Authors:
Maradona Gatara
and
Jason Cohen
Affiliation:
University of the Witwatersrand (WITS), South Africa
Keyword(s):
Mobile-Health, Community Health Worker, Information and Communication Technologies for
Development, Information and Communication Technologies for Community Health Workers, Healthcare
Service Delivery, Kenya, Task-Technology Fit, Use, User Performance.
Related
Ontology
Subjects/Areas/Topics:
Biomedical Engineering
;
Design and Development Methodologies for Healthcare IT
;
Distributed and Mobile Software Systems
;
Evaluation and Use of Healthcare IT
;
Health Engineering and Technology Applications
;
Health Information Systems
;
Mobile Technologies
;
Mobile Technologies for Healthcare Applications
;
Neural Rehabilitation
;
Neurotechnology, Electronics and Informatics
;
Software Engineering
Abstract:
Equipping Community Health Workers (CHWs) in resource-constrained settings with mobile-health or
‘mHealth’ tools has the potential to improve healthcare service delivery. mHealth tool functionality must
however match CHW task needs before these tools are likely to have any significant impacts on CHW
performance. This paper contributes by drawing on Task-Technology Fit theory to test the extent to which a
match between CHW tasks and mHealth technology characteristics influences the performance of 201
CHWs using an mHealth tool in the counties of Siaya, Nandi, and Kilifi in Kenya. Results showed that the
interaction of paired task and technology characteristics did not always impact mHealth tool use and user
performance in the manner expected. When mHealth tool functions matched the task interdependence and
information dependency needs of the CHWs then CHW performance increased but CHW performance
decreased for some CHWs when mHealth functionality for time criticality and mobility was
high.
Moreover, while information dependency had an independent positive effect on mHealth tool use, CHWs
came to depend less on the mHealth tool to support time criticality, interdependence, and mobility needs
when functional support was high. These findings have implications for the design and deployment of
mHealth tools.
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