Techno(Stress) and Techno(Distress): Validation of a Specific TechnoStressors Index (TSI) Among Quebec Lawyers
Bibliographic record
Abstract
The pervasive and ubiquitous characteristics of information technology has been associated to technostress. Current measures oftechnostress do not consider some recent issues of the stress generated by technology in the day-to-day work of lawyers. This paper presents the validation of a 25-item self-report scale (TechnoStressors-Index-TSI) for the study of technostress in lawyers’ professional context. Items were constructed through qualitative exploratory interviews (N=22) and adaptation of existing scales. The scale was tested (N=40) and retested (N=2027) among Quebec lawyers using EFA and CFA. This scale proposes a second order reflexive model of five dimensions to understand technostress. The scale validation among a large sample of professionals helped to fulfill the gap regarding specific techno-stressors to which lawyers are exposed and leading to technostress at work or other health outcomes, such as psychological distress. For further research, it needs to be validated with other professionals to confirm its relevance in different contexts.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".