Abstract
Although many interventions are effective for health behavior initiation, maintenance has proven elusive. Interventions targeting maintenance often extend the duration with which initiation content is delivered or the duration of follow-up without intervention. We posit that health behavior initiation and maintenance require separate psychological processes and skills. To determine the value of operationalizing maintenance as a process separate from initiation, we conducted a pilot study of a telephone-delivered intervention to assist people in transitioning from behavior initiation to maintenance. Participants were 20 veterans who had initiated lifestyle changes during a randomized controlled trial of a cholesterol reduction intervention. After completing the randomized controlled trial, these participants were enrolled in the pilot maintenance intervention, which involved three monthly telephone calls from a nurse interventionist focusing on behavioral maintenance skills. To evaluate the feasibility and acceptability of this intervention, we assessed recruitment and retention rates as well as 4-month pre–post changes in health behaviors and associated psychological processes. We also conducted individual interviews with participants after study completion. Although not powered to detect significant changes, there was evidence of improvement in dietary intake and of maintenance of physical activity and low-density lipoprotein cholesterol during the 4-month maintenance study. Participants found it helpful to plan for relapses, self-monitor, and obtain social support, but they had mixed reactions about reflecting on satisfaction with outcomes. Participants accepted the intervention and desired ongoing contact to maintain accountability. This pilot maintenance intervention warrants further evaluation in a randomized controlled trial.
Coronary heart disease is the leading cause of death in the United States (Denhaerynck et al., 2003). Disease risk reduction may be achieved through lifestyle changes and medication. Several behavioral strategies have proven effective for helping people initiate risk-reducing health behaviors, yet these new behaviors typically falter after 6 months, resulting in weight regain, failure to engage in physical activity, and medication nonadherence or discontinuation (Berrigan, Dodd, Troiano, Krebs-Smith, & Barbash, 2003; Foster et al., 2010; Vrijens, Vincze, Kristanto, Urquhart, & Burnier, 2008).
Various theoretical approaches suggest that there are important differences between behavior initiation and maintenance. For example, the transtheoretical model distinguishes behavior initiation and maintenance according to the length of time they have been enacted (Prochaska, 1984): Action refers to a behavior change lasting from 1 day to 6 months, whereas maintenance is achieved if individuals have sustained the behavior for at least 6 months. Although the time frame is arbitrary, many researchers believe that a newly initiated behavior must be repeated a certain number of times or for a certain duration before it can be considered maintained (Kumanyika et al., 2000; Marcus et al., 2000). Others have suggested that initiation and maintenance involve different psychological processes and behavioral strategies (Hertel et al., 2008; Jeffery et al., 2000; Kiernan et al., 2012; Perri et al., 2001; Rauscher, Hawley, & Earp, 2005; Rothman, 2000; Schwarzer, 2008; Schwarzer et al., 2007; West et al., 2011). However, the various distinctions have not been incorporated into a unifying model to inform intervention design.
Accordingly, the goals of this article are threefold. First, we present a conceptual model that unifies the cognitive and behavioral processes involved in initiation versus maintenance of a new behavior. Second, we describe the use of this model to design an intervention aimed at health behavior maintenance. Third, we present data derived from a pilot study on the feasibility and acceptability of the model-based intervention.
Theoretical Approach
A primary difference between behavior initiation and maintenance lies in the self-regulatory focus of the behavior (Rothman, 2000). In initiation, the focus is on approaching a favorable end state, thereby reducing the uncomfortable discrepancy between the current state (e.g., being overweight) and the desired end state (e.g., being a healthy weight; see Table 1). In contrast, in maintenance, the focus is on avoiding a less favorable alternative state, thereby sustaining the comfortable discrepancy between the current situation (e.g., being a healthy weight) and an undesired state (e.g., reverting to being overweight). These foci inform the cognitive and behavioral strategies employed to maintain health behaviors and the resulting beneficial health outcomes.
Comparison of Cognitive and Behavioral Strategies Involved in Behavior Initiation and Maintenance.
One such strategy is consideration of anticipated positive and negative outcomes of the new behavior relative to the current behavior (e.g., improved mobility as a result of weight loss vs. feelings of deprivation as a result of fewer food indulgences, respectively). To the extent that people hold favorable expectations—that is, that the anticipated positive outcomes of the new behavior outweigh not only the costs of the new behavior but also the benefits of the old behavior—behavior initiation should occur (Baldwin et al., 2006; Hertel et al., 2008; Rothman, 2000). In contrast, the decision to maintain a behavior entails considering the outcomes of that behavior. When it is sufficient, perceived satisfaction with outcomes will lead to behavior maintenance (Baldwin, Rothman, & Jeffery, 2009; Hertel et al., 2008). In contrast, unrealistic expectations about initiating a health behavior may result in dissatisfaction with actual outcomes, and thus may hinder maintenance (Rothman, 2000).
Another difference between initiation and maintenance is the type of self-efficacy that drives behavior (Bandura, 1986; Marlatt, Baer, & Quigley, 1995; Schwarzer et al., 2007; Schwarzer & Renner, 2000). Self-efficacy is relevant in the motivational phase of behavior, when behavior intentions are being formulated (Gollwitzer, 1990). To initiate a new health behavior, individuals must be confident in their ability and skills to perform that behavior (action self-efficacy). To maintain behavior, individuals must be confident in their ability to overcome barriers in order to continue that behavior (maintenance self-efficacy) and to utilize skills to get back on track once derailed (recovery self-efficacy; Schwarzer et al., 2007).
Behavior initiation and maintenance also differ in terms of behavior planning, which occurs in the volitional phase of behavior. Initiation involves setting measurable, attainable goals and action plans (also called implementation intentions) specifying where, when, and how to perform the action (Gollwitzer, 1993). Specific action plans result in greater behavior change than broader goals (Gollwitzer, Sheeran, & Mark, 2006). Furthermore, action plans help replace habitual unhealthy behavior with new, more desirable behavior (Adriaanse, Gollwitzer, DeRidder, de Wit, & Kroese, 2011).
Once healthy habits have been established, everyday situations and demands may threaten those habits (Rothman, Sheeran, & Wood, 2009). Long-term behavior change therefore may be promoted by explicitly identifying high-risk situations and developing strategic plans to deal with those situations of greatest risk, a process termed relapse prevention (Bouton, 2000). Thus, maintenance of behavior change may be enhanced both by the formation of new, healthy habits during initiation and the explicit planning for risky situations in which habitual responding may be less likely.
Another distinction between initiation and maintenance lies in who guides the monitoring. In a behavior initiation intervention, monitoring frequently is guided by the interventionist. For example, an interventionist may set weight loss goals and review food journals, physical activity logs, or biological markers of success such as cholesterol levels or blood pressure. By monitoring patient progress, the interventionist can provide targeted education or skills training to bolster behavior change; interventionist-guided monitoring also may improve success rates by promoting accountability to an external perceived locus of causality (Ryan & Deci, 2000).
The initiation context also provides the opportunity for the interventionist to teach patients self-monitoring skills. Monitoring involves tracking health status and health behaviors, as well as setting a threshold that would indicate a lapse or relapse. Ideally, relapse prevention would include actions to prevent a lapse such that it prepares an individual for risky situations that promote slips into old habits (e.g., eating high-calorie meals while on a vacation). Self-monitoring that is practiced during initiation and continued during maintenance serve as a cue to assess when a lapse has occurred (e.g., exceeding daily caloric intake) and when a lapse turns into a relapse (e.g., weight regain of 3 pounds). Thus, the sensitivity of the monitoring plan to deviations in behavior may play a large role in the distinction between a lapse and a relapse.
A final key distinction between initiation and maintenance is the source of social support. In the context of a health behavior intervention, social support for achieving a behavioral goal may be derived from an interventionist and/or similar others, such as participants in a group intervention. The patient also may be taught to elicit support effectively from social network members (e.g., family members, coworkers, peers). Alternatively, a support person may be actively involved in the behavior initiation intervention and taught support strategies, with the interventionist acting as a moderator (Sperber, Sandelowski, & Voils, 2013). When the intervention is withdrawn, these structured sources of support and the teaching of support skills largely disappear, leaving patients and their network members on their own to implement and sustain strategies to enhance support (Prochaska, Redding, & Evers, 1997).
The conceptual model shown in Figure 1 unites all of these distinctions. The proposed model indicates how the key constructs—favorable outcome expectations and action self-efficacy—function in the motivational phase in the formulation of intentions to initiate behavior change. Next, these intentions are translated to behavior initiation in the volitional phase via goal setting and action planning. Action produces outcomes associated with that behavior (e.g., weight loss, lower blood pressure). An evaluation of those outcomes results in perceived satisfaction with outcomes to influence intentions to maintain behavior. Maintenance intentions are also influenced by maintenance self-efficacy and recovery self-efficacy. The link between intentions to maintain and maintenance actions is enhanced by relapse prevention planning.
Conceptual model of behavior initiation and maintenance.
This model was used to inform the content of a telephone-based intervention directed at the maintenance of dietary and physical activity behaviors. In the remainder of this article, we provide data derived from a pilot study on the feasibility and acceptability of the intervention.
Method
Setting and Design
This mixed methods pilot study took place at the Durham Veterans Affairs Medical Center, where approval was obtained from the local institutional review board. The study was a one-group pretest–posttest design with outcomes assessed at baseline and at 4-month follow-up, and individual semistructured and open-ended interviews conducted subsequent to the follow-up outcome assessment.
Participant Recruitment and Enrollment
Because participants must have initiated health behaviors before they could enroll in the maintenance intervention, we purposefully recruited patients who had recently concluded follow-up in a behavioral intervention focused on lifestyle change (the Couples Partnering for Lipid Enhancing Strategies intervention [CouPLES]). Briefly, the 11-month spouse-assisted intervention was aimed at increasing patient adherence to health behaviors to reduce low-density lipoprotein cholesterol levels (Voils et al., 2013). In this trial, 11-month caloric, total fat, and saturated fat intake were significantly lower, and the frequency of moderate-intensity physical activity was 20% greater (p = .06), for patients in the intervention than the usual care control arm. Although the CouPLES intervention included patients and spouses, the maintenance intervention reported here included patients only. In addition, because funding for this pilot study was obtained near completion of the parent trial, only the last 25 patients completing the intervention arm of the trial were approached. At the final-assessment visit of the parent trial, patients were informed about the maintenance study and asked for permission to call them 1 week later to discuss participation and obtain telephone consent.
Procedure
An intervention to promote behavior change and then to promote maintenance of those changes ideally would be intensive during the initiation phase to promote behavior change (LeBlanc, O’Connor, Whitlock, Patnode, & Kapka, 2011), after which intensity could be reduced while still maintaining the health benefits achieved by the initial behavior changes. Telephone is a viable mode of delivery for maintenance intervention because telephone-delivered interventions can achieve similar effects as face-to-face interventions (Radcliff et al., 2012). Yet telephone delivery has the additional advantages of allowing greater reach, reducing patient burden, and allowing focus on individual barriers and problem solving rather than on the more universal issues covered in a group setting. Therefore, we designed the maintenance intervention to be delivered by telephone.
Beginning 1 month after the final visit for the parent trial (baseline for the maintenance intervention), verbally consented participants received three monthly telephone calls from the same nurse interventionist who delivered the CouPLES intervention. We chose monthly telephone calls because this was the frequency of intervention contact used in the parent intervention. We chose an intervention duration of 3 months with the outcome assessment at 4 months because this was feasible within the study funding period and because we believed that this would be sufficient for evaluating the feasibility of operationalizing the theoretical constructs for communication to patients.
In the CouPLES intervention, patients were asked to make goals and action plans in relation to their choice of diet, physical activity, patient–physician communication, or medication adherence. No patient selected medication adherence, and patient–physician communication was selected only once by each of two patients. Therefore, virtually, all goals and action plans were related to dietary change and physical activity (Voils et al., 2013). During the CouPLES intervention, the nurse interventionist recorded the goals and action plans in a custom intervention software package; these were retrieved for the purpose of this maintenance pilot study.
The maintenance intervention was designed around maintenance strategies described previously. Table 2 shows each construct and the corresponding intervention strategy. During the first call, the interventionist provided participants with an overview of the study, indicating that the focus would be on maintaining a behavior change they had made during the CouPLES study. The interventionist reminded participants of the goals and action plans they had set during the CouPLES study and asked them to rate the importance of continuing each on a 1 to 10 scale (not at all important to very important). Then, the interventionist asked participants to select one behavior to maintain during the upcoming 3 months or helped them select one if they wanted to focus on multiple goals. Participants were asked to focus on only one goal for this pilot study because they were being introduced to new concepts and the combination of the new concepts with multiple goals over a short period of time could have been overwhelming.
Maintenance Constructs and Corresponding Operationization.
In reference to their behavioral maintenance goal, participants were asked why they had selected that goal (i.e., because it was hard or easy to maintain), sacrifices associated with the behavior change, and benefits they had experienced. Participants also discussed outcomes with which they were satisfied. Participants were asked to reflect on their health status before they had made the behavior change and to discuss why they wished to avoid reverting to that state.
The next, and most lengthy, part of the conversation was around enhancing recovery self-efficacy through relapse planning. Participants were asked to think about at least one situation in which they would be tempted to slip back into their old habits and to develop a contingency plan for each situation. When necessary, the interventionist offered suggestions and guided problem solving. Participants were encouraged to take note of any additional situations encountered over the next month so that they could discuss those situations during the next telephone call.
After relapse planning, the interventionist encouraged participants to self-monitor target behaviors to increase the likelihood of maintaining the behavior change. Because goals and action plans were participant driven, there was no target behavior for self-monitoring that would apply to all participants. Therefore, participants identified monitoring strategies appropriate for their goal (e.g., keeping a physical activity diary for the goal of continuing physical activity) and were asked to specify how frequently they would self-monitor.
Social support was not discussed separately but in conjunction with other maintenance strategies, including relapse prevention and self-monitoring. The nurse interventionist asked participants to identify a person from whom they could obtain support, which might have been their spouse or someone else. The second and third intervention calls followed the same general procedure, except that they also included a review of the previous month’s discussion.
Like the CouPLES intervention, the maintenance intervention was delivered using a standardized script presented via a computer software package. The software allowed keyboard input and retrieval of input from the previous month’s call. All intervention telephone calls were recorded and reviewed within 1 week by three investigators (CIV, JMG, and JLS). This allowed the investigative team to monitor fidelity and to evaluate the operationalization of the maintenance constructs. The intervention script was amended whenever the investigators felt that a construct was not well operationalized in the script or that participants did not understand what was asked of them. As these wording changes were slight, they were not expected to affect pre–post changes in outcomes.
To examine the potential impact of this intervention on outcomes, participants returned for outcome assessments 1 month after the final maintenance telephone call (i.e., 4 months post-baseline). The final outcome assessment for the parent trial served as the baseline assessment for the pilot; the same measures were administered at the 4-month follow-up so that we could examine descriptive changes in these variables. Because the previous trial did not include measures of maintenance self-efficacy, recovery self-efficacy, and satisfaction with outcomes, these variables were not assessed in this pilot study. A nonfasting blood specimen was obtained for the direct measurement of serum of low-density lipoprotein cholesterol. Adherence to a cholesterol-lowering diet was assessed with the Block Brief Food Frequency Questionnaire (Block et al., 1986), which provides information on macronutrient intake. Adherence to physical activity was assessed with the Community Healthy Activities Model Program for Seniors (CHAMPS) questionnaire (Stewart et al., 2001). Instrumental spousal support for dietary change was measured with the Evaluation of Spouse Support Scale (Bovbjerg et al., 1995). Spousal support for exercise was measured with the Family Support for Exercise Scale (Sallis, Grossman, Pinski, Patterson, & Nader, 1987). Self-efficacy to follow a low-fat diet was assessed with the revised Eating Self-Efficacy Scale (McCann et al., 1995). Self-efficacy for exercise was assessed with a scale developed and validated for the Stanford Chronic Disease Self-Management Program (Lorig et al., 1996). Satisfaction with the marital relationship was assessed with the Global Satisfaction Subscale of the Relationship Rating Form (Davis & Todd, 1982).
To evaluate feasibility of operationalizing the maintenance constructs for communication with participants, semistructured and open-ended interviews with each participant were conducted by telephone by CIV within 2 weeks of the final-outcome assessment visit. Because some intervention strategies were cognitive in nature (i.e., satisfaction with outcomes and relapse planning) and some were behavioral (i.e., self-monitoring and enlisting social support), we queried recall of discussing the strategies with the interventionist as well as use of each strategy. To evaluate acceptability of the maintenance intervention dose, participants were asked also to comment on the frequency and length of the intervention telephone calls so that dosing changes could be considered for a future trial.
Data Analysis Plan
Feasibility of enrollment and retention were indicated by enrollment and retention rates. For each outcome, means and standard deviations were calculated at baseline and follow-up among participants who had data at both time points. Cohen’s d, calculated from paired t tests, reflected the direction and magnitude of change of each variable. In the current study, positive values indicate an increase from baseline to follow-up, values of 0 indicate no change, and negative values indicate a decrease. If behaviors were maintained, we would expect the follow-up means on the behavior outcomes (i.e., diet, exercise) to be similar to baseline (i.e., end of CouPLES intervention). Positive or negative values of greater magnitude would indicate either further improvement or recidivism, depending on the behavior (e.g., −0.30 reflecting decrease in fat intake would indicate further improvement, whereas −0.30 reflecting decrease in physical activity would indicate recidivism). Interview data were content analyzed (Hsieh & Shannon, 2005) to provide evidence of acceptability. Participant reactions to the intervention were organized for analysis by key maintenance constructs (i.e., satisfaction with outcomes of behavior change, relapse prevention, self-monitoring, and social support).
Results
Feasibility of Enrollment and Retention
Twenty-five patients were approached; of those, 20 were consented and enrolled. Participants were nearly 61 years old on average, 75% were White and 90% were male (Table 3). The majority (85%) had some college education, and 40% were employed full-time.
Demographic Characteristics of Enrolled Participants (n = 20).
Of the 20 patients who agreed to participate, two did not respond to telephone calls. One additional patient withdrew during the first telephone call, indicating he did not need maintenance calls. Another patient experienced an interruption during the first telephone call and did not return subsequent calls from the interventionist. These four participants were similar in race (75% White, 25% Black), education (100% had college education), sex (100% males), and age (average 57 years) to those who remained in the study. The 16 participants who were retained received all three telephone calls, which averaged 22 minutes (range 8-37 minutes). This sample size was considered to be sufficiently information rich—a key criterion of purposeful sampling (Sandelowski, 1995)—to achieve our study aims of assessing the feasibility of enrollment, retention, and communication of maintenance constructs to patients, and of patient acceptability of intervention content.
Process Data
As an example of participant relapse and monitoring plans, data from the first maintenance call are provided in Table 4. When asked why they chose a particular goal, all responded that the goal was difficult to maintain. High-risk situations cited included eating away from home, being tired, emotional issues, and watching television (for diet) and bad weather (for physical activity). Monitoring plans included diary keeping, self-weighing, and checking the refrigerator and cabinets for unhealthy foods. Monitoring frequency ranged from several times per week to once every 2 weeks. All participants named their spouse as the primary support person, although one participant also named his son.
Patient Behavior Maintenance Plans From the First Intervention Telephone Call.
Note. Data are missing for one participant because of software malfunction.
Descriptive Changes in Outcomes
Over the 4-month intervention, the low-density lipoprotein cholesterol level and physical activities were maintained (ds < .12; Table 5). Participants who returned their follow-up Block Brief Food Frequency Questionnaires continued to improve dietary intake of all macronutrients examined except dietary cholesterol (absolute values of d ranging from .59 to .71). Spousal support for exercise decreased (d = −.39), whereas spousal support for diet, self-efficacy for diet and exercise, and satisfaction with the marital relationship were maintained (absolute value of ds ranging from .00 to .04).
Changes in Outcomes From Baseline to 4-Month Follow-up.
Note. M = mean; SD = standard deviation; LDL-C = low-density lipoprotein cholesterol. Baseline was the final assessment in a larger randomized controlled trial of a spousal support intervention for reducing serum LDL-C. Of 20 patients who were enrolled, 4 dropped out. Missing follow-up data were because of the following reasons: did not have blood drawn for LDL-C (n = 1), did not complete the survey (n = 2), and did not complete the Block Brief Food Frequency Questionnaire (n = 5).
d was calculated from a paired t test and is based on the number of participants for whom data were available at both time points; positive values indicate increase over time, whereas negative values indicate decrease over time.
Feasibility of Operationalizing Theoretical Constructs for Optimal Communication With Participants
Perceived Satisfaction With Outcomes
Although participants were asked to list sacrifices and benefits they had experienced from making lifestyle changes, they often spoke of the level of success in changing their behavior (e.g., how much weight they had lost) rather than the outcomes from changing their behavior (e.g., improved stamina). When asked whether they recalled discussing satisfaction with outcomes and whether it was helpful to do so, two participants did not recall discussing this strategy during the intervention telephone calls, even when discussion could be confirmed from the audio-recordings. A 25-year-old woman stated, The reason I said that it wasn’t important (to think of satisfaction with outcomes) is because I barely remember it. After you brought it up, I remembered everything else that she (the interventionist) did, but this thing I forgot, so that means that this was not as important to me.
The remaining participants affirmed that they recalled discussing satisfaction with outcomes and that it helped. A 74-year-old man indicated, I can do things and I’m not as tired as I usually was. . . . I had to change my wardrobe. Got that machine to take up some pants; that was the exciting part for me.
Relapse Planning
Initially, participants were asked to think of one contingency plan for a high-risk situation. To maximize the potential of relapse planning, the script was amended so that participants were asked to think of several contingency plans instead of just one. Additionally, the interventionist suggested high-risk situations that were not mentioned.
In the interviews, participants indicated that relapse prevention was important to their success. Participants reported that they had encountered the situations for which they had planned and that having a plan in place helped them avoid relapse. Additionally, asking participants to think of those situations and practice these new maintenance-oriented skills with the interventionist helped them start to take control of behavior change so that they would be able to drive their own behavioral maintenance forward. A 57-year-old man stated, Before we went on a trip, I was really concerned we were going to be out of town for about eight days. We talked about doing salads and chicken—like a southwestern salad or whatever where you would have the sliced chicken breast on it. And that was really helpful there. . . . So just by adjusting where you eat, and if you couldn’t eat there, how you could make the difference.
Another participant indicated that she would not have engaged in relapse planning without the help of the interventionist: “Even though I came up with it by myself, I probably would not have thought about it without her help.”
Self-Monitoring
Self-monitoring was cited as a successful strategy to maintain weight loss. A 60-year-old man stated, I’ve gone to weighing myself daily and sometimes 2 or 3 times daily. I could kind of monitor the changes from the morning to the evening like that. And I noticed after supper sometimes I will weigh and notice that my weight has gone up, and if I go out and walk and get out and break a good sweat, you know, that it will go back down. So it is something I think that is really good to be aware of, to keep a close eye on the weight because it can fluctuate so fast.
Participants who focused on something other than weight loss maintenance, such as maintaining a new physical activity habit, identified other monitoring strategies, such as recording whether they walked each day.
Enlisting Social Support
Another maintenance strategy, obtaining social support from social network members, was perceived as helpful. Despite the fact that spouses were not actively involved in this maintenance intervention, participants reported that their spouses continued to assist with behavior changes, such as by cooking healthier meals or coparticipating in physical activity. A 69-year-old man stated, I don’t think that I will get to that point where I make goals on my own because my wife, she makes the goals and not only for her, but me. I’m the type of person where I follow the train, but I’m not usually the engine. I’m the caboose.
Acceptability
When asked about the desired frequency of contact, participants reported that contacts would need to be made regularly, with the frequency depending on the individual’s needs. As noted by a 60-year-old man, You know still, it would depend on the individual. For me personally, as long as I am standing in front of a mirror I’m getting reminded of what I need to be doing. But, for some people they might need a call weekly to keep them on the right track. I think it would vary so much with individuals that it would be hard to say.
A 59-year-old man thought that the calls should be unannounced, I think at random times so like two months one time, three months the next time, one month another time, it keeps me guessing when you’re going to call. . . . Because when you plan it you know every two months or every three months or whatever, you know I’ll slide for a month or two, and when you call me I’ll be back on track. Random calls would keep me more on track.
Discussion
Although behavioral interventions focused on maintenance are becoming more common in the literature, few reports of such interventions include details on how the theoretical constructs were operationalized for the intervention. Fewer still distinguish the processes involved in initiation and maintenance (West et al., 2011). The maintenance intervention developed in this pilot study was designed with the explicit intent of distinguishing the processes of initiation and maintenance and exploring the extent to which maintenance-specific constructs were able to be communicated clearly to participants and the extent to which they helped participants maintain health behavior changes.
These results provide some indication about the outcomes that might be maintained from this intervention. Although informationally rich, the sample size does not provide sufficient power to perform inferential statistics, and the effect size estimates may not reflect the true population effect size (Kraemer, Mintz, Noda, Tinklenberg, & Yesavage, 2006). Comparison of relative effect sizes from the study can provide information on which outcomes responded more to the intervention. The largest effect sizes were obtained for outcomes that had the most missing data (i.e., dietary intake), however, clouding interpretation. Because this pilot study was uncontrolled, we are uncertain how much of the maintenance effects were attributable to the intervention. Also, because this study was an extension of a previous study, the measures were predetermined and did not include maintenance constructs such as satisfaction with outcomes or maintenance or recovery self-efficacy.
Despite these limitations, study findings offer important lessons about the feasibility of communicating to patients the constructs theorized to be important for maintenance of health behaviors. For example, participants were able to envision situations in which lapses might occur and plan for those situations, and they found this strategy helpful. Participants also found it helpful to self-monitor, although it was more feasible to self-monitor health status than health-promoting behaviors. For participants who wished to maintain weight loss, frequent self-weighing was an obvious strategy. For participants whose goal was, for example, to refrain from purchasing food items at a store, strategies were less obvious. Self-monitoring using daily diaries is one possibility, but this poses a large burden on participants, and adherence to self-monitoring strategies is likely to dwindle over time if the strategies cannot be routinized. Finally, participants involved their spouses and intended to continue doing so even though this protocol did not actively involve spouse participation. Unclear, however, is whether spousal involvement was a carryover effect from the CouPLES intervention during which spouses were actively engaged in supporting patient behavior change.
Less easy to operationalize for communication to participants was satisfaction with outcomes. In most previous research on behavior change, this variable has been measured as a covariate rather than manipulated (Baldwin et al., 2009). The few studies in which researchers have attempted to enhance satisfaction with outcomes have not led to improved weight maintenance (Finch et al., 2005; Jeffery, Linde, Finch, Rothman, & King, 2006). We revised the telephone script several times to better engage participants in a dialogue about their satisfaction with the outcomes of their health behavior changes. Yet participants had mixed reactions as to whether it was helpful to reflect on the outcomes. Perhaps satisfaction could be made more salient via alternative strategies, such as reviewing pictures of themselves taken prior to making lifestyle changes or examining a list of struggles they experienced before the behavior change. Certainly, priming satisfaction with outcomes may have only transient effects that are no longer present at outcome assessments, or it may be effective only in conjunction with other intervention strategies. More research is needed to examine these possibilities.
Implications for Practitioners
Commonly, intensive behavior change interventions are delivered for a specified amount of time and then withdrawn, leaving patients to their own devices to maintain outcomes. Although some maintenance-specific skills may be incorporated in behavioral interventions, the focus typically is on changing habits rather than maintaining them. Our position is that long-term health behaviors and outcomes could be enhanced if there were an explicit shift to maintenance-specific content and skills building. Qualitative data from this pilot demonstrate that patients have an interest in learning maintenance-specific skills and need the help of skilled practitioners to help them gain confidence in these skills before applying them.
The exact time that a practitioner should switch from initiation-specific to maintenance-specific skills likely varies by behavior and an individual’s personal circumstances. In this study, the shift to maintenance-specific skills occurred after 11 months of involvement in another intervention. In an ongoing weight loss maintenance trial, we transition patients to maintenance-specific skills after 4 months if they successfully lose at least 4 kilograms during initiation. In practice, specific behavior initiation goals could be set that, when reached, mark the shift to maintenance-specific skills. Likely, relapse will occur; thus, practitioners should facilitate self-monitoring plans and relapse thresholds when shifting to maintenance. If relapse has occurred, the practitioner may need to revert to initiation-specific skills to facilitate a return to maintenance. Although it is still untested if these maintenance-specific skills work across behaviors not explored in this pilot, they should translate to other nonaddictive health behaviors.
Finally, this intervention was designed to be lower in cost to facilitate widespread implementation by using telephone as a mode of delivery (Radcliff et al., 2012). The nurse interventionist spent approximately 1 day per month to reach 16 patients. If this telephone-delivered intervention leads to sustained changes in health behavior and/or clinical outcomes in a randomized controlled trial, then larger panels could be followed.
Conclusion
In summary, the construct satisfaction with outcomes was difficult for the interventionist to communicate to participants, whereas relapse planning, self-monitoring, and eliciting social support were successfully communicated to patients. Future randomized controlled trials should be conducted to evaluate maintenance-specific interventions that incorporate key constructs theorized to enhance behavior maintenance.
Footnotes
Acknowledgements
We express our gratitude to Alecia Slade, MSW, for her recruitment and data collection efforts. We also thank Danny Almirall, PhD, and Maren Olsen, PhD, for statistical consultation.
Authors’ Note
Views expressed in this article are those of the authors and do not necessarily represent the Department of Veterans Affairs.
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by a grant from the Health Services and Development Service of the Department of Veterans Affairs (Grant No. PPO 09-310) and with resources and facilities at the Veterans Affairs Medical Center in Durham, North Carolina. Dr. Gierisch was supported by an AHRQ NRSA postdoctoral traineeship at Duke University Medical Center (Grant No. T-32-HS000079 to Dr. Gierisch). Dr. Strauss was supported by a Research Career Development Award–II from the Health Services and Development Service of the Department of Veterans Affairs (Grant No. RCD 06-020 to Dr. Strauss).