When Technologies are Not Enough: The Challenges of Digital Interventions to Address Loneliness in Later Life
Bibliographic record
Abstract
This article discusses sociotechnical challenges of technology-based interventions to address loneliness in later life. We bring together participatory and multidisciplinary research conducted in Canada and Australia to explore the limits of digital technologies to help tackle loneliness among frail older people (aged 65+). Drawing on three case studies, we focus on instances when technology-based interventions, such as communication apps, were limiting or failed, seeming to enhance rather than lessen loneliness. We also unpack instances where the technologies being considered did not match participants’ social needs and expectations, preventing adoption, use, and the intended outcomes. To better grasp the negative unintended consequences of these technological interventions, we combine a relational sociological approach to loneliness with the Strong Structuration Theory developed by sociologist Rob Stones. This combined lens highlights the connection between sociotechnical factors and their agentic and structural contexts, facilitating a rich understanding of why and when technologies fail and limit.
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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 | 0.024 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".