Perceived information and communication technology (ICT) demands on employee outcomes: The moderating effect of organizational ICT support.
Bibliographic record
Abstract
Although many employees are using more information communication technology (ICT) as part of their jobs, few studies have examined the impact of ICT on their well-being, and there is a lack of validated measures designed to assess the ICT factors that may impact employee well-being. Therefore, we developed and validated a measure of ICT demands and supports. Using Exploratory Structural Equation Modeling, we found support for 8 ICT demands (i.e., availability, communication, ICT control, ICT hassles, employee monitoring, learning, response expectations, and workload) and two facets of ICT support (personal assistance and resources/upgrades support). Jointly, the ICT demands were associated with increased strain, stress, and burnout and were still associated with stress and strain after controlling for demographics, job variables, and job demands. The two types of ICT support were associated with lower stress, strain, and burnout. Resources/upgrades support moderated the relationship between learning expectations and most strain outcomes and between ICT hassles and strain. Personal assistance support moderated the relationship between ICT hassles and strain.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".