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      Intrapreneurship and technological innovation in optimizing qualitative research as evidenced at Infectious Diseases Institute, Uganda

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          Abstract

          Background

          Discrepancies between what is transcribed and the actual interview recordings were noticed in qualitative research reports. This study aimed at the development of a new transcription software (Jiegnote), and the evaluation of its effectiveness in the optimization of the transcription process, to minimize transcription completion time, and errors in qualitative research.

          Methods

          The study was a mixed methods project implemented from September to November 2020. The qualitative aspect of the study was phenomenological in perspective whereas the quantitative consisted of a randomized controlled trial (RCT) with a parallel design.

          Results

          At the time of the study, the Jiegnote software was a working prototype. We enrolled a total of 26 participants; 14 participants had their data analyzed in the RCT part of the study, 13 participated in the in-depth interviews, and 22 in the answering of Semi Structured Questionnaires. Upon the execution of an independent t test, results showed that, there was no statistical significance between the intervention and control means. On considering the total average transcription completion time and the type of language in which an audio case was recorded, the effect size evaluation implied that the Jiegnote software had a small impact (Hedges' g = 0.413438) in reducing the total average time taken to translate and transcribe audio cases that were recorded in a local language (Luganda), and a large impact (Hedges' g = 1.190919) in reducing the total average time taken to transcribe audio cases that were recorded in a foreign language (English). On considering the total average number of transcription errors and the type of language in which an audio case is recorded, the effect size evaluation implied that the Jiegnote software had a small impact (Hedges' g = 0.213258) in reducing the total average time taken to translate and transcribe audio cases that were recorded in a local language (Luganda). This was further observed (Hedges' g = 0.039928) in the transcription of cases that were recorded in a foreign language (English). On considering the in-depth interview data outcomes, participants responded that the Jiegnote software media looping functions (algorithm) enabled them to accomplish their transcription tasks in a shorter time and with fewer errors compared to the traditional methods.

          Conclusion

          The study demonstrates utilities associated with intrapreneurship and technological innovation in an organization setting whereby, the Jiegnote technology that was developed by the researchers, had some impact on the optimization of the qualitative research value chain. This was observed through the effect size (impact) evaluations that were conducted to investigate the superiority of the Jiegnote software against the traditional transcription methods, in minimizing the average number of errors committed, and time taken to complete a transcription process.

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          Most cited references17

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          How to Construct a Mixed Methods Research Design

          This article provides researchers with knowledge of how to design a high quality mixed methods research study. To design a mixed study, researchers must understand and carefully consider each of the dimensions of mixed methods design, and always keep an eye on the issue of validity. We explain the seven major design dimensions: purpose, theoretical drive, timing (simultaneity and dependency), point of integration, typological versus interactive design approaches, planned versus emergent design, and design complexity. There also are multiple secondary dimensions that need to be considered during the design process. We explain ten secondary dimensions of design to be considered for each research study. We also provide two case studies showing how the mixed designs were constructed.
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            Randomised controlled trials - the gold standard for effectiveness research

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              T test as a parametric statistic

              Tae Kim (2015)
              In statistic tests, the probability distribution of the statistics is important. When samples are drawn from population N (µ, σ2) with a sample size of n, the distribution of the sample mean X̄ should be a normal distribution N (µ, σ2/n). Under the null hypothesis µ = µ0, the distribution of statistics z = X ¯ - µ 0 σ / n should be standardized as a normal distribution. When the variance of the population is not known, replacement with the sample variance s 2 is possible. In this case, the statistics X ¯ - µ 0 s / n follows a t distribution (n-1 degrees of freedom). An independent-group t test can be carried out for a comparison of means between two independent groups, with a paired t test for paired data. As the t test is a parametric test, samples should meet certain preconditions, such as normality, equal variances and independence.
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                Author and article information

                Contributors
                Mulkent90@gmail.com
                pkatumba@gmail.com
                Rp549@medschl.cam.ac.uk
                atwimukye@idi.co.ug
                bcastelnuovo@idi.co.ug
                ananvuma@idi.co.ug
                gakileng@gmail.com
                Journal
                J Innov Entrep
                J Innov Entrep
                Journal of Innovation and Entrepreneurship
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                2192-5372
                5 December 2021
                5 December 2021
                2021
                : 10
                : 1
                Affiliations
                [1 ]GRID grid.11194.3c, ISNI 0000 0004 0620 0548, Infectious Diseases Institute, ; Kampala, Uganda
                [2 ]GRID grid.11194.3c, ISNI 0000 0004 0620 0548, Makerere University, ; Kampala, Uganda
                Article
                188
                10.1186/s13731-021-00188-y
                8645294
                0569393e-af0c-41ac-aed3-2a39ec968b2e
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                Funding
                Funded by: Dr. Janneke Cox
                Funded by: Capacity Building Unit, Infectious Diseases Institute, Kampala, Uganda
                Categories
                Research
                Custom metadata
                © The Author(s) 2021

                intrapreneurship,technological innovation,qualitative research optimization,transcription and translation errors,business process reengineering

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