Recentering responsible and explainable artificial intelligence research on patients: implications in perinatal psychiatry.

Meghan Reading Turchioe, Alison Hermann, Natalie C Benda
Author Information
  1. Meghan Reading Turchioe: School of Nursing, Columbia University School of Nursing, New York, NY, United States.
  2. Alison Hermann: Department of Psychiatry, Weill Cornell Medicine, New York, NY, United States.
  3. Natalie C Benda: School of Nursing, Columbia University School of Nursing, New York, NY, United States.

Abstract

In the setting of underdiagnosed and undertreated perinatal depression (PD), Artificial intelligence (AI) solutions are poised to help predict and treat PD. In the near future, perinatal patients may interact with AI during clinical decision-making, in their patient portals, or through AI-powered chatbots delivering psychotherapy. The increase in potential AI applications has led to discussions regarding responsible AI and explainable AI (XAI). Current discussions of RAI, however, are limited in their consideration of the patient as an active participant with AI. Therefore, we propose a patient-centered, rather than a patient-adjacent, approach to RAI and XAI, that identifies autonomy, beneficence, justice, trust, privacy, and transparency as core concepts to uphold for health professionals and patients. We present empirical evidence that these principles are strongly valued by patients. We further suggest possible design solutions that uphold these principles and acknowledge the pressing need for further research about practical applications to uphold these principles.

Keywords

References

  1. J Am Med Inform Assoc. 2020 Apr 1;27(4):592-600 [PMID: 32106285]
  2. Dev Psychopathol. 2001 Summer;13(3):629-52 [PMID: 11523852]
  3. J Midwifery Womens Health. 2023 Jul-Aug;68(4):480-489 [PMID: 36734375]
  4. Infant Behav Dev. 2017 Nov;49:120-128 [PMID: 28886563]
  5. Brief Bioinform. 2021 Sep 2;22(5): [PMID: 33406530]
  6. Minds Mach (Dordr). 2018;28(4):689-707 [PMID: 30930541]
  7. Soc Sci Med. 2022 Mar;296:114782 [PMID: 35152047]
  8. Digit Health. 2023 Jul 6;9:20552076231186064 [PMID: 37434728]
  9. J Affect Disord. 2022 Jul 15;309:350-357 [PMID: 35460742]
  10. Curr Psychiatry Rep. 2022 Sep;24(9):419-429 [PMID: 35870062]
  11. J Am Med Inform Assoc. 2021 Dec 28;29(1):207-212 [PMID: 34725693]
  12. JAMA. 2019 Feb 12;321(6):580-587 [PMID: 30747971]
  13. Sci Eng Ethics. 2020 Aug;26(4):2141-2168 [PMID: 31828533]
  14. J Biomed Inform. 2021 Jan;113:103655 [PMID: 33309898]
  15. BMJ Open. 2022 Apr 27;12(4):e059033 [PMID: 35477874]
  16. Obstet Gynecol. 2015 Nov;126(5):1048-1058 [PMID: 26444130]
  17. Curr Opin Obstet Gynecol. 2019 Apr;31(2):116-119 [PMID: 30694850]
  18. Sci Eng Ethics. 2022 May 31;28(3):26 [PMID: 35639210]
  19. JMIR Ment Health. 2021 Nov 24;8(11):e29838 [PMID: 34822337]
  20. AMA J Ethics. 2019 Feb 1;21(2):E125-130 [PMID: 30794121]
  21. NPJ Digit Med. 2019 Jun 14;2:53 [PMID: 31304399]
  22. Br J Psychiatry. 2002 Jun;180:502-8 [PMID: 12042228]
  23. J Med Internet Res. 2020 Jul 13;22(7):e16021 [PMID: 32673216]
  24. JAMA Netw Open. 2022 May 2;5(5):e2210309 [PMID: 35507346]
  25. J Am Med Inform Assoc. 2020 May 1;27(5):677-689 [PMID: 31999316]
  26. J Psychiatr Res. 2020 Nov;130:35-40 [PMID: 32771679]
  27. Obstet Gynecol. 2016 Dec;128(6):1233-1240 [PMID: 27824771]
  28. Obstet Gynecol. 2000 Apr;95(4):487-90 [PMID: 10725477]
  29. BMC Med Inform Decis Mak. 2020 Nov 30;20(1):310 [PMID: 33256715]
  30. Birth. 2006 Dec;33(4):323-31 [PMID: 17150072]
  31. PLoS One. 2024 Aug 28;19(8):e0309161 [PMID: 39197051]
  32. Sensors (Basel). 2023 Jan 05;23(2): [PMID: 36679430]
  33. J Affect Disord. 2021 Jan 15;279:1-8 [PMID: 33035748]
  34. JAMA. 2019 Feb 12;321(6):588-601 [PMID: 30747970]
  35. JMIR Pediatr Parent. 2022 Feb 10;5(1):e30941 [PMID: 35142618]
  36. NPJ Digit Med. 2021 Sep 21;4(1):140 [PMID: 34548621]
  37. JMIR Ment Health. 2017 Jun 06;4(2):e19 [PMID: 28588005]
  38. Inf Syst Front. 2023 Jun 5;:1-6 [PMID: 37361886]
  39. J Dev Behav Pediatr. 1995 Dec;16(6):391-6 [PMID: 8746547]
  40. JAMIA Open. 2021 Nov 12;4(4):ooab092 [PMID: 34805776]
  41. Am J Obstet Gynecol. 2019 Nov;221(5):489.e1-489.e9 [PMID: 31173749]
  42. Arch Gen Psychiatry. 2010 Oct;67(10):1012-24 [PMID: 20921117]
  43. Nature. 2019 Oct;574(7780):608-609 [PMID: 31664201]
  44. J Am Med Inform Assoc. 2017 May 01;24(3):520-528 [PMID: 28040686]
  45. Am J Epidemiol. 2003 Jan 1;157(1):14-24 [PMID: 12505886]
  46. J Pers Med. 2021 Mar 12;11(3): [PMID: 33809177]
  47. PLoS One. 2013;8(2):e57447 [PMID: 23451231]
  48. JAMIA Open. 2023 Jul 08;6(3):ooad048 [PMID: 37425486]
  49. Obstet Gynecol. 2005 Nov;106(5 Pt 1):1071-83 [PMID: 16260528]
  50. Eur J Clin Nutr. 2003 Feb;57(2):266-72 [PMID: 12571658]
  51. Am J Bioeth. 2023 Jan;23(1):4-6 [PMID: 36269302]
  52. J Perinat Neonatal Nurs. 2019 Apr/Jun;33(2):108-115 [PMID: 31021935]
  53. Artif Intell Med. 2023 Sep;143:102616 [PMID: 37673561]
  54. Curr Opin Psychiatry. 2009 Nov;22(6):601-6 [PMID: 19734786]
  55. J Midwifery Womens Health. 2002 Sep-Oct;47(5):331-6 [PMID: 12361344]
  56. Artif Intell Med. 2020 Jan;102:101753 [PMID: 31980092]

Grants

  1. R00 MD015781/NIMHD NIH HHS
  2. R00 NR019124/NINR NIH HHS
  3. R41 MH124581/NIMH NIH HHS

Word Cloud

Created with Highcharts 10.0.0AIperinatalintelligencepatientspatientexplainableupholdprinciplesPDsolutionsapplicationsdiscussionsresponsibleXAIRAIresearchartificialpsychiatrysettingunderdiagnosedundertreateddepressionArtificialpoisedhelppredicttreatnearfuturemayinteractclinicaldecision-makingportalsAI-poweredchatbotsdeliveringpsychotherapyincreasepotentialledregardingCurrenthoweverlimitedconsiderationactiveparticipantThereforeproposepatient-centeredratherpatient-adjacentapproachidentifiesautonomybeneficencejusticetrustprivacytransparencycoreconceptshealthprofessionalspresentempiricalevidencestronglyvaluedsuggestpossibledesignacknowledgepressingneedpracticalRecenteringpatients:implicationsbioethicscenteredcare

Similar Articles

Cited By