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Views About Perceived Training Needs of Health Care Professionals in Relation to Socially Assistive Robots: An International Online Survey Publisher Pubmed



Papadopoulos I1 ; Koulouglioti C2 ; Lazzarino R1 ; Ali S1 ; Wright S1 ; Martingarcia A3 ; Oterquintana C4 ; Kouta C5 ; Rousou E5 ; Papp K6 ; Krepinska R7 ; Tothova V8 ; Malliarou M9 ; Apostolara P10 Show All Authors
Authors
  1. Papadopoulos I1
  2. Koulouglioti C2
  3. Lazzarino R1
  4. Ali S1
  5. Wright S1
  6. Martingarcia A3
  7. Oterquintana C4
  8. Kouta C5
  9. Rousou E5
  10. Papp K6
  11. Krepinska R7
  12. Tothova V8
  13. Malliarou M9
  14. Apostolara P10
  15. Lesinskasawicka M11
  16. Nagorska M12
  17. Liskova M13
  18. Nortvedt L14
  19. Alpers LM15
  20. Bigletepangilinan S16
  21. Oconerrubiano MF17
  22. Chaisetsampun W18
  23. Wichit N18
  24. Ghassemi AE19
  25. Jafarjalal E20
  26. Zorba A21
  27. Kuckertwostheinrich A22
  28. Malla R23
  29. Toda T24
  30. Akman O25
  31. Ozturk C26
  32. Puvimanasinghe T27
  33. Ziaian T28
  34. Eldarregev O29
  35. Nissim S30

Source: Contemporary Nurse Published:2023


Abstract

Background: As Artificial Intelligence and social robots are increasingly used in health and social care, it is imperative to explore the training needs of the workforce, factoring in their cultural background. Objectives: Explore views on perceived training needs among professionals around the world and how these related to country cultures. Design: Cross-sectional, descriptive, mixed-methods international online survey. Methods: Descriptive statistical analysis explored the ranking across countries and relationships with three Hofstede cultural dimensions. Thematic analysis was conducted on the open-ended text responses. Results: A sample of N = 1284 participants from eighteen countries. Knowing the capabilities of the robots was ranked as the top training need across all participating countries and this was also reflected in the thematic analysis. Participants' culture, expressed through three Hofstede's dimensions, revealed statistically significant ranking differences. Conclusions: Future research should further explore other factors such as the level of digital maturity of the workplace. Impact Statement: Training needs of health and social care staff to use robotics are fast growing and preparation should factor in patient safety and be based on the principles of person- and culture-centred care. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.