The present study is structured as a thesis consisting of eleven chapters as shown in Figure 1.3. Given the design, research questions, and objectives of the study, the thesis is not structured as a typical monograph, and instead comprises an introductory chapter, a contextual background chapter, theoretical underpinnings and conceptual model development chapters, six empirical chapters within which methods and data analyses are embedded, and a conclusion chapter.
Figure 1.3. Structure of Thesis
In Chapter 2, the contextual background of this study is discussed. First, the existing literature on mHealth and CHW work in developing countries is reviewed. Second,
typical examples of mobile technology applications for healthcare are identified. Third, shortcomings in prior works in the areas of mHealth and community health work are identified. Fourth, several implications of these shortcomings are derived.
In Chapter 3, the quasi-experimental post-test (Harris, McGregor, Perencevich, Furino, Zhu, Peterson and Finkelstein, 2006) that was conducted to compare the performance of CHWs using an mHealth tool with those using a traditional paper-based system, is reported on. For analysis, the multi-variate techniques of ANCOVA and Sequential (Hierarchical) Regression (Brace et al., 2012) were used.
In Chapter 4, the theoretical underpinnings of the study are discussed. First, existing literature pertaining to the theory of TTF (Vessey, 1991; Vessey and Galleta, 1991;
Goodhue, 1992; Goodhue, 1994; Vessey, 1994; Goodhue and Thompson, 1995) is reviewed to inform the development of the study’s technology-to-performance chain model. In Chapter 5, the TPC conceptual model is described in detail and the links between the concepts of TTF, use, user performance, and precursors of use, are developed.
In Chapter 6, the adoption and use of the Fit as Matching perspective (Venkatraman, 1989, p. 430) to examine the ‘fit’ between the CHW task and mHealth tool characteristics (TTF) and its effects on use and user performance, is described. This ‘fit’ was operationalized as the product of corresponding (complementary) pairwise task and technology characteristics. To assess the impact of TTF, continuous moderator effects were modelled using the PLS-SEM product indicator approach to create interaction terms (Hair et al., 2014). In Chapter 7, the adoption and use of the Fit as Moderation perspective (Venkatraman, 1989, p. 424) to examine the ‘fit’ between the CHW task and mHealth tool characteristics (TTF) and its effects on use and user performance, is described. This ‘fit’ was operationalized as the cross-product interaction of all pairwise task and technology characteristics. To assess the impact of TTF, continuous moderator effects were also modelled using the PLS-SEM product indicator approach to create interaction terms (Hair et al., 2014). This Moderation ‘fit’ perspective was extended by examining TTF for non-linear effects on mHealth tool use and CHW performance, using Response Surface Methodology with Polynomial Regression (Edwards, 2002). In Chapter 8, the adoption and use of the Fit as Mediation perspective (Venkatraman, 1989, p. 428)
to examine the ‘fit’ between the CHW task and mHealth tool characteristics (TTF) and its effects on use and user performance, is described. This ‘fit’ was operationalized as a perceived intervening mechanism between antecedent CHW task and mHealth tool characteristics and consequent use and user performance outcomes. To assess the impact of TTF, PLS-SEM mediator analysis with bootstrapping was used (Hair et al., 2014, p.
219). In Chapter 9, the adoption and use of the Fit as Covariation perspective (Venkatraman, 1989, p. 435) to examine the ‘fit’ between the CHW task and mHealth tool characteristics (TTF) and its effects on use and user performance, is described. This
‘fit’ was operationalized as an observed pattern of co-aligned and internally consistent CHW task and mHealth tool characteristics. To assess the impact of TTF, PLS-SEM (Hair et al., 2014) was used to model ‘fit’ as a reflective first-order reflective second-order construct (Jarvis, Mackenzie and Podsakoff, 2003, p. 205).
In Chapter 10, the examination of the impacts of (1) mHealth tool use on CHW performance, (2) perceived TTF on mHealth tool use and CHW performance, and (3) precursors of use on mHealth tool use, including the use of PLS-SEM mediator analysis with bootstrapping (Hair et al., 2014), is described. In doing so, determinants of use and user performance in addition to TTF, were examined. In addition, the intervening role of use between precursors and user performance was considered.
In Chapter 11, the present study is concluded. A summary of the study is provided and limitations in research design are highlighted. Subsequently, study contributions to theory, methodology, practice, and context, are described, and implications for future research are derived.
A number of thesis chapters have already been published. The thesis publications are listed in Table 1.3. In all instances, the published papers have been re-formatted and updated for inclusion in this thesis.
Table 1.2. Thesis Publications Thesis
Component
Publication
Abstract Gatara (2013) ‘Mobile Technology-Enabled Healthcare Service Delivery Systems for Community Health Workers in Kenya: A Technology-to-Performance Chain Perspective’, Journal for Health Informatics in Africa (JHIA) vol.1, no. 1, pp. 179-180. This paper was also part of proceedings of the 8th Health Informatics in Health Informatics in Africa Conference (HELINA), Nairobi, Kenya).
5 Gatara, M. and Cohen, J.F (2015) Mobile Health Tool Use and Community Health Worker Performance: A Quasi-Experimental Post-Test Perspective, Journal for Health Informatics in Africa (JHIA), vol. 2, no.2, pp.
44-54. This paper was also part of proceedings of the 9th Health Informatics in Africa Conference (HELINA), Accra, Ghana.
6 Gatara, M. and Cohen, J.F (2015) ‘Matching Task and Technology Characteristics to Predict mHealth Tool Use and User Performance’, A Study of Community Health Workers in the Kenyan Context’, Proceedings of the 8th International Conference on Health Informatics (HEALTHINF), Lisbon, Portugal, pp. 454-461.
8 Gatara, M. and Cohen, J.F (2014) ‘The Mediating Effect of Task-Technology Fit on mHealth Tool Use and Community Health Worker Performance in the Kenyan Context’, Proceedings of the 8th International Development Informatics Association Conference, Port Elizabeth, South Africa, pp. 323-336.
9 Gatara, M. and Cohen, J.F. (2014) ‘Mobile-Health Tool Use and Community Health Worker Performance in the Kenyan Context: A Task-Technology Fit Perspective’, Proceedings of the Southern African Institute for Computer Scientists and Information Technologists (SAICSIT) Annual Conference 2014, Pretoria, South Africa, pp. 1-10.
6 to 9 Gatara, M. (2016) ‘Mobile Health Tool Use and Community Health Worker Performance in the Kenyan Context: A Comparison of Task-Technology Fit Perspectives, In mHealth Ecosystems and Social Networks in Healthcare, Lazakidou, A.A., Zimeras, S., Iliopoulou, D. and Koutsouris, D. [Eds.], Springer, pp. 55 – 78.