows that the effect is greater for users with high consumption levels, in high-tier cities, or with high digital literacy.

CONCLUSIONS

This study estimated the causal effect of health and fitness app adoption on hospital visits. The results and sensitivity analysis showed that app adoption can reduce users' hospital visits. The effect varies with users' consumption levels, city tiers, and digital literacy. These findings provide useful insights for multiple stakeholders in the Chinese health care context.

Explaining multistability: postphenomenology and affordances of technologies

A central issue in postphenomenology is how to explain the multistability of technologies: how can it be that specific technologies can be used for a wide variety of purposes (the “multi”), while not for all purposes (the “stability”)? For example, a table can be used for the purpose of sleeping, having dinner at, or even for staging a fencing match, but not for baking a cake. One explanation offered in the literature is that the (material) design of a technology puts constraints on the purposes for which technologies can be used. In this paper, I argue that such an explanation—while partly correct—fails to address the role of the environment in which human beings operate in putting constraints on technology use. I suggest that James Gibson’s affordance theory helps highlighting how stabilities in technology use arise in the interaction between human being and environment. Building on more recent approaches in affordance theory, I suggest that the environment can be conceptualized as a “rich landscape of affordances” that solicits certain actions, which are not just cued by the environment’s material structure, but also by the normativity present in the form of life in which a human being participates. I briefly contrast the approach to affordances developed in this paper with how Klenk (2020) and Tollon (2021) have conceptualized the “affordance character” of technological artifacts, and highlight how a focus on the situated nature of affordances augments these earlier conceptualizations.