Beyond the Debate on Promises and Risks in Digital Health: Analysing the Psychological Function of Wearable Devices
Bibliographic record
Abstract
In the past years, the recording and collection of physical and physiological data from the body through wearable devices has become an increasingly common health-related practice in contemporary Western societies. The rapid development of digital self-tracking technologies has given rise to the production of different scientific discourses. The analysis of 200 published articles has led to the definition of a continuum between “technophile-promises” and “technocritical-risks” representations. However, these representations include different views of corporeality and sociality. Beyond this debate, we propose an alternative theoretical framework that links corporeality and sociality. It interrogates the psychological function that wearable devices may take (or not) for subjects to which these “tools” are addressed. We argue that such psychological function must be embraced by taking into consideration of activity done by the users of these technologies, which engages meaning: It is not the device, but the user him/herself who is confronted to the interpretation of biometric data linked to his/her own body functions on the basis of concrete lived experience. Moreover, we discuss that the activity of users can only be analysed in the sociocultural context to which the associated practices relate (health, sports, play, medicalisation). The conclusion highlights the need to further study the appropriation process of new personal experimentation instruments as to better understand the potential collaborations, risks or resistances that users may develop.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.036 |
| Scholarly communication | 0.023 | 0.024 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".