In 2003, Cummings et al. outlined in-depth review criteria for “5 A’s” of Health Behavior Change Treatment on the Internet (advise, assist, assess, anticipatory guidance, and arrange follow-up). The criteria were meant to identify the minimum requirements for a program to produce behavior change. Evers et al. suggested that online health behavior and disease management programs were pre-occupied with the results among early adopters without considering the needs of the majority who are not interested or willing to engate in online behavioral change programs. Evers is the co-president and CEO of Pro-Change Behavior Systems, Inc., a company focused on creating population health programs based on the Transtheoretical Model of Behavior Change (precontemplation, contemplation, preparation, action and maintenance). The company identifies cognitive/affective experiential processess (consciousness raising, dramatic relief, environmental regulation, self-reevaluation, and social liberation) and behavioral processes (self-liberation, counter conditioning, helping relationships, reinforcement management and stimulus control) as additional elements to successfully implement behavior change.
An alternative explanation is that the Transtheoretical Model is insufficient to promote behavior change among wider segements of a population. Haical Sajovic Haddad’s Amazon review of James Clear’s Atomic Habits highlights Clear’s three-layer concentric circle of behavior change (outcome change, process change and identity change). Clear also includes a four-step model for habit formation:
- A cue triggers a craving,
- The craving motivates a response,
- The response provides the reward,
- The reward satisfies the craving, and, ultimately, becomes associated with the cue
Clear’s focus on identity (most closely reated to “self-reevaluation” concept in Pro-Change’s cognitive/affective experiental processes) suggests that changing how we see ourselves is more important for initiating and sustaining behavior change than setting up a series of punishments and rewards. Deci and Ryan developed the self-determination theory (SDT), a framework that suggests that understanding the individual’s needs for competence, relatedness and autonomy are critical for understanding the what and why of goal pursuits. Interestingly, the theory suggests that extrinisic rewards (e.g., cash incentives) threaten an individual’s autonomy and decrease intrinsic motivation, reducing the likelihood than an individual will continue the behavior without the reward. Intrinsic motivation involves people freely engaging in activities that they find interesting, that provide novelty and optimal challenge. This approach echoes Csikszentmihalyi’s flow theory and its focus on internal motivation.
Empowering patients to make their own decisions about behaviors that support their new identity may be the first step in a SDT-centric process. Even if quitting smoking is an individual’s single most important new health behavior to adopt, if the individual does not choose to quit smoking on their own, they are unlikely to sustain that behavior. We in the healthcare system could help patients clarify their new identify and any associated behaviors linked to that identity. We could then highlight cues, triggers and rewards that may reinforce or diminish that new identity. Patients may also look to peers or loved ones to consider a new identity with its associated behaviors. SDT suggests we do not establish goals or enter games as many people struggle with converting an external motivation to an internal one. Although the decisions about choosing a behavior may be driven by a patient-healthcare worker interaction, the interaction could be mediated by different types of health information technology (synchronous or asynchronous communication, information-sharing about risks and benefits, or identifying patterns of behavior that support the new identity).
After choosing a behavior (or set of behaviors), healthcare providers might help the patient increase their competence by demonstrating a skill (e.g., tracking weights daily) over time. If a patient considers themself an ex-smoker, healthcare workers might help patients identify triggers and behaviors that support that new identity. As the patient’s skill increases, they may be encouraged to attempt more challenging skills to demonstrate a higher level of competence. Health information technology can provide tools that supports the patient’s behavior by tracking adherence to new skills without engaging a human who might be seen as judgmental or unsupportive. As patients gain profiency in maintaining a behavior, they may look for a new identity that requires different behaviors to achieve a different reward.
Finally, we in healthcare can help patients feel more connected with others as well as connected to projects larger than themselves. Patients may not be aware of disease-specific support groups that can help patients and caregivers realize they are not alone and help manage the condition (disclaimer: my current employer, UnitedHealth Group, recently purchased PatientsLikeMe, an online patient community portal). Some patients may be interested in contributing to research to help treat patients like them. Health information technology can facilitate these interactions in secure or open environments.
Healthcare and health information technology appear to be focused on Prochaska’s transtheoretical model of health behavior change. Although the model can be helpful in some instances, we have not been able to activate large groups of patients online to adopt and sustain new health behaviors with this paradigm. The Self-Determination Theory offers a different approach that uses autonomy, competence and connectedness to engage individuals in health behavior change. The model’s focus on intrinsic motivation may be the key to help entities using health information techology to reliably engage prospective patients and their caregivers.