PubMed Health⌕ Search

PubMed · 14768461

Mixed methods, mixed methodology health services research in practice.

Abstract

Mixed methods, mixed methodology research is a little documented but increasingly accepted approach employed to investigate organizational phenomena. The author presents a synthesis of literature that informed the decision to adopt a mixed methods, mixed methodology, dominantly naturalistic study approach to health services research in which she explored the process and organizational consequences of new artifact adoption in surgery. She describes the way whereby a collective case study involving five Australian hospitals yielded quantitative and qualitative data that were analyzed using inductive and/or deductive reasoning. She goes beyond the theoretical rational for employing a mixed methods, mixed methodology approach to present a summative conceptual model of the research process and describe the structural aspects of the dissertation in which the research was reported that should benefit researchers contemplating the value of such an approach.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

P Lynne Johnstone. 2004. Mixed methods, mixed methodology health services research in practice.. https://doi.org/10.1177/1049732303260610

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Probability estimation when some observations are grouped.

This paper considers the use of additional questions for decreasing survey non-response rates and an approach for estimating a probability based on the results obtained. In a survey, the respondents are asked to answer an original question and follow-up questions, where the answers for the follow-up questions are grouped answers for the original question. For example, respondents are asked to provide an exact number of incidents, but in cases of 'Do not know' or 'Refuse' responses, they are subsequently asked to pick an answer from a less specific categorical scale. The new estimator obtains smaller variance asymptotically and does not depend on a distribution family. This method is applied to income questions in a survey regarding injury prevention and behaviours. Another application is survey data on intimate partner violence, where some amendments were applied for incorporating post-stratification weights and for using non-random grouping. For additional illustration, an example of parameter estimation on artificially generated data is presented.

Data Collection↗