I recently came across this article by Milou A Feijt, et. al., in the Journal of Medical Internet Research titled “Perceived Drivers and Barriers to the Adoption of eMental Health by Psychologists: The Construction of the Levels of Adoption of eMental Health Model”. Here I am summarizing this model for its relevance, and because such models are as scarce as they are needed. This is a splendid example of how researchers are delving into attitudes and factors driving and hindering clinician adoption of mentaltech.
The author defines eMental Health as “any delivery of mental and behavioral health services, including but not limited to therapy, consultation, and psycho-education, by a licensed practitioner to a client in a non-face-to-face setting through distance communication technologies such as the telephone, asynchronous email, synchronous chat, and videoconferencing .” My personal working definition is broader than this, thus my noting it so you are aware.
This research is critical as we see that “despite growing evidence for the effectiveness of these [eMental Health] services, their acceptance and use in clinical practice remains low”.
The Levels of Adoption of eMental Health (LAMH) Model, which this article introduces, provides a “structured representation of factors that influence the adoption of eMental Health”, and is based on Roger’s “diffusion of innovations” theory and interview research with 12 Dutch psychologists. The value of such models is that they provide a visual construct and checklist for experience development & adoption planning. When looking at this model, you see, on a horizontal axis, how it delineates 5 adoption levels from non-use and awareness of advantages (Level 1) to entrepreneurship and innovative use (Level 5). You also see, on a vertical axis, adoption factors inclusive of general characteristics, barriers, drivers and change requirements. This is definitely a model I will be integrating into my adoption segmentation work, and I wonder if this is as applicable to consumers as to clinicians, with some modification.
Insights from this article which resonated with other research I have read or executed myself, are that:
- drivers, uncovered, are beliefs and experiences that confirm personal and client benefits which include: a) treatment process acceleration, b) increase therapeutic relationship intimacy, c) new treatment possibilities, d) increased client self-reflection, e) greater access convenience & frequency, and f) increase emotional expression. It is not surprising that use experiences are also a driver of belief as to the adage, “seeing is believing”, and experiencing all the more so.
- barriers, uncovered, include: a) concerns about a lack of nonverbal cues which may lead to misunderstandings, b) inadequate dealing with crisis situations online, c) tech- and client-related disconnections, d) client misrepresentations, e) tech-infrastructure set-up & maintenance, f) licensure & jurisdiction complexities, g) lack of clear ethical guidelines, h) HIPAA privacy concerns, i) contextual factors related to sociocultural institutional productivity and cost pressures, related to training, scheduled, tool usability, etc., j) clinician tech-comfort (knowledge, experience & expertise), and k) anticipation of increased client demand and workload, along with digital channel engagement complexity.
- getting non-users to use eMental Health impacts their focus shift from barriers to advantages, transferring eMental Health from theory to personal advantageous perception. This gets at the importance of initial, and successful, trial of these services, where current levels of adoption suggest there is room for improvement here.
- the author’s key contribution in developing this model is that they take these factors and organize, even prioritize, them by stage of adoption, creating a more orderly way of thinking through their deployment in strategies and programs. You get to see the behaviors and mindsets, which when evident indicate which adoption level a clinician occupies. This also has the potential for identifying advanced adopters who are in a position to lead opinion for less advanced adopters.
- LAMH’s key application is that of gauging clinical readiness to accept eMental Health as well as to support organizational implementation decisions. It is further a good discussion and planning guide in the strategy development process.
This research definitely needs expansion for further validation, as well as project application, and it would be good to even have a think tank of researchers who help each other with further development as well as identification and integration of additional applicable models.
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