Transtheoretical Model Technology-based Interventions to Improve Health Behaviors in Veterans

Abstract

The Transtheoretical Model of Health Behavior Change (TTM) is a leading theoretical framework of motivation for healthful lifestyle modification and has been employed nationally and internationally within the civilian sector for decades. The TTM has demonstrated effectiveness in reducing the public health burden related to various chronic diseases that are largely preventable through successful health behavior change intervention. Because the VA healthcare system (VA) is committed to providing quality care to Veterans who, all too often, suffer from complex physical and psychological comorbidities, it is critical to reduce Veterans’ unhealthy behaviors while also helping them adopt and sustain adaptive health behaviors. TTM interventions are typically delivered remotely via computer or mobile devices using Expert Systems (ES) programs (TTM-ES). As such, TTM-ES offers the VA an opportunity to access a larger number of Veterans and provide a variety of care choices that can fit into their personal life context. While the VA already utilizes numerous computer- based behavior change applications for a variety of psychological and physical health conditions, the TTM-ES is comprised of unique characteristics that keeps it at the forefront of effective health behavior change interventions. TTM-ES, now referred to as computer tailored interventions (CTIs), are individually tailored for each Veteran, based on initial and ongoing assessment of their degree of motivation for change, and utilizes evidence- based algorithms to provide the Veteran with feedback to synergistically move them toward health behavior modification. Further development, testing, implementation and dissemination of the TTM framework and TTM-CTIs for Veterans are discussed.

Rationale for Transtheoretical Model-Based Interventions to Improve Health Behaviors in Veterans

Health promotion and chronic disease prevention strategies have been in place to improve individuals’ overall health through a targeted reduction in negative health behaviors at a population- based level since the late 1970s (Prochaska et al., 2012). Subsequently, the Transtheoretical Model of Health Behavior Change (TTM) was developed in the early 1980s to understand and modify risky health behaviors known to contribute to the development of chronic disease and premature mortality. In essence, there was a recognized need to develop effective interventions at a relatively low cost that could reach a significantly large number of people. Predicated on the premise that treatment efficacy can be increased by matching the treatment to the individual needs of the client, the task was to develop an intervention approach that had utility, was effective, and was cost-effective. Smoking cessation and physical inactivity were among the first unhealthy behaviors targeted for change to reduce the economic burden they exerted on the healthcare system (Velicer et al., 1993). In the following years, other behaviors have been targets of TTM-based interventions, e.g., improving diet quality, diabetes management, reducing excessive sun exposure, etc. (Di Noia & Prochaska, 2010; Partapsingh et al., 2011; Rodriguez et al., 2019; Santiago-Rivas et al., 2013; Wright et al., 2009; Xu et al., 2020).

Among the various unhealthy behaviors targeted by the TTM, smoking, alcohol and drug (ab)use, physical inactivity, and poor diet quality are all determinant factors in the development of chronic disease, premature mortality, and rising health care costs (Zhang et al., 2021; Prochaska et al., 2008). As a subgroup of the general population, Veterans often have multiple chronic conditions (in the context of poor general health) that put them at increased risk of developing additional medical problems and premature mortality (Jakovljevic et al., 2006; Lee et al., 2006). Thus, Veterans represent a remaining subpopulation that can benefit from TTM-based interventions promoting multiple health behavior change in these areas.

As an example, posttraumatic stress disorder (PTSD) is highly prevalent among combat Veterans, irrespective of combat theatre (Kok et al., 2012). Chronic pain is one common comorbidity of PTSD that often leads to increased levels of distress, interference in functioning and disability (Otis et al., 2003). Approximately 50% of Veterans endorse experiencing pain on a regular basis (Kerns & Dobscha, 2009), and between 34% and 50% of Veterans diagnosed with chronic pain also have significant symptoms of PTSD (Otis et al., 2010). Further, among combat-exposed Veterans, reports of pain are as high as 80% (Beckham et al., 1997; Shipherd et al., 2007).

Veterans with PTSD are at risk for developing additional medical conditions that extend beyond chronic musculoskeletal pain, such as unexplained somatic symptoms, cardiovascular disease, and gastrointestinal diseases--- all of which are predictors/correlates of premature mortality (Gupta, 2013; Boscarino, 2006). Further, associated risky behaviors include substance (i.e., tobacco, alcohol and other drugs) use and abuse, maladaptive eating behavior, and suicidal behavior (Sommer et al., 2020). Such risky behaviors contribute to additional morbidity and premature mortality (Prochaska & Velicer, 1997). Fortunately, these risky behaviors are modifiable lifestyle factors that can be reduced in response to appropriate, tailored and motivationally driven psychological intervention.

Based on over 30 years of TTM research in the civilian sector and in the absence of a TTM-based expert system (ES), which evolved to now being referred to as computer tailored intervention (CTI)¹ programs, for Veterans, the STR²IVE pilot program tested a TTM- CTI for Veterans with PTSD focused on smoking cessation, stress management and depression management (Jordan et al., 2011). The goal of this work was to develop a fully integrated, scalable, “multibehavioral system” to be disseminated online for Veterans who present with multiple health risks or health risk behaviors. As such, the combination of the TTM framework paired with the CTI (TTM-CTI) holds promise because it would allow VA healthcare to address large numbers of patients while not over burdening them or the VA healthcare system. Much of the published behavioral research is limited by an implicit assumption that all patients are ready for “action” when, in fact, they may be at different stages of readiness. This implicit assumption limits access to many individuals, and most likely, the majority who present with varying degrees of readiness upon receiving an intervention (Hellsten et al., 2008). The TTM-CTI addresses this limitation and has the potential to yield higher rates of participation for addressable health risk behaviors compared to the rates observed in “action- oriented” clinic- based treatments.

Importantly, TTM-CTI addresses the concept of “coaction” which is defined as the probability that taking “action” on one health behavior is related to taking action on another health behavior. Further, individuals who engage in coaction are likely to take effective action on untreated behaviors that are related to the targeted behaviors for treatment (Prochaska et al., 2008). In fact, the concept of coaction is “the most promising phenomenon of multiple behavior change” (Paiva et al., 2012). The TTM-CTI is effective at addressing multiple target behaviors without reducing the efficacy compared with treating one behavior at a time.

In the STR²IVE pilot study, a mixed method methodology approach was implemented, which included usability and feasibility testing, as part of a 3-phase trial for Veterans suffering from PTSD and depression. This study revealed the TTM CTIs were effective for producing clinically meaningful changes in PTSD, depression, smoking cessation and better stress management in Veteran samples. In addition, this study indicated that the TTM can intervene on treatment resistant behaviors (i.e., failing to present to appointments or dropping out of treatment prematurely). These behaviors are especially common among Veterans, particularly those with PTSD and/or chronic pain, and it can support patients prone to relapse such as those dealing with depression and PTSD (King et al., 2012; Levesque et al., 2011).

Although preliminary, the STR²IVE pilot study by Jordan et al. (2011) has laid the foundation from which we can now further develop, test and extend this work to Veterans who use VA healthcare. In fact, TTM-CTI can be accessible to all Veterans within the Veterans Health Administration (VHA), broadly, as well as to target specific subpopulations, e.g., those suffering from PTSD and common comorbidities. Due to the advanced nature of protective military equipment utilized in the most recent conflicts, returning Veterans survived physical injuries that would have been fatal in prior conflicts (Scioli et al., 2010). Such physical injuries increase the risk of the development of various chronic musculoskeletal pain conditions which likely contribute to the high co-prevalence rates of PTSD and chronic pain. As stated previously, because Veterans with comorbid PTSD and chronic pain report higher levels of distress as well as interference in functioning and disability than those with either condition by itself (Otis et al., 2003), TTM-CTI development can be extended to this population. Thus, the TTM-CTI can serve multiple purposes and apply to all Veterans who use VA services if they wish to improve their general health. As such, TTM-CTI can be implemented either as a stand- alone intervention or with subpopulations of Veterans with complex medical and psychiatric comorbidities as an integral component of their overall clinical treatment plan.

In summary, given the success of TTM-CTI initiatives in the general population with the promise of similar success in the Veteran population, the health field is now in an era of extending beyond the core definition of health towards promoting overall well-being. (Prochaska et al., 2012). This advanced health initiative is critical for all Veterans because decreasing risky behaviors while improving adaptive health behaviors, thereby improving overall quality of life, has important beneficial effects for the Veteran community as well as the entire VA healthcare system. Essentially, there is a great need for providers to help patients become more proactive and independent in their overall health management to optimize their overall recovery process, decrease provider burden, and lower health care utilization costs.

With the VA healthcare system’s adoption of the TTM framework of health behavior change, providers treating Veterans with complex comorbid conditions can interact with the TTM-CTI’s and serve as “change agents” to help Veterans work towards prevention and/or better management of their chronic health concerns and overall well-being through effective lifestyle modification (Hall et al., 2016; Ketola et al., 2000). Specifically, although CTI’s focus on coaction concepts and target unhealthful lifestyle behaviors to promote healthier behaviors, the provider, as an “agent of change”, can play a critical role within this context who can implement motivational interviewing techniques (defined below) to work with the patient to resolve ambivalence for change, reduce real and perceived barriers to change and facilitate solidification of the newly learned behavior change strategies. Taken together, this approach can help Veterans with complex comorbidities successfully adopt and sustain health behaviors to ultimately improve their overall well-being. Thus, it is the combination of the CTI interaction with patient and provider, who is skilled in motivational interviewing, that will create the necessary synergy toward lasting behavior change and promotion of overall well-being for Veterans with complex medical and psychiatric comorbidities (see figure 1).

Figure 1.

Heuristic Model of Individual TTM-ES Components Complementing Clinical Treatments for PTSD and Chronic Pain

Note. a) Patient and provider discuss the benefits of engaging with the TTM-ES framework to target relevant health behaviors. Provider gives the patient the link to access the TTM-ES system; b) After a brief orientation to the TTM model by the TTM-ES system, the patient completes a baseline assessment using the full TTM battery; c) Following the assessment and interactive intervention, based on the TTM constructs, TTM-ES system then generates an individualized, feedback report indicating which stage of change the patient falls into, and which processes of change the provider should include in the MI-driven intervention (TTM+MI); d) The patient and the provider work as a “team” as the provider implements the TTM+MI script. The focus is on resolving patient ambivalence about changing unhealthy behaviors while fostering intrinsic motivation to adopt healthy coping behaviors; e) The participant interacts with the TTM-ES system and the provider weekly until clinically meaningful changes in health behavior targets have occurred (i.e., progression through the stages of change toward Action and Maintenance utilizing the weekly TTM-ES feedback report and the provider-driven TTM+MI script); f) In sum, a positive progression through the stages of change results when more healthy coping behaviors are adopted via interaction with the TTM-ES system and provider, who implements the TTM+MI script. Changes indirectly and positively influence the patient’s chronic pain, depression and PTSD symptoms, and/or, (g) enhance readiness to engage evidenced based therapies that directly target chronic pain, depression and PTSD symptoms; h) The TTM+MI script can be delivered by the therapist implementing the evidenced based therapy or by an interventionist who communicates regularly with the provider on how the patient is progressing with their health behavior changes; and i) motivational interviewing can indirectly benefit clinical treatment engagement

In this paper, we recommend an approach that includes further developing, validating, evaluating and implementing TTM-CTIs broadly, to reduce negative health behaviors while improving adaptive health behaviors among all Veterans within VHA. We also propose an approach of using the TTM-CTI as an integral component of the treatment plan for Veterans with complex medical and psychiatric conditions, such as chronic pain and PTSD. Extrapolating from studies conducted in five health behaviors (i.e., physical activity, smoking cessation, alcohol and substance abuse prevention, nutrition and stress management), we posit that TTM-CTIs will benefit: 1) all Veterans directly via increased care options and decreased barriers to care, such as time and travel costs, 2) providers by reducing their direct-service burden, and 3) the VA healthcare system by reducing the costs of caring for Veteran patients with multiple chronic conditions in person (Aveyard et al., 2006; DiClemente et al., 2009; Dishman et al., 2010; Harrold et al., 2018; Jordan et al., 2011; Levesque et al., 2011; Prochaska et al., 2012; Rodriguez et al., 2019; Spencer et al., 2002; Velasquez et al., 2010; Wright et al., 2009). We will also advance recommendations for: 1) the systematic investigation into the feasibility, adaptability, flexibility, useability, and efficacy of the TTM-CTIs, currently validated in civilian populations, as a treatment approach for all Veterans and 2) the introduction, implementation, and dissemination of TTM-CTIs as a care choice for Veterans that can complement existing evidence-based treatments for complex, multimorbid conditions.

The remainder of the paper will discuss key aspects of the TTM and the TTM-CTI: 1) the classification system employed for assessing an individual’s stage of readiness to make changes for readers unfamiliar with the full TTM model, 2) its design as a system to modify health-related behaviors, 3) the use of provider implementation of motivational interviewing to facilitate engagement with the change process, and 4) the delivery of the TTM-CTI intervention with which the individual Veteran patients interact online, either in clinic or outside the hospital system. This approach to modifying selected health risk behaviors is considered a promising telehealth option for helping all Veterans across the national VA healthcare system.

TTM Defined

The TTM is an integrative, theoretical model of health behavior change. It draws upon the leading psychological theories of behavior change and clinical decision making in which key constructs (defined below) are integrated (Prochaska & Velicer, 1997). The TTM proposes that adopting and maintaining new health behaviors involves progressing through multiple stages of change, and that different processes of change move the individual through successive stages of readiness along the continuum of health behavior change (Prochaska & Velicer, 1997).

Essentially, individuals are classified into one of five stages of change along a motivational continuum: Precontemplation, Contemplation, Preparation, Action and Maintenance. The model of change allows for bidirectional and cyclical movement, driven by ambivalence and uncertainty about change, which is accepted as an inevitable part of the change process. Precontemplation is characterized as the person not considering changing or adopting new health behaviors at any point in the near future (typically within six months). In the Contemplation stage, new health behavior at some point in the near future is being considered (usually within the next six months). In the Preparation stage, the person plans to adopt the new health behavior within the next 30 days. Preparation leads to Action, which are overt behaviors within the last six months demonstrating adoption of the health behavior (i.e., making the change). The Maintenance stage is the individual incorporating the change into life routines and sustaining the new health behavior for six months or longer (Prochaska & Velicer, 1997).

Different from the stages of change, the processes of change are key theoretical constructs comprised of cognitive and behavioral principles used to facilitate intentional change by the individual. Essentially, they are the independent variables or concepts to explain factors that facilitate the progression along the continuum of the stages of change. These include: Consciousness Raising, Dramatic Relief, Environmental Reevaluation or Social Reappraisal, Social Liberation or Environmental Opportunities, Self-Reevaluation, Stimulus Control, Helping Relationships, Counter Conditioning, Reinforcement Management, and Self Liberation or Committing to Change. For detailed examples of these ten, empirically based, processes of change, please see the sample TTM script below as well as Velicer et al. (1998).

In the change process, individuals are positioned between continuing their old, established unhealthy behaviors or patterns of behavior, versus shifting to new untested behaviors. Accordingly, the TTM helps to resolve patient’s ambivalence for change. Old behaviors are familiar but result in poor health outcomes; new unfamiliar behaviors require effort to adopt but are likely to improve health outcomes. In considering the balance between remaining the same and changing, individuals engage in a cognitive process that considers multiple factors to ultimately inform their decision to make a positive and healthy change.

Managing decisional balance is each individual weighing of the “pros and cons” for adopting a prescribed healthy behavior, and the result of this process is the resolution of ambivalence about what is the best personal decision. To change an unhealthy behavior (i.e., smoking), a shift needs to occur such that the pros for changing begin to outweigh the cons for changing and/or the pros for remaining the same as the person moves along the continuum of the stages of change towards Action. Likewise, for adopting new healthy behaviors, such as physical activity, the pros for moving to Action must be stronger than the cons for changing as well as the pros for not improving. The cons for changing and the pros for remaining the same must continue to diminish over time to support progression to the Maintenance stage.

Self-efficacy is a salient factor contributing to the resolution of the decision. This construct involves the degree of confidence a person must have to engage in a healthy behavior given certain barriers. Self-efficacy is situation-specific and ideally involves having a strong belief in being able to maintain positive behavior changes, even under high stress situations. Self-efficacy is responsive to TTM-based intervention using the tailored intervention via the TTM-CTI or by the provider. High self-efficacy supports moving to the Action stage and staying in the Maintenance stage once achieved. Thus, the TTM framework, in its entirety, is a bidirectional continuum that individuals can freely move along. The goal is achieving healthy behavior change over time and across situations, under varying degrees of stress or challenge.

What are Expert Systems?

Before discussing the TTM-ES specifically, we will briefly review expert systems. An expert system (ES) is a software program that stores information derived from human experts and uses algorithms to mimic the processes leading to judgments and decisions ordinarily made by humans or organizations possessing expertise or experience (i.e., subject matter experts). Early ES captured knowledge in the form of decision rules and used algorithms to put these rules together into a set of decision systems to communicate tailored feedback based on a database comprised of content elements (Krebs et al., 2010; Marcus et al., 2000). The output of an ES is typically an individualized feedback report, tailored to the individual’s stage of change, including which processes of change to focus on to help the individual progress across the stage of change continuum. Thus, ES simulate human decision-making by employing a knowledge base from a particular domain and applying that knowledge to the facts of a particular situation. Heuristic knowledge, which includes the rules of thumb used by human experts working in the domain is contained in the ES knowledge base. ES derive their power mostly from the knowledge base that stores specific knowledge about narrow domains. An ES assists by automating problem-solving or decision-making about issues that would ordinarily be handled solely by a human expert. Although some ES have been designed to fully replace human decision making, we focus here on the use of ES not as a replacement but as a complement for human experts, particularly when working with Veterans suffering from complex multimorbid conditions. ES work well when functioning like domain experts who can provide theory-based feedback through judgments or predictions. ES are becoming commonly used for making medical diagnoses (Munaiseche et al., 2018), in accounting (Brown & Wensley, 2000), and in gaming (Qualls & Russomanno, 2009).

TTM-CTI Defined

The TTM-CTI incorporates the pros and cons, self-efficacy, and the processes of change specific to each stage of change, thus providing a stage tailored feedback report to promote stage progression. Based on the continuum of change---ranging from no intention to change behavior (precontemplation stage) to maintaining a behavior change over a considerable period of time (maintenance stage), interventions based on TTM-ES or TTM-CTI intervention offers a concrete structure that informs individuals about what they need to do specific to their stage in order to progress (Norcross et al., 2011). TTM-ES was designed to be delivered with Motivational Interviewing (MI: discussed in detail below) implemented by a provider and integrated with the ES platforms. The systems have continued to evolve and now can be implemented on portable tablets (e.g., iPads), smart phones, and other hand-held devices. Ultimately, the TTM-ES was designed to expand the limits of the traditional provider and patient relationship and reach a greater number of people engaging in risky health behaviors.

At the time the TTM-ES was developed, it was known that treatment efficacy could be increased by matching the treatment to the individual needs of the client. The challenge became to develop a cost-effective approach; thus, the TTM-ES matched aspects of the traditional individual human-guided approach to behavior change with the low cost of the public health approach (Velicer et al., 1993).

As stated previously, TTM-ES interventions have been successfully applied for changing behavior in civilian populations (Romain et al., 2018) and hold promise for Veteran populations (Jordan et al., 2011). Future success depends on the VA healthcare system including the full TTM battery of constructs: Stages of Change, Processes of Change, Decisional Balance and Self-Efficacy for the TTM to be most effective. Through patient-computer interaction the patient provides input on the TTM relevant variables, and the computer provides individually tailored feedback. Using information from the patient-computer interaction, the stage-tailored feedback is returned to the participant during the session to guide their change process (cf. Fig 1). The TTM-ES, using pre-determined, theory informed algorithms, is a cost-effective way to deliver the intervention to many people remotely (Prochaska et al., 1993; Prochaska & Velicer, 1997). For more detailed information about the TTM-ES intervention, see Marcus, et al. (2000).

Motivational Interviewing

Motivational Interviewing (MI) is a client-focused counseling style that is supportive and non-confrontational in helping a patient to resolve their ambivalence for adaptive behavior change (Noonan & Moyers, 2004). The TTM is one successful health behavior change model that effectively incorporates elements of MI to develop the patient’s intrinsic motivation critical to sustain health behavior changes (Bolognesi et al., 2006; Novotny et al., 2015). The TTM is considered the most “significant theoretical structure supporting MI” (Atkinson & Woods, 2017, p. 341). As the development of intrinsic motivation is the central tenet and “spirit” of MI (Hettema et al., 2005), research to date has substantiated that MI integrates well with the TTM across multiple health behaviors, including exercise adoption and maintenance (Muscat, 2005). Further, recent calls for research in this area have sought to integrate MI with existing cognitive behavioral treatments with the ultimate goal of effecting lasting behavior change in multiple domains of functioning (Naar & Safren, 2017). Thus, it is our contention that the TTM-ES framework, which integrates salient MI principles and processes, can facilitate the true “spirit” of MI. Taken together, the TTM and MI components can synergistically interact within the TTM-ES framework to produce individualized feedback. Such tailored feedback can either serve as a stand-alone intervention to Veterans broadly, or as an integral component of an individual Veteran’s overall treatment plan. Regarding the latter, the Veteran’s provider, skilled in MI and utilizing a team approach, can work with the Veteran and support their development of intrinsic motivation while also addressing their clinical symptoms, leading to lasting behavioral change. Please see sample TTM+MI script along with the Figure to demonstrate how the TTM and MI components can work within an Expert System format.

How Has TTM Been Applied?

Since its creation decades ago, and throughout their early development until the present, the TTM and TTM-ES have been employed nationally and internationally for health behavior and clinical behavior change in civilian clinical and non-clinical populations. To show the range of applications, examples of civilian applications for which any aspect of the TTM framework has been employed are show in Table 1. This is not an exhaustive list, but Table 1 includes a selection of studies for behaviors and conditions that are also relevant to Veterans.

Table 1.

TTM Driven Health Behavior Change Interventions Among Various Populations

Behavior Group	Author(s), Year	Population	Outcomes
Exercise
	Dishman et al., 2010	Adults living in Hawaii	Participants that maintained physical activity had higher TTM variable scores over 2 years.
	Harrold et al., 2018	Veterans with mental health concerns	Mean decrease in weight post-intervention (9lbs); increase in percentage of controlled blood pressure post-intervention (84% vs 60%); decrease in percentage of uncontrolled blood pressure post-intervention (16% vs 40%).
	Jeon et al., 2014	Korean university students	Self-efficacy predicted transition from preparation phase to active phase (p≤0.05). For early stage of change, one-on-one training or education is most effective; for later stages of change, self-directed exercise to improve self-efficacy is effective.
	Mardani et al., 2010	Iranian adults with inflammatory bowel disease	Intervention group showed increase in self-efficacy, decisional balance, and physical activity compared to control group (p<0.05).
	Moeini et al., 2010	Iranian government employees	Intervention group showed improved physical capacity (p=0.016) and increased self-efficacy and decisional balance scores (p<0.001).
	Mohammadi & Mehri, 2012	Iranian university students	Self-efficacy and behavioral process of change were most effective in predicting increased physical activity (β=0.350; β=0.399).
	Shaver et al., 2019	African American Adolescents	Stages of change predicted physical activity (p≤0.04). Self-efficacy associated with advanced stages of change (p=0.02).
	Zhu et al., 2014	Sedentary adults diagnosed with coronary heart disease	Stage-matched intervention group showed improvement in exercise behavior, including stage of change progression, self-efficacy, and motivation (p<0.01), compared to education and control groups.
Nutrition
	Di Noia et al., 2008	Urban African American adolescents	Adolescents in the computer intervention group progressed to later stages of change regarding fruit and vegetable intake and maintained intake post-intervention (p<0.05).
	Di Noia & Prochaska, 2010	Economically disadvantaged African American adolescents	Stages of changes accounted for 72% of intervention effect.
	Horwath et al., 2013	Adults living in Hawaii	TTM behavioral processes predict transition out of precontemplation stage of change for adult fruit and vegetable consumption (p<0.001).
	Rodriguez et al., 2019	Veterans with uncontrolled hypertension	TTM Intervention group showed improved dietary habits at 6 months (p≤0.01).
	Salehi et al., 2014	Elderly Iranians	Intervention group showed increased fruit and vegetable consumption compared to control group (3.08± 1.35 vs 1.79± 1.08; p=0.001) and progressed to later stages of change (p≤0.004).
	Wright et al., 2009	Adults at risk for smoking, high-fat diet, sun exposure, or lack of mammography screening	TTM stages of change predicted changes in dietary fat intake, with ≥92% confirmation for predictions based on precontemplation, contemplation, and preparation stages.
Smoking Cessation
	Aveyard et al., 2006	Pregnant women smoking at 12 weeks gestation	Treatment group more likely to move to advanced stage of change compared to control at 30 weeks gestation (OR=1.65) and 10 days post-partum (OR= 1.39).
	Buja et al., 2011	Pregnant and non-pregnant women who smoked in the previous year	Pregnant women were more likely to be in a later stage of behavior change regarding smoking cessation (p<0.01).
	Prochaska et al., 1993	Adult smokers in Rhode Island	Individuals receiving expert-system computer reports along with stage-matched manuals scored more than double in smoking abstinence measures over those receiving either standard or stage-matched manuals alone.
	Prochaska et al., 2004	Parents of teenagers	Expert-system intervention group reported greater reductions in smoking compared to control group.
	Prochaska et al., 2005	Primary care patients	Treatment group receiving expert-system reports had more participants in action or maintenance stage for smoking cessation comparted to the control group.
	Sharifi et al., 2012	Iranian university smokers and ex-smokers	Individuals in earlier stages of change for smoking cessation identified more pros than their counterparts in later stages of change (p<0.05).
	Spencer et al., 2002	Review paper	TTM interventions for smoking cessation are successful in various populations. More research is needed to evaluate the best stage-matching methods.
Alcohol and Substance Use
	Bewick et al., 2008	UK university students	Intervention group showed greater decrease in alcohol consumption compared to control group (p=0.02).
	Çapuk & Aylaz, 2024	Adults in the criminal justice system in Turkey	Experimental group showed a significant increase in Self-Efficacy Scale (p<0.05) and decrease in Beliefs about Substance Use Scale (p<0.05) between pre and post intervention scores.
	DiClemente et al., 2009	Adults with alcohol dependence	Drinking behavior was predicted by Readiness to Change (RTC) constructs, although the results indicate that other variables play a role.
	Levesque et al., 2018	Health center providers; Primary care patients with known substance use disorder	Substance use risk intervention was well received by both providers and patients; average acceptability score of 4.4 out of 5 from providers and 4.5 out of 5 from patients.
	Ruggiero et al., 2006	New York City residents	Increased score on post module knowledge checks. Internet based intervention pilot showed promise and bears further development.
	Velasquez et al., 2010	Women at risk of an alcohol-exposed pregnancy	Behavior change was seen in both target behaviors which contribute to the risk of alcohol-exposed pregnancy. Results call for future investigation in adapting the intervention to various populations and settings.
	von Sternberg et al., 2018	Women at risk of an alcohol-exposed pregnancy	Women that reduced drinking to below risk levels had: greater pros (p<0.001) and lower cons (p=0.012) for change, greater confidence (p=0.030), and lower temptation (p<0.001) regarding alcohol use during pregnancy.
Stress Management & Mental Health
	Evers et al., 2006	Adults, national sample	TTM intervention group showed increase in effective stress management over control group.
	Jordan et al., 2011	Veterans at risk for PTSD	Proposes the adaptation of Pro-Change CTI for veteran populations with or at risk for PTSD.
	Levesque et al., 2011	Adults with depression symptoms that are not in active treatment	CTI intervention group showed significant improvement in depression symptoms (d=0.220–0.355).
	Li et al., 2020	Hospitalized patients with coronary heart disease	Intervention group showed a decrease in depression scores at multiple time points compared to the control group.
	Prochaska et al., 2008	Employees at a medical university	MI and TTM groups had more participants in the Action stage for stress management than the HRI only group.
Multiple Behavior Change
	Johnson et al., 2008	Overweight or obese adults	More participants in the expert system intervention group progressed to action/maintenance stage compared to control for nutrition, exercise, and stress management behaviors.
	Mauriello et al., 2011	Low-income pregnant women	Pilot computer-tailored intervention to promote positive health behaviors during pregnancy was confirmed both feasible and acceptable to patients.
	Partapsingh et al., 2011	Type 2 diabetics in Trinidad	Improved glycemic control in intervention group (p=0.025). A greater proportion of intervention group participants moved to more favorable stage of change for exercise and diet compared to control group.
	Prochaska et al., 2012	Adults, national sample showing risk behaviors for exercise and stress management	Both TTM treatment groups showed higher percentage of progression to the Action stage for stress management and exercise compared to the control group.
	Xu et al., 2020	Individuals at high risk for Type 2 diabetes in Beijing, China	Intervention group participants were more likely to be at advanced stages of changes for dietary and physical activity behaviors at 6 months (p<0.001).

As just a subset of the topics in the published TTM literature, it is evident from Table 1 that the TTM for health behavior change has utility for conceptualizing and structuring study designs, staging the readiness of study participants to engage study protocols, and maximizing study endpoints. Clinical benefits can similarly derive from TTM based interventions delivered in direct service settings.

TTM-ES and Application with Veterans

A main point of this paper is that the TTM and TTM-ES should be fully adopted by the VA healthcare system, and once further developed and validated, employed as both a population- based intervention for all Veterans who utilize VA services, as well as an adjunct to the clinical care of specific patient subgroups of Veterans, e.g., those faced with complex comorbidities such as PTSD and chronic pain. Veteran patients represent an especially vulnerable population because of both the individual effects from these co-prevalent conditions, and the combination with unhealthful lifestyle factors (Jakovljevic et al., 2006; Lee et al., 2006; Otis et al., 2010). Adopting and maintaining healthy lifestyle behaviors is critical to forestalling the advance of chronic diseases, as well as increasing overall general health, well-being, daily functioning, and reducing individual disability rates (Bookwalter et al., 2019; Yang et al., 2019). Embracing healthy lifestyle behaviors is a critical component of Veterans’ recovery from, and management of, complex medical and psychiatric conditions. Further, at the population level, improving general health will benefit all Veterans and the overall VA healthcare system.

As stated previously, an example of a complex comorbidity commonly seen among Veterans in the VA healthcare system is PTSD and chronic pain. Veterans suffering from these comorbid conditions report greater affective distress, disability, and interference in functioning than those suffering from either one of these conditions alone (Kind & Otis, 2019; Otis et al., 2010). Comorbid PTSD and chronic pain, combined with unhealthy coping behaviors, can have deleterious effects. As stated previously, Veterans represent a remaining subpopulation that can benefit from TTM-based interventions promoting multiple health behavior change in these areas.

Attempts to cope with the clinical symptoms and emotional impacts of PTSD and chronic pain often lead to unhealthy choices and poor self-management strategies. For example, Veterans with PTSD and chronic pain are more likely to engage in less exercise, have poor diet quality, and use substances (e.g., nicotine, alcohol, drugs) to manage their pain and PTSD symptoms. In turn, these behaviors increase risk for metabolic syndrome (i.e., high blood pressure, obesity, high cholesterol, poor glucose control; Heppner et al., 2009; Jakovliević et al., 2006), accelerated aging and premature death (Alford et al., 2016; Chapman et al., 2015; Gros et al., 2015; Kearns et al., 2018; Mills, 2009; van den Berk-Clark et al., 2018; Wolf et al., 2018, Zen et al., 2012).

Using the tailored ES feedback, both the provider and Veteran patient can collaborate as a team to set and track realistic goals that are designed to foster the necessary health behavior changes over the course of their evidence-based treatment. Providers, trained in MI, can integrate TTM-ES interventions into their treatment plans as supplement or adjuncts to their primary therapy, which then simultaneously works to improve health while decreasing symptoms. Integrating the two goals into one coordinated treatment plan is possible because the TTM-ES intervention delivers individualized and tailored feedback to the Veteran which supports the person-centered approach of MI. If extra motivational enhancement is needed to facilitate the change process, the therapist can introduce additional MI techniques (cf. Figure 1). These techniques can be implemented either by phone, another remote platform or in person by a therapist or an interventionist trained in MI who can help the Veteran move along the stages of change continuum and increase their readiness to take action toward their immediate health behaviors change goals, as well as sustaining changes long after the treatment process has ended.

TTM-ES Addressing Veteran and VA Healthcare System Needs

There are several positive impacts on both Veterans and the VA healthcare system that could result from implementing TTM-ES in VA clinics and offering it as a program to Veteran patients. These include individual benefits to the patients in general health improvement and in access to care. For the VA healthcare system, distributed effects of decreased utilization across clinics in the larger system combined with greater treatment engagement by remote patients should result in lower costs and better health.

Time and Financial Cost Reduction to the Veteran

Veterans living with comorbid conditions are often burdened as patients by having many appointments with a host of providers, in many specialized care clinics, to address each of their separate conditions (Otis et al., 2003, 2010). This is time consuming and financially costly for the Veteran, VA healthcare system providers and the VA health care system (Slightam et al., 2020). TTM-ES interventions can be added to treatment plans and administered along with other existing evidenced based treatments without adding extra visits. Flexible and tailored to the Veteran’s needs, it can be implemented as an extension of in-clinic care. Combining tailored TTM-ES interventions—self-administered in the patient’s online (home) environment—with traditional patient-provider appointments will decrease cost burdens for Veterans and care providers because multiple treatment goals can be addressed concurrently within an integrated treatment plan.

Besides the personal economic and existential costs of living with complex comorbidities and persistent poor health, the resulting dysfunction in key domains and diminished quality of daily life can lead to increased disability (Cook et al., 2015). The individual monetary and psychological costs are substantial for the Veterans, as is the attendant cost to the VA healthcare system of providing disability support for unemployability (Davis et al., 2022).

VA Healthcare System Needs

National VA healthcare system needs partially overlap with local hospital needs to provide greater access to care and work within hospital wide budgetary limits. Veterans with complex comorbidities and healthcare needs would benefit greatly from an effective health behavior change intervention to help them mitigate serious health outcomes and improve general well-being. However, as lifestyle factors are often viewed as less critical or not acute enough to need immediate remediation, they are less frequently or adequately addressed by many clinical providers within the healthcare system (Guthrie, 2016). However, if a convenient, feasible, effective, and well-received option were available as a choice to add to clinical treatments or care plans, it would be easier for the system, the provider, and the Veteran to directly address unhealthy behaviors. The TTM-ES intervention offers such an option as an efficient, effective, relatively low-cost, complementary care intervention for changing health behaviors that need to be improved. Care that can be provided at lower costs frees funds for other needs within the system. For a geographically diverse national healthcare system like the VA healthcare system, the TTM-ES is a good fit because it allows the same access to this care regardless of setting. At a population level, Veterans in rural locations would receive the same opportunities to engage with the TTM-ES program as Veterans residing closer to VA healthcare system hospitals in urban settings. At the individual level, TTM-ES could be integrated with other traditional medical treatments, pharmacological or non-pharmacological, as cost-effective adjunctive care (Prochaska et al., 1993; Prochaska & Velicer, 1997).

As a nationwide healthcare system with an integrated computer system widely used to provide telecare, the VA healthcare system could implement TTM-ES as a pilot program at test sites around the country, in medicine and mental health clinics by staff who have been oriented and trained to incorporate health behavior change as another component of their treatment plans. After monitoring and fine-tuning, it could be disseminated to clinics across the whole VA healthcare system. As TTM-ES was originally developed and validated in civilian settings, eventually this version of TTM-ES could be shared outside of the VA healthcare system with other community healthcare settings in a public-private sector partnership.

TTM-ES and VA Healthcare System Telehealth for the Future

Decades ago, forward-thinking individuals anticipated the development of eHealth (Atkinson & Gold, 2002) that employed the burgeoning internet to study health behavior and provide care. At the present time, when the VA healthcare system has remodeled its approach to care in response to the coronavirus pandemic to emphasize virtual care, online appointments have become accepted for routine, outpatient care (Office of Public and Intergovernmental Affairs; 2019; VA News, 2022). Prior to the coronavirus pandemic, the VA healthcare system already had the biggest telehealth program in the US (Federal News Network, 2019; The American Legion, 2020). The VA healthcare system expanded its use of telehealth to prevent spread of COVID-19 (Vantage Point, 2020) and VA healthcare system video visits increased 1000% during the pandemic (ALG, 2020). The TTM-ES intervention is a highly promising approach for reaching Veterans to support and guide healthy lifestyle modification. Whereas many existing interventions needed to be adapted for telehealth or abandoned when VA healthcare system face-to-face care was interrupted by concerns over the spread of COVID-19 infections, TTM-ES was designed for virtual administration and, thus, it would be trivial to incorporate TTM-ES during or after routine visits. In principle, this could be implemented in a browser-based tool at the VA healthcare system.

Once TTM-ES is further developed and validated for Veterans, one might envision this platform initially being integrated into the VA healthcare system’s Whole Health nationwide initiative. In brief, the VA healthcare system’s Whole Health is a patient centered “team” approach in which providers help patients shift from the traditional disease-based model to a prevention -based health model of care (US Department of Veterans Affairs, n.d.b). The central focus of Whole Health is based on the provider working with the patient to identify the Veteran’s current values with respect to “what matters most to them” and their subsequent “reasons” for adopting a healthier lifestyle (US Department of Veterans Affairs, n.d.a). Whole Health has been in place since 2011 and already incorporates elements of MI (Purcell et al., 2021). Integration of the TTM-ES within the Whole Health initiative can reduce both patient and provider burden on the entire VA healthcare system, as detailed earlier, and can provide the Veteran with more novel and effective telehealth options for a range of health behaviors. Although the VA healthcare system already has a variety of telehealth based applications for both physical and psychological health conditions, a defining feature of the TTM framework and the TTM-ES platform is its ongoing, continuous assessment of the patient’s health risk behaviors and degree of motivation to change such behaviors that can be individually tailored to both the patient’s current stage of change and their life circumstances or context (US Department of Veterans Affairs, n.d.c, US Department of Veterans Affairs, n.d.d). Further, since the TTM-ES platform utilizes evidence-based algorithms to provide the individually tailored feedback to the patient, it can complement the existing team approach already in place in Whole Health. Promisingly and most notably, TTM-ES can continuously be updated with the most recent empirical findings on many adaptive health behaviors to better inform clinical best practices (Jordan et al., 2011), within the Whole Health initiative.

Discussion

This paper discusses an important approach to delivering health behavior change interventions remotely at Veterans’ convenience that would focus on improving their overall health and well-being. These interventions can be adjunct to other provider-based treatments, or as stand-alone. States of general health and well-being are principal intervention targets for prevention and post-treatment recovery, in part because the top ten causes of mortality in the U.S. are considered preventable if lifestyle factors are modified (CDC, 2012). Although the notion of promoting health and disease prevention is not novel, behavioral aspects that are under an individual’s control often receive less attention from healthcare systems, providers and patients than do procedures that remediate active clinical symptoms. Behaviors associated with healthy lifestyles are recognized as important factors for decreasing clinical disease development, successful post-treatment rehabilitation, maintenance of improvements after treatment and diminished recurrence of conditions (Espinosa-Salas & Gonzalez-Arias, 2023). While the converse is also true, formal support for healthy behaviors is inconsistent across healthcare systems. Patients could receive some brief aftercare to promote recovery following a procedure. Insurance companies might offer limited outpatient support/psychoeducation programs aimed at health promotion; often though, individuals are on their own to identify and modify negative lifestyle factors that might contribute to their clinical condition. Achieving and maintaining healthy lifestyle behaviors requires effort. These are more likely to occur, and be maintained, when they are accepted, adopted, and incorporated by individuals into their daily routines. These personal modification processes happen more readily when guided by structured and tailored programs of health behavior change. The TTM-ES approach of health behavior change discussed in this paper is just such a guided structured and tailored program.

Developed as a self-paced, computerized application for changing behavior, various TTM-ES have been validated in civilian populations and applied internationally for decades along with change agents yielding robust positive findings. It is proposed here as a viable, virtual health behavior intervention for Veterans. The target clinical group would initially be Veterans served by the VA healthcare system who have complex comorbidities and secondary health problems, like PTSD and chronic pain patients. Complex comorbidities can complicate their care, increase vulnerability, and heighten risk of developing worsening morbidity for existing conditions and premature mortality (natural or self-inflicted). These Veterans would benefit from a structured program aimed at decreasing negative health behaviors and habits (e.g., physical inactivity, smoking, poor nutrition, substance (ab)use) and increasing positive health behaviors (e.g., regular exercise, smoking cessation, substance ab(use) prevention, improved diet quality, stress management, improved sleep quality, engagement in psychological treatment). TTM-ES is a flexible intervention that can be tailored to individual Veteran’s needs and motivation, and thus can function, with the provider trained in MI, such as those based in the VA healthcare system’s Whole Health initiative, as a remedial/current change agent or in a proactive, preventative capacity by increasing positive behaviors while decreasing negative behaviors.

Future Directions

The TTM-ES is a theoretically-based set of interventions, based on the targeted health behavior, that has been developed, validated, then field tested in civilian populations (Aveyard et al., 2009; Johnson et al., 2006a; Johnson et al., 2006b; Nigg et al., 2019). This provides benchmarks and expectations for performance. However, corresponding outcomes in Veteran samples cannot be assumed even though they were civilians before active duty and became civilians again after discharge from service. Because of their military service, Veterans have unique experiences that combined with their complex comorbidities, do not allow us to generalize successes in civilian populations to military and veteran populations. Further development, validation and additional evidence is required. Thus, similarities and differences in responses to the ES protocol, and in quantity and quality of outcomes needs to be empirically examined for equivalence before generalization from civilians to Veterans can be asserted.

Questions about generalization in this context implicitly ask whether the TTM-ES can be adapted and applied to Veterans. It is possible. Effective health behavior change interventions, such as the TTM with well more than 30 years of empirical evidence, have been found to be helpful in preventing and managing chronic disease, consequently yielding benefits in overall health for individuals while lowering care provision costs incurred by healthcare systems. This would likely be true as well for Veterans in the VA healthcare system because of the complex comorbidities that they often experience. To gauge the full impact, future research needs to examine both the effects on individual patients and more broadly on clinical service utilization within the VA healthcare hospital system.

A more complete understanding of the effectiveness of the program and benefits from implementing TTM-ES would derive from extending the work by Jordan et al. (2011) and using mixed methods research that collect both quantitative and qualitative data (Creswell & Plano-Clark, 2011). Mixed methods designs are a good fit for addressing research questions that are not easily answered separately by either quantitative or qualitative approaches (Ivankova et al., 2006). Having both forms of data collected within the same study allows the two types of data to complement each other. Use of a mixed-methods design would permit qualitative data about Veterans’ experiences with the TTM-ES, as a telehealth application, to be collected from focus groups and systematic individual debriefings for: 1) examination alongside objectively measured changes, and 2) for use as feedback about the expert system to identify areas needing improvement and further tailoring to the unique needs of Veterans. These types of program evaluations would need to be conducted in the future to assess any systemwide implementation undertaken.

Real World Data (RWD) and Real World Evidence (RWE)

Collecting RWE data will be a natural outgrowth of using TTM-ES as a remote, self-administered intervention. RWE is based on RWD and could be considered the complementary information obtained from randomized controlled studies, akin to Efficacy vs. Effectiveness, i.e., highly controlled vs. as used in the field. RWD can be obtained from electronic health records, insurance claims, institutional billing activities, large health registries, or patient-generated information from used-in-home and portable devices. RWE then is the clinical evidence that results from analyzing RWD related to usage patterns of devices plus risks and benefits. Since Congress enacted the 21^st Century Cures Act in 2016, RWD and RWE are used to assist the development of new treatments, in regulatory processes for new medications, and for health care decisions in clinical practice (Song et al., 2021). While the signal from RWD may be more challenging to discern because of noise, it is nonetheless very important to have when determining whether findings from RCTs will generalize to the intended populations, and in the intended applied contexts. Any treatment application needs systematically collected RWD when effectiveness depends on unsupervised patient involvement away from the clinic setting. This is particularly relevant in light of trends in healthcare where telehealth and telemedicine are routine methods of delivering care. As a computer-based, self-paced and in-the-home intervention, TTM-ES is well-suited for collecting RWD that generates the RWE about outcomes and treatment-patient matching effectiveness.

Parametric Studies

In addition to RWD generated by the use and documentation of TTM-ES, systematic research will be needed to understand the parameters that potentially affect TTM-ES clinical and research outcomes in Veteran populations, from basic demographic characteristics (i.e., age, gender, education, IQ, race, medications taken, clinical complexity, duration of chronicity) to the design of clinical and research protocols. It will be important to know: Are the outcomes different when TTM-ES is administered in clinic settings vs. self-administered at home? How does compliance with treatment affect degree of behavior change achieved? What is the impact of self-efficacy and intrinsic motivation for engagement and maintenance of health behavior changes? Are there impacts on outcomes related to service providers or clinics where the TTM-ES intervention is delivered? Depending on the health behavior target, Veterans needing help will do too little (of the positive behaviors) or too much (of the negative behaviors). Is there differential effectiveness of TTM-ES when effecting increases vs. decreases in health behaviors? Will it make a difference if TTM-ES is administered sequentially or concurrently as a co-intervention? If sequentially, will TTM-ES be more effective if administered after treatment for clinical conditions? Does stage of readiness change after successful therapy? Alternatively, could success from TTM-ES increase the Veteran’s readiness for response to empirically supported treatment, like those recommended for chronic pain and/or PTSD? Results from these parametric studies will aid in fine-tuning the TTM-ES protocols for Veterans in the VA healthcare system.

Establish TTM-ES Best Practices for Veterans

All of the cross-validation work above will be needed to establish the utility of TTM-ES as a useful intervention for Veterans in the VA healthcare system. With most interventions, differential responding occurs across people and some derive no benefit. Given well over 30 years of use in civilians, positive outcomes can be predicted, but who might respond well cannot. As outcomes from TTM-ES accumulate, Clinical Best Practice guidelines (CBPG) can be created to direct service providers as they incorporate the program into treatment plans. CBPGs could be used to structure educational programs for new trainees who will use TTM-ES in the future. What will constitute best practices will emerge from research and practical observation from using it with Veterans, for a range of health behavior targets, plus combining it with standard, empirically supported or complementary alternative medicine treatments.

Dissemination within the VA Healthcare System and to non-VA Healthcare settings

As the largest integrated healthcare system in the country, standardization, implementation, and dissemination would be the long-term clinical and systems goals for TTM-ES so that its benefits can be distributed to Veterans in all geographic localities. Knowledge gained about TTM-ES could eventually be a shared benefit that the VA healthcare system offers to civilian healthcare systems.

As conceptualized and discussed for this paper, TTM-ES is a complementary care option and not a replacement of existing evidence-based treatments for psychiatric disorders or medical conditions. As a complementary intervention integrated into clinical care treatment plans, the aim of TTM-ES is to foster improvements in functioning, in well-being, and reduce disability as a result of overall improvement in health.