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(p. 296) Stages of Change 

(p. 296) Stages of Change
Chapter:
(p. 296) Stages of Change
Author(s):

Paul Krebs

, John C. Norcross

, Joseph M. Nicholson

, and James O. Prochaska

DOI:
10.1093/med-psych/9780190843960.003.0010
Page of

date: 23 September 2019

Individuals seeking psychotherapy do not arrive at a therapist’s doorstep with identical motivation, preparation, or capacity for behavior change. For most practitioners and programs, patients are heterogeneous in terms of their desire and skill to change. Virtually all psychotherapists readily acknowledge that a patient’s readiness for behavior change profoundly influences the process and outcome of treatment.

In the transtheoretical model (TTM), behavior change is conceptualized as a process that unfolds over time and involves progression through a series of five stages: precontemplation, contemplation, preparation, action, and maintenance. At each stage of change, we propose that different change processes and relational stances produce optimal progress. Adapting or tailoring psychotherapy to the individual patient thus requires matching the processes of change and the therapeutic relationship to his or her stage of change. Further, as clients progress from one stage to the next, the therapeutic relationship evolves accordingly.

In this chapter, we review the voluminous research evidence on the stages of change as it applies to psychotherapy. We define the stages of change and related readiness constructs, describe popular measures to assess them, and offer clinical examples and landmark studies. Our meta-analysis is intended to address two specific aims: first, to assess the ability of stages of change and related readiness measures to predict psychotherapy outcomes, and second, to assess the outcomes from psychotherapy studies that matched treatment to specific stages or readiness levels of change. We then analyze potential moderators of the stages–outcome association, address limitations of the research evidence, and review patient contributions and diversity considerations. The chapter concludes with training implications and therapeutic practices for the stages of change in psychotherapy.

Definitions

Stages of Change

Following are brief descriptions of each of the five stages of change. Each stage represents a period of time as well as a set of tasks needed for movement to the next (p. 297) stage. Although the time an individual spends in each stage will vary, the tasks to be accomplished are assumed to be invariant.

Precontemplation is the stage at which there is no intention to change behavior in the foreseeable future. Most patients in this stage are unaware or under-aware of their problems. Families, friends, neighbors, or employees, however, are often well aware that the precontemplators have problems. When precontemplators present for psychotherapy, they often do so because of pressure from others. Usually they feel coerced into changing by a spouse who threatens to leave, an employer who threatens to dismiss them, parents who threaten to disown them, or courts that threaten to punish them. Resistance to recognizing or modifying a problem is the hallmark of precontemplation, which is frequently known to the public by the prejorative term denial.

Contemplation is the stage in which patients are aware that a problem exists and are seriously thinking about overcoming it but have not yet made a commitment to take action. Contemplators struggle with their positive evaluations of their dysfunctional behavior and the amount of effort, energy, and loss it will cost to overcome it. People can remain stuck in the contemplation stage for long periods. In one study we followed a group of 200 smokers in the contemplation stage for two years; the modal response of this group was to remain in the contemplation stage for the entire time of the study without ever moving to significant action (Prochaska & DiClemente, 1983). Serious consideration of the problem characterizes contemplation.

Preparation is a stage that combines intention and behavioral criteria. Individuals in this stage are intending to take action in the next month and are frequently taking small behavioral changes—“baby steps,” so to speak. While they have made some reductions in their problem behaviors, patients in the preparation stage have not yet reached the criterion for effective action, such as abstinence from alcohol abuse or remission of depression. They are intending, however, to take such action in the immediate future.

Action is the stage in which individuals modify their behavior, experiences, and/or environment to overcome their problems. Action involves the most overt behavioral changes and requires considerable commitment of time and energy. Modifications of the problem made in the action stage tend to be most visible and receive the greatest external recognition, leading some to erroneously equate this single stage with the entire change process. Individuals are in the action stage if they have successfully altered the dysfunctional behavior for a period from one day to six months. Modification of the target behavior to an acceptable criterion and overt efforts to change are the hallmarks of action.

Maintenance is the stage in which people work to prevent relapse and consolidate the gains attained during action. For some behaviors, such as addictions, maintenance can last a lifetime; for other behaviors, maintenance can end at three to nine months when patients remain free of the problem behavior and/or consistently engage in a new incompatible behavior. Stabilizing behavior change and avoiding relapse are the hallmarks of maintenance.

(p. 298) Processes of Change

The stages of change represent when people change; the processes of change entail how people change. The processes of change represent an intermediate level of abstraction between metatheoretical assumptions and clinical techniques spawned by those theories. While there are 500-plus ostensibly different psychotherapies (Pearsall, 2011), we have identified only 8 to 10 different processes of change based on repeated principal components analysis. Behavior change is conceptualized in terms of processes or principles, not in terms of specific techniques.

Change processes are overt and covert activities that individuals engage in when they attempt to modify problem behaviors. Each process is a broad category encompassing multiple methods and relationship stances traditionally associated with dissonant theoretical orientations.

Table 10.1 presents the processes of change receiving the most research evidence across 50 behavioral disorders along with their definitions and representative interventions (the process of helping relationships has been deleted from the table). A common and finite set of change processes has been repeatedly identified across these diverse problems (Prochaska et al., 1985).

Table 10.1. Definitions and Representative Interventions of the Processes of Change

Process of Change

Definition: Interventions

Consciousness Raising

Increasing information about self and problem: observations, confrontations; interpretations, awareness exercises, bibliotherapy

Self-Reevaluation

Assessing how one feels and thinks about oneself with respect to a problem: value clarification, imagery, corrective emotional experience

Dramatic Relief/

Experiencing and expressing feelings about one’s

Emotional Arousal

problems and solutions: psychodrama, cathartic work, grieving losses, role-playing, two-chair work

Self-Liberation

Choosing and commitment to act or belief in ability to change: decision-making methods, motivational interviewing, commitment-enhancing techniques

Counterconditioning

Substituting alternative or incompatible behaviors for problem: relaxation, desensitization, assertion, cognitive restructuring, behavioral activation

Stimulus Control

Avoiding or controlling stimuli that elicit problem behaviors: restructuring one’s environment, avoiding high-risk cues, fading techniques, altering relationships

Reinforcement

Rewarding one’s self or reward by others for making changes: contingency contracts, overt and covert reinforcement, self-reward

(p. 299) Stages × Processes

The TTM posits that different processes of change are differentially effective in certain stages of change. In general terms, change processes traditionally associated with the experiential, cognitive, and psychoanalytic persuasions are most useful during the earlier precontemplation and contemplation stages. Change processes traditionally associated with the existential and behavioral traditions, by contrast, prove most useful during action and maintenance.

Consciousness raising helps clients progress from precontemplation to contemplation. In particular, patients need to increase their awareness of the advantages of changing and the multiple benefits of psychotherapy. They also typically benefit from enhanced awareness of themselves, their disorders, and their defenses.

Contemplation can be a safe haven for clients and therapists alike. Clients are intending to make major changes, but not right now. First they need to continue to increase consciousness. Reflecting, feeling, and re-evaluating how they have been and how they might become can be hard work at times. But it can also prove meaningful and even fun. And such sharing builds a therapeutic bond that can be hard to let go. Who wants to give up such a close relationship? How can you fail as a therapist by having such a good therapeutic relationship? The answer is by allowing your client to stay stuck in contemplation.

The process of dramatic relief (emotional arousal) can include anticipatory grieving, the sadness and loss of letting go of behaviors and relationships that no longer work. Dramatic relief can also include facing the fear, guilt, or regret that would come from not changing. If a patient clings tenaciously to safe and secure patterns that are also self-defeating and self-destructive, how will he or she feel in the future?

As people progress from precontemplation to contemplation, they rely more on the process of self-reevaluation. “How do I think and feel about myself as an angry or depressed person? How will I think and feel about myself as a more active and mindful person?” Reevaluation entails a courageous assessment of how one experiences and prizes oneself with respect to the problem. As patients progress into the preparation stage, they use more of self-liberation and its numerous methods. This is the belief that they have the ability to change their behavior and the commitment to act on that belief.

During action, clients receiving adequate reinforcement for their efforts secure better treatment outcomes. Clients may expect to be reinforced by others more than others will reinforce them. Thus clients need to be prepared to depend more on self rather than social reinforcements, including the psychotherapist.

Patients will learn and practice counterconditioning (reciprocal inhibition) as they replace healthier behaviors for their problem behaviors. This process includes the classic reciprocal inhibition methods: assertion to counter passivity, relaxation to replace anxiety, cognitive substitutions instead of negative thinking, exposure to counteravoidance, acceptance in place of hypercontrol.

As clients progress into the maintenance stage, they do not have to work as hard but they have to apply change processes to prevent relapse. They particularly have to be prepared for the situations that are most likely to induce relapse. Stimulus control in its (p. 300) multiple ways assist patients in avoiding or controlling triggers (emotions, thoughts, places, people) that elicit problem behaviors. Across numerous studies, stimulus control is the change process least frequently used by psychotherapists and patients alike (Prochaska & Norcross, 2018).

But for all patients, psychotherapy will probably terminate before the problem has completely resolved. This is one reason clinicians and clients alike can feel anxious about termination. They both know that under certain conditions the risk of relapse is real. Of course, clients can return for further treatment if they lapse or relapse. They can analyze what they did right, what mistakes they made, and what they need to do differently to keep moving ahead.

Measures

Multiple assessment devices have been developed over the years to assess a person’s stage of change or “readiness to change.” The measures vary in format (e.g., questionnaires, algorithms, ladders, and interviews) as well as in specificity (e.g., generic measures for multiple problems and disorder-specific measures).

The most frequent measure in psychotherapy research has been the University of Rhode Island Change Assessment (URICA; McConnaughy et al., 1989). This 32-item questionnaire yields separate scores on four continuous scales: Precontemplation, Contemplation, Action, and Maintenance (precontemplators score high on both the Contemplation and Action scales). Scores for each stage range from 8 to 40, with higher scores indicating stronger endorsement of each subscale. Psychometric evaluation of the URICA or the Stages of Change scale, as it is widely known, demonstrates a stable four-factor structure (Pantalon et al., 2002) and subscale consistency (Cronbach’s alphas .74–.88 [Petry, 2005]; 88–.89 [McConnaughy et al., 1983]).

Items used to identify precontemplation include “As far as I’m concerned, I don’t have any problems that need changing” and “I guess I have faults but there’s nothing that I really need to change.” Contemplators endorse such items as, “I have a problem and I really think I should work on it” and “I’ve been thinking that I might want to change something about myself.” Patients in the action stage endorse statements like, “I am really working hard to change” and “Anyone can talk about changing; I am actually doing something about it.” Representative maintenance items are, “I may need a boost right now to help me maintain the changes I’ve already made” and “I’m here to prevent myself from having a relapse of my problem.”

Other measures of change readiness include the Stages of Change and Treatment Eagerness Scales (SOCRATES), developed for measuring readiness for change with regard to problem drinking as an alternate measure to the URICA (Miller & Tonigan, 1996). This 19-item measure produces three continuous scales: Ambivalence, Recognition, and Taking Steps, which represent continuously distributed motivational processes. The SOCRATES has been found to be related to quit attempts for smoking cessation (DiClemente et al., 1991), alcohol use (Isenhart, 1997; Zhang et al., 2004), and drug use (Henderson et al., 2004).

(p. 301) In fewer research studies but more frequently in clinical practice, the stages are assessed using a series of questions that result in a discrete categorization. The practitioner asks if patients are seriously intending to change the problem in the near future, typically within the next six months. If not, they are classified as precontemplators. Clients who state that they are seriously considering changing the problem behavior in the next six months are classified as contemplators. Those intending to take action in the next month are in the preparation stage. Clients who state that they are currently changing their problem are in the action stage.

Clinical Examples

The following exchange from a psychotherapy session demonstrates the relational stance a transtheoretical therapist (Prochaska) would probably adopt with a patient in the precontemplation stage. The client is a 32-year-old stockbroker in precontemplation for chronic cocaine abuse. The stage of change dimension was briefly outlined and then the client, “Donald,” was given feedback that his assessment indicated he was in the precontemplation stage. Did he concur? “Yeh, probably.”

Therapist: We know that individuals in the precontemplation stage often feel coerced into entering therapy rather than being there by choice. What pressures were there on you to seek psychotherapy?

Client: Lots of people have been on my back. My girlfriend, my mother. My job may be in jeopardy. They all think it’s caused by cocaine. But I’ve been using it for years and it’s never been a problem.

Therapist: How do you react when people pressure you to quit cocaine when you’re not ready?

Client: I get angry. I tell them to mind their own business.

Therapist: You get defensive.

Client: Sure, wouldn’t you? Nobody likes to be told what to do, to be treated like a kid.

Therapist: How would you react if I told you to quit cocaine?

Client: I would get angry. I would tell myself you’re just like all the others—think you know better than me how to run my life.

Therapist: Would you want to drop out of therapy?

Client: Probably. I don’t react well to being controlled.

Therapist: I appreciate you sharing your reactions with me. Let me share my main concern. I am concerned that you might drop out of therapy before I have a chance to make a significant difference in your life.

I don’t want to coerce or control you. I do want to help you to be freer to do what is best for your life. So will you let me know if I am pressuring you or parenting you?

Client: You’ll know.

Historically, confrontation was one of the recommended ways of relating to defensive and resistant clients. By confronting patients’ defenses and resistance, therapists (p. 302) expected to break through the denial and other defenses. Research has consistently shown, however, that a confrontational style of relating drives many patients away and increases premature termination (Miller & Rollnick, 2012). Motivational interviewing, by contrast, rolls with patient resistance and typically demonstrates large impacts in a small number of sessions for precontemplators and contemplators (Lundahl et al., 2010).

Later, in the same session, the psychotherapist adopts an affirming, Socratic style and relies primarily on consciousness-raising methods that the research evidence suggests will assist a patient to progress from precontemplation to contemplation. This entails increasing awareness of the advantages of changing and the multiple benefits of sticking with treatment.

Therapist: We know people are likely to complete therapy if they appreciate its many benefits. Donald, how do you think people benefit from therapy?

Client: It makes the therapist better off.

Therapist: That’s good! And how about the client?

Client: I expect it helps them solve their problems.

Therapist: That’s true. And would that help them to feel better about themselves?

Client: Yeh, it should.

Therapist: And would that improve their moods?

Client: Sure.

Therapist: Would that improve their relationships?

Client: It should.

Therapist: And be more open and less defensive.

Client: I can see that.

Therapist: And do better in their job and make more money.

Client: I don’t know about that.

Therapist: It’s true. How about we make a deal. If your income goes up 10%, my fee goes up 10%?

Client: That would be worth it.

Therapist: You might not believe this, but there’s only one other thing you could do for an hour a week that would give you more benefits than therapy.

Client: What’s that?

Therapist: I’m not going to tell you because you might invest in that instead. (Client laughs)

The psychotherapist’s stage-matched relational stance can be characterized as follows. With patients in precontemplation, often the optimal role is like that of a nurturing parent joining with a resistant and defensive youngster who is both drawn to and repelled by the prospects of becoming more independent. With clients in contemplation, the therapist stance is akin to a Socratic teacher who encourages clients to achieve their own insights into their condition. With clients in the preparation stage, the stance is more like that of an experienced coach who has been through many crucial matches and can provide a fine game plan or can review the participant’s own plan. With clients (p. 303) progressing into action and maintenance, the psychotherapist becomes more of a consultant who is available to provide expert advice and support when action is not progressing smoothly. As termination approaches in lengthier treatment, the therapist is consulted less often as the patient experiences greater autonomy and enhanced ability to live a life free from previously disabling problems.

Landmark Studies

The earliest studies on the stages of change involved a longitudinal examination of self-change of tobacco smokers (Prochaska & DiClemente, 1982, 1983). The five stages were identified within an integrative model of change, and that model was tested on 872 smokers. The processes of change were expected to receive differential emphases during particular stages of change. Results indicated that self-changers: (a) used the fewest processes of change during precontemplation, (b) relied on consciousness raising during the contemplation stage, (c) emphasized self-reevaluation in both contemplation and action stages, (d) employed self-liberation and reinforcement management during the action stage, and (e) used counterconditioning and stimulus control the most in both action and maintenance stages. These patterns of stage matching among self-changers have been subsequently replicated in hundreds of studies across disorders. These 1982 and 1983 articles launched the vocabulary and utility of the stages of change, initially in addictive disorders and self-change and then eventually in mental disorders and psychological intervention.

One of the earliest stage of change studies in psychotherapy concerned patient continuation and dropouts. Approximately one-quarter of patients prematurely discontinue psychotherapy (Swift & Greenberg, 2012); however, the characteristics of these dropouts have not been reliably known. In one pivotal study (Brogan et al., 1999), premature termination was predicted using traditional predictors—client characteristics and problem characteristics, such as chronicity and intensity. These variables, however, had zero ability to predict therapy dropouts. When the stages and processes of change were used, 93% of the premature terminators—as opposed to therapy continuers and early but appropriate terminators—were correctly identified. The stage of change profile of the 40% who dropped out of therapy was that of precontemplators. The stage profile of the 20% who terminated quickly but appropriately was that of people in the action stage. The stage profile of the therapy continuers was that of contemplators. In sum, the stage measure demonstrated its ability to identify and predict premature dropouts.

In a study of dropout from drug treatment, the greater readiness for treatment as measured by the SOCRATES was associated with reduced program dropout whereas demographic variables (age, race, sex) were not predictive (Evans et al., 2009). In another study of resident drug treatment retention, higher scores on the Contemplation, Action, and Maintenance subscales of the URICA were associated with staying in the program at least 30 days, whereas higher scores in the Precontemplation subscale was associated with early termination (Choi et al., 2013). (These and other studies predicting psychotherapy dropouts and outcomes are included in this chapter’s meta-analysis.)

(p. 304) In another psychotherapy study involving male perpetrators of partner violence, stage-tailored treatments were added to mandatory weekly group therapy. At the six-month follow-up with the first 200 participants, the addition of stage matching produced significant reduction in violence compared to the weekly group counseling alone. In the stage-matched condition, only 3% of the female partners of the perpetrators had been beaten in the past six months compared to 23% of the women whose partners received only the group therapy (Levesque et al., 2012). As well, about twice as many perpetrators had progressed to the action or maintenance stage during group therapy. Matching treatments to patients’ stage of change has been found to decrease dropouts, improve retention, and boost outcomes in multiple disorders, including interpersonal violence.

A final landmark study reviewed here illustrates the TTM goal of increasing treatment impacts with entire populations. This large study, adopting the World Health Organization’s definition of health as more than the absence of physical or mental illness, aimed treatment at enhancing emotional well-being (Prochaska et al., 2012). The intervention reached nearly 4,000 people in 39 states in the United States. The adult sample averaged four chronic conditions and four risk behaviors, such as inadequate exercise, unhealthy eating, depression, and poor stress management (Prochaska et al., 2012). The participants also scored well below national averages on emotional and physical well-being, and the majority were struggling rather than thriving. The success rates for TTM-tailored telephone counseling, a TTM-tailored online program, and the control condition were respectively 57%, 47%, and 37% for exercise; 75%, 65%, and 53% for stress management; and 31%, 26%, and 21% for healthy eating, which was not treated. Those effectiveness patterns were clear and consistent for target behaviors.

In addition, the brief stage-matched interventions produced large impacts on overall well-being. Comparing the TTM treatments to controls showed well-being increased about twice as much for those using counselors and two-thirds as much for those using the online program. It was striking that the percentage of patients thriving almost doubled for the counseling condition (67% vs. 34% in control). This study exemplifies how psychotherapy can raise the bar to help the population to feel better and live better.

Results of Previous Meta-Analyses

Empirical research on the stages of change has taken a number of tacks over the past 35 years (for a review, see Prochaska & Norcross, 2010), resulting in a vast literature. In this section, we review the results of earlier meta-analyses on the integration of the stages and processes, the ability of the stages of change to predict psychotherapy outcomes, and the efficacy of tailoring treatments to the stages.

Integrating Stages × Processes

Years of research in behavioral medicine and psychotherapy converge in showing that different processes of change are differentially effective in certain stages of change. (p. 305) A meta-analysis of 47 cross-sectional studies examined the relations of the stages and the processes of change (Rosen, 2000). The studies involved smoking, substance abuse, exercise, diet, and psychotherapy. The mean effect sizes (d) were approximately .70 for variation in cognitive-affective processes by stage and .80 for variation in behavioral processes by stage, both moderate to large effects. Effect sizes for stages by processes did not vary significantly by the problem treated. For the five studies that examined the change processes in psychotherapy, behavioral processes peaked in action while cognitive-affective processes peaked in the contemplation or preparation stages.

Predicting Psychotherapy Outcomes

In the previous edition of this volume, we conducted a random-effects meta-analysis of 39 psychotherapy studies involving 8,238 patients (Norcross et al., 2011). The stages of change reliably predicted psychotherapy outcomes (d = .46). These results indicate that patients beginning in the preparation and action stages (or with greater readiness scores) do better than those beginning in precontemplation or contemplation (or those with lower readiness to change scores). These studies in this meta-analysis, however, did not tailor interventions by assessing stage of change and providing different combinations of intervention components by stage.

Tailoring Treatments to Stages

A large number of psychosocial treatments have been tailored to stage of change or readiness for change. These have primarily been population-based studies delivered via computer, mail, or phone, with a focus on health behaviors. Such interventions have assessed and provided specific feedback by stage of change and other constructs, such as self-efficacy. Results of these studies clearly show the effectiveness of tailoring or matching psychological interventions to the patient’s stage of change.

We conducted a meta-analysis on 87 prospective, tailored interventions delivered via computer or mail across smoking cessation, physical activity, healthy diet, and mammography screening (Krebs et al., 2010). The mean effect size (d) of .18 (95% confidence interval [CI] = .16–.20) represents a 39% increase (odds ratio = 1.39) over the nontailored intervention or minimal care conditions and indicates a small to medium-size effect for population-based interventions (Rossi, 2002). The subset of studies that intervened on smoking cessation, for instance, resulted in an absolute increase of 6% in quit rates, a rate comparable to that observed with four to eight individual in-person counseling sessions (Fiore, 2008). Hence, use of stage tailoring proved more effective than non-tailoring for health behaviors.

These stage-matching studies, however, did not include face-to-face psychotherapy nor did they address the disorders most commonly treated by mental health professionals. Thus, in addition to updating our meta-analysis on the ability of the stages of change to predict psychotherapy outcomes, we undertook a meta-analysis specifically focusing on stage matching in psychotherapy.

(p. 306) Meta-Analytic Review: Stages Predicting Outcome

Here, we present the results of a meta-analysis, updated from the last edition of this book, performed to gauge the effect of the stages of change on psychotherapy outcomes.

Search Strategy and Criteria

A medical librarian experienced in systematic reviews (Nicholson) conducted searches in PubMed/MEDLINE, EMBASE (Ovid), PsycINFO (Ovid), CINAHL (Ebsco), Cochrane CENTRAL (Ovid), and Web of Science. The search strategies included MeSH and Emtree terms as well as keywords to reflect the three main concepts: stages of change (e.g., readiness, motivation, as well as the measures of these constructs, such as URICA, SOCRATES, Contemplation Ladder), psychotherapy (e.g., counseling, therapy, intervention, psychosocial treatment), and individualized psychotherapy (e.g., stages of change, matching, tailored, treatment adaptation). To locate studies that may have employed similar terms, we also conducted a forward search for articles that cited identified studies, examined reference lists from published studies, and searched for articles published by authors of studies deemed for inclusion. We also tracked citations of selected references and hand-searched relevant sources to identify studies that had not been identified by database searches.

A restriction of the search strategies concerned publication dates. We searched for studies published from 2009 onward since the earlier meta-analysis searched from 2009 (Norcross et al., 2011). Otherwise, there were no language or other limits used in the search. A total of 1,872 citations were retrieved from across the six databases. After computerized de-duplication, the number of unique citations was 1,155.

Studies selected for the meta-analysis met the following criteria, which were consistent with inclusion criteria for other meta-analytic reviews in this volume: (a) studies reported results of behavioral/psychological face-to-face treatment, (b) treatment was provided by mental health professionals, (c) patients had a diagnosable mental disorder (Diagnostic and Statistical Manual of Mental Disorders or International Classification of Diseases criteria), (d) treatments consisted of at least three group or individual sessions, (e) readiness to change measured prior to treatment was used to tailor or predict treatment outcome, and (f) sufficient statistical information was available to calculate an effect size. Studies were excluded if they (a) only used a computerized program to provide feedback, (b) did not involve a mental health professional, (c) only involved health behavior change counseling, and (d) did not include a measure of readiness to change.

Abstracts of all 1,155 references were examined by two reviewers for possible inclusion according to the aforementioned inclusion criteria. Of these, 145 papers were chosen for full text review as they potentially could meet criteria upon further review. From the 145 studies, the reviewers excluded 108 largely for study design not meeting criteria, insufficient information to code effect size, no measure of readiness to change, and no translation available in English. Figure 10.1 presents a flowchart of study selection and the reasons for excluding studies. (p. 307)

In the end, 37 new studies met the inclusion criteria and were analyzed in the present review. Along with the 39 studies from the previous meta-analysis, that resulted in a total of 76 studies for analysis.

Methodological Decisions

The primary database was created and the results were analyzed using the Comprehensive Meta-Analysis software package (Biostat, 2006). Results reported as correlations (r), mean differences (F or t), or tests of variance (X2) were transformed to Cohen’s d (Lipsey & Wilson, 2001). Each obtained effect size estimate was weighted by the inverse of the variance of the estimate, which gives greater weight to studies with better estimates (for the most part, studies with larger sample sizes). If insufficient information was reported for effect size calculation, the study was excluded. Twenty-six studies were randomized controlled trials (RCTs) while the remainder used a one-group pre–post design. Regardless of study design, all effect sizes were calculated as the relation between pretreatment stage of change and treatment outcome(s).

We employed a random effects model. This model assumes both study-level error and variability among studies due to sampling of studies from a population of studies. This model enables generalization to a population of studies.

Publication bias, the tendency for significant study results to be reported more often than nonsignificant results, can upwardly bias effect size estimates in meta-analysis. We assessed mean effects for degree of publication bias using two techniques: fail-safe N and trim and fill. Fail-safe N calculates the number of unpublished studies with a null effect size that would be needed to reduce the overall effect to nonsignificance. (p. 308) Trim and fill (Duval & Tweedie, 2000) assesses the symmetry of a plot of effect size by sample size (funnel plot) under the assumption that when publication bias exists, a disproportionate number of studies will fall to the bottom right of the plot. This technique then determines the number of asymmetrical outcomes, imputes their counterparts to the left, and estimates a corrected mean effect size.

The 76 studies represented a variety of diagnoses and outcome measures with some studies reporting more than one outcome (e.g., substance use and treatment dropout). To ensure statistical independence of outcomes, when studies reported more than one outcome, an overall mean effect size per study was included for calculating the overall mean effect (using formulas by Borenstein et al., 2009).

To determine if moderator analysis was appropriate, variability between studies was assessed via the Q test that employs weighted data and compares within- and between-group heterogeneity using the Q statistic. A significant Q test indicates that there is sufficient variability among the effect sizes of the studies to look for moderators that could explain the variability.

Continuous moderators were examined using meta-regression. We conducted moderator analyses for patient characteristics (adolescent vs. adult study populations; ≥60% minority participants vs. not; percentage of female participants) and treatment features (inpatient vs. outpatient setting; use of a treatment manual vs. not; number of treatment sessions; theoretical orientation; RCT vs. nonrandomized design). We also present effect sizes by psychotherapy outcomes: adherence to treatment, eating disorder outcomes, substance use outcomes, and mood disorders/relational distress.

The Studies

Table 10.2 summarizes the attributes of the 76 studies, encompassing 21,424 psychotherapy patients. We included data only from each study’s final assessment, most of which were immediately upon treatment completion. Nine studies concerned treatments for adolescents (ages 13–18), while the others focused on adults (18+). Sample sizes (N) ranged from 30 to 1,588, with an average of 278 participants at recruitment and a 73% retention rate at follow-up. Most samples (k = 41) were comprised of primarily White participants (>60%), 6 had primarily African American participants (>60%), 10 studies recruited a racially mixed sample, and 16 did not report racial/ethnic makeup. (Note that k denotes the number of studies, in contrast to N, which refers to the number of participants in a study.) Patients on average were 45% female (and ranged from 0% to 100%). Twenty-five studies conducted interventions in an inpatient setting. The number of treatment sessions ranged from 1 (in some conditions) to 30 with 13 being the mean. Thirty-one studies did not report the number of sessions (most of these provided inpatient treatment). Thirteen studies reported using a treatment manual, with cognitive-behavioral treatment the most common (k = 36), followed by motivational enhancement (k = 9) and a combination of other orientations (k = 14). The most frequent readiness measures were the URICA (k = 46) and the SOCRATES (k = 10). (p. 309)

Table 10.2. Summary of Studies and Samples (k = 76) Included in the Meta-Analysis

Characteristic

k

%

Country

    United States

46

60

    Canada

9

12

    Australia

3

4

    Europe

16

21

    Africa

2

3

Study Design

    Single group pre–post

50

66

    Randomized controlled trial

26

34

Patient Age

    Adult (18+)

67

88

    Adolescent (13–17)

9

12

Patient Race/Ethnicity

    White (>60% of sample)

41

54

    Mix (none greater than 60% of sample)

10

13

    African American (>60% of sample)

6

8

    Data not reported

16

21

Treatment Setting

    Outpatient

49

64

    Inpatient

25

33

    Not reported

2

3

    Treatment Manual Used

13

17

Number of Treatment Sessions

    <10

17

22

    10–19

19

25

    20+

9

12

    Data not reported

31

41

Treatment Orientation

    Cognitive-behavioral

36

47

    Motivational enhancement

9

12

    12-step

5

7

    Other

12

16

    Data not reported

14

18

Readiness Measure

    University of Rhode Island Change Assessment

46

61

    Stages of Change Readiness and Treatment Eagerness Scale

10

13

    Anorexia Stages of Change Questionnaire

4

5

    Other

16

21

(p. 310) Effect Size

The 76 studies reported 137 separate data points, as a number of studies reported associations between stage of change and multiple outcome variables (depression, anxiety, etc.). Results of the individual studies are summarized in Table 10.3.

Table 10.3. Effect Sizes by Study

Study

Primary Diagnosis

Readiness Measure

N

d

SE

95% CI

Lower

Upper

Abd Elbaky et al., 2014

Eating disorder

ANSOCQ

63

.24

.26

–.27

.75

Alexander & Morris, 2008

Domestic abuse

URICA

210

.45

.20

.07

.84

Alexander et al., 2010

Domestic abuse

URICA

528

.12

.12

–.12

.36

Algars et al., 2015

Eating disorder

MSCARED

32

.19

.37

–.54

.92

Allen, 1998

Alcohol abuse

URICA

806

.28

.07

.14

.42

Alosso, 2012

Obsessive-compulsive disorder

URICA

148

.18

.20

–.21

.56

Ametller et al., 2005

Eating disorder

ANSOCQ

70

.34

.12

.10

.58

Bachiller et al., 2015

Substance abuse

URICA

46

.59

.33

–.05

1.24

Bates, 2014

Eating disorder

RMI + MSCARED

46

1.09

.35

.41

1.77

Bauer et al., 2014

Alcohol dependence

SOCRATES

805

.03

.01

.01

.06

Berry, 2012

Mixed diagnoses

URICA

163

.35

.16

.03

.66

Blanchard et al., 2003

Substance abuse

URICA

252

.16

.13

–.10

.42

Boswell et al., 2012

Anxiety disorders

URICA

37

2.20

.58

1.06

3.34

Brodeur et al., 2008

Domestic abuse

URICA-DV

302

.11

.12

–.12

.34

Callaghan et al., 2005

Substance abuse

URICA

130

.74

.19

.37

1.11

Callaghan et al., 2008 (Budney et al., 2000)

Substance abuse

URICA

60

.18

.40

–.61

.97

Callaghan et al., 2008 (Budney et al., 2006)

Substance abuse

URICA

90

.93

.31

.33

1.52

Carpenter et al., 2002

Substance abuse

URICA

174

.58

.17

.25

.92

Castro et al., 2011

Eating disorder

BNSOCQ

40

.85

.41

.05

1.66

Choi et al., 2013

Substance abuse

URICA

1317

.08

.03

.02

.14

Chung & Maisto, 2009

Substance abuse

Contemplation Ladder

142

.03

.23

–.43

.49

Clarke et al., 2012

Substance abuse

URICA

138

.41

.19

.03

.78

Connors et al., 2000a

Alcohol abuse

URICA

1187

.49

.08

.34

.65

Connors et al., 2000b

Alcohol abuse

URICA

1187

.52

.10

.33

.70

Cook et al., 2015

Alcohol abuse

URICA

590

.62

.15

.33

.91

Dale et al., 2011

Alcohol abuse

RCQ (TV)

742

–.02

.01

–.03

.00

Demmel et al., 2004

Alcohol abuse

SOCRATES

350

.58

.13

.33

.83

Derisley et al., 2000

General

URICA

60

1.30

.32

.68

1.92

Dove, 2016

Depression

SOCQ

439

.04

.15

–.25

.33

Dozois et al., 2004

Anxiety

URICA

81

.68

.24

.20

1.15

Eckhardt et al., 2008

Domestic abuse

URICA-DV

199

.72

.17

.39

1.04

Emmerling et al., 2009

Mixed diagnoses

URICA

93

.63

.22

.20

1.06

Evans et al., 2009

Substance abuse

SOCRATES

1588

.51

.04

.43

.58

Field et al., 2009

Alcohol abuse

URICA

831

–.04

.11

–.25

.17

Freyer et al., 2009

Alcohol abuse

RCQ (TV)

538

.37

.15

.06

.67

Frias et al., 2016

Dysthymia

URICA

61

.70

.30

.11

1.28

Geller et al., 2004

Eating disorder

RMI

60

.75

.36

.04

1.45

Genders et al., 2010

Eating disorder

Motivational ruler

30

1.04

.49

.07

2.01

Gomez et al., 2012

Problem gambling

URICA

191

.82

.16

.51

1.13

Gossop et al., 2007

Substance abuse

SOCRATES

1075

.90

.08

.74

1.06

Gouse et al., 2016

Substance abuse

SOCRATES

986

.37

.18

.01

.72

Haller et al., 2004

Substance abuse

URICA

75

.87

.26

.36

1.38

Henderson et al., 2004

Substance abuse

URICA

96

.68

.22

.25

1.10

Hewes & Janikowski, 1998

Alcohol abuse

SOCRATES

58

2.49

.60

1.31

3.68

Hillen et al., 2015

Eating disorder

ANSOCQ

40

1.10

.45

.22

1.98

Hunt et al., 2006

Posttraumatic stress disorder and alcohol dependence

URICA

42

.68

.35

.00

1.36

Ilagan et al., 2015

Mixed diagnoses

Self-report scale

331

.61

.23

.16

1.07

Isenhart 1997

Alcohol abuse

SOCRATES

125

.69

.19

.32

1.07

Jakupcak et al., 2013

Mixed diagnoses

URICA

104

.78

.21

.36

1.19

Kerns et al., 2005

Pain

Pain SOC

68

.00

.27

–.52

.52

Kinnaman et al., 2007

Alcohol abuse

CSOC

120

.72

.20

.34

1.11

Lewis et al., 2009

Depression

Bellis SOC

332

.30

.12

.08

.53

Lewis et al., 2012

Mixed diagnoses

SOCQ

173

.32

.16

.01

.62

Litt et al., 2013

Marijuana dependence

RTCQ

215

.27

.14

–.01

.54

Mahon et al., 2015

Mixed diagnoses

URICA

124

.29

.35

–.39

.97

Mander et al., 2013

Eating disorder

URICA

35

.18

.40

–.61

.97

McKay et al., 2013

Substance abuse

URICA

268

.46

.14

.18

.74

Mitchell, 2006

Substance abuse

SOCRATES

357

.63

.11

.41

.85

Myers et al., 2016

Substance abuse

SOCRATES

335

.27

.15

–.02

.57

Pantalon et al., 2002

Substance abuse

URICA

117

.46

.20

.06

.85

Pantalon et al., 2003

Psychiatric inpatients

URICA

120

–.20

.09

–.38

–.01

Petry et al., 2005

Gambling disorder

URICA

234

.47

.15

.17

.78

Ronan et al., 2010

Violence

SCQ

262

.14

.16

–.17

.45

Rooney et al., 2005

Posttraumatic stress disorder

URICA

50

.63

.31

.03

1.23

Scott & Wolfe, 2003

Domestic abuse

URICA

194

.59

.21

.19

.99

Sherman et al., 2016

Substance abuse

SOCRATES

175

–.05

.25

–.55

.44

Smith et al., 1995

General therapy

URICA

74

1.84

.33

1.20

2.48

Soberay et al., 2014

Gambling

URICA

77

.26

.24

–.22

.74

Solem et al., 2016

Obsessive-compulsive disorder

URICA

121

.30

.19

–.07

.66

Soler et al., 2008

Borderline personality disorder

URICA

60

.54

.61

–.67

1.74

Stotts et al., 2003

Alcohol and tobacco abuse

URICA

115

.49

.24

.03

.96

Tambling & Johnson, 2008

Relationship issue

URICA

469

–.13

.11

–.35

.08

Treasure et al., 1999

Eating disorder

URICA

125

.68

.29

.11

1.24

Wade et al., 2009

Anorexia

ANSOCQ

47

.31

.31

–.29

.91

Willoughby et al., 1996

Alcohol abuse

URICA

152

–.15

.17

–.49

.18

Zemore et al., 2014

Substance abuse

URICA and TREAT

200

–.02

.20

–.42

.38

Overall Effect Size

.41

.03

.34

.48

Note. SE = standard error; CI = confidence interval; URICA = University of Rhode Island Change Assessment; SOCRATES = Stages of Change Readiness and Treatment Eagerness Scale; RMI = Readiness and Motivation Interview.

The mean effect size was d = .41 with a 95% CI of .34 to .48 (range –.45 to 2.49), Q(75) = 786.62, p < .001. Analysis of publication bias indicated a fail-safe N of 8,991.

By convention (Cohen, 1988), a d of .41 indicates a medium effect, demonstrating that the stages of change is robustly associated with and predictive of outcomes in psychotherapy. That is, the amount of progress clients make during treatment tends to be a function of their pretreatment stage of change. For example, an intensive action- and maintenance-oriented smoking cessation program for cardiac patients achieved success for 22% of precontemplators and 43% of contemplators; 76% of those in action or prepared for action at the start of the study were not smoking six months later (Ockene et al., 1992).

Comparison to Previous Meta-Analysis

The results of the present meta-analysis parallel and extend those obtained eight years earlier. That meta-analysis was based on fewer studies and produced an average weighted d of .49 (95% CI = .35–.58). The present effect size of .41 (95% CI = .34–.48) is in the same neighborhood as the previous meta-analysis but has a slightly lower mean than found earlier.

Potential Moderators

The significant Q test for our meta-analysis indicated that there was sufficient variability among the effect sizes of the studies to examine moderators that might explain this variability. We conducted moderator analyses for patient characteristics, treatment features, and outcome measures.

With regard to patient characteristics, we found no statistically significant difference between adolescent and adult populations (p = .96), nor by race/ethnicity (p = .90). Effect size was not related to the relative number of male/female patients (p = .37).

With regard to treatment features, we found no differences in effect size between inpatient (k = 25, d = .42) and outpatient treatment settings (k = 49, d = .38, p = .55), between treatments that used a manual (p = .39) and those that did not, nor by number of treatment sessions (p = 1.0). For studies reporting primary theoretical orientation, the effect sizes were similar (p = .23): 12-step programs (k = 5, d = .42), cognitive-behavioral treatment (k = 32, d = .42), motivational enhancement (k = 7, d = .18), and combination (k = 14, d = .33). Randomized trials (k = 26, d = .33) did not differ from pre–post designs (k = 50, d = .43, p = .19).

We analyzed the effect size by type of treatment outcome. For adherence to treatment/premature dropout (k = 36) the mean effect size was d = 0.36 (95% CI = .26–.47). Nine studies assessed the relation between baseline readiness to change and eating (p. 311) (p. 312) (p. 313) (p. 314) (p. 315) disorder outcomes. Studies employed the Eating Disorders Inventory, measures from the European COST Action B6 Project, and count of relapse to assess outcomes. The average effect size was d = .59 (95% CI = .34–.85). Twenty-two studies predicted substance use outcomes using baseline readiness to change. The most frequently used outcome measures were the Addiction Severity Index, Severity of Dependence Scale, Timeline Followback, and the Alcohol Use Questionnaire. The mean effect size was d = .31 (95% CI = .20–.42). Twenty studies assessed the relation between baseline readiness to change and outcomes for mood disorder symptoms or relational distress, which were deemed sufficiently similar to group together to increase reliability of the estimate. Outcome measures included the State-Trait Anxiety Scale, Beck Depression Inventory, Children’s Depression Rating Scale, and Outcome Questionnaire 45. The mean effect size was d = .39 (95% CI = .27–.51).

Met-Analytic Review: Stage-Matched Treatments

Our second aim was to conduct a meta-analysis on psychotherapy studies that matched treatment to specific stages or readiness levels of change. We were interested in learning whether tailoring psychotherapy to the client’s stage of change produced the superior results found in behavioral medicine and population-based studies reviewed earlier. Unfortunately, we located no controlled group studies meeting our inclusion criteria that matched psychotherapy to client stage or readiness. As a result, we could not perform a meta-analysis.

A number of studies did use in-person sessions and delivered treatment based on stage or readiness to change but otherwise did not meet inclusion criteria in that treatment either was a single session, provided by medical staff, or focused on health behaviors such as smoking, physical activity, or diabetes management (Champion et al., 2003; Chouinard & Robichaud-Ekstrand, 2007; Clark et al., 2004; Patten et al., 2008; Van Sluijs et al., 2005; Wiggers et al., 2005). The one study that intervened on mental and addictive disorders was not individually stage-tailored (James et al., 2004).

The failure to locate stage-matching studies in psychotherapy reflects, first, the obvious dearth of such studies, and second, the pervasiveness of the medical model in matching treatments to the patient’s disorder (Wampold & Imel, 2015). Third, the paucity of such studies underscores the limited reach of conventional psychotherapy. Psychotherapy has traditionally taken a passive and narrow approach to healthcare—passively waiting for individuals suffering from mental health disorders in the contemplation or preparation stages to contact clinicians’ offices. In stark contrast, behavioral medicine has adopted a proactive approach to recruiting and intervening with entire populations in all stages of change. Not surprisingly, there are now hundreds of published stage-matching studies in behavioral medicine.

Evidence for Causality

In behavioral medicine and the addictions, the patient’s stage of change reliably predicts outcomes, and matching treatments to the patient’s stage of change demonstrably (p. 316) improves treatment outcomes. Dozens of RCTs and several meta-analyses provide evidence of the causal link.

In psychotherapy, the stages of change are moderately associated with and reliably predict patient outcomes, as evidenced in the current meta-analytic results. However, there are insufficient RCTs to make any causal claim for the efficacy of stage matching in psychotherapy at this time. Of course, the absence of evidence does not mean the evidence of absence. Based on all the available research, stage-matching psychotherapy likely produces similar benefits as in behavioral medicine and the addictions, but such psychotherapy studies await completion.

Limitations of the Research

Although more than 4,000 research studies have been published on the stages of change, none have directly and prospectively matched and mismatched psychotherapy to the patient’s stage of change. Rather, the available research concerns the predictive utility of the stages of change in terms of outcomes and dropouts, the differential use of the processes of change at various stages of change, and the relative efficacy of assorted forms of service delivery. Further, the majority of published research concern health behaviors and addictive disorders, as contrasted to the wide range of mental disorders.

In the future, we anticipate controlled trials of such stage matching will be conducted in psychotherapy proper. The merits and technologies of those RCTs are widely understood, as seen in controlled studies of treatment adaptations for patient cultures, preferences, and reactance levels (see other chapters in this volume).

More broadly, we enthusiastically recommend that psychotherapy researchers join the paradigm shift, in part initiated by the TTM, toward proactive outreach to entire populations. Proactive outreach will markedly increase the percentage of high-risk and suffering people receiving psychosocial treatment for behavioral disorders. Because only a small minority of the population will be ready to take action, psychotherapists will design treatments for the population at every stage: the 20% or less in the preparation stage, the 40% in the contemplation stage, and the 40% in the precontemplation stage. By reaching out and customizing services to readiness to change, psychotherapists can achieve a quantum increase in our ability to care for those suffering (Kazdin & Rabbitt, 2013; Prochaska & Prochaska, 2016).

Diversity Considerations

The stages of change have been found, in hundreds of studies, to apply to self-changers and psychotherapy patients of diverse ages, cultures, disability statuses, ethnicities, gender identities, races, religions, and sexual orientations. The moderator analyses found that the stages of change evidenced similar outcome association and prediction for patients of disparate ages, genders, and races/ethnicities. The stages are largely generalizable across cultures, disorders, and treatment settings as they represent, in our view, the underlying structure of behavior change (Prochaska et al., 1992).

(p. 317) Nonetheless, the majority of patient samples in our meta-analysis consisted primarily of Whites, and over 90% of the studies were conducted in North America or Europe (Table 10.2). Moreover, we were unable to include five potential studies in the meta-analysis because they were published in non-English outlets. More studies on the stages of change in psychotherapy from cultures and populations outside Western developed countries are sorely needed.

One implicit cultural assumption of the TTM concerns the value of behavior change itself. Change as progress is typically a Western and especially an American ideology. Different cultures raise serious challenges to the belief that change represents progression, individually or culturally.

As with any transdiagnostic patient characteristic, practitioners cannot assume that the stage of change defines the person’s experience. We respectfully discuss with the client which factors, including cultures or intersections of cultures, prove fundamental to tailoring psychotherapy. Automatically presuming that a client’s stage of change should be the primary determinant of treatment selection is probably as hurtful as ignoring it altogether.

Training Implications

On the basis of the research evidence and our training experience, we offer the following recommendations for clinical training and supervision.

  • Train students to assess the client’s stage of change. Probably the most obvious and direct implication is to assess the stage of a client’s readiness for change and to tailor treatment accordingly. In clinical practice, assessing stage of change typically entails a straightforward question: “Would you say you are not ready to change in the next six months (precontemplation), thinking about changing in the next six months (contemplation), thinking about changing in the next month (preparation), or have you already made some progress (action)?” Additionally, for specific diagnoses and treatment settings, measures such as the URICA and or Anorexia Nervosa Stages of Change Questionnaire (ANSOQ) can easily be administered.

  • Help students expect variability in patients’ stages of change. A useful guide is the “40–40–20 rule” in the population at large (not in action-oriented treatment programs): approximately 40% will be in precontemplation, 40% in contemplation, and 20% in preparation or ready for action (Velicer et al., 1995).

  • Train students integratively. Competing systems of psychotherapy have promulgated apparently rival processes of change. However, ostensibly contradictory processes become complementary when embedded in the stages of change. Specifically, change processes traditionally associated with the experiential, cognitive, and psychoanalytic persuasions prove most useful during the precontemplation and contemplation stages. Change processes traditionally associated with the existential and behavioral traditions, by contrast, are most useful during the action and maintenance stages. Each psychotherapy system has (p. 318) a place, but a differential place, in the therapeutic repertoire to assist clients to traverse the stage of change.

  • Teach students to predicate their therapeutic relationships more on the patient’s characteristics (e.g., stage of change, preferences) than on their theoretical prescriptions. Do not ask what Freud, Rogers, or Beck theorized about the therapeutic relationship. Instead, ask the consequential questions of what the patient prefers, what matches his or her stage, and what the research indicates will facilitate movement to maintenance and well-being.

  • Provide integrative supervision that tailors supervision to the individual trainee as he or she simultaneously adapts psychotherapy to individual clients. As students are learning to match psychotherapy to their patient’s transdiagnostic features, such as stage of change, culture, preferences, and reactance level, in parallel process their supervisors are tailoring supervision to multiple student characteristics (Norcross & Popple, 2017). “Example is always more efficacious than precept,” as Samuel Johnson observed.

  • Train students to pursue and calculate societal impact, not only treatment efficacy. Historically, psychotherapy outcome was evaluated by efficacy, the percentage of patients who were successful at posttreatment or follow-up. The TTM maintains that treatment success is more than efficacy alone. Impact is defined as the participation rate × efficacy. If the best practice that produces 30% efficacy generates 5% participation, its impact is 1.5%. If an alternative practice that produces 20% efficacy generates 75% participation, its impact is 15%. The apparently less effective practice (in terms of efficacy) actually has 10 times as much impact on the population. From the beginning, psychotherapy students should be mindful of the larger, bolder goal of impact.

Therapeutic Practices

Almost four decades of clinical research on the stages of change, including the meta-analyses reviewed in this chapter, have identified a number of therapist behaviors that will probably improve psychotherapy outcomes.

  • Beware of treating all patients as though they are in action. Professionals frequently design excellent action-oriented treatments but then are disappointed when only a small percentage of clients seek that therapy. The vast majority of patients are not in the action stage, and thus professionals offering only action-oriented programs are likely underserving or misserving the majority of their target population. The therapeutic recommendation is to move from an action paradigm to a stage paradigm.

  • Set realistic goals by moving one stage at a time. A goal for many patients, particularly in a time-limited managed care environment, is to set realistic goals, such as helping patients progress from precontemplation to contemplation. Such progress means that patients are changing if we view change as a process that (p. 319) unfolds over time, through a series of stages. Helping patients break out of the chronic, stuck phase of precontemplation is a therapeutic success, since it almost doubles the chances that patients will take effective action in the next six months. If we help them progress two stages with brief therapy, we triple the chances they will take effective action.

  • Treat precontemplators gingerly. We know that people in precontemplation underestimate the pros of changing, overestimate the cons, feel defensive when pressured, and are not particularly conscious of their defenses’ mistakes (Hall & Rossi, 2008). Patients in preaction stages of change have lower expectations of therapist acceptance, genuineness, and trustworthiness (Satterfield et al., 1995). When psychotherapists try to impose action on these patients, they are likely to drive them away, consequently blaming the clients for being resistant, unmotivated, or noncompliant. Instead, match your relationships and change processes to the stage. Motivational interviewing (Miller & Rollnick, 2012) has brilliantly incorporated these lessons into its philosophical spirit and its treatment methods. A number of studies included in this meta-analysis found that a few brief motivational sessions can improve retention and ultimately outcome (Carroll et al., 2006; Sorsdahl et al., 2015).

  • Tailor the processes to the stages. The research reliably demonstrates that patients optimally progress from precontemplation and contemplation into preparation by use of consciousness-raising, self-liberation, and dramatic relief/emotional arousal. Patients progress best from preparation to action and maintenance by use of counterconditioning, stimulus control, and reinforcement management. To simplify: Use change processes traditionally associated with the insight or awareness therapies for the early stages and change processes associated with the action therapies for the later stages.

  • Avoid mismatching stages and processes. A person’s stage of change provides proscriptive as well as prescriptive information on treatments of choice. Action-oriented therapies may prove quite effective with individuals who are in the preparation or action stages. These same programs tend to be ineffective or detrimental, however, with individuals in precontemplation or contemplation.

    We have observed two frequent mismatches (Prochaska et al., 1995). First, some therapists rely primarily on change processes most indicated for the contemplation stage—consciousness raising, self-reevaluation—while they are moving into the action stage. They try to modify behaviors by becoming more aware, a common criticism of classical psychoanalysis: insight alone does not necessarily bring about behavior change. Second, other therapists rely primarily on change processes most indicated for the action stage—reinforcement management, stimulus control, counterconditioning—without the requisite awareness, decision-making, and readiness provided in the contemplation and preparation stages. They try to modify behavior without awareness, a common criticism of radical behaviorism: overt action without insight is likely to lead to temporary change.

  • Prescribe stage-matched relationships of choice as well as treatments of choice. Similar to using treatments of choice offering “therapeutic relationships of choice” could enhance therapy outcomes (Norcross & Beutler, 1997). Once you know a (p. 320) patient’s stage of change, then you will know which relationship stances to apply to help him or her progress to the next stage and eventually maintenance. These relational matches, as reviewed earlier, entail a nurturing parent stance with a precontemplator, a Socratic teacher role with contemplator, an experienced coach with a patient in action, and then a consultant once into maintenance.

  • Practice integratively. Psychotherapists moving with their patients through the stages of change over the course of treatment will probably employ relational stances and change processes traditionally emphasized by disparate systems of psychotherapy. That is, they will practice de facto psychotherapy integration (Norcross & Goldfried, 2005). Our research has consistently documented that psychotherapists in their consultation rooms (and self-changers in their natural environments) can be remarkably effective in synthesizing powerful change processes across the stages (Connors et al., 2013).

  • Anticipate recycling: Most psychotherapy patients will recycle several times through the stages before achieving long-term maintenance. Accordingly, professionals and programs expecting people to progress linearly through the stages of change are likely to gather disappointing results. Be prepared to include relapse prevention in treatment, anticipate the probability of recycling patients, and try to minimize therapist guilt and patient shame over recycling (Prochaska et al., 2013).

  • Integrate readiness to change into treatment resources. Readiness to change measures can be built into self-help materials, health apps, online treatments, and similar resources to enable tailoring of interventions in ways that improve outcomes. The stages of change have been incorporated into several online assessments (e.g., ProChange [http://www.prochange.com/], InnerLife [http://www.innerlife.com/]) and self-help books (e.g., Changing to Thrive by Prochaska and Prochaska, 2016; Changeology by Norcross, 2015). But the opportunities for more are expanding rapidly with the increased availability and popularity of health apps and online treatments. These resources can complement and expand psychotherapy, as well as reach underserved populations.

  • Shift to an expanded view of psychotherapy as proactive, population-based healthcare. Psychotherapists need not discard effective means of assisting individuals suffering from mental disorders. Instead, they can add to these invaluable services by providing proactive recruitment and treatment of entire populations suffering from chronic biobehavioral conditions. Such an expansion could produce unprecedented impacts on the health and happiness of the populace.

References

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