Procrastination on social media: predictors of types, triggers and acceptance of countermeasures
Authors: Alblwi, A., McAlaney, J., Al Thani, D.A.S., Phalp, K. and Ali, R.
Journal: Social Network Analysis and Mining
Volume: 11
Issue: 1
eISSN: 1869-5469
ISSN: 1869-5450
DOI: 10.1007/s13278-021-00727-1
Abstract:Procrastination refers to the voluntary delay of urgent tasks and can have several negative consequences such as stress, health issues and academic under-achievement. Several factors including personality, culture and gender have been identified as predictors of procrastination, although there are some conflicting findings within the literature. Social networking sites have been identified as a possible facilitator of procrastination, in part due to their design features that encourage immersion and continual interaction. However, social networking sites also provide the opportunity for intelligent, real-time prevention and intervention strategies to be delivered that can reduce the experience of procrastination. In this paper, we build upon our research in which we used a mixed-method approach to explore the types, triggers and acceptance of countermeasures for procrastination on social media. Following a survey of 288 participants from the UK (n = 165) and the Kingdom of Saudi Arabia (n = 123), we conducted a series of multiple regression and binary logistic regression models to determine predictors of these factors. Several predictors such as self-control and conscientiousness were found to be significant predictors, but overall, the amount of variance explained by the regression models was relatively low. The results demonstrate that participants are receptive to countermeasures for procrastination being delivered through social networking sites but suggest that the predictors of procrastination related phenomena experienced in social networking sites are different than in offline settings.
https://eprints.bournemouth.ac.uk/35210/
Source: Scopus
Procrastination on social media: predictors of types, triggers and acceptance of countermeasures
Authors: Alblwi, A., McAlaney, J., Al Thani, D.A.S., Phalp, K. and Ali, R.
Journal: SOCIAL NETWORK ANALYSIS AND MINING
Volume: 11
Issue: 1
eISSN: 1869-5469
ISSN: 1869-5450
DOI: 10.1007/s13278-021-00727-1
https://eprints.bournemouth.ac.uk/35210/
Source: Web of Science (Lite)
Procrastination on social media: predictors of types, triggers and acceptance of countermeasures.
Authors: Alblwi, A., McAlaney, J., Thani, D.A.S.A., Phalp, K. and Ali, R.
Journal: Soc. Netw. Anal. Min.
Volume: 11
Pages: 19
DOI: 10.1007/s13278-021-00727-1
https://eprints.bournemouth.ac.uk/35210/
Source: DBLP
Procrastination on social media: predictors of types, triggers and acceptance of countermeasures
Authors: Alblwi, A., McAlaney, J., Al Thani, D.A.S., Phalp, K.T. and Ali, R.
Journal: Social Network Analysis and Mining
Volume: 11
Issue: 1
ISSN: 1869-5450
Abstract:© 2021, The Author(s). Procrastination refers to the voluntary delay of urgent tasks and can have several negative consequences such as stress, health issues and academic under-achievement. Several factors including personality, culture and gender have been identified as predictors of procrastination, although there are some conflicting findings within the literature. Social networking sites have been identified as a possible facilitator of procrastination, in part due to their design features that encourage immersion and continual interaction. However, social networking sites also provide the opportunity for intelligent, real-time prevention and intervention strategies to be delivered that can reduce the experience of procrastination. In this paper, we build upon our research in which we used a mixed-method approach to explore the types, triggers and acceptance of countermeasures for procrastination on social media. Following a survey of 288 participants from the UK (n = 165) and the Kingdom of Saudi Arabia (n = 123), we conducted a series of multiple regression and binary logistic regression models to determine predictors of these factors. Several predictors such as self-control and conscientiousness were found to be significant predictors, but overall, the amount of variance explained by the regression models was relatively low. The results demonstrate that participants are receptive to countermeasures for procrastination being delivered through social networking sites but suggest that the predictors of procrastination related phenomena experienced in social networking sites are different than in offline settings.
https://eprints.bournemouth.ac.uk/35210/
Source: BURO EPrints