How Do Public Relations Practitioners Experience Technostress? Voices of PR Practitioners in a Hyperconnected World
Bibliographic record
Abstract
This research examined the lived experience of public relations (PR) practitioners who use Information and Communication Technologies (ICTs) such as smartphones and laptops for work purposes, not only during the regular work day but also after hours and on weekends. Through the voices of the practitioners themselves, experiences of stress, work-life balance, satisfaction, and other factors were studied. This research followed a critical approach focused on the hyperconnected, hypermodern society in which everything is socially accelerated. Research questions examined the experience of technostress of public relations practitioners, the strategies practitioners used to resist or emancipate themselves from the constant call of technology for work purposes, and what this means for PR practitioners and the practice of PR. Practitioner views on the right to disconnect were also probed and this research was able to gather reflections from practitioners on their experience of working during the COVID-19 pandemic. Mixed methods consisted of an online survey (N=123) with PR practitioners followed by interviews (N=25) with a sub-set of survey respondents. This study found that PR practitioners appreciated the flexibility that remote and hybrid forms of work have brought to the workplace. However, the range of strategies applied by practitioners to get relief or free themselves from the constant call of connection was limited in many cases. Practitioners felt better resourcing, better support and role modelling from senior leadership, stronger boundaries, as well as a shared understanding of what constituted a crisis needing communications support outside of regular working hours would support practitioners. These findings contribute to public relations scholarship by focusing on the voices of PR practitioners in Canada and the experiences they face with ICTs and their work.
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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 | 0.021 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.012 | 0.023 |
| Scholarly communication | 0.018 | 0.020 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".