Linking User Age and Stress in the Interruption Era: The Role of Computer Experience
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The workforce is rapidly growing older; especially the number of older workers (60 years and over) is increasing sharply. At the same time, the number of interruptions mediated by modern information technologies is growing rapidly. These interruptions include, for example, instant messages and email notifications. Recent research has shown that interruptions have harmful consequences for workers as they can lead to stress. Interruptions might be especially problematic for older workers, implying severe problems for this fast-growing group of users regarding their well-being and performance at work. This study proposes that older workers perceive more interruption-based technostress than their younger counterparts because of differences in computer experience between older and younger individuals. Thus, the study answers recent calls for exploring users’ age as a substantive variable in IS research, and it also contributes to the literature on technostress by demonstrating how technostress might affect certain groups of users more than others.
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.
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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.015 | 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 it