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      Exposure to digital marketing enhances young adults’ interest in energy drinks: An exploratory investigation

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      PLoS ONE

      Public Library of Science

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          Abstract

          Young adults experience faster weight gain and consume more unhealthy food than any other age groups. The impact of online food marketing on “digital native” young adults is unclear. This study examined the effects of online marketing on young adults’ consumption behaviours, using energy drinks as a case example. The elaboration likelihood model of persuasion was used as the theoretical basis. A pre-test post-test experimental research design was adopted using mixed-methods. Participants (aged 18–24) were randomly assigned to control or experimental groups ( N = 30 each). Experimental group participants’ attitudes towards and intended purchase and consumption of energy drinks were examined via surveys and semi-structured interviews after their exposure to two popular energy drink brands’ websites and social media sites (exposure time 8 minutes). Exposure to digital marketing contents of energy drinks improved the experimental group participants’ attitudes towards and purchase and consumption intention of energy drinks. This study indicates the influential power of unhealthy online marketing on cognitively mature young adults. This study draws public health attentions to young adults, who to date have been less of a focus of researchers but are influenced by online food advertising.

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          A power primer.

           Jacob Cohen (1992)
          One possible reason for the continued neglect of statistical power analysis in research in the behavioral sciences is the inaccessibility of or difficulty with the standard material. A convenient, although not comprehensive, presentation of required sample sizes is provided here. Effect-size indexes and conventional values for these are given for operationally defined small, medium, and large effects. The sample sizes necessary for .80 power to detect effects at these levels are tabled for eight standard statistical tests: (a) the difference between independent means, (b) the significance of a product-moment correlation, (c) the difference between independent rs, (d) the sign test, (e) the difference between independent proportions, (f) chi-square tests for goodness of fit and contingency tables, (g) one-way analysis of variance, and (h) the significance of a multiple or multiple partial correlation.
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            The qualitative content analysis process.

            This paper is a description of inductive and deductive content analysis. Content analysis is a method that may be used with either qualitative or quantitative data and in an inductive or deductive way. Qualitative content analysis is commonly used in nursing studies but little has been published on the analysis process and many research books generally only provide a short description of this method. When using content analysis, the aim was to build a model to describe the phenomenon in a conceptual form. Both inductive and deductive analysis processes are represented as three main phases: preparation, organizing and reporting. The preparation phase is similar in both approaches. The concepts are derived from the data in inductive content analysis. Deductive content analysis is used when the structure of analysis is operationalized on the basis of previous knowledge. Inductive content analysis is used in cases where there are no previous studies dealing with the phenomenon or when it is fragmented. A deductive approach is useful if the general aim was to test a previous theory in a different situation or to compare categories at different time periods.
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              Is verbatim transcription of interview data always necessary?

              Verbatim transcription of interview data has become a common data management strategy in nursing research and is widely considered to be integral to the analysis and interpretation of verbal data. As the benefits of verbal data are becoming more widely embraced in health care research, interviews are being increasingly used to collect information for a wide range of purposes. In addition to purely qualitative investigations, there has been a significant increase in the conduct of mixed-method inquiries. This article examines the issues surrounding the conduct of interviews in mixed-method research, with particular emphasis on the transcription and data analysis phases of data management. It also debates on the necessity to transcribe all audiorecorded interview data verbatim, particularly in relation to mixed-method investigations. Finally, it provides an alternative method to verbatim transcription of managing audiorecorded interview data.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                2 February 2017
                2017
                : 12
                : 2
                Affiliations
                Early Start Research Institute, School of Health and Society, Faculty of Social Sciences, University of Wollongong, Wollongong, New South Wales, Australia
                University of Cambridge, UNITED KINGDOM
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                • Conceptualization: LB BK HY.

                • Data curation: LB.

                • Formal analysis: LB.

                • Funding acquisition: LB.

                • Investigation: LB.

                • Methodology: LB BK HY.

                • Project administration: LB.

                • Resources: LB.

                • Software: LB.

                • Supervision: LB BK HY.

                • Validation: LB.

                • Visualization: LB BK.

                • Writing – original draft: LB.

                • Writing – review & editing: LB BK HY.

                Article
                PONE-D-16-37053
                10.1371/journal.pone.0171226
                5289551
                28152016
                © 2017 Buchanan et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Page count
                Figures: 1, Tables: 5, Pages: 16
                Product
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100001777, University of Wollongong;
                Award ID: Higher Degree Research (HDR) Fund
                Award Recipient :
                This work was supported in part by the Higher Degree Research (HDR) funding from the School of Health and Society, Faculty of Social Sciences, University of Wollongong.
                Categories
                Research Article
                Social Sciences
                Sociology
                Communications
                Marketing
                People and Places
                Population Groupings
                Age Groups
                Young Adults
                Biology and Life Sciences
                Nutrition
                Diet
                Beverages
                Medicine and Health Sciences
                Nutrition
                Diet
                Beverages
                Biology and Life Sciences
                Physiology
                Physiological Processes
                Food Consumption
                Medicine and Health Sciences
                Physiology
                Physiological Processes
                Food Consumption
                Social Sciences
                Sociology
                Communications
                Social Communication
                Social Media
                Computer and Information Sciences
                Network Analysis
                Social Networks
                Social Media
                Social Sciences
                Sociology
                Social Networks
                Social Media
                Social Sciences
                Sociology
                Communications
                Marketing
                Advertising
                Biology and Life Sciences
                Nutrition
                Diet
                Alcohol Consumption
                Medicine and Health Sciences
                Nutrition
                Diet
                Alcohol Consumption
                Computer and Information Sciences
                Computer Networks
                Internet
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

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