Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Feb 3, 2019
Date Accepted: Aug 2, 2019
A need for Consensual Behavioral Intervention Technology Validation and Surveillance Paradigm
ABSTRACT
Background:
Changing health behaviors such as smoking, unhealthy diet, inactivity and alcohol abuse may have a greater impact on population health than any curative strategy. One of the suggested strategy is the use of Behavioral Intervention Technologies (BIT). They open up new opportunities in the area of prevention and therapy and begin to show benefits in durable change of health behaviors in patients or at-risk people. A consensual and international paradigm has been adopted by health authorities for drugs 50 years ago. It guides their development from research units to their authorization and surveillance. BITs’ generalization brings their upstream evaluation before being placed on the market and their downstream monitoring once on the market into question, particularly in view of the marketing information of the manufacturers, the scarcity and the methodological limits of the scientific studies on these tools.
Objective:
To register, characterize and categorize BITs’ validation and monitoring frameworks, in order to reach their underlying paradigm.
Methods:
We have conducted a narrative literature review using Medline, PsychInfo and Web of Science. Analysis criteria were: name, publication year, name of the creator, country, funding organization, health focus, target group, design (linear, iterative, evolutive and/or concurrent). The frameworks were then categorized based on (1) the translational research thanks to a linear continuum of steps that we called here Prototyping, Mechanisms, Concept, Evidence, Surveillance (P-MCES) steps and (2) the three paradigms that may have inspired the frameworks: biomedical, engineering and/or behavioral.
Results:
We identified 33 frameworks, 39% created in the 2010s. 45% involved the final user in an early and systematic way. 6% had a linear only sequence of their phases, 33% a linear and iterative structure, 39% added an evolutive structure and 18% frameworks also associated a parallel process. Only 7 covered the full P-MCES spectrum, 7 frameworks relied on the 3 paradigms.
Conclusions:
To date, 33 frameworks of BITs’ validation and surveillance coexist, without the predominance of one of them or a convergence to a consensual model. Their number has increased exponentially the three last decades. Two dangers are possible, an anarchic continuous development of BITs depending of companies, amalgaming health benefits and usability (user experience, data security, ergonomics) and limiting implementation to several countries, or the absence of clinical research before the access to market trusting bigdata analyses and self-regulation. The paper recommends the convergence to an international validation and surveillance framework based on specificities of BITs (not equivalent to medical devices) to guarantee their effectiveness and safety for users.
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