Data accompanying the research on Emotional user engagement of a food reporting game-based mobile app

Datacite citation style:
K. A. (Kadian) Davis-Owusu; Natalia Romero Herrera; S. (Sonja) van Oers; M. (Marian) de van der Schueren; T. (Tippi) de Bruin et. al. (2020): Data accompanying the research on Emotional user engagement of a food reporting game-based mobile app. Version 1. 4TU.ResearchData. dataset.
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The study aimed to investigate the long term impact of experiences in user engagement of a food reporting mobile game app. The study recruited 10 participants, with 8 being able to complete the study. The period consider at least 6 weeks of continuous use of the DigestInn application. A one year licence of the DigestInn mobile app was given for free to each participant. A mixed dataset was collected: Daily mood reporting: Experience Sampling Method [1] was used to sample daily participants' mood towards their experience using the application. Whatsapp [2] and the visual Pick-A-Mood tool [3] were used to prompt participants daily. Weekly user engagement reporting: a user engagement scale was used and adjusted for this purpose [4]. The survey was implemented in TypeForm [5]. The prompt/reminder was done through whatsapp via a visual summary of the mood reporting, based on Daily reconstruction method [6] 6 weeks interviews: individual interviews were conducted in person and via Skype. Focus group were conducted in the establishment of Arhnem-Nijmegen Applied Science University. In all cases visual prompts of food and mood reports were presented as probes [6] Raw data was processed for analysis. Coded transcripts: two students assistant and a code manager processed the transcripts using the software Atlas.ti [7] version 8.4.4. A coding scheme was initially developed, code manager trained the student assistant till a higher than .9 interrelated coder was achieved [8] Parsed json files: a json file containing the complete dataset of the complete study period was parsed to extract each participants food reports during. First the file was split in 8 files (one for each participant). A python program and a bash script were developed in Mac OSX to parse the json files into .csv files. In excel, .csv files were parsed by means of two Visual Basic macros to obtain a tabular view of the food reports per participant. [1] Larson, R., & Csikszentmihalyi, M. (2014). The experience sampling method. In Flow and the foundations of positive psychology (pp. 21-34). Springer, Dordrecht. [2] [3] Desmet, P., Vastenburg, M., and Romero, N. (2016) Mood measurement with Pick-A-Mood: review of current methods and design of a pictorial self-report scale. Journal Design Research, 14 (3), pp. 241-279 [4] O’Brien, H. L., Cairns, P., & Hall, M. (2018). A practical approach to measuring user engagement with the refined user engagement scale (UES) and new UES short form. International Journal of Human-Computer Studies, 112, 28-39 [5] [6] Kahneman, D., Krueger, A. B., Schkade, D. A., Schwarz, N., & Stone, A. A. (2004). A survey method for characterizing daily life experience: The day reconstruction method. Science, 306(5702), 1776-1780. [7] Atlas.ti [8] Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook. sage.
  • 2020-07-01 first online, published, posted
4TU.Centre for Research Data
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  • ZonMw, 40-44300-98-133
Arhnem-Nijmegen Applied Science University
TU Delft, Faculty of Industrial Design Engineering, Department Human-Centered Design


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