Privacy Attitudes and Concerns in the Digital Lives of Older Adults: Westin’s Privacy Attitude Typology Revisited
Bibliographic record
Abstract
There is a growing literature on teenage and young adult users’ attitudes toward and concerns about online privacy, yet little is known about older adults and their unique experiences. As older adults join the digital world in growing numbers, we need to gain a better understanding of how they experience and navigate online privacy. This article fills this research gap by examining 40 in-depth interviews with older adults (65+ years) living in East York, Toronto. We found Westin’s typology to be a useful starting point for understanding privacy attitudes and concerns in this demographic. We expand Westin’s typology and distinguish five categories: fundamentalist, intense pragmatist, relaxed pragmatist, marginally concerned, and cynical expert. We find that older adults are not a homogenous group composed of privacy fundamentalists; rather, there is considerable variability in terms of their privacy attitudes, with only 13% being fundamentalists. We also identify a group of cynical experts who believe that online privacy breaches are inevitable. A large number of older adults are marginally concerned, as they see their online participation as limited and harmless. Older adults were also grouped as either intense or relaxed pragmatists. We find that some privacy concerns are shared by older adults across several categories, the most common being spam, unauthorized access to personal information, and information misuse. We discuss theoretical implications based on the findings for our understanding of privacy in the context of older adults’ digital lives and discuss implications for offering training appropriate for enhancing privacy literacy in this age group.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.006 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".