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Diabetic patient review helpfulness: unpacking online drug treatment reviews by text analytics and design science approach

Author

Listed:
  • Yi Feng

    (Sichuan University)

  • Yunqiang Yin

    (University of Electronic Science and Technology of China)

  • Dujuan Wang

    (Sichuan University)

  • Lalitha Dhamotharan

    (University of Exeter Business School)

  • Joshua Ignatius

    (Aston University)

  • Ajay Kumar

    (EMLYON Business School)

Abstract

The transparency of online reviews of drug treatment in patients with diabetes supports the use of text analytics to investigate review helpfulness based on the dual-process theory and design science approach. The first purpose of our study is to explore the influences of informational elements (emotions with the degrees of different arousal, review length) and normative elements (perceived effectiveness and ease of use, and patient satisfaction) in online drug treatment reviews on review helpfulness. We also examine the moderate role of review length on the relationship between patient satisfaction and review helpfulness. The second purpose is to explore the influences of the review topics on review helpfulness. Our study reveals four essential findings. First, not all emotions significantly influence review helpfulness, and only low-arousal emotions have a significant positive influence on review helpfulness. Second, an inverted U-shaped relationship between review length and review helpfulness and a U-shaped relationship between patient satisfaction and review helpfulness are confirmed. Third, review length has a moderate influence on the inverted U-shaped relationship between patient satisfaction and review helpfulness. Finally, the review topics related to blood sugar, family medical history, dosing time and injection significantly influence review helpfulness. These findings may serve as a stepping stone for future research on review helpfulness in the healthcare context, offering guidance for patients with diabetes, design implications for platform providers, and drug improvement suggestions for pharmaceutical companies.

Suggested Citation

  • Yi Feng & Yunqiang Yin & Dujuan Wang & Lalitha Dhamotharan & Joshua Ignatius & Ajay Kumar, 2023. "Diabetic patient review helpfulness: unpacking online drug treatment reviews by text analytics and design science approach," Annals of Operations Research, Springer, vol. 328(1), pages 387-418, September.
    • Handle: RePEc:spr:annopr:v:328:y:2023:i:1:d:10.1007_s10479-022-05121-4
    DOI: 10.1007/s10479-022-05121-4
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    References listed on IDEAS

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