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Building partnerships: a pilot study of stakeholders’ attitudes on technology disruption in behavioral health delivery and research

  • Original Research
  • Published:
Translational Behavioral Medicine

Abstract

Collaborations between scientists, care providers, and technology industry professionals are becoming more relevant for developing, testing, and implementing behavioral health technologies. As the need for such partnerships increases, it is important to understand stakeholders’ attitudes about their role in partnering for developing such technologies and how much do they expect technology to impact behavioral research and care. The aim of this study was to investigate how much technology disruption do stakeholders expect in healthcare, as well as their perceived contribution in partnering for developing behavioral health technologies. Stakeholders (N = 74) responded to an online convenience sampling survey. Over 89% of participants reported expecting that technology will bring at least a moderate amount of disruption in the current models of behavioral healthcare, with respondents with the most experience in digital health expecting the most disruption. As for their perception of each other’s role in partnering for developing behavioral health technologies, one group’s weakness was considered to be complemented by another group’s strength. Academics were perceived as having more theoretical and research expertise but being less technology-savvy, while industry professionals were considered to excel at technological and marketing activities. Providers were considered to have the most clinical and real-world healthcare industry expertise. Our results indicate that technology is expected to disrupt current healthcare models, while also highlighting the need for collaboration, as no single group was considered to have sufficient expertise and resources to develop successful, effective behavioral health technologies on its own. These results may contribute to a better understanding of how technology disruption is affecting behavioral healthcare from the standpoint of its key players, which may lead to better collaborative models of research and care delivery.

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References

  1. Nilsen, W., Kumar, S., Shar, A., et al. (2012). Advancing the science of mHealth. Journal of Health Communication, 17(Suppl 1), 5–10. doi:10.1080/10810730.2012.677394.

    Article  PubMed  Google Scholar 

  2. Marsch, L. A., & Gustafson, D. H. (2013). The role of technology in health care innovation: a commentary. Journal of Dual Diagnosis., 9, 101–103.

    Article  PubMed  Google Scholar 

  3. Mohr, D., Schueller, S., Riley, W., Brown, C. H., Cuijpers, P., Duan, N., et al. (2015). Trials of intervention principles: evaluation methods for evolving behavioral intervention technologies. Journal of Medical Internet Research., 17(7), e166.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Mohr, D. C., Burns, M. N., Schueller, S. M., Clarke, G., & Klinkman, M. (2013). Behavioral intervention technologies: evidence review and recommendations for future research in mental health. General Hospital Psychiatry., 35(4), 332–338.

    Article  PubMed  Google Scholar 

  5. Oh, H., Rizo, C., Enkin, M., & Jadad, A. (2005). What is eHealth (3): a systematic review of published definitions. Journal of Medical Internet Research., 7(1), e1.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Eckard, C., Asbury, C., Bolduc, B., et al. (2016). The integration of technology into treatment programs to aid in the reduction of chronic pain. Journal of Pain Management & Medicine., 2(3), 118.

    Google Scholar 

  7. Bakker D, Kazantzis N, Rickwood D, Rickard N. Mental health smartphone apps: review and evidence-based recommendations for future developments. Eysenbach G, ed. JMIR Mental Health. 2016;3(1):e7. doi:10.2196/mental.4984.

  8. Teyhen, D. S., Aldag, M., Edinborough, E., et al. (2014). Leveraging technology: creating and sustaining changes for health. Telemedicine and E-Health., 20, 835–849.

    Article  PubMed  Google Scholar 

  9. Wang, C. J., & Huang, A. T. (2012). Integrating technology into health care what will it take? JAMA-Journal of the American Medical Association., 307, 569–570.

    Google Scholar 

  10. Schueller, S. M., Munoz, R. F., & Mohr, D. C. (2013). Realizing the potential of behavioral intervention technologies. Current Directions in Psychological Science., 22(6), 478–483.

    Article  Google Scholar 

  11. Kumar, S., Nilsen, W. J., Abernethy, A., Atienza, A., Patrick, K., Pavel, M., et al. (2013). Mobile health technology evaluation: the mHealth evidence workshop. American Journal of Preventive Medicine., 45(2), 228–236.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Mohr, D. C., Cheung, K., Schueller, S. M., Hendricks, B. C., & Duan, N. (2013). Continuous evaluation of evolving behavioral intervention technologies. American Journal of Preventive Medicine., 45(4), 517–523. doi:10.1016/j.amepre.2013.06.006.

    Article  PubMed  Google Scholar 

  13. Riley, W. T., Glasgow, R. E., Etheredge, L., & Abernethy, A. P. (2013). Rapid, responsive, relevant (R3) research: a call for a rapid learning health research enterprise. Clinical Translational Medicine., 2(1), 10.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Estrin, D., & Sim, I. (2010). Health care delivery. Open mHealth architecture: an engine for health care innovation. Science, 330(6005), 759–760.

    Article  CAS  PubMed  Google Scholar 

  15. Williams, S., Yardley, L., & Wills, G. B. (2013). A qualitative case study of LifeGuide: users’ experiences of software for developing Internet-based behaviour change interventions. Health Informatics Journal, 19(1), 61–75.

    Article  PubMed  Google Scholar 

  16. Schueller SM, Begale M, Penedo FJ, Mohr DC. Purple: a modular system for developing and deploying behavioral intervention technologies. Eysenbach G, ed. J Med Internet Res. 2014; 16(7): e181.

  17. NSF: Smart and Connected Health (SCH) Available at https://www.nsf.gov/funding/pgm_summ.jsp?pims_id=504739. Accessibility verified on September 9 2016.

  18. NIH: CRADAs. Available at https://www.ott.nih.gov/cradas. Accessibility verified on September 9 2016.

  19. Fereday, J., & Muir-Cochrane, E. (2006). Demonstrating rigor using thematic analysis: a hybrid approach of inductive and deductive coding and theme development. International Journal of Qualitative Methods., 5(1), 80–92. doi:10.1177/160940690600500107.

    Article  Google Scholar 

  20. Booth, R. G. (2016). Informatics and nursing in a post-nursing informatics world: future directions for nurses in an automated, artificially intelligent. Social-Networked Healthcare Environment. Nursing Leadership., 28(4), 61–69.

    Article  PubMed  Google Scholar 

  21. Chowdhury B, D’Souza C, Sultana N. The use of emerging technology to improve the performance of health service delivery. Tencon 2009–2009 Ieee Region 10 Conference, Vols 1–4, 134−+.

  22. Posadzki P, Mastellos N, Ryan R, Gunn LH, Felix LM. Automated telephone communication systems for preventive healthcare and management of long-term conditions. Cochrane Database of Systematic Reviews(12). 2006; Artn Cd009921 doi: 10.1002/14651858.Cd009921.Pub2

  23. Gagnon, M. P., Desmartis, M., Labrecque, M., Car, J., & Pagliari, C. (2012). Systematic review of factors influencing the adoption of information and communication technologies by healthcare professionals. Journal of Medical Systems., 36(1), 241–277. doi:10.1007/s10916-010-9473-4.

    Article  PubMed  Google Scholar 

  24. Gagnon, M. P., Ngangue, P., Payne-Gagnon, J., & Desmartis, M. (2016). m-Health adoption by healthcare professionals: a systematic review. Journal of American Medical Informatics Association., 23(1), 212–220. doi:10.1093/jamia/ocv052.

    Article  Google Scholar 

  25. Ioannidis, J. P. (1998). Effect of the statistical significance of results on the time to completion and publication of randomized efficacy trials. Journal of the American Medical Association, 279(4), 281–286.

    Article  CAS  PubMed  Google Scholar 

  26. Pham, Q., Wiljer, D., & Cafazzo, J. A. (2016). Beyond the randomized controlled trial: a review of alternatives in mHealth clinical trial methods. JMIR Mhealth Uhealth., 4(3), e107. doi:10.2196/mhealth.5720.

    Article  PubMed  PubMed Central  Google Scholar 

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Correspondence to Frederick Muench Ph.D..

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Implications

Policy: Our findings have implications for research policy, shedding light on a topic that is becoming more and more relevant in the behavioral medicine field and catalyzing conversation on developing better collaborative models of research and care delivery.

Research: We believe our study has also has research implications, as understanding stakeholders’ attitudes towards technology, and the need for academia-industry partnerships when employing it in healthcare will contribute to a better understanding of how technology disruption is affecting the behavioral healthcare from the standpoint of its key players.

Practice: The study also has implications for practice, as it will spark debate on practice frameworks that can accommodate and benefit from technology disruption.

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Sucala, M., Nilsen, W. & Muench, F. Building partnerships: a pilot study of stakeholders’ attitudes on technology disruption in behavioral health delivery and research. Behav. Med. Pract. Policy Res. 7, 854–860 (2017). https://doi.org/10.1007/s13142-017-0498-9

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  • DOI: https://doi.org/10.1007/s13142-017-0498-9

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