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In employees’ favour or not?—The impact of virtual office platform on the work-life balances

ABSTRACT: Social mobility and physical restrictions imposed to contain the spread of the COVID-19 pandemic have posed a severe challenge to operate under conventional nine to five work practices in a physical office setting. As a coping strategy for the survival of business, economy, and livelihoods, certain organisations were compelled to transform to virtual office platforms. This was a sudden transformation of work practices and consequently, impacting with mixed outcomes on lifestyles of workers. Given that very limited studies have shed light into the context, this study contributes immensely to fill research gap. The main objective of this study is to identify the impact of the virtual office platform on work-life balance in the Sri Lankan context. The methodology adopted for this study is quantitative. An online questionnaire to collect data was primarily distributed to employees in the virtual platform. Analysis of this study is based on three regression models and results ascertain that both working and non-working environments have highly significant impact on the work-life balance, although non-working environment has a bigger influence on work balance (Gender and no of children). Findings are useful and unique, enabling both employers and employees to adopt a focused approach to maximize the potential of virtual platforms to enhance employee well-being so that mutual benefits can be materialized.

SUBMITTER: Rathnaweera D

PROVIDER: S-EPMC8604353 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:At present, many researchers see hope that artificial intelligence, machine learning in particular, will improve several aspects of the everyday life for individuals, cities and whole nations alike. For example, it has been speculated that the so-called machine learning could soon relieve employees of part of the duties, which may improve processes or help to find the most effective ways of performing tasks. Consequently, in the long run, it would help to enhance employees' work-life balance. Thus, workers' overall quality of life would improve, too. However, what would happen if machine learning as such were employed to try and find the ways of achieving work-life balance? This is why the authors of the paper decided to utilize a machine learning tool to search for the factors that influence the subjective feeling of one's work-life balance. The possible results could help to predict and prevent the occurrence of work-life imbalance in the future. In order to do so, the data provided by an exceptionally sizeable group of 800 employees was utilised; it was one of the largest sample groups in similar studies in Poland so far. Additionally, this was one of the first studies where so many employees had been analysed using an artificial neural network. In order to enable replicability of the study, the specific setup of the study and the description of the dataset are provided. Having analysed the data and having conducted several experiments, the correlations between some factors and work-life balance have indeed been identified: it has been found that the most significant was the relation between the feeling of balance and the actual working hours; shifting it resulted in the tool predicting the switch from balance to imbalance, and vice versa. Other factors that proved significant for the predicted WLB are the amount of free time a week the employee has for themselves, working at weekends only, being self-employed and the subjective assessment of one's financial status. In the study the dataset gets balanced, the most important features are selected with the selectKbest algorithm, an artificial neural network of 2 hidden layers with 50 and 25 neurons, ReLU and ADAM is constructed and trained on 90% of the dataset. In tests, it predicts WLB based on the prepared dataset and selected features with 81% accuracy.

Project description:BackgroundRegular participation in moderate-to-vigorous physical activity (MVPA) is related to decreased risk of morbidity and mortality. Among working populations, lack of MVPA may also be a risk factor for absenteeism and presenteeism. Both traditional workplace-based and web-based interventions have been suggested as being effective in promoting participation MVPA, health-related outcomes, and work-related productivity. However, several challenges limit their application in real world contexts. A 'blended' intervention approach combining the two intervention strategies is proposed to overcome these limitations. The proposed intervention aims to utilize the blended approach to increase participation in MVPA, health-related outcomes, and work productivity among inactive workers.MethodsThe study will comprise of a three-group cluster randomized controlled trial (cluster-RCT), comprising a three-month actual intervention and a nine-month behavioral follow-up period. The three groups will be: a web-based intervention group, a blended intervention group combining the web-based components with face-to-face workshops and posters, and a control group. Physically inactive office employees (N = 495) from 33 companies (i.e., clusters) will be recruited and randomly assigned to the three groups by cluster randomization. The intervention mapping (IM) framework will be used for selecting and applying effective health behavioral theories and behavioral change techniques (BCTs) to the development, implementation and assessment of the intervention, which will be personally tailored. The primary outcome variable will be objectively-measured MVPA using an accelerometer. Secondary outcomes will consist of indices of health including adiposity, blood pressure, blood sugar, blood lipids, self-reported depression, anxiety, stress, health-related quality of life and work-related variables including absenteeism and presenteeism.DiscussionThe proposed study adopts a robust blended intervention approach that is expected to overcome challenges in applying workplace-based and web-based interventions separately and yield larger effects in promoting MVPA participation, health-related outcomes and work productivity. Improvements in work productivity outcomes will be of particular interest to employers. If more effective, the new blended intervention has the potential to be implemented on a larger scale to benefit workplace populations.Trial registrationThe trial is prospectively registered at the ClinicalTrials.gov PRS (Trial ID: NCT04391270; Date of First Posted: May 18, 2020).

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In employees’ favour or not?—The impact of virtual office platform on the work-life balances

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