Unlocking behaviour change. Examining predictors of motivational interview components, self-regulation, intention and behaviour change

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Unlocking Behaviour Change: Examining Predictors of Motivational Interview Components, Self-regulation, Intention and Behaviour Change

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(Paginanummers) A step closer to ‘the secret’ of a succesfull Physical

activity intervention. Relationships between patients characteristics,

MI-quality, change talk, self-regulation techniques within a physical activity

intervention examined.

Anouk Möller

Masterthesis Health Psychology

Faculty Social Sciences – Leiden University [March, 2015]

Supervisor: Keegan Knittle Studentnumber: 1039024 Begeleider: [Dr(s). B. Begeleider]

Unlocking behaviour change

Examining Predictors of Motivational Interview Components,

Self-regulation, Intention and Behaviour Change

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change through motivational interviewing (MI) and self-regulation (SR) techniques. In the context of a PA intervention for patients with rheumatoid arthritis, this study investigates (a) the extent to which patients’ baseline factors or therapists’ experience predict MI-quality and change talk (CT), (b) the extent to which MI-quality and CT lead to higher PA intention, and (c) the extent to which MI-quality, CT, and used SR techniques predict increases in PA behaviour.

Method: This study examined the treatment group of a randomised controlled trial.

Twenty-seven patients received an educational session, MI session, and self-regulation sessions. Questionnaires measured intention, SR techniques and PA. MI-quality was assessed with the Motivational Interviewing Treatment Integrity scale and CT was counted. First, Pearson correlations examined relationships with MI-quality and CT. Hierarchical regression analysis examined predictors of MI-quality, CT, PA intention change and behaviour change.

Results: Overall the independent variables of baseline self-efficacy and intention explained 35%

of the variance in quality. Only baseline self-efficacy was a significant predictor of MI-quality (β = .479, p = .038). No significant relationships with CT were found. Neither MI-MI-quality nor CT predicted changes in PA intention (R² = .011). Also, MI-quality, CT and SR techniques did not predicted changes in PA behaviour (R² = .284).

Conclusion: Surprisingly, quality and CT did not predict PA intention change, and

MI-quality, CT and SRT did not predict PA behaviour change significantly. Only baseline self-efficacy predicted MI-quality significantly.

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Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease that causes progressive damage to the musculoskeletal system (Carvalho, Tebexreni, Salles, & Barros, 2004). It is well documented that physical activity (PA) plays a central role in managing the disease as it is essential to maintain muscle strength and endurance, range of motion and the ability to perform daily life activities (Plasqui, 2008).

Unfortunately, most RA patients do not meet the recommended norm of 5 days per week, 30-45 minutes moderate-intensity PA (5x30 recommendation) (Haskell et al., 2007). Previously, it appeared that interventions to increase PA lead to large increases in PA behaviour, and to small improvements in pain and both subjectively and objectively measured functional ability (Conn, Hafdahl, Minor, Nielsen, 2008). Also PA interventions specifically for RA patients showed to have a small, but significant effect on the PA behaviour (Knittle, Maes, & de Gucht, 2010).

To create an effective intervention, a good understanding of how behaviour change occurs is required. There are several theories that can give more insight into PA behaviour change

(Plotnikoff, Costigan, Karunamuni, & Lubans, 2013).

Theories of Behaviour Change

One of those theories is the theory of planned behaviour (TPB). A central factor in TPB is the need to have an intention to perform a given behaviour. Intentions are assumed to capture the motivational factors that influence a given behaviour. The TPB assumes that intention for

behaviour can be predicted from attitudes toward the behaviour, subjective norms with respect to the behaviour, and perceived self-efficacy (Ajzen, 1985, pp. 11-39).

Also the Health Action Process Approach (HAPA) and the Rubicon model acknowledge the importance of intention in behaviour change. According to HAPA, risk perception, positive outcome expectancies and perceived self-efficacy are needed to form intentions (Schwarzer, 2008). The theory of HAPA suggests there is a distinction between (a) pre-intentional motivation processes that lead to a behavioural intention, and (b) post-intentional volition processes that lead to the actual health behaviour. In the initial motivation stage, a person develops an intention to act (Schwarzer, 2008).

Following the theory of Rubicon the first transition of behaviour change is also intention formation, which marks the shift from the motivational phase of deliberation on motivational tendencies to the volitional phases of planning and action. It is at this point that the individual determines which motivational tendencies are allowed to pass the threshold. The second

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transition is from intention formation to the initiation of action (i.e., from the volition to action) (Heckhausen & Gollwitzer, 1987).

Intention Formation and Motivational Interviewing

The HAPA and Rubicon models are both theories that constitute an implicit stage model. In the first stage, called motivational stage, ambivalence about behaviour is formed into intention to act (Heckhausen & Gollwitzer, 1987; Schwarzer, 2008). Motivational interviewing (MI) is a tool to accomplish this in patients. Motivational interviewing (MI) incorporated the techniques to elicit the factors that are required to form an intention to change (Miller, 1983; Rubak, Sandbœk, Lauritzen, & Christensen, 2005). Miller (1983) introduced MI to promote positive behavioural changes in the treatment of alcohol abuse. To date, MI has been used successfully for numerous behaviour changes including PA behaviour (Friederichs et al., 2014a; Harland et al., 1999; Rubak, Sandbœk, Lauritzen, & Christensen, 2005). The main principles of MI are expressing empathy, develop discrepancy, roll with resistance and support self-efficacy (Miller 1983). Examples of themes that are discussed in MI include: looking back, a typical day, the importance of change, looking forward, and confidence about change (Levensky, Forcehimes, O’Donohue, & Beitz, 2007).

Four basic interaction skills are needed for a successful motivational interview. These are: the ability to ask open-ended questions; the ability to provide affirmations strategically; the capacity for reflective listening; and the ability to provide summaries at the right moment. The skills of the therapist in adhering to the MI techniques seems to be an important factor in the MI outcome. The relational components such as empathy, congruence and positive regard are

predicted to be important in MI efficacy and from research results it seems that MI fidelity scores are significantly related to behaviour change (Miller, 1983; van Keulen, Mesters, van Breukelen, de Vries, & Brug, 2010, chapter 6).

Factors of MI-Quality

It seems that therapists’ interviewing skills are an important factor in eliciting PA behaviour change. Therefore the factors influencing the quality of an MI are interesting for understanding behaviour change. MI training showed to improve therapists’ proficiency score. Especially training with follow-up support showed to be important for improvement in MI proficiency (Barwick, Bennett, Johnson, McGowan, & Moore, 2012). Research about individual

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therapist effects on intervention outcomes with alcoholics showed substantial differences in effectiveness due to therapist characteristics (Najavits & Weis, 1994).

On the other hand, certain characteristics of the patient also appear to have an influence on the quality of the MI. Analyses showed that physicians use more MI consistent techniques with female patients and with heavier patients. Older age of the patient was associated with physicians spending less time discussing weight-related topics. A higher BMI percentile was associated with physicians spending more time discussing weight-related topics (Pollak et al., 2014).

Change Talk and MI-quality

Research showed that the quality of the MI also showed to be related to the patients’ expressed change talk (CT) during the MI (Moyers & Martin, 2006; Moyers, Martin, Christopher, Houck, Tonigan, & Amrein, 2007). CT is the client expressing a desire, ability, reason, need or commitment, or is taking steps to change the problem behaviour (Rollnick, Miller, & Buttler, 2008). There is a hypothesis that proficient use of MI techniques will increase clients’ language in favour of change. In the research of Moyers et al. (2007) they analysed audiotaped MIs and found that therapists using MI-consistent (MICO) behaviours were the most likely to lead to client CT. Similarly, a therapist using MI-inconsistent (MIIN) behaviour increased the immediate likelihood of speech against change. MIIN is even more likely to be followed by client resistance. This research shows that quality of MI is a good predictor of CT (Moyers & Martin, 2006). Study 1 of Moyers et al. (2007) also confirmed the hypothesis that proficient use of MI will be followed by positive CT.

Study 2 of Moyers et al. (2007) examined whether client CT during MI sessions would predict a positive behaviour change, which in this case was a decrease in alcohol consumption. In this study they analysed 45 sessions, looking at four client behaviours, including CT, by counting frequency. Results show that CT appeared an unique predictor of the outcome behaviour of the client. This relationship was maintained when the measure of readiness to change was included in the model (Moyers et al., 2007). Based on this research, it appears that MI skills predict CT and that CT predicts positive behaviour change (Moyers & Martin, 2006; Moyers et al., 2007).

Action Phase

However, it is important to mention that in practice many people develop an intention to change their health behaviour, but don’t manage to take any action (Webb & Sheeran, 2006).

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This discrepancy has been labelled the "intention-behaviour gap'' (Sniehotta, Scholz & Schwarzer, 2005).

The HAPA model appears to be successful in overcoming the intention-behaviour gap in behaviour change (Sniehotta, Scholz, & Schwarzer, 2005b; Sniehotta, Scholz, Schwarzer,

Fuhrmann, Kiwus, & Völler, 2005a). After the previously mentioned motivational stage there are certain post-intentional volitional processes that help turn intentions into actual health

behaviours. The post-intentional phase (action/volitional phase) can be broken down into more distinct elements, such as action planning, coping planning and recovery self-efficacy

(Schwarzer, 2008).

The Rubicon Model of action phases also tries to overcome the intention-behaviour gap. This theory states that after the motivational stage in which an intention to change is formed, the shift goes to the volitional phases of planning and action. It is at this point that the individual determines which motivational tendencies are allowed to pass the threshold. The second

transition is from intention formation to the initiation of action (i.e., from the volition to action). (Heckhausen & Gollwitzer, 1987). One tool which showed to help to overcome the intention-behaviour gap is called self-regulation (SR) techniques (Michie, Abraham, Whittington, & McAteer, 2009; Sniehotta et al., 2005a).

Trials and meta-analyses have demonstrated that lifestyle modification programs based on SR techniques have significant effects on behaviour. This is also the case for programs designed to increase PA. SR techniques that have been examined include planning, action control, coping planning, barrier management, problem solving, self-efficacy enhancement, self-monitoring, goal setting, feedback and prompting. In particular, self-monitoring appears to be a volitional factor in behaviour change (Chase, 2011; Janssen, de Gucht, Exel, & Maes, 2014; Janssen, de Gucht, Exel, & Maes, 2012; Knittle, Maes & de Gucht, 2010; Michie, Abraham, Whittington, & McAteer, 2009; Sniehotta et al.,2005a; Sniehotta, Scholz, & Schwarzer, 2005b). Michie, Abraham, Whittington, & McAteers’ (2009) research shows that the inclusion of self-monitoring in combination with other SR techniques is likely to enhance the effectiveness of PA and dietary interventions. SR techniques could also be mediators between intention and behaviour (Sniehotta et al., 2005; Sniehotta, Scholz & Schwarzer, 2005). Several PA interventions for RA patients who utilize SR techniques showed to increase PA behaviour (Knittle, Maes & de Gucht, 2010).

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Current Research

Concluding, MI and SR techniques have already shown to be effective tools in increasing PA (Friederichs et al., 2014a; Harland et al., 1999; Janssen, de Gucht, Exel & Maes, 2014;

Knittle, Maes & de Gucht, 2010). Several components of a MI such as the quality and the elicited CT during the MI showed to be related to behaviour change, but a bigger evidence base is needed (Moyers & Martin, 2006; Moyers et al., 2007). Also, there is only a handful of research about the patient characteristics and the therapists’ experience intervening with components of MI such as the quality and the elicited CT.

This study aims to gain more knowledge about the process of behaviour change through motivational interviewing (MI) and SR techniques. Therefore, this study will examine a number of research questions relating to the process of motivational interviewing and the sequential phases of behaviour change.

1. First, in relation to the process of MI, to what extent do characteristics of patients (i.e.

age, sex, BMI, baseline self-efficacy, baseline intention) and therapists’ experience (i.e. amount of MIs conducted and amount of feedback received) predict quality of MI delivery and the amount of CT produced in MI sessions?

2. Second, to what extent do MI-quality and the amount of CT produced in MI sessions

predict higher intention for PA following the intervention?

3. And third, to what extent do CT, MI-quality and use of SR techniques contribute to

increases in PA behaviour at the end of the intervention? Method

Design

This study is a randomised controlled trial and has a pre-post intervention design. In this research, only the intervention group is used for analysis.

Participants

Seventy-eight participants were recruited from the patient databases of Leiden University Medical Centre; HAGA Hospital, The Hague; and Reinier De Graaf Gasthuis, Delft. Patients were included if they were diagnosed with RA according to the American College of

Rheumatology criteria (Arnett et al, 1988). In addition, patients had to be older than 18 years of age and reported engaging in physical activity for less than 30 minutes on fewer than five days per week. Patients who had received physical therapy for their RA within the last six months,

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who had difficulty walking, or who could not attend the treatment sessions due to scheduling or transportation issues were excluded. Patients were randomly allocated to receive an educational session, a motivational interview and a self-regulation coaching intervention (treatment group), or the educational session alone (control group). As this study focuses solely on the process of motivational interviewing, it includes only 27 participants from the treatment group whose interviews were recorded.

Procedures

Recruiting. The patients who were identified as eligible for participation were randomly

selected in groups of 250 and were mailed leaflets describing the physical activity program tested in this study. Participants who responded with interest in participating were screened on

eligibility via telephone. The remaining patients who provided informed consent were randomly assigned and allocated to either the control or intervention group using a random number

generator. After randomization, patients were mailed a baseline questionnaire. Between one and two weeks later they returned the questionnaire at the group patient-education meeting.

Interventions. The group educational session provided information about the importance

of physical activity for people with RA, and about pacing when beginning a new activity. The session also focused on dispelling myths surrounding PA and RA, and providing arthritis patient organizations or exercise classes in the area. The educational session was delivered in a small group of 3-7 people. The physical therapist who conducted the session provided similar educational talks to arthritis patients for five years, and was unaware of participants’ group allocations.

One week later, a physical therapist conducted an one-on-one MI and two one-on-one self-regulation (SR) coaching sessions. The MIs lasted between 15 and 45 minutes. The MIs were conducted by three different physical therapists who all had previously received a 15-hour

training course in MI, and had practiced MI with three simulation patients and at least three RA patients. The therapists also received feedback each time after conducting two or three MIs. During the MI, patients weighed the pros and cons of (re-)engaging in regular PA, and attempts were made to link a more physically active lifestyle with long-term goals that were important to the patient (for example, maintaining independence or being able to play outside with their children). At the end of the MI, patients set a long-term outcome goal that could be achieved through PA, and received a folder containing an exercise diary. Patients completed the exercise

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diary on seven consecutive days by noting down periods of physical activity lasting at least 10 minutes, and were instructed to bring the diary along to the first self-regulation coaching session.

A rheumatology nurse delivered the two SR coaching sessions two and three weeks after the MI. These sessions followed the structure of a workbook that was developed for this study and emphasized the tenets of self-regulation theory (Maes & Karoly, 2005). Additional workbook components covered barrier identification and problem solving (coping planning), breaking large goals down into smaller ones, activating social support, self-reward, and the use of prompts/cues as reminders to be physically active. Both SR sessions began with a review of the exercise diary that the patients had completed in the previous week. Patients received feedback on their

progress, and worked together with the rheumatology nurse to set a short-term, realistic PA goal and create a corresponding action plan for the upcoming week (i.e. what physical activities would take place, as well as when, where, and for how long each activity would take place). At the end of each session, patients were again prompted to complete the exercise diary for the following week.

In weeks 6, 12 and 18 of the intervention, patients in the intervention group received a follow-up phone call from the rheumatology nurse to further discuss the patients’ efforts in self-regulating his or her physical activity. These phone calls lasted between 10 and 20 minutes and utilized the same techniques as the face-to-face sessions.

Measures

Quality of MI delivery. To assess the quality of the MIs, two coders applied the

Motivational Interviewing Treatment Integrity (MITI) scale to the audio recordings of 20 minutes of the MI sessions. Previous research showed that the MITI scale is a valid and reliable

instrument to evaluate competence of the therapist in the use of MI skills (Moyers, Martin, Manuel, Hendrickson, & Miller, 2005). Both coders had undergone three weeks of training in the

use of the MITI. This training included coding four interviews accompanied by the trainer, and then another five interviews independently. Following this, their trainer gave feedback on

discrepancies and challenges. The coders were blind to changes in all the participants’ measures, including PA levels. The MITI scale consists of five, 5-point scales: evocation, collaboration, autonomy/support, direction and empathy. The meaning of these scores are detailed in Table 3. The MITI also takes account of seven types of therapist behaviours which are also detailed in Table 3: information provision, open questions, closed questions, simple reflections, complex

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reflections, MI-adherent behaviours and MI-non-adherent behaviours. The 5-point scales are used to calculate summary scores. For each summary score, the MITI puts forward a proficiency threshold which, when met, indicates that an MI is adequately delivered. The total MITI interview score is the number of scores that meet the threshold. Table 4 provides details of the summary score calculations and proficiency thresholds.

Change Talk. One coder assessed the amount of change talk during the MIs by counting.

The coder had been trained to count CT during the three-week MITI-scale training. Within this training, the coder listened to nine MIs on audio twice. The first time she applied the quality measures for the MI and the second time she counted the number of CTs during the whole MI. The trainer provided feedback and talked it through. Different types of CT were specified. These included: desire (for example, “I wish I could exercise more”), ability (for example, “I think I can walk for an hour”), reasons (for example, “I want to be able to keep up with my children”), need (for example, “I’ve got to get back some energy”), commitment (for example, “I will swim once a week”) and taking steps (for example “I bought some running shoes”) (Rollnick, Miller, & Buttler, 2008).

regulation Techniques. Used SR techniques were assessed using the 40-item

Self-regulation Skills Battery (SRSB) post-MI. Previous research showed this is a valid tool to measure self-regulation within a life-style intervention (Maes & de Gucht, 2008). This

questionnaire assesses to which extent an individual has used each of eight self-regulation skills in pursuit of a previously stated physical activity goal. The eight self-regulation skills include action planning (four items), problem solving and coping planning (four items), self-monitoring (three items), obtaining feedback (three items), focusing attention on goal pursuit (three items), and avoiding self-criticism (three reverse-scored items). Each item is scored on a 5-point Likert scale with responses ranging from ‘Strongly Disagree’ (1) to ‘Strongly Agree’ (5). The score for each of the SR skills is calculated by taking an arithmetic mean of the answered items, and a total self-regulation score is the sum of the eight SR skill scores.

Self-efficacy for PA. Self-efficacy was assessed with the 18-item exercise self-efficacy

scale created by Bandura (2006). Research showed that this measure is valid and reliable with an alpha of .95 ( Everett, Salamonson, & Davidson, 2009). This scale consists of items with

situations in which it may be difficult to engage in PA (e.g. when you have other things to do, when it’s raining). The participants rate the likelihood that he/she would be physically active in

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the given situation with a number from 0 (not at all likely) to 10 (certainly). The total self-efficacy score is calculated by summing up the 18 item scores.

Number of MIs Conducted and Feedback Received.

Number of MIs conducted and the amount of feedback received increased based on the order in which patients were seen. All three therapists received after every two or three MIs feedback. The maximum amount of feedback received was four times and the mean amount of feedback was 1.41 (SD = 1.15). The maximum amount of conducted MIs was 12 and the mean was 5.26 (SD = 3.08). The amount of previously conducted MIs and received feedback of the therapist of every patient was tracked.

PA Intention. Items from the treatment self-regulation questionnaire (TSRQ) were used

to give a proxy measure of PA intention. The validity of the TSRQ appeared to be good, since the alpha of the internal validity scores mostly was higher than .73 (Levesque et al., 2007). The used items of the TSRQ actually measure autonomous motivation. However, scores of autonomous motivation have been shown to predict and correlate highly with intention (Hagger,

Chatzisarantis, & Harris, 2006). Each item presents participants with a reason why one is/might be physically active on a regular basis. Participants responded on a 7-point Likert scale with responses ranging from ‘Strongly Disagree’ (1) to ‘Strongly Agree’ (7) to statements of why one is/might be physically active on a regular basis. The items that were used to assess intention were: ’because I think it is important to stay healthy myself’; ‘because I really think that it is a good thing to do’; and ‘because I choose for it myself ‘. The intention score is calculated by taking the mean of the three items.

Physical Activity. At both the Baseline and Post-treatment measurement points, PA was

assessed using the short Questionnaire to Assess Health-enhancing Physical Activity (SQUASH). Previous research showed that this questionnaire is a fairly valid and reliable instrument to evaluate the PA of a population (Wendel-Vos, Schuit, Saris, Kromhout, 2003). The SQUASH assesses PA in the past four weeks in domains such as travel, work, household activities, free time, and sport. In each domain, participants indicate on how many days in a typical week they engaged in such activities, and on average, how many minutes they were engaged in those activities per day. For each domain a total score of minutes/week is calculated by multiplying days/week and minutes/day (days/week X minutes/day).

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Statistical Analysis

Data Preparation. Change scores in intervention outcomes, PA behaviour, and PA

intention were calculated by subtracting baseline values from those obtained post-MI. The inter-rater reliability of the MITI scores was examined with the intra-class correlation. Pearson

correlations between all study variables were calculated to examine the data for multicollinearity.

Examining Predictors of MI-quality and Change Talk.

Due the small sample, first Pearson correlations were calculated of patient characteristics (i.e. age, sex, BMI, baseline self-efficacy, baseline intention) and therapists’ experience (i.e. amount of MIs conducted and amount of feedback received), and the MI-quality. Only the variables that correlated significantly with MI-quality were used in the hierarchical regression model to identify predictors of the quality of the MI. The same process was followed in examining predictors of CT. Eventually, the hierarchical regression analysis was conducted block-wise with two blocks. Block 1 examined the effect of the independent patient variable baseline self-efficacy. Block 2 examined the effect of the independent patient variable baseline intention.

Examining Predictors of Changes in Intention and PA Behaviour.

To examine whether the intervention led to increases in PA intention or behaviour, paired t-tests were conducted. Then hierarchical regression analyses were conducted to answer the research question to what extent MI-quality and the amount of CT leads to higher PA intention. These analyses were conducted block-wise with independent variable MI-quality in block 1, and CT in block 2. Hierarchical regression analysis was also used to examine the predictors of PA

behaviour change. These analyses were conducted block-wise in three blocks. Block 1 consisted of the independent variable used SR techniques, block 2 consisted of the independent variable MI-quality, and block 3 consisted of the independent variable CT.

All analyses were conducted in SPSS 20.0 against a significance level of P < 0.05.

Results Patient Characteristics

At post-treatment, two participants (3%) had dropped out of the trial, and eight of the remaining participants had failed to complete the questionnaires assessing self-regulation skills and self-efficacy for PA. All 38 patients allocated to the intervention condition received the educational session, MI and self-regulation coaching sessions. Of the 38 MI sessions, 27 were

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recorded and included in this study. Table 1 shows the demographic characteristics of the

patients. The mean age of the patients who received a MI was 60 (range 29-83). Seventy percent consisted of women and 30% consisted of men. See Table 1 for a description of educational level and the BMI of the patients.

Note. M (SD) = Mean (Standard deviation).

Inter-Rater Reliability of MITI Coding

The intra-class correlations (ICC) of the MITI scores between the two raters was excellent (>.74) for the following scores: evocation, empathy, amount of giving information, amount of open questions, amount of closed questions, amount of complex reflections, and the amount of non-adherence. Collaboration was fair (.40-.59) and autonomy/support, direction and MI-adherent behaviour was poor (<.40). The ICC overall proficiency score between the two raters was .66. Table 2 shows an overview the MITI ratings and the mean scores with ICC.

Table 1. Demographic characteristics of participants at baseline

min-max n (%) M (SD) Woman 19 (70,4) Man 8 (29,6) Age 29-93 60 (12,76) Weight (BMI) 18,42-36,89 28 (5,00) Healthy 18,6-24,9 8 (29,0) Underweight 0-18.4 1 (3,7) Overweight 25+ 18 (66,6) Education Primary 10 (14,9) Secondary 10 (14,9) Tertiary 5 (7,5)

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Table 2. Inter-rater reliability and mean of global ratings and behaviour counts of 27 MIs

coded with the MITI scales

MITI Variable Description M (SD) ICC

Global ratings

Evocation Understanding of clients motivation for change

3.70 (.62) .97 Collaboration Therapist acts as patients equal 3.19 (.57) .58 Autonomy/Support Therapist fosters clients perception of

choice

3.30 (.47) .356 Direction Therapist stays focused on target behaviour 3.85 (.73) .29 Empathy Therapist grasps the clients perspective and

feelings

3.72 (.71) .92 Behaviour counts

#Giving information

Therapist provides information 8.19 (6.9) .92 #Open questions Therapist asks an open-ended question 12.07 (4.7) .95 #Closed questions Therapist asks yes/no questions 20.8 (8.7) .94 #Complex

reflections

Therapist gives a reflection which deepens clients original meaning

11.0 (4.1) .77 #Simple

reflections

Therapist simply restates what the client has said

9.1 (4.1) .69 #MI-adherent Therapist asks permission, affirms the

client, or emphasizes control

3.9 (3.1) .27 #MI-non-adherent Therapist provides unsolicited advice, or

assumes the expert role

2.9 (2.8) .86

Overall rate .66

Note. M (SD) = Mean (Standard deviation); ICC – Intra-class coefficient measure of coding reliability.

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MITI Summary Scores

Across the 27 MIs, almost all means of the five MITI summary scores fell below the corresponding thresholds of proficiency. However, the mean of the percentage of complex reflections fell above the corresponding threshold of proficiency (Table 3).

Regarding individual MIs, several did meet one or more proficiency thresholds: seven MIs met the global spirit rating threshold; two MIs exceeded the threshold of the ratio of reflections to questions; eight MIs exceeded the threshold for the percentage of open

questions; twenty-four MIs exceeded the threshold of the percentage complex reflections; and four MIs exceeded the threshold for the percentage of MI-adherent behaviours. The mean number of thresholds met (MITI proficiency score) was 2.1.

Table 3. MITI score description, proficiency threshold, and mean scores

MITI Summary score Description (MITI Proficiency threshold) M (SD) Global Spirit (Evocation + Collaboration + AutonomySupport) / 3 (>3.5) 3.4 (.45) Reflections/Questions # Total Reflections / Total Questions (>1.0) .64 (.47) % Open questions # Open Questions / # Total Questions (>.50) .39 (.17) % Complex

reflections

# Complex Reflections / # Total Reflections (>.40) .55 (.15) % MI-adherent # MI-adherent / (# MI- adherent + # MI-non-adherent) (>.90) .54 (.26) Proficiency Score # of MITI Summary Scores meeting its corresponding threshold 2.1 (.78) Note. M (SD) = Mean (Standard deviation).

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Predictors of MI-quality and Change Talk

None of the correlations exceeded the threshold for multicollinearity. Therefore it was assumed that muliticollinearity did not influence the results of the regression analyses (Field, 2000).

Pearson correlations between patient characteristics at baseline (i.e. age, sex, BMI, baseline self-efficacy, baseline intention) and each of the MITI summary scores revealed several significant associations (See Table 4). Higher BMI was associated with a greater percentage of MI-adherent statements (p = .002). A positive relationship was found between baseline self-efficacy and baseline intention, and MITI summary score Global Spirit (p = .005, p = .007) and higher Proficiency score (p = .038, p = .019). The MITI summary scores showed to have no significant relationships with therapists’ amount of conducted MIs or amount of received feedback. Regarding predictors of CT, Pearson correlations showed there were no significant relationships between CT and any of the variables of patients’ characteristics or therapists experience in conducting MIs and receiving feedback.

Hierarchical regression analysis showed that baseline self-efficacy and baseline intention of patients explained 35% of the variance of MI-quality (R² = .35). There was support that baseline self-efficacy and baseline intention of patients in step 2 have a significant relationship with MI-quality (F(2,16) = 4.35, p = .031). As seen in Table 5, only baseline self-efficacy predicted MI-quality in block 1 individually significantly, in which higher baseline intention led to higher quality MI (β= .479, p = .038).

Predictors of Changes in Intention and PA

None of the correlations exceeded the threshold for multicollinearity. Therefore it was assumed that multicollinearity did not influence the results of the regression analyses (Field, 2000).

Pearson correlation coefficients showed that none of the MITI summary scores were associated with increase in intention. A positive association has been found between the ratio of reflections and questions, and participants PA change score (p = .001) (See Table 4).

Baseline intention score mean was 6.0 (SD = .08) and post-intervention mean was 5.5 (SD = 1.3). There was no significant difference in prepost intervention intention score (t(26) = -0.245, p = .81).

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the variance found in intention change score (R² = .01). There was no significant effect of MI-quality and CT on intention change score (F(2,24) = .13, p = .879).

The mean of the PA score at baseline was 1549.6 (SD = 1095.7) and the post-intervention means was 1255.3 (SD = 872.5). A t-test showed no significant difference between pre-post intervention PA behaviour score (t(26) = 1.607, p = .12). As seen in Table 7 the independent variables MI-quality, CT, and used SR techniques together showed to explain 18% of the variance in PA change score (R² = .18). There is no support that the variables MI-quality, CT, and used SR techniques have a relationship with PA change score (F(3,21)= 1.49, p = .246).

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Table 4. Pearson correlations between MITI summary scores and patient characteristics

MITI Summary Score

Age Sex BMI Baseline self-efficacy Baseline intention Intention change score PA change score Change talk # MI of therapist # therapist received feedback Global Spirit -.243 .001 -.296 .612** .510** -.165 -.214 .228 .254 .149 Reflections/ Questions .233 -.149 .127 .164 -.064 -.214 .644** -.113 .033 .042 % Open questions .141 -.350 .014 .195 .115 .331 .213 .079 .325 .125 % Complex reflections -.145 .267 .156 .269 -.011 .168 -.213 -.185 -.295 .-466 % MI adherent -.011 -.102 -.576** .152 .377 -.187 -.242 -.145 .140 .114 Proficiency Score

(MI quality score)

-.193 -.380 -.101 .479* .449* -.149 .174 -.010 .231 .051 Change talk -.241 -.276 .696 .365 .139 -.053 .085 -.135 -.115 Note. * P < 0.05; ** P < 0.01.

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Note. * P < 0.05; ** P < 0.01; β = Standardized Coefficient.

Table 5. Hierarchical regression analysis predicting MI-quality

MI-quality R² Step 1 β Step 2 β Block 1 .229* Baseline self-efficacy .479* .289 Block 2 .352* Baseline intention .399

Table 6. Hierarchical regression analysis predicting change score in PA intention

Intention change score

R² Step 1 β Step 2 β

Block 1 .008

MI quality score -.088 -.089

Block 2 .011

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Table 7. Hierarchical regression analysis predicting change score in PA behaviour

PA change score

R² Step 1 β Step 2 β Step 3 β

Block 1 .052 Self-reg. skills .228 .260 .293 Block 2 .096 MI quality score .213 .241 Block 3 .175 Change talk .284

Note. * P < 0.05; ** P < 0.01; β = Standardized Coefficient

Discussion

It is already known that MI and SR techniques can be effective tools in eliciting behaviour change. However there is still a lot indistinct about how components of MI, such as the quality and the elicited CT, relate to patient factors and how MI factors and use of SR techniques leads to behaviour change. Therefore this study aimed to give more insight in the relationships between patient and therapists’ experience factors, MI factors, SR techniques, and PA behaviour change. More specifically, this study examined: (a) to what extent the characteristics of RA patients (age, sex, BMI, baseline intention, and baseline self-efficacy) and therapists’ experience in conducting MIs and receiving feedback on the MIs predict MI-quality and CT in MI sessions, (b) to what extent MI-quality and the amount of CT during the MI sessions predict higher intention for PA following the intervention, and (c) to what extent CT, MI-quality and use of SR techniques contribute to PA behaviour change at the end of the intervention.

Predictors of MI-quality

In this study only baseline self-efficacy and intention of the patient showed to have a relationship with the quality of the MIs. Hierarchical regression analysis showed that 35% of the variation of MI-quality was understood by these independent variables significantly (see Table 5). Especially baseline self-efficacy showed to be important in the proficiency score of the therapist, since hierarchical regression analysis showed that higher baseline self-efficacy of the patient led significantly to higher proficiency score of the therapist during the MI.

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Previous research already showed that patients’ baseline characteristics could influence the quality of the MI, but baseline self-efficacy did not show to predict MI-quality before (Pollak et al., 2014). However, Bandura did state that the self-efficacy was important in behaviour change (Bandura, 1977).

The finding that self-efficacy a predictor of MI-quality is in this study, also raises the question how the efficacy level of the patient influences the level of proficiency of the therapist. According to Bandura (1977) self-efficacy is often a mix of hope, wishful thinking, belief in the potency of the procedures, and faith in the therapist. Those things, especially the faith in the therapist, could have given the therapist a higher self-efficacy in adhering to the MI skills, which possibly has led to actual better proficiency in conducting the MI. However, more research is needed to state this. Therefore future research should examine the verbal and nonverbal

differences in expressions of patients with high and low self-efficacy. Subsequently, qualitative research should interview the therapists about how and why they adhere more to the MI skills with high self-efficacy patients than with low self-efficacy patients.

Predictors of Change Talk

Pearson correlations showed that CT had no relationship with any of the patients’

characteristics (i.e. sex, age, BMI, baseline self-efficacy, baseline intention). Also the therapists’ amount of conducted MIs and received feedback on conducted MIs appeared to have no

relationships with CT. Knowing that MI-quality predicts CT (Moyers & Martin, 2006; Moyers et al., 2007), it its surprising to see that the significant predictor of MI-quality, baseline

self-efficacy, has no relationship with CT. On the other hand, it is not very peculiar to observe

different predictors since this study shows no relationship between MI-quality and CT (Table 4). An explanation of the fact that patients’ characteristics combined with therapists’

experience in conducted MIs and received feedback were not predicting the variance of CT significantly could be that patients’ locus of control or health beliefs are responsible for a significant amount of CT variance, since this can also influence a patients’ behaviour (Nir & Neumann, 1995; Norman et al., 1998; Radtke & Rackow, 2014). However, because these variables are not measured in this study, statements about this cannot be made. In addition, it is possible that a bias occurred due to the weak reliability of the CT count. However, statements about the inter-rater reliability could not be made because of the lack of a second CT rater.

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Surprisingly, this study shows that the quality of the MI coded with the MITI and CT during the MI did not predict change in PA intention significantly. This is contrary to the results of previous research (Miller, 1983; Moyers & Martin, 2006; Moyers et al., 2007; van Keulen, Mesters, van Breukelen, de Vries & Brug, 2010, Chapter 6). The quality of the MI did not predict PA intention pre-post intervention change.

A possible explanation is that the MI does not have a significant influence on the patient. Instead it could be that other variables set at baseline account for the variance in intention change score, such as the characteristics of the patient. However, more research is needed to state this.

The lack of a causal relationship between MI-quality and change in intention, plus CT and change in intention should be interpreted with caution. Since a possible explanation could be the lack of variance in intention change scores. The pre-post intervention difference in the intention score was not significant. This could have caused the association between MI-quality and intention change or between CT and intention change to appear weaker than it potentially was. Another possible bias in this finding could be a weak validity measure for CT. If the measure of CT was unreliable, it means that the true variance of CT of the patients during the MIs might be different. This possibly could have distorted the relationship between CT and intention change. However, due to the lack of a second rater, statements about the validity of CT can not be given.

It is also important to bear in mind that an autonomous motivation measure was used as a proxy measure of intention. This seems no problem, since scores of autonomous motivation predict and correlate highly with intention, this proxy measure could still give a unreliable score of intention (Hagger, Chatzisarantis, & Harris, 2006). However, the intention measure consists of only three items. This might not include all patients’ possible intentions to become physically active, which possibly could have led to a distortion the intention scores.

Predictors of PA Behaviour Change

Contrary to the expectation, MI-quality, CT and used SR techniques did not predict change in PA behaviour after the intervention, and there was no relationship found between PA behaviour change score and MI-quality or CT. This is surprisingly, because previous research stated that better proficiency in MI and more CT leads to more successful behaviour change (Miller, 1983; Moyers & Martin, 2006; Moyers et al., 2007; van Keulen, Mesters, van Breukelen, de Vries, & Brug, 2010, Chapter 6). Also the lack of a relationship between used SR techniques and PA behaviour change is surprising, as from previous research it is hypothesized that used SR

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techniques score is a mediator between intention and behaviour change (Sniehotta et al., 2005; Sniehotta, Scholz, & Schwarzer, 2005).

A possible explanation for the lack of an association between the variables MI-quality, CT, and SR techniques score, with PA behaviour change could be that patient characteristics set at baseline such as intention, demographic factors account for a significant amount of variance in PA behaviour change. It is also important to bear in mind that an autonomous motivation

measure was used as a proxy measure of intention. Therefore, differences in how patients decided to join the trial might have played a role in the amount of PA change. For example, joining the trial for autonomous reasons such as ‘they wanted to themselves’ could have led to better PA outcomes than if people were coerced into joining the trial for reasons such as ‘their husband wanted them to’. More research is required before this aspect can be discussed. Likewise for intention change score, future research should focus on the relationship between patient characteristics and PA behaviour change score to state this.

The lack of a causal relationship of the independent variables MI-quality, CT and used SR techniques with PA behaviour change found in this study should be interpreted with caution. A possible explanation could be the lack of variance in PA change scores. The pre-post intervention difference in the PA score was not significant. This could have caused the associations to appear weaker than it potentially was. Again, another possible bias in the lack of a relationship between CT and PA behaviour change could be a weak validity measure of CT. However, due to the lack of a second rater, statements about this matter cannot be made. An explanation regarding the lack of an association between used SR techniques and PA behaviour change could be that the data of used SR techniques is not a good representation of the SR techniques actually used. Before the patients filled out the questionnaire assessing used SR techniques, they learned that it is good to use SR techniques at the self-regulation coaching sessions. This could have led to socially

desirable answers in a way that the patients scored use of SR techniques higher than was actually used. However, statements about this could not be made.

Limitations

This study provides more clarity about factors related to PA behaviour change in an intervention aimed to increase PA among RA patients. However, there are several limitations that require some tempering of the conclusions drawn.

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participants did not attend the MI session and 10 participants dropped out later in the trial. Thirty-one participants completed the intervention, but only 27 MIs were recorded, leading to a

relatively small sample size. Studies with findings that are contrary to this study had significantly larger sample sizes. Studies of 149 and 170 MI sessions found a significant relationship between MI-quality and CT, and between CT and MI-quality (Gaume, Bertholet, Faouzi, Gmel, &

Daeppen, 2010; Barnett et al., 2013). Also contrary to the results of this study, studies with a larger sample size found a significant relationship between used SR techniques and PA behaviour change (Michie, Whittington, Abraham, & McAteer, 2009; Knittle, Maes, & de Gucht, 2010). Therefore, the results of this study must be interpreted with caution.

Statements about CT are based on the judgement of only one rater. Therefore, caution is required when drawing conclusions about the results, since it is impossible to give a judgement about the validity of this measure. Contrary to CT, this study did have a second rater for MI-quality. Inter-rater reliability was good, except for the non-adherence score. This probably did not cause a bias in the results since most of the MITI summary scores appeared to have no

relationship with the hypothesized variables.

With regard to statements about intention, it is important to keep in mind that this is measured using an autonomous motivation measure. Another limitation of this research is that the variables health locus of control, health beliefs and disease factors were not measured and

examined in relation to PA behaviour change, as these might be significant predictors of behaviour change (Bernstein, 2015; Nir & Neumann, 1995; Norman et al., 1998; Radtke & Rackow, 2014).

Conclusions and Implications

Contrary to expectations from previous research, SRT, MI-quality and CT appeared in this study to have no significant influence on PA intention change or PA behaviour change.

Interestingly baseline self-efficacy seemed to predict the proficiency of the therapist conducting the MI. Higher self-efficacy of the patient seemed to led to higher proficiency score of the

therapist. This raises the question of how the self-efficacy of the patient is expressed and how this has an effect on the therapists’ behaviour in adhering to the MI skills. Future research should investigate this.

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Unlocking behaviour change. Examining predictors of motivational interview components, self-regulation, intention and behaviour change

(Paginanummers) A step closer to ‘the secret’ of a succesfull Physical

activity intervention. Relationships between patients characteristics,

MI-quality, change talk, self-regulation techniques within a physical activity

intervention examined.

Anouk Möller

Unlocking behaviour change

Examining Predictors of Motivational Interview Components,

Self-regulation, Intention and Behaviour Change

Table of contents