Predicting the success of Twitter in healthcare A synthesis of perceived quality, usefulness and flow experience by healthcare professionals

PurposeThe purpose of this paper is to predict Twitter satisfaction by healthcare professionals through integrating constructs of Csikszentmihalyi’s flow theory, quality dimensions and usefulness.Design/methodology/approachSurvey responses of 108 physicians from a variety of specialisations in the U...

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Bibliographic Details
Published in:Online information review Vol. 42; no. 6; pp. 898 - 922
Main Author: Aboelmaged, Mohamed Gamal
Format: Journal Article
Language:English
Published: Bradford Emerald Group Publishing Limited 13.09.2018
Subjects:
Caregivers
Content analysis
Data Analysis
Digital media
Flow theory
Health care
Health services
Mass media
Mathematical models
Medical education
Medical personnel
Nurses
Patients
Personal health
Physicians
Professionals
Public health
Quality of service
Quality of service architectures
Research Methodology
Resistance
Responses
Satisfaction
Social acceptance
Social media
Social networks
Social research
Structural equation modeling
Success
Teaching Methods
Technology Acceptance Model
Traditions
Usefulness
User behavior
User generated content
User training
Vendors
Web 2.0
ISSN:1468-4527, 1468-4535
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Summary:PurposeThe purpose of this paper is to predict Twitter satisfaction by healthcare professionals through integrating constructs of Csikszentmihalyi’s flow theory, quality dimensions and usefulness.Design/methodology/approachSurvey responses of 108 physicians from a variety of specialisations in the United Arab Emirates have been validated and analysed by means of partial least squares-based structural equation modelling method using smartPLS software.FindingsService quality has emerged as the most influential quality dimension that positively impact flow state and perceived usefulness of Twitter, while information quality, surprisingly, does not show any effect. The findings also indicate that flow state plays a significant role in shaping physicians’ satisfaction with Twitter. The study also enhances our understanding concerning the effects of perceived usefulness on flow state and satisfaction.Research limitations/implicationsUnderstanding factors that influence Twitter satisfaction can help healthcare managers construct appropriate intervention strategies for maximising professional benefits of social media and minimising user resistance. This is important because top managers usually ratify traditional practices that are only of limited effect. Also, the findings help vendors to accentuate user’s concerns in addition to system functionalities in social media applications.Originality/valueThe paper is an early attempt to propose a model for social media success in a professional context in general and healthcare in particular. It also one of first studies that examine social media satisfaction through integrating contemporary information system success and acceptance models with flow theory.
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ISSN:1468-4527
1468-4535
DOI:10.1108/OIR-01-2017-0018