Unpacking public resistance to health Chatbots: a parallel mediation analysis.

Xiqian Zou, Yuxiang Na, Kaisheng Lai, Guan Liu
Author Information
  1. Xiqian Zou: School of Journalism and Communication, Tsinghua University, Beijing, China.
  2. Yuxiang Na: School of Journalism and Communication, Jinan University, Guangzhou, Guangdong, China.
  3. Kaisheng Lai: School of Journalism and Communication, Jinan University, Guangzhou, Guangdong, China.
  4. Guan Liu: Center for Computational Communication Studies, Jinan University, Guangzhou, Guangdong, China.

Abstract

Introduction: Despite the numerous potential benefits of health chatbots for personal health management, a substantial proportion of people oppose the use of such software applications. Building on the innovation resistance theory (IRT) and the prototype willingness model (PWM), this study investigated the functional barriers, psychological barriers, and negative prototype perception antecedents of individuals' resistance to health chatbots, as well as the rational and irrational psychological mechanisms underlying their linkages.
Methods: Data from 398 participants were used to construct a partial least squares structural equation model (PLS-SEM).
Results: Resistance intention mediated the relationship between functional barriers, psychological barriers, and resistance behavioral tendency, respectively. Furthermore, The relationship between negative prototype perceptions and resistance behavioral tendency was mediated by resistance intention and resistance willingness. Moreover, negative prototype perceptions were a more effective predictor of resistance behavioral tendency through resistance willingness than functional and psychological barriers.
Discussion: By investigating the role of irrational factors in health chatbot resistance, this study expands the scope of the IRT to explain the psychological mechanisms underlying individuals' resistance to health chatbots. Interventions to address people's resistance to health chatbots are discussed.

Keywords

References

  1. J Med Syst. 2019 Apr 4;43(5):135 [PMID: 30949846]
  2. Addict Behav. 2016 Sep;60:160-4 [PMID: 27155242]
  3. Health Educ Behav. 2007 Aug;34(4):686-99 [PMID: 16885507]
  4. JMIR Mhealth Uhealth. 2021 Aug 30;9(8):e26845 [PMID: 34459745]
  5. Pers Soc Psychol Bull. 2007 Oct;33(10):1380-91 [PMID: 17933734]
  6. JMIR Mhealth Uhealth. 2018 Aug 29;6(8):e172 [PMID: 30158101]
  7. Addict Behav. 2007 Sep;32(9):1753-68 [PMID: 17270356]
  8. J Med Internet Res. 2020 Jul 13;22(7):e16649 [PMID: 32673231]
  9. Lancet. 2020 May 16;395(10236):1579-1586 [PMID: 32416782]
  10. Int J Inf Manage. 2022 Apr;63:102468 [PMID: 36540570]
  11. Internet Interv. 2017 Oct 10;10:39-46 [PMID: 30135751]
  12. Digit Health. 2019 Aug 21;5:2055207619871808 [PMID: 31467682]
  13. Front Psychol. 2022 May 31;13:922503 [PMID: 35712132]
  14. NPJ Digit Med. 2019 Jun 14;2:53 [PMID: 31304399]
  15. Health Equity. 2018 Aug 01;2(1):174-181 [PMID: 30283865]
  16. BMC Med Inform Decis Mak. 2020 Jul 22;20(1):170 [PMID: 32698869]
  17. Int J Med Inform. 2014 Aug;83(8):559-71 [PMID: 24961820]
  18. Health Promot Perspect. 2014 Jul 12;4(1):46-53 [PMID: 25097836]
  19. J Med Internet Res. 2020 Aug 7;22(8):e17158 [PMID: 32763886]
  20. Comput Hum Behav Rep. 2020 Jan-Jul;1:100014 [PMID: 34235291]
  21. BMC Med Inform Decis Mak. 2020 Nov 30;20(1):310 [PMID: 33256715]
  22. J Appl Psychol. 2001 Feb;86(1):114-21 [PMID: 11302223]
  23. J Pediatr Psychol. 2005 Jun;30(4):305-18 [PMID: 15863428]
  24. J Med Internet Res. 2021 Jan 6;23(1):e19928 [PMID: 33404508]
  25. BMJ Open. 2023 Jan 4;13(1):e066322 [PMID: 36599634]
  26. Front Public Health. 2021 Feb 15;9:588590 [PMID: 33659232]
  27. Int J Med Inform. 2022 Sep;165:104827 [PMID: 35797921]
  28. Psychol Health Med. 2016;21(3):317-29 [PMID: 26075410]
  29. Front Psychol. 2024 Jan 24;14:1339782 [PMID: 38327504]
  30. Digit Health. 2022 Mar 30;8:20552076221090031 [PMID: 35381977]
  31. J Med Internet Res. 2021 Jun 22;23(6):e26771 [PMID: 34155984]
  32. J Med Internet Res. 2019 Apr 05;21(4):e12887 [PMID: 30950796]
  33. J Med Internet Res. 2018 Nov 19;20(11):e11032 [PMID: 30455169]
  34. Health Psychol Rev. 2016;10(1):1-24 [PMID: 26824678]
  35. Front Psychol. 2019 Aug 08;10:1823 [PMID: 31440187]
  36. BMC Public Health. 2019 May 14;19(1):559 [PMID: 31088446]
  37. J Med Internet Res. 2019 Oct 17;21(10):e14316 [PMID: 31625950]
  38. Addict Behav. 2007 Aug;32(8):1728-32 [PMID: 17223281]
  39. JMIR Form Res. 2022 Mar 23;6(3):e28750 [PMID: 35319465]
  40. Int J STD AIDS. 2023 Oct;34(11):809-816 [PMID: 37269292]
  41. J Appl Psychol. 2003 Oct;88(5):879-903 [PMID: 14516251]
  42. Front Psychol. 2024 Feb 07;15:1268549 [PMID: 38384353]
  43. Psychol Bull. 1959 Mar;56(2):81-105 [PMID: 13634291]
  44. J Med Internet Res. 2023 Feb 24;25:e40789 [PMID: 36826990]
  45. Br J Health Psychol. 2010 Sep;15(Pt 3):561-81 [PMID: 19857374]
  46. Inf Syst Front. 2022;24(6):2099-2122 [PMID: 35095331]
  47. Psychol Addict Behav. 2016 May;30(3):325-34 [PMID: 27099959]
  48. Psychol Addict Behav. 2003 Dec;17(4):312-23 [PMID: 14640827]
  49. J Pers Soc Psychol. 1995 Sep;69(3):505-17 [PMID: 7562392]
  50. Int J Environ Res Public Health. 2022 Aug 29;19(17): [PMID: 36078473]
  51. J Pers Soc Psychol. 1998 May;74(5):1164-80 [PMID: 9599437]
  52. Telemed J E Health. 2015 Oct;21(10):845-51 [PMID: 26348844]
  53. Br J Health Psychol. 2010 May;15(Pt 2):435-52 [PMID: 19769797]
  54. Expert Rev Med Devices. 2021 Dec;18(sup1):37-49 [PMID: 34872429]
  55. J Med Internet Res. 2019 May 09;21(5):e13216 [PMID: 31094356]

Word Cloud

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