Computers, cell phones, and social media. How after-hours communication impacts work-life balance and job satisfaction
Bibliographic record
Abstract
Abstract The purpose of this study was to test for correlation of after-hours work communication on work-life balance and job satisfaction. The correlation results did not conform to the expectations derived from the literature. Thus, we used follow-up qualitative interviews to understand why the study-participants did not experience a reduction in work-life balance or job satisfaction. Results of the correlations showed a weak positive correlation between after-hours communication via computer and cellphone with work-life balance and job satisfaction. Follow-up interviews showed that participants enjoyed the flexibility afforded by after-hours work communication that contributed to positive work satisfaction and greater balance of work and family. Work after-hours was not viewed as added work, but as an opportunity for flexibility, with a greater focus on family. Recent research confirms this development. Findings imply an organizational need for flexibility to further ensure work-life balance and job satisfaction in light of technological advancements. Key Words: After-Hours Communication, Facebook, Computer-Assisted Communication, Working From Home, Work-Life Balance, Job Satisfaction, Flexibility. Authors’ Bio * Arian T. Moore, Ph.D., serves as an adjunct professor for a number of universities teaching leadership and communication courses. She currently teaches the Leadership and Communication course at Ottawa University and Organizational Communication at Indiana Wesleyan University. She is Editor-in-Chief of Bibs & Business Magazine, a magazine providing resources for working mothers on work life balance. She holds a Ph.D. in Organizational Leadership from Regent University. ** Kathleen Patterson, Ph.D. is a Professor and the Director of the Doctor of Strategic Leadership program in the School of Business & Leadership at Regent University, Virginia Beach, Virginia, U.S.A. She is noted as an expert on servant leadership, and coordinates an annual Servant Leadership Research Roundtable in Virginia Beach, and has co-coordinated three Global Servant Leadership Research Roundtables, in the Netherlands, Australia, and Iceland. *** Bruce Winston Ph.D. is a Professor of Business and Leadership with the School of Business and Leadership at Regent University, Virginia Beach, Virginia, U.S.A. He is the Director of Regent’s PhD in Organizational Leadership Program. ****James A. (Andy) Wood, Jr., Ph.D. is an adjunct professor of Organizational Leadership at Regent University, Virginia Beach, Virginia, U.S.A., as well as a professional leadership coach and consultant. He holds a Ph.D. in Organizational Leadership from Regent University. JCMR Journal of Communication and Media Research, Vol. 11, No. 2, October 2019, pp. 1 - 14
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".