Journal of Counseling Psychology 2015, Vol. 62, No. 2, 106 –114

© 2015 American Psychological Association 0022-0167/15/$12.00 http://dx.doi.org/10.1037/cou0000057

The Temporal Order of Change in Daily Mindfulness and Affect During Mindfulness-Based Stress Reduction Evelien Snippe

Ivan Nyklícˇek

University of Groningen

Tilburg University

Maya J. Schroevers and Elisabeth H. Bos This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

University of Groningen Increases in mindfulness are assumed to lead to improvements in psychological well-being during mindfulness-based treatments. However, the temporal order of this association has received little attention. This intensive longitudinal study examines whether within-person changes in mindfulness precede or follow changes in negative affect (NA) and positive affect (PA) during a mindfulness based stress reduction (MBSR) program. This study also examines interindividual differences in the association between mindfulness and affect and possible predictors of these differences. Mindfulness, NA, and PA were assessed on a daily basis in 83 individuals from the general population who participated in an MBSR program. Multilevel autoregressive models were used to investigate the temporal order of changes in mindfulness and affect. Day-to-day changes in mindfulness predicted subsequent day-to-day changes in both NA and PA, but reverse associations did not emerge. Thus, changes in mindfulness seem to precede rather than to follow changes in affect during MBSR. The magnitude of the effects differed substantially between individuals, showing that the strength of the relationship between mindfulness and affect is not the same for all participants. These between-subjects differences could not be explained by gender, age, level of education, average level of mindfulness home practice, or baseline levels of mindfulness and affect. Mindfulness home practice during the day did predict subsequent increases in mindfulness. The findings suggest that increasing mindfulness on a daily basis can be a beneficial means to improve daily psychological well-being. Keywords: mindfulness, mechanism, diary, intensive longitudinal design, training

relations with measures of distress, anxiety, and depression, as well as positive associations with positive affect measures (e.g., Baer, Smith, Hopkins, Krietemeyer, & Toney, 2006; Brown & Ryan, 2003). In addition, mindfulness-based interventions have been found to decrease symptoms of stress, anxiety, and depression as well as to improve quality of life and positive affect (e.g., Nyklícˇek & Kuijpers, 2008; Schroevers & Brandsma, 2010; see also reviews by Hofmann, Sawyer, Witt, & Oh, 2010; Khoury et al., 2013). Although the evidence suggests that cultivation of mindfulness is associated with psychological well-being, the temporal order of this association is unclear. The prevailing way to test whether mindfulness leads to increases in psychological well-being has been to examine whether a pretreatment to posttreatment change in mindfulness statistically mediates the effect of treatment on the prepost change in psychological well-being, which boils down to showing that prepost changes in mindfulness are associated with prepost changes in well-being. Several studies indeed showed that mindfulness statistically mediates the effects of mindfulness-based treatments on measures of psychological well-being (Bränström, Kvillemo, Brandberg, & Moskowitz, 2010; Carmody & Baer, 2008; Heeren et al., 2014; Jislin-Goldberg, Tanay, & Bernstein, 2012; Nyklícˇek & Kuijpers, 2008; Shahar, Britton, Sbarra, Figueredo, & Bootzin, 2010; Shapiro, Oman, Thoresen, Plante, & Flinders, 2008; Vøllestad, Sivertsen, & Nielsen, 2011), although in two

Mindfulness involves the ability to be aware of present-moment experiences and observing these experiences as they are instead of judging them (Bishop et al., 2004; Brown, Ryan, & Creswell, 2007; Kabat-Zinn, 1994). Responding mindfully to experiences in daily life is assumed to be beneficial for one’s well-being because it may enhance emotion regulation (Chambers, Gullone, & Allen, 2009; Hölzel et al., 2011) and decrease negative cognitive responses (Segal, Williams, & Teasdale, 2002). In observational studies, mindfulness has been associated with state and trait measures of psychological well-being, including negative cor-

This article was published Online First January 26, 2015. Evelien Snippe, Department of Health Psychology, University of Groningen, University Medical Center Groningen; Ivan Nyklícˇek, Department of Medical and Clinical Psychology, Center of Research on Psychology in Somatic disease (CoRPS), Tilburg University; Maya J. Schroevers, Department of Health Psychology, University of Groningen, University Medical Center Groningen; Elisabeth H. Bos, Interdisciplinary Center Psychopathology and Emotion regulation, University of Groningen, University Medical Center Groningen. Correspondence concerning this article should be addressed to Elisabeth H. Bos, University Medical Center Groningen, University of Groningen, Interdisciplinary Center Psychopathology and Emotion regulation (ICPE), PO Box 30.001, 9700 RB Groningen, the Netherlands. E-mail: elske [email protected] 106

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THE ORDER OF CHANGE IN MINDFULNESS AND AFFECT

studies this mediation effect was not found consistently (Labelle, Campbell, & Carlson, 2010; van Aalderen et al., 2012). An important limitation of the above studies is that they do not allow the investigation of the temporal order of change in mindfulness and psychological well-being. Clarity about the temporal order of change is a first prerequisite for making inferences regarding the causal direction of an association. Changes in the assumed mechanism (e.g., mindfulness) should therefore temporally precede changes in the outcome (e.g., psychological wellbeing; Kazdin, 2007; Kraemer, Wilson, Fairburn, & Agras, 2002). The temporal order of change cannot be examined in standard prepost treatment designs because the presumed mediator and outcome are assessed only twice at the same moment in time. Alternative explanations for the found associations are therefore still plausible. The causal direction may be the reverse: Improvements in psychological well-being may lead to increases in mindfulness. For example, feeling less blue, fatigued, or tense may enhance the capacity to observe and be aware of experiences. Also, when one’s mood is improved, there are fewer reasons to be judgmental about oneself and to react to negative experiences. Improvements in psychological well-being may be caused by other factors, such as self-efficacy or social support obtained during mindfulness-based treatment and subsequently enhance the ability to establish a state of mindfulness (Bishop, 2002). The relationship may also be reciprocal, with small increases in either mindfulness or well-being generating a positive feedback loop (Baer, Carmody, & Hunsinger, 2012). Two studies have aimed to examine the temporal order of change in mindfulness-based treatments (Baer et al., 2012; Vøllestad et al., 2011). Baer et al. (2012) measured mindfulness and perceived stress on a weekly basis and found that improvements in mindfulness skills over the first 3 weeks of mindfulness based stress reduction (MBSR) predicted change in perceived stress over the course of treatment. Vøllestad et al. (2011) found that average levels of mindfulness did not change from pre-MBSR to midMBSR, and therefore they could not examine whether change in mindfulness predicted change in symptoms of anxiety from midtreatment to posttreatment. Yet, these studies did not examine the dynamic interplay between mindfulness and well-being within individuals, including possible reverse associations and feedback loops. A related issue that has received little attention is whether daily mindfulness home practice could set a change process in motion within individuals. It is assumed that frequent practice of mindfulness enhances the benefits of mindfulness-based interventions (Segal, Williams, Teasdale, & Gemar, 1996). If it would be shown that daily mindfulness practice is associated with daily increases in mindfulness within individuals, this is an indication that daily home practice is indeed an active ingredient of mindfulness-based interventions. Finally, there is a lack of knowledge on possible heterogeneity between individuals in the dynamic interplay between mindfulness and psychological well-being. Psychological mechanisms underlying change during treatment may differ across individuals (Bouchard et al., 2007; Molenaar, 2004). The findings of a previous replicated single-subject time-series study indeed suggested some heterogeneity in the dynamic associations between mindfulness, repetitive thinking, and depressive symptoms during a mindfulness-based treatment (Snippe et al., 2014). Day-to-day

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increases in mindfulness were followed by decreases in depressive mood in one out of six participants, although no reverse effects were found. Examining individual differences in the association between daily mindfulness and well-being may reveal individual differences in change processes and may provide clues on who benefits most from MBSR. The aforementioned questions on mechanisms of change call for suitable methodologies to be able to draw conclusions about the temporal order of change within individuals (Hofmann, Asmundson, & Beck, 2013; Kazdin & Nock, 2003). The designs of the studies done thus far are not suitable to examine processes that operate within individuals because the number of time points is too low (Curran & Bauer, 2011; Hamaker, 2012; Molenaar, 2004). Intensive longitudinal designs have been put forth as the method of choice to study within-person processes because they allow to disaggregate within-person and between-person associations, and therefore they allow examining true within-subjects effects (Bolger & Laurenceau, 2013; Curran & Bauer, 2011; Hamaker, Dolan, & Molenaar, 2005). Because of the multitude of repeated measurements, these designs are very suitable to investigate whether increases in mindfulness consistently precede or follow changes in psychological well-being within individuals. In addition to that, interindividual differences in these dynamic associations can be examined using such designs. In sum, the evidence so far is not compelling regarding the assumption that increases in mindfulness induce improvements in psychological well-being in daily life rather than the other way around, as there is a lack of studies suitably designed to investigate this. This study examined the within-person temporal order of change in daily observations of mindfulness and psychological well-being using an intensive longitudinal design. This was investigated within the context of an MBSR program, because day-today variability in mindfulness is more likely to be observed within such a context. To check whether the increases in mindfulness are at least partly resulting from the MBSR program, we examined whether daily mindfulness home practice predicts increases in daily mindfulness. For the assessment of psychological well-being, we measured both negative affect (NA) and positive affect (PA), as these are considered the dominant and relatively independent dimensions of emotional experience (Watson, Clark, & Carey, 1988; Watson & Tellegen, 1985). We examined whether day-today changes in mindfulness precede or follow day-to-day changes in PA and NA during an MBSR program. We also examined interindividual differences in the temporal order of change, to gain more insight into possible heterogeneity between individuals in the mechanism of change. Furthermore, we explored whether these interindividual differences could be explained by characteristics of the participants (i.e., gender, age, level of education, daily mindfulness home practice, and baseline levels of mindfulness as well as affect). We hypothesized that, on average, day-to-day changes in mindfulness precede day-to-day changes in NA and PA. It was expected that the average reverse association would be weaker, with changes in mindfulness following changes in PA and NA to a lesser extent. Furthermore, we hypothesized that mindfulness home practice would be associated with same-day increases in mindfulness. In addition, we hypothesized to find considerable heterogeneity between individuals in these within-subject associations.

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with a heterogeneous sample of 972 patients of Dutch general practices (Wald & Mellenbergh, 1990).

Method

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Participants Participants were recruited between January 2010 and June 2012 by means of a website and advertisements in the local newspapers of Tilburg, the Netherlands. The MBSR intervention was advertised as a group intervention to reduce feelings of distress by means of cultivating mindfulness. The accompanying diary study was promoted by offering a 10% discount on the MBSR intervention to those willing to participate in the diary study. An online screening was performed to examine potential exclusion criteria, if necessary supplemented by a telephone interview. The exclusion criteria were assessed by a psychologist/ researcher (IN). Exclusion criteria were severe psychiatric disorders (e.g., current severe major depression episode, suicidal, or psychotic tendencies) and an inability to read and write in Dutch. None of the individuals interested in the MBSR program were excluded because of presence of exclusion criteria. Of the 187 individuals who participated in the MBSR program during the study period 85 individuals (45%) agreed to participate in the diary study. Two of these individuals filled out the diary measures on only 2 days and were therefore excluded from the analyses. The final sample of 83 participants all provided written informed consent. Table 1 displays the characteristics of the study participants at baseline. The majority of the sample was White, female, highly educated, and received treatment for psychological problems in the past. The participants had elevated scores on mood symptoms; the average score on the POMS was more than 1 SD higher compared

Table 1 Baseline Characteristics of the Study Participants Variable

M/% (SD)

Age (M) Caucasian Female Education Lower vocational–primary school Vocational–secondary school Higher post-education–college Employed, full time or part time Married or living together Chronic somatic disease Past psychological treatment Current use of antidepressant POMS-SF Depression Anger Tension Fatigue Vigor FFMQ Observing Describing Acting with awareness Nonjudging Nonreacting

40.6 (10.0) 99% 69.5% 2.4% 36.6% 61.0% 78.0% 61.0% 28.1% 62.2% 16.6% 18.7 (7.3) 16.3 (6.4) 16.9 (5.2) 16.3 (6.4) 13.0 (4.1) 24.1 (4.4) 27.2 (5.6) 21.3 (4.7) 22.9 (7.0) 18.0 (4.9)

Note. N ⫽ 82. POMS ⫽ Profile Of Mood Scale-SF subscales; FFMQ ⫽ Five Facet Mindfulness Questionnaire.

Procedure Before the start of the intervention, participants were asked to fill out an online pretreatment questionnaire. After the first MBSR session, participants were instructed to fill out the daily questions online after 5 p.m. each day until the day of the last session of the treatment. The daily questionnaire started with questions on mindfulness, followed by questions on negative and positive affect, mindfulness home practice, and circumstances. Participants were told that they were allowed to miss one entry per week. During the study, the frequency of completing the questions was monitored, and if lower than six entries per week were completed, participants received an e-mail reminder to be more adherent.

Intervention The provided MBSR program is the manualized group program by Jon Kabat-Zinn (1990). The MBSR program consists of eight sessions over 8 to 9 weeks of 2.5 hr, an optional silent retreat session of 6 hr, and daily homework practice of at least 40 min. The MBSR program is aimed at training mindfulness by means of meditation practice (e.g., body scan and sitting meditation), yoga, psychoeducation (e.g., automatic vs. mindful response), and group sharing of experiences during the practices. In these mindfulness practices, participants are instructed to observe their experiences, recognize when their attention drifts away, and to redirect their attention to their experiences in a nonjudgmental way. During the study period, 16 groups of 8 –14 participants were run by a qualified psychologist who received extensive training in MBSR and is certified by the Dutch association for Mindfulness (VVM). This 44-year-old White male trainer had almost 5 years of experience as an MBSR trainer at the start of the study period and provided on average five classes per year.

Measures Baseline assessment. The preintervention questionnaire included questions on demographic and clinical variables. Affect and mindfulness were assessed with full-scale self-report questionnaires at baseline. NA and PA were assessed using the short form of the Profile of Mood States (POMS-SF), a frequently used questionnaire developed to assess transient mood states (Shacham, 1983). The Dutch version of the POMS-SF consists of 32 selfreport items covering five subscales (Wald & Mellenbergh, 1990). The subscales Depression, Anger, Fatigue, and Tension were used to measure NA, and the Vigor subscale was used to measure PA. Each item is rated on a 5-point Likert scale ranging from 1 (not at all) to 5 (extremely). Studies have shown adequate convergent and discriminant validity of the POMS-SF (Baker, Denniston, Zabora, Polland, & Dudley, 2002; Wald & Mellenbergh, 1990). Mindfulness was assessed using the Five Facet Mindfulness Questionnaire (FFMQ; Baer et al., 2006, 2008;). The questionnaire consists of 39 items that address five facets of mindfulness: observing, describing, acting with awareness, nonjudging of inner experience, and nonreactivity to inner experience. Each item is rated on a 5-point Likert scale ranging from 1 (never or very rarely

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true) to 5 (very often or always true). The psychometric properties of the FFMQ are adequate (Baer et al., 2008; Baer et al., 2006). Daily assessment. For the daily assessments, we selected items from validated questionnaires with high loadings on the corresponding subscales (based on previous findings) in combination with their applicability in daily life. Only two items were selected per subscale because it has been recommended to use short questionnaires in diary research (Thiele, Laireiter, & Baumann, 2002) as lengthy questionnaires may induce unreliable automatic responses, reduce compliance (Morren, van Dulmen, Ouwerkerk, & Bensing, 2009), and result in dropout (Thiele et al., 2002). As a measure of negative affect, eight items were selected with high factor loadings on the original subscales of the POMS-SF (Baker et al., 2002): blue and miserable (Depression), angry and peeved (Anger), tense and nervous (Tension), fatigued and exhausted (Fatigue). Because Vigor is the only positive affect subscale of the POMS-SF, we selected three instead of two items to be able to assess positive affect reliably, namely, energetic, lively, and cheerful (Vigor). We added two extra positive affect items; relaxed and happy. These items were considered relevant in the context of MBSR as these are affective states that participants of MBSR often aim for and are often mentioned as important effects of MBSR (Kabat-Zinn, 1990; Nyklícˇek, 2011). The NA and PA scores were calculated by taking the mean of the eight, respectively five mentioned items. The composite NA and PA scores can range from 1 to 5. The internal consistency of the scales was sufficient. For the first day of the diary measurement period, Cronbach’s alpha was .84 for NA and .88 for PA. The item-total correlations of the two extra positive affect items were .74 and .71 on the first day of the diary measurement period. Furthermore, the NA items and PA items selected from the POMS at baseline correlated highly with the total NA scale (r ⫽ .95) and the total PA scale (r ⫽ .96) assessed at baseline. Also, the selected items belonging to the NA subscales correlated highly with the original NA subscales at baseline (r ⫽ .91 for depression, r ⫽ .89 for tension, r ⫽ .94 for anger, and r ⫽ .93 for fatigue). Factor analyses on the first day of the diary measurement period did not indicate a two-factor structure for NA and PA but rather supported a onefactor structure for affect. The average factor loading of the NA and PA items on one factor was .68, with a minimum of .41 and a maximum of .85. Therefore, a total daily affect score was calculated as well (i.e., the mean of the scores on the eight NA items and reversed scores on the five PA items). For the daily mindfulness measure, we selected two items for each facet of the FFMQ, again based on high loadings on the corresponding subscale in previous research (Baer et al., 2006). The chosen items were the original Items 1 and 20 for Observing, Items 12 and 16 for Describing, 23 and 28 for Acting with Awareness, 30 and 39 for Nonjudging, and 9 and 33 for Nonreacting. To make the items suitable for daily assessment, we reworded the items slightly to reflect relevance to the day that just passed. For instance, Item 1 of the FFMQ “When I am walking, I deliberately notice the sensations of my body moving” was reworded into “When I was walking, I deliberately noticed the sensations of my body moving.” Other examples of selected items to measure mindfulness were, “It was hard for me to find the words to describe what I was thinking” (Describing), “I rushed through activities without being really attentive to them” (Acting with Awareness), “I thought some of my emotions were bad or inap-

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propriate and I shouldn’t feel them” (Nonjudging), and “When I had distressing thoughts, I just noticed them and let them go” (Nonreacting). A total score for mindfulness was constructed by calculating the mean of the 10 items (range ⫽ 1–5). The Cronbach’s alpha of the daily mindfulness measure was .81 on the first day of the study. Also, the total of these 10 items assessed at baseline correlated highly with the total FFMQ score assessed at baseline (r ⫽ .93). A factor analysis on the first day of the measurement period showed that the 10 mindfulness diary items loaded sufficiently on one factor representing mindfulness, with an average factor loading of .61, a minimum of .35, and a maximum of .75. As a measure of daily mindfulness practice, the following question was included in the diary: “Did you already do a formal mindfulness exercise today?” The answer categories included “yes” and “no, not yet.” The question was asked after the daily mindfulness and mood questions.

Statistical Analysis We investigated whether day-to-day within-person changes in mindfulness precede and predict within-person changes in NA and PA, and/or the other way around. Autoregressive multilevel models (see Rovine & Walls, 2006) were specified using the STATA xtmixed command. In a first model, it was tested whether daily values of NA at each time point (t) could be predicted by lagged values of mindfulness (t-1), controlling for lagged values of NA (t-1). In a second model, the reverse lagged association was tested, that is, whether values of mindfulness at each time point (t) could be predicted by lagged values of NA (t-1), controlling for lagged values of mindfulness (t-1). Two similar models were specified to test the cross-lagged associations between mindfulness and PA. In addition, two sensitivity analyses were performed to test the crosslagged associations between mindfulness and a composite affect score including both the NA and PA items. A lag of one day was specified as it seems likely that if mindfulness affects PA and NA, it will show the next day rather than after 2 days. An additional multilevel model was specified to test whether values of mindfulness at each time point (t) could be predicted by practice of at least one mindfulness exercise during that day, controlling for lagged values of mindfulness (t-1). To explore whether the betweensubjects variability in the association between lagged values of mindfulness and affect could be explained by characteristics of the participants, we tested cross-level interactions between lagged values of mindfulness (t-1) and between-subjects factors in predicting NA and PA at time point (t). As a measure of average levels of mindfulness home practice, the mean of the item measuring daily mindfulness practice was calculated for each individual. Because a decrease or increase in the variables over time may induce spurious correlations among the variables (Rovine & Walls, 2006), any trends in the diary data were removed before the analyses were performed. To separate within-subject effects from between-subjects effects, we used the recommended approach of person-mean centering of the predictor variables, by calculating daily within-person deviations from the person’s mean (Bolger & Laurenceau, 2013; Curran & Bauer, 2011). The coefficients were allowed to differ across individuals by modeling them as random effects, to gain insight into the heterogeneity of the effects. To

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visualize this between-subjects variation in the within-subject effects, individual coefficients were predicted by best linear unbiased prediction (BLUP; a method to predict the deviation from the fixed effect for each individual based on the random effects of the multilevel model) and presented in histograms (Rabe-Hesketh & Skrondal, 2008). The concurrent (same-day) associations were not included in the autoregressive models. This was done to separate the dynamic from the simultaneous part of the model because the temporal order of the latter associations is not clear (Brandt & Williams, 2007). To provide insight in the concurrent associations, the residuals of the autoregressive multilevel models were saved and correlated. Because the diary series of some participants were either short or contained a lot of missing data (18% on average), the results of all 83 participants were compared with the results of 46 compliant participants. Participants were considered compliant if the series covered at least 45 days, with observations on at least 80% of the days. The 83 study participants provided 3,355 diary entries of which 3,236 were included in the analyses; the other 119 observations were considered invalid because the questionnaires were filled out before 5 p.m. or after 4 a.m. the next day. The length of the individual series ranged between 10 and 62 days, with an average of 47 days (SD ⫽ 10.6). The 46 compliant participants did not differ from the noncompliant participants regarding demographic variables, levels of mindfulness, and the POMS-SF at baseline.

Results Model 1: Do Changes in Mindfulness Precede Changes in NA? Consistent with our hypothesis, the fixed effects of the multilevel model for NA indicated that within-person changes in mind-

fulness preceded changes in NA. That is, higher levels of mindfulness on a certain day were followed by lower levels of NA the next day (B ⫽ ⫺0.10, 95% confidence interval [CI] ⫽ ⫺0.16 to ⫺0.04, p ⫽ .03; see Model 1 in Table 2). The random effects showed significant variability between subjects in the effect of mindfulness on NA. The variation around the Mindfulness (t-1) slope was 0.012, corresponding with 0.108 SDs. On the basis of this standard deviation, it can be estimated that 95% of the population has coefficients between ⫺0.31 and 0.11 for the effect of mindfulness on NA. On the basis of BLUP, a smaller range of between-subjects variability was predicted (see Figure 1).

Model 2: Reversing the Order: Do Changes in NA Precede Changes in Mindfulness? Changes in NA did not predict subsequent changes in mindfulness (B ⫽ 0.00, 95% CI ⫽ ⫺0.03 to 0.03, p ⫽ .96; see Model 2 in Table 2). The random effect of lagged values of NA on mindfulness was nonsignificant and removed from the model to improve model fit.

Model 3: Do Changes in Mindfulness Precede Changes in PA? Consistent with our hypothesis, the third model showed that changes in mindfulness preceded changes in PA. That is, increases in mindfulness were followed by increases in PA the next day (B ⫽ 0.07, 95% CI ⫽ 0.004 to 0.14, p ⫽ .04; see Model 3 in Table 2). The random effects indicated variability between subjects in the lagged effect of mindfulness on PA, with estimated slopes ranging between ⫺0.08 and 0.22 in approximately 95% of the population. A smaller range of between-subjects variability was indicated based on BLUP, which showed only positive coefficients for the lagged effect of mindfulness on PA (see Figure 1).

Table 2 Estimates From the Autoregressive Multilevel Models Outcome Variable Fixed effects Intercept Mindfulnesst-1 NAt-1 PAt-1 Random-effect variances Level 2 (between person) Intercept Mindfulnesst-1 NAt-1 PAt-1 Level 1 (within person) Residual ICC N/observations

NA Model 1

Mindfulness Model 2

PA Model 3

Mindfulness Model 4

1.78 (.06)ⴱⴱ ⫺0.10 (.03)ⴱⴱ 0.14 (.03)ⴱⴱ

3.31 (.05)ⴱ 0.14 (.03)ⴱ ⫺0.00 (.02), ns

2.59 (.07)ⴱⴱ 0.07 (.04)ⴱ

3.31 (.05)ⴱⴱ 0.23 (.03)ⴱⴱ

0.19 (.03)ⴱⴱ

⫺0.00 (.01), ns

0.203 (.032)ⴱ 0.015 (.007)ⴱ omitted

0.439 (.070)ⴱⴱ 0.006 (.012)ⴱ

0.204 (.032)ⴱⴱ 0.017 (.007)ⴱ

0.021 (.008)ⴱ

omitted

0.025 (.007)ⴱⴱ 0.61 83/2669

0.100 (.003)ⴱⴱ 0.67 83/2671

0.251 (.040)ⴱⴱ 0.012 (.010)ⴱ 0.018 (.007)ⴱ 0.173 (.005)ⴱⴱ 0.59 83/2669

0.101 (.003)ⴱ 0.67 83/2671

Note. ns ⫽ nonsignificant; NA ⫽ negative affect; PA ⫽ positive affect; ICC ⫽ intraclass correlation coefficient based on the random intercept model. Estimates are unstandardized coefficients (B). Between parentheses: standard error of the estimate (SE). Omitted ⫽ random effects omitted from the model because of ns. ⴱ p ⬍ .05. ⴱⴱ p ⬍ .01.

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ranging between ⫺0.43 and 0.19 in 95% of the population. Also, the random effects showed some variation between subjects in the lagged effect of affect on mindfulness, with slopes ranging between ⫺0.09 and 0.08 in approximately 95% of the population.

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Model 5: Does Daily Mindfulness Practice Predict Changes in Mindfulness? On average, home practice of at least one mindfulness exercise during the day was followed by higher levels of mindfulness in the evening (B ⫽ 0.03, 95% CI ⫽ 0.01 to 0.05, p ⬍ .01; not shown in a table). The random effect of mindfulness practice was nonsignificant, indicating that there was no significant variability in the slope, and was therefore omitted to improve model fit.

Model 1–5: Results in the Compliant Sample Rerunning the models on the data of the subsample of 46 compliant participants showed that the fixed effects were similar to those found in the total sample; increases in mindfulness were followed by decreases in NA (B ⫽ ⫺0.09, 95% CI ⫽ ⫺0.16 to ⫺0.02, p ⬍ .01) and increases in PA (B ⫽ 0.07, 95% CI ⫽ 0.001 to 0.16, p ⫽ .046) the next day. Reverse effects were not found; changes in mindfulness were not predicted by previous changes in NA (B ⫽ 0.01, 95% CI ⫽ ⫺0.03 to 0.05, p ⫽ .56) or PA (B ⫽ ⫺0.01, 95% CI ⫽ ⫺0.04 to 0.02, p ⫽ .51). Also, mindfulness practice during the day was followed by increases in mindfulness (B ⫽ 0.03, 95% CI ⫽ 0.01 to 0.05, p ⬍ .01) in the compliant sample.

Explaining Individual Differences Figure 1. Between-subjects variation in the within-subject effects of mindfulness on affect. PA ⫽ positive affect; NA ⫽ negative affect; BLUP ⫽ best linear unbiased prediction.

Model 4: Reversing the Order: Do Changes in PA Precede Changes in Mindfulness? The last model indicated that there were no reverse effects in the current sample. Changes in PA were not followed by changes in mindfulness the next day (B ⫽ 0.00, 95% CI ⫽ ⫺0.03 to 0.02, p ⫽ .90; see Model 4 in Table 2). The random effect of lagged values of PA on mindfulness was nonsignificant and removed from the model to improve model fit.

Sensitivity Analyses: Are the Results Similar for a Combined Measure of NA and PA? Additional multilevel models indicated similar results when testing the lagged associations between mindfulness and a composite measure of affect; changes in mindfulness were followed by changes in affect the next day (B ⫽ ⫺0.12, 95% CI ⫽ ⫺0.19 to ⫺0.05, p ⬍ .01) while changes in affect did not predict subsequent changes in mindfulness (B ⫽ ⫺0.01, 95% CI ⫽ ⫺0.04 to 0.01, p ⫽ .70). The between-subjects variability in the lagged effect of mindfulness on affect was larger, with estimated slopes

The between-subjects differences in the effect of lagged values mindfulness on PA and NA could not be explained by characteristics of the participants. In predicting NA, there was no significant interaction between lagged values of mindfulness and age (B ⬍ 0.01, 95% CI ⫽ ⫺0.00 to 0.01, p ⫽ .42), gender (B ⫽ 0.03, 95% CI ⫽ ⫺0.11 to 0.17, p ⫽ .70), level of education (B ⬍ 0.01, 95% CI ⫽ ⫺0.05 to 0.05, p ⫽ .85), average level of daily mindfulness practice (B ⫽ 0.10, 95% CI ⫽ ⫺0.26 to 0.47, p ⫽ .59), baseline levels of negative affect (B ⫽ ⫺0.01, 95% CI ⫽ ⫺0.08 to 0.07, p ⫽ .89), and baseline levels of mindfulness (B ⫽ ⫺0.01, 95% CI ⫽ ⫺0.14 to 0.12, p ⫽ .92). Similarly, day-to-day changes in PA were not predicted by the interaction between changes in mindfulness and age (B ⬍ ⫺0.01, 95% CI ⫽ ⫺0.01 to 0.00, p ⫽ .54), gender (B ⫽ ⫺0.11, 95% CI ⫽ ⫺0.26 to 0.04, p ⫽ .15), level of education (B ⫽ 0.05, 95% CI ⫽ ⫺0.11 to 0.12, p ⫽ .10), average level of daily mindfulness practice (B ⫽ ⫺0.04, 95% CI ⫽ ⫺0.45 to 0.37, p ⫽ .85), baseline levels of negative affect (B ⫽ 0.01, 95% CI ⫽ ⫺0.01 to 0.01, p ⫽ .84), and baseline levels of mindfulness (B ⫽ 0.01, 95% CI ⫽ ⫺0.13 to 0.15, p ⫽ .88).

Concurrent Associations Between Mindfulness, NA, and PA Strong concurrent (same-day) correlations were found among the variables. The same-day correlation between mindfulness and NA was ⫺0.47, and the correlation between mindfulness and PA was 0.45. These correlations were controlled for the lagged asso-

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ciations by using residuals of the four autoregressive multilevel models.

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Discussion To gain more insight into the direction of the association between mindfulness and psychological well-being, we examined the temporal order of within-person changes in mindfulness and NA as well as PA over the course of an MBSR program. Day-to-day changes in mindfulness predicted subsequent day-to-day changes in both NA and PA. Our results did not support reverse associations; changes in NA and PA did not predict subsequent changes in mindfulness. Similar results were obtained in analyses on the within-person lagged associations between mindfulness and a composite measure of affect including both NA and PA. Furthermore, mindfulness home practice during the day predicted subsequent increases in mindfulness. The findings held both in the total sample and in a subsample of compliant individuals. These results provide empirical support for the assumed role of mindfulness in reducing NA and enhancing PA in daily life during mindfulnessbased treatment. Our findings imply that when an individual’s levels of mindfulness are increased, this is followed by improvements in NA and PA for at least one day. It is of interest that changes in mindfulness seem to precede changes in both negative affect and positive affect, as these mood states have been shown to be relatively independent (Watson & Tellegen, 1985). When one does not feel blue or tense, this does not necessarily imply that one is energetic or cheerful. It is therefore an important finding that observing one’s experiences in an aware, nonjudgmental, and nonreacting way may be followed by feelings of liveliness and cheerfulness besides reduced feelings of anger, fatigue, or tension the next day. The results suggest that the relationship between mindfulness and affect is not reciprocal, implying that increases in mindfulness are not merely a side effect of improved mood. Increases in mindfulness preceded improvements in psychological well-being rather than the other way around. Emphasis of the value of practicing mindfulness skills by mindfulness trainers therefore does not seem superfluous, as such skills indeed seem beneficial for one’s daily well-being. Our study also showed that daily mindfulness home practice predicted increases in mindfulness, making a strong case that mindfulness can be improved by mindfulness home practice. However, people may also become more mindful because of other reasons, for example, because of working in a vegetable garden. Thus, the observed sequence of changes may also occur outside a treatment context. Future studies are encouraged to examine the studied associations in other contexts. The aim of this study was not only to investigate average lagged associations but also to examine interindividual differences in the found effects. The random effect variances indicated considerable individual differences in the magnitude of the lagged effect of mindfulness on NA and PA and also covered some associations with an opposite sign, for example, positive associations between mindfulness and NA. The individual coefficients as predicted by the BLUPs showed a smaller range of variation, which is as expected since BLUPs are shrunken toward the population mean (Rabe-Hesketh & Skrondal, 2008). It remains a matter of debate whether or not random effect models can capture such interindividual differences adequately (Gates & Molenaar, 2012). The

BLUP predictions are based on the assumption of a normal distribution of the random effects, which may result in biased estimates in case of substantial heterogeneity. A unit-by-unit approach, by using single-subject time-series analyses, may therefore be a preferable alternative when between-subjects heterogeneity is large and the number of time points is sufficient (Horváth & Wieringa, 2008). Nevertheless, the degree of heterogeneity found in the present study indicates that the found average temporal associations do not generalize to all individuals. These findings strengthen observations from other studies showing that psychological change mechanisms may differ between individuals (Bouchard et al., 2007; Molenaar, 2004). In this study, characteristics of the participants (i.e., age, gender, level of education, daily mindfulness practice, and baseline levels of mindfulness as well as affect) did not explain the observed individual differences in the effect of daily mindfulness on daily affect. The heterogeneity found in the present study may be because of differential strength of the associations or differences in the duration of the effects. In the former case, people differ in the strength of the association between daily mindfulness and subsequent affect. In the latter case, it may be that the effect of daily increases in mindfulness does not last until the next day in some persons. Future studies including within-the-day assessments may shed light on this question. The interindividual differences found in this study may also explain why changes in mindfulness predicted changes in depressive mood in only one of the six participants in our previous single-subject time-series study (Snippe et al., 2014). Consistent with our current findings, this previous study did not find evidence for reverse effects; changes in depressive symptoms did not predict changes in mindfulness in any of the six participants. The study also showed strong concurrent (same-day) associations between the variables under study in all participants, similar to the findings of this study. Our present study adds to our previous investigation by including a positive affect measure as well as by studying a large sample from the general population. Our results are also in accordance with Baer et al. (2012), who found that improvements in mindfulness in the first weeks of MBSR predicted subsequent change in weekly measures of stress. We extend this finding by using more fine-grained and bidirectional analyses of daily withinperson changes and by studying interindividual differences. This study had a number of strengths. We used an intensive longitudinal design to study the temporal order of change. This design overcomes limitations of previous studies as it allows making inferences on the temporal order of the dynamic processes that take place within individuals. Also, we presented detailed information on individual differences in the within-person dynamic associations. Several limitations should be mentioned as well. First, the variables were assessed only once a day and shorter measurement intervals may have yielded different results. Therefore, we cannot rule out that some effects were already established during the day or that there were positive feedback loops between mindfulness and affect during the day. Future studies may use more intensive sampling schedules to examine which time interval matches the speed of the effect of mindfulness on affect. Furthermore, the use of only 10 daily mindfulness and affect items might limit the validity of the measures, although our measures correlated highly with the original total scores. Although baseline levels of anxiety and depression were substantially higher

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THE ORDER OF CHANGE IN MINDFULNESS AND AFFECT

in the present sample compared to the general population, the findings may not generalize to individuals with a psychiatric diagnosis or a lower level of education as the sample was not a psychiatric sample and the majority of the sample was highly educated. For counseling psychologists, it is relevant to know that training mindfulness skills may be a beneficial means to increase psychological well-being. Our findings suggest daily mindfulness home practice may improve the capacity for mindfulness. Daily mindfulness practice is part of different training programs, such as MBSR, mindfulness-based cognitive therapy, and acceptance and commitment therapy. A recent trial has shown that also an individual form of mindfulness-based cognitive therapy is effective in reducing depressive symptoms (Tovote et al., 2014). Counseling psychologists might consider assigning mindfulness practice to their clients in an aim to improve their mood. However, therapists may bear in mind that increasing the capacity for mindfulness may not benefit everyone. This is evidenced by the observed individual differences in the effects. Future research should show whether daily well-being of these individuals is more likely to be improved through enhancing other skills in different forms of treatment or whether mindfulness enhances a positive mood of these individuals already within the day. In addition, future studies could examine factors, such as personality, that may predict the differential impact of mindfulness on affect. In conclusion, our results make a reasonable case that increases in mindfulness precede improvements in negative affect and positive affect, instead of increases in mindfulness being a side effect of an improved mood. The findings of the study could also be valuable beyond the context of MBSR as individuals may also improve their daily psychological well-being by practicing mindfulness in their daily life.

References Baer, R. A., Carmody, J., & Hunsinger, M. (2012). Weekly change in mindfulness and perceived stress in a mindfulness-based stress reduction program. Journal of Clinical Psychology, 68, 755–765. http://dx.doi.org/ 10.1002/jclp.21865 Baer, R. A., Smith, G. T., Hopkins, J., Krietemeyer, J., & Toney, L. (2006). Using self-report assessment methods to explore facets of mindfulness. Assessment, 13, 27– 45. http://dx.doi.org/10.1177/1073191105283504 Baer, R. A., Smith, G. T., Lykins, E., Button, D., Krietemeyer, J., Sauer, S., . . . Williams, J. M. (2008). Construct validity of the five facet mindfulness questionnaire in meditating and nonmeditating samples. Assessment, 15, 329 –342. http://dx.doi.org/10.1177/1073191107313003 Baker, F., Denniston, M., Zabora, J., Polland, A., & Dudley, W. N. (2002). A POMS short form for cancer patients: Psychometric and structural evaluation. Psycho-Oncology, 11, 273–281. http://dx.doi.org/10.1002/ pon.564 Bishop, S. R. (2002). What do we really know about mindfulness-based stress reduction? Psychosomatic Medicine, 64, 71– 83. http://dx.doi.org/ 10.1097/00006842-200201000-00010 Bishop, S. R., Lau, M., Shapiro, S., Carlson, L., Anderson, N. D., Carmody, J., . . . Devins, G. (2004). Mindfulness: A proposed operational definition. Clinical Psychology: Science and Practice, 11, 230 –241. http://dx.doi.org/10.1093/clipsy.bph077 Bolger, N., & Laurenceau, J. (2013). Intensive longitudinal methods: An introduction to diary and experience sampling research. New York, NY: Guilford Press. Bouchard, S., Gauthier, J., Nouwen, A., Ivers, H., Vallières, A., Simard, S., & Fournier, T. (2007). Temporal relationship between dysfunctional

113

beliefs, self-efficacy and panic apprehension in the treatment of panic disorder with agoraphobia. Journal of Behavior Therapy and Experimental Psychiatry, 38, 275–292. http://dx.doi.org/10.1016/j.jbtep.2006 .08.002 Brandt, P. T., & Williams, J. T. (2007). Multiple time series models. Thousand Oaks, CA: Sage. Bränström, R., Kvillemo, P., Brandberg, Y., & Moskowitz, J. T. (2010). Self-report mindfulness as a mediator of psychological well-being in a stress reduction intervention for cancer patients—A randomized study. Annals of Behavioral Medicine, 39, 151–161. http://dx.doi.org/10.1007/ s12160-010-9168-6 Brown, K. W., & Ryan, R. M. (2003). The benefits of being present: Mindfulness and its role in psychological well-being. Journal of Personality and Social Psychology, 84, 822– 848. http://dx.doi.org/10.1037/ 0022-3514.84.4.822 Brown, K. W., Ryan, R. M., & Creswell, J. D. (2007). Mindfulness: Theoretical foundations and evidence for its salutary effects. Psychological Inquiry, 18, 211–237. http://dx.doi.org/10.1080/10478400701598298 Carmody, J., & Baer, R. A. (2008). Relationships between mindfulness practice and levels of mindfulness, medical and psychological symptoms and well-being in a mindfulness-based stress reduction program. Journal of Behavioral Medicine, 31, 23–33. http://dx.doi.org/10.1007/s10865007-9130-7 Chambers, R., Gullone, E., & Allen, N. B. (2009). Mindful emotion regulation: An integrative review. Clinical Psychology Review, 29, 560 – 572. http://dx.doi.org/10.1016/j.cpr.2009.06.005 Curran, P. J., & Bauer, D. J. (2011). The disaggregation of within-person and between-person effects in longitudinal models of change. Annual Review of Psychology, 62, 583– 619. http://dx.doi.org/10.1146/annurev .psych.093008.100356 Gates, K. M., & Molenaar, P. C. M. (2012). Group search algorithm recovers effective connectivity maps for individuals in homogeneous and heterogeneous samples. NeuroImage, 63, 310 –319. http://dx.doi .org/10.1016/j.neuroimage.2012.06.026 Hamaker, E. L. (2012). Why researchers should think ‘within-person’: A paradigmatic rationale. In M. R. Mehl & T. S. Conner (Eds.), Handbook of research methods for studying daily life (pp. 43– 61). New York, NY: Guilford Press. Hamaker, E. L., Dolan, C. V., & Molenaar, P. C. M. (2005). Statistical modeling of the individual: Rationale and application of multivariate stationary time series analysis. Multivariate Behavioral Research, 40, 207–233. http://dx.doi.org/10.1207/s15327906mbr4002_3 Heeren, A., Deplus, S., Peschard, V., Nef, F., Kotsou, I., Dierickx, C., . . . Philippot, P. (2014). Does change in self-reported mindfulness mediate the clinical benefits of mindfulness training? A controlled study using the French translation of the Five Facet Mindfulness Questionnaire. Mindfulness. http://dx.doi.org/10.1007/s12671-014-0287-1 Hölzel, B. K., Lazar, S. W., Gard, T., Schuman-Olivier, Z., Vago, D. R., & Ott, U. (2011). How does mindfulness meditation work? Proposing mechanisms of action from a conceptual and neural perspective. Perspectives on Psychological Science, 6, 537–559. http://dx.doi.org/ 10.1177/1745691611419671 Hofmann, S. G., Asmundson, G. J. G., & Beck, A. T. (2013). The science of cognitive therapy. Behavior Therapy, 44, 199 –212. http://dx.doi.org/ 10.1016/j.beth.2009.01.007 Hofmann, S. G., Sawyer, A. T., Witt, A. A., & Oh, D. (2010). The effect of mindfulness-based therapy on anxiety and depression: A metaanalytic review. Journal of Consulting and Clinical Psychology, 78, 169 –183. http://dx.doi.org/10.1037/a0018555 Horváth, C., & Wieringa, J. E. (2008). Pooling data for the analysis of dynamic marketing systems. Statistica Neerlandica, 62, 208 –229. http:// dx.doi.org/10.1111/j.1467-9574.2007.00382.x Jislin-Goldberg, T., Tanay, G., & Bernstein, A. (2012). Mindfulness and positive affect: Cross-sectional, prospective intervention, and real-time

This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

114

SNIPPE, NYKLÍCˇEK, SCHROEVERS, AND BOS

relations. The Journal of Positive Psychology, 7, 349 –361. http://dx.doi .org/10.1080/17439760.2012.700724 Kabat-Zinn, J. (1990). Full catastrophe living: Using the wisdom of your body and mind to face stress, pain, and illness. New York, NY: Delacourt. Kabat-Zinn, J. (1994). Wherever you go, there you are: Mindfulness meditation in everyday life. New York, NY: Hyperion. Kazdin, A. E. (2007). Mediators and mechanisms of change in psychotherapy research. Annual Review of Clinical Psychology, 3, 1–27. http:// dx.doi.org/10.1146/annurev.clinpsy.3.022806.091432 Kazdin, A. E., & Nock, M. K. (2003). Delineating mechanisms of change in child and adolescent therapy: Methodological issues and research recommendations. Journal of Child Psychology and Psychiatry, 44, 1116 –1129. http://dx.doi.org/10.1111/1469-7610.00195 Khoury, B., Lecomte, T., Fortin, G., Masse, M., Therien, P., Bouchard, V., . . . Hofmann, S. G. (2013). Mindfulness-based therapy: A comprehensive meta-analysis. Clinical Psychology Review, 33, 763–771. http://dx .doi.org/10.1016/j.cpr.2013.05.005 Kraemer, H. C., Wilson, G. T., Fairburn, C. G., & Agras, W. S. (2002). Mediators and moderators of treatment effects in randomized clinical trials. Archives of General Psychiatry, 59, 877– 883. http://dx.doi.org/ 10.1001/archpsyc.59.10.877 Labelle, L. E., Campbell, T. S., & Carlson, L. E. (2010). Mindfulnessbased stress reduction in oncology: Evaluating mindfulness and rumination as mediators of change in depressive symptoms. Mindfulness, 1, 28 – 40. http://dx.doi.org/10.1007/s12671-010-0005-6 Molenaar, P. C. M. (2004). A manifesto on psychology as idiographic science: Bringing the person back into scientific psychology, this time forever. Measurement: Interdisciplinary Research and Perspectives, 2, 201–218. http://dx.doi.org/10.1207/s15366359mea0204_1 Morren, M., van Dulmen, S., Ouwerkerk, J., & Bensing, J. (2009). Compliance with momentary pain measurement using electronic diaries: A systematic review. European Journal of Pain, 13, 354 –365. http://dx .doi.org/10.1016/j.ejpain.2008.05.010 Nyklícˇek, I. (2011). Mindfulness, emotion regulation, and well-being. In I. Nyklícˇek, A. Vingerhoets, & M. Zeelenberg (Eds.), Emotion regulation and well-being (pp. 101–118). New York, NY: Springer Science ⫹ Business Media. Nyklícek, I., & Kuijpers, K. F. (2008). Effects of mindfulness-based stress reduction intervention on psychological well-being and quality of life: Is increased mindfulness indeed the mechanism? Annals of Behavioral Medicine, 35, 331–340. http://dx.doi.org/10.1007/s12160-008-9030-2 Rabe-Hesketh, S., & Skrondal, A. (2008). Multilevel and longitudinal modeling using stata (2nd ed.). College Station, TX: Stata press. Rovine, M. J., & Walls, T. A. (2006). Multilevel autoregressive modeling of interindividual differences in the stability of a process. In T. A. Walls & J. L. Schafer (Eds.), Models for intensive longitudinal data (pp. 124 –147). New York, NY: Oxford University Press. http://dx.doi.org/ 10.1093/acprof:oso/9780195173444.003.0006 Schroevers, M. J., & Brandsma, R. (2010). Is learning mindfulness associated with improved affect after mindfulness-based cognitive therapy? British Journal of Psychology, 101, 95–107. http://dx.doi.org/10.1348/ 000712609X424195 Segal, Z. V., Williams, J. M. G., & Teasdale, J. D. (2002). Mindfulnessbased cognitive therapy for depression. New York, NY: Guilford Press.

Segal, Z. V., Williams, J. M., Teasdale, J. D., & Gemar, M. (1996). A cognitive science perspective on kindling and episode sensitization in recurrent affective disorder. Psychological Medicine, 26, 371–380. http://dx.doi.org/10.1017/S0033291700034760 Shacham, S. (1983). A shortened version of the Profile of Mood States. Journal of Personality Assessment, 47, 305–306. http://dx.doi.org/ 10.1207/s15327752jpa4703_14 Shahar, B., Britton, W. B., Sbarra, D. A., Figueredo, A. J., & Bootzin, R. R. (2010). Mechanisms of change in mindfulness-based cognitive therapy for depression: Preliminary evidence from a randomized controlled trial. International Journal of Cognitive Therapy, 3, 402– 418. http://dx.doi .org/10.1521/ijct.2010.3.4.402 Shapiro, S. L., Oman, D., Thoresen, C. E., Plante, T. G., & Flinders, T. (2008). Cultivating mindfulness: Effects on well-being. Journal of Clinical Psychology, 64, 840 – 862. http://dx.doi.org/10.1002/jclp.20491 Snippe, E., Bos, E. H., Ploeg, K. M., Sanderman, R., Fleer, J., & Schroevers, M. J. (2014). Time-series analysis of daily changes in mindfulness, repetitive thinking, and depressive symptoms during mindfulnessbased treatment. Mindfulness, Advance online publication. http://dx.doi .org/10.1007/s12671-014-0354-7 Thiele, C., Laireiter, A., & Baumann, U. (2002). Diaries in clinical psychology and psychotherapy: A selective review. Clinical Psychology & Psychotherapy, 9, 1–37. Tovote, K. A., Fleer, J., Snippe, E., Peeters, A. C. T. M., Emmelkamp, P. M. G., Sanderman, R., . . . Schroevers, M. J. (2014). Individual mindfulness-based cognitive therapy and cognitive behavior therapy for treating depressive symptoms in patients with diabetes: Results of a randomized controlled trial. Diabetes Care, 37, 2427–2434. http://dx.doi .org/10.2337/dc13-2918 van Aalderen, J. R., Donders, A. R. T., Giommi, F., Spinhoven, P., Barendregt, H. P., & Speckens, A. E. M. (2012). The efficacy of mindfulness-based cognitive therapy in recurrent depressed patients with and without a current depressive episode: A randomized controlled trial. Psychological Medicine, 42, 989 –1001. http://dx.doi.org/10.1017/ S0033291711002054 Vøllestad, J., Sivertsen, B., & Nielsen, G. H. (2011). Mindfulness-based stress reduction for patients with anxiety disorders: Evaluation in a randomized controlled trial. Behaviour Research and Therapy, 49, 281– 288. http://dx.doi.org/10.1016/j.brat.2011.01.007 Wald, F. D., & Mellenbergh, G. J. (1990). De verkorte versie van de nederlandse vertaling van de profile of mood states (POMS). Nederlands Tijdschrift voor de Psychologie en Haar Grensgebieden, 45, 86 –90. Watson, D., Clark, L. A., & Carey, G. (1988). Positive and negative affectivity and their relation to anxiety and depressive disorders. Journal of Abnormal Psychology, 97, 346 –353. http://dx.doi.org/10.1037/0021843X.97.3.346 Watson, D., & Tellegen, A. (1985). Toward a consensual structure of mood. Psychological Bulletin, 98, 219 –235. http://dx.doi.org/10.1037/ 0033-2909.98.2.219

Received July 10, 2014 Revision received November 24, 2014 Accepted November 25, 2014 䡲