Living with chronic headache
Ciere, Yvette
IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below.
Document Version
Publisher's PDF, also known as Version of record
Publication date: 2018
Link to publication in University of Groningen/UMCG research database
Citation for published version (APA):
Ciere, Y. (2018). Living with chronic headache: A personal goal and self-regulation perspective. University of Groningen.
Copyright
Other than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons).
Take-down policy
If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.
Downloaded from the University of Groningen/UMCG research database (Pure): http://www.rug.nl/research/portal. For technical reasons the number of authors shown on this cover page is limited to 10 maximum.
Positive affect buffers affective reactivity
in chronic migraine – an experience
sampling study
Yvette Ciere, Evelien Snippe, Mariëlle Padberg, Bram
Jacobs, Annemieke Visser, Robbert Sanderman, Joke Fleer
Revision
Chapter
ABSTRACT
Background: High affective reactivity to pain (i.e., increased negative affect in response to
pain) can have an adverse impact on the health and well-being of individuals with chronic pain. The present study examined the role of positive affect and mindfulness in protecting against affective reactivity to pain in the context of chronic migraine.
Methods: The sample included 61 adults with chronic migraine. Following the Experience
Sampling Method, participants completed smartphone based assessments of momentary pain intensity, positive affect (PA), and negative affect (NA) at 9 random moments a day, for 7 consecutive days. The Five-Facet Mindfulness Questionnaire was used to assess two dimensions of mindfulness: non-judging and non-reactivity.
Results: Multilevel regression models showed that higher momentary PA predicted weaker
concurrent and time-lagged associations between pain intensity and NA. Higher average PA predicted only the time-lagged, but not the concurrent associations between pain intensity and NA. Higher non-judging was associated with weaker time-lagged pain-NA associations. Unexpectedly, higher non-reactivity was associated with stronger pain-NA associations.
Discussion: Results suggest that higher PA during pain episodes protects against affective
reactivity to chronic migraine pain. Findings also provide partial support for a protective role of trait PA and mindfulness in reducing the association between pain at one moment in time and NA at the next moment in time. Interventions promoting mental well-being in individuals with chronic migraine should therefore focus on the ability to access positive emotions during pain episodes, as well as in between pain episodes.
INTRODUCTION
For individuals with chronic pain, episodes of pain can be a daily stressor that elicits a range of negative emotions (e.g., sadness, tension, frustration). Some individuals may show greater affective reactivity to pain than others, displaying a higher increase in negative affect (NA) in response to pain flare ups. Greater affective reactivity to daily stressors has been associated with poorer physical and mental health outcomes in healthy individuals (O'Neill, Cohen, Tolpin, & Gunthert, 2004; Piazza, Charles, Sliwinski, Mogle, & Almeida, 2013; Sin, Graham-Engeland, Ong, & Almeida, 2015; van Winkel et al., 2015) and in individuals with chronic pain (Rost et al., 2016; van Middendorp et al., 2010; Zautra & Smith, 2001). It is therefore important to gain insight into factors that protect against affective reactivity. Such factors could act as targets for interventions aimed at improving health and well-being in individuals with chronic pain. The present study examined whether affective reactivity in chronic migraine can be buffered by two factors: positive affect and mindfulness.
The Dynamic Model of Affect (DMA) poses that during a stressful event, the presence of positive affect (PA) may buffer against affective reactivity (Zautra, Potter, & Reich, 1997). PA refers to pleasant mood or emotions, such as joy, contentment, or pride (Watson, Clark, & Tellegen, 1988). Although PA is relatively independent from NA in normal circumstances, the DMA assumes that PA and NA become more interdependent during a stressful event. As a result of this increased interdependence, higher PA at the time of the stressor may counteract the increase of NA in response to stress or pain (Zautra, Smith, Affleck, & Tennen, 2001). Accordingly, a few intensive longitudinal studies in individuals with arthritis and fibromyalgia have found that increases in pain are less strongly associated with NA in the presence of higher PA (Strand et al., 2006; Zautra, Johnson, & Davis, 2005; Zautra et al., 2001). These studies were however limited to the examination of concurrent associations and therefore did not provide insight into whether PA actually predicts an increase in NA from one moment to the next.
A different yet complementary role of positive affect in the context of stress has been proposed by the Broaden-and-Build Model (BBM) (Fredrickson, 1998). According to the BBM, positive emotions help build coping resources by broadening attention and
promoting goal-directed action (Fredrickson, 2001). Individuals who generally experience higher levels of positive affect may therefore be better equipped for coping with stressful events and hence respond to such an event with less NA. Thus, while the DMA assumes a protective role for state PA, the BBM assumes a similar role for trait PA. Although the BBM was not specifically developed to explain stress-responses in the context of pain, Zautra et al. did find that average (i.e., trait) PA moderated the associations between weekly pain and negative affect in women with fibromyalgia and osteoarthritis (Zautra et al., 2005). This finding however awaits replication in other chronic pain conditions, including chronic migraine.
ABSTRACT
Background: High affective reactivity to pain (i.e., increased negative affect in response to
pain) can have an adverse impact on the health and well-being of individuals with chronic pain. The present study examined the role of positive affect and mindfulness in protecting against affective reactivity to pain in the context of chronic migraine.
Methods: The sample included 61 adults with chronic migraine. Following the Experience
Sampling Method, participants completed smartphone based assessments of momentary pain intensity, positive affect (PA), and negative affect (NA) at 9 random moments a day, for 7 consecutive days. The Five-Facet Mindfulness Questionnaire was used to assess two dimensions of mindfulness: non-judging and non-reactivity.
Results: Multilevel regression models showed that higher momentary PA predicted weaker
concurrent and time-lagged associations between pain intensity and NA. Higher average PA predicted only the time-lagged, but not the concurrent associations between pain intensity and NA. Higher non-judging was associated with weaker time-lagged pain-NA associations. Unexpectedly, higher non-reactivity was associated with stronger pain-NA associations.
Discussion: Results suggest that higher PA during pain episodes protects against affective
reactivity to chronic migraine pain. Findings also provide partial support for a protective role of trait PA and mindfulness in reducing the association between pain at one moment in time and NA at the next moment in time. Interventions promoting mental well-being in individuals with chronic migraine should therefore focus on the ability to access positive emotions during pain episodes, as well as in between pain episodes.
Affective reactivity in chronic migraine _________________________________________________________________________
INTRODUCTION
For individuals with chronic pain, episodes of pain can be a daily stressor that elicits a range of negative emotions (e.g., sadness, tension, frustration). Some individuals may show greater affective reactivity to pain than others, displaying a higher increase in negative affect (NA) in response to pain flare ups. Greater affective reactivity to daily stressors has been associated with poorer physical and mental health outcomes in healthy individuals (O'Neill, Cohen, Tolpin, & Gunthert, 2004; Piazza, Charles, Sliwinski, Mogle, & Almeida, 2013; Sin, Graham-Engeland, Ong, & Almeida, 2015; van Winkel et al., 2015) and in individuals with chronic pain (Rost et al., 2016; van Middendorp et al., 2010; Zautra & Smith, 2001). It is therefore important to gain insight into factors that protect against affective reactivity. Such factors could act as targets for interventions aimed at improving health and well-being in individuals with chronic pain. The present study examined whether affective reactivity in chronic migraine can be buffered by two factors: positive affect and mindfulness.
The Dynamic Model of Affect (DMA) poses that during a stressful event, the presence of positive affect (PA) may buffer against affective reactivity (Zautra, Potter, & Reich, 1997). PA refers to pleasant mood or emotions, such as joy, contentment, or pride (Watson, Clark, & Tellegen, 1988). Although PA is relatively independent from NA in normal circumstances, the DMA assumes that PA and NA become more interdependent during a stressful event. As a result of this increased interdependence, higher PA at the time of the stressor may counteract the increase of NA in response to stress or pain (Zautra, Smith, Affleck, & Tennen, 2001). Accordingly, a few intensive longitudinal studies in individuals with arthritis and fibromyalgia have found that increases in pain are less strongly associated with NA in the presence of higher PA (Strand et al., 2006; Zautra, Johnson, & Davis, 2005; Zautra et al., 2001). These studies were however limited to the examination of concurrent associations and therefore did not provide insight into whether PA actually predicts an increase in NA from one moment to the next.
A different yet complementary role of positive affect in the context of stress has been proposed by the Broaden-and-Build Model (BBM) (Fredrickson, 1998). According to the BBM, positive emotions help build coping resources by broadening attention and
promoting goal-directed action (Fredrickson, 2001). Individuals who generally experience higher levels of positive affect may therefore be better equipped for coping with stressful events and hence respond to such an event with less NA. Thus, while the DMA assumes a protective role for state PA, the BBM assumes a similar role for trait PA. Although the BBM was not specifically developed to explain stress-responses in the context of pain, Zautra et al. did find that average (i.e., trait) PA moderated the associations between weekly pain and negative affect in women with fibromyalgia and osteoarthritis (Zautra et al., 2005). This finding however awaits replication in other chronic pain conditions, including chronic migraine.
Another factor that may explain individual differences in affective reactivity to pain is trait mindfulness, in particular a non-judgmental and non-reactive orientation towards experience (e.g., pain, emotions) (Bishop et al., 2004). The ability to experience pain without judging or reacting to it may help to reduce maladaptive cognitive and behavioral responses to pain (e.g., catastrophizing, worrying) and subsequent increases in negative affect (Davis, Zautra, Wolf, Tennen, & Yeung, 2015; Garland et al., 2012). Studies in chronic pain have indeed found that higher trait mindfulness is associated with lower catastrophizing and negative affect, but these studies did not focus specifically on non-judging and non-reactivity (Cassidy, Atherton, Robertson, Walsh, & Gillett, 2012; McCracken, Gauntlett-Gilbert, & Vowles, 2007; Schutze, Rees, Preece, & Schutze, 2010). Moreover, they did not examine the role of trait mindfulness in the moment-to-moment associations between pain and negative affect in daily life, which limits ecological validity of findings.
In sum, while the DMA assumes that positive affect during a pain episode buffers affective reactivity to pain, other theories suggest that these associations could depend on individual differences in average positive affect and mindfulness. The aim of this study was to conduct a first examination of these assumptions in individuals with chronic migraine. The Experience Sampling Method (Csikszentmihalyi & Larson, 1987; de Vries, 1992) was used to obtain ecologically valid assessments of pain (i.e., the intensity of headache) and affect in daily life, as well as to examine both concurrent and prospective (i.e., time lagged) relationships between these variables. We hypothesized that increases in pain would be less strongly associated with negative affect (at the same and the next moment in time) when individuals experienced higher levels of positive affect at the moment of pain. Furthermore, we expected lower affective reactivity to pain in individuals with higher average levels positive affect and mindfulness (i.e., non-judging and non-reactivity).
METHODS Participants
Patients with chronic migraine were recruited via i) two neurology outpatient clinics, ii) the Dutch Society for Headache Patients, and iii) local newspapers. Interested patients were called by the researcher to provide further information and screening. Patients were eligible if they were 18 years or older, currently fulfilled ICHD-III criteria for chronic migraine (Headache Classification Committee of the International Headache Society (IHS, 2013). Exclusion criteria were: diagnosis of a secondary headache disorder (i.e., headache
attributed to a structural lesion), with exception of medication-overuse headache; pregnancy in the past year; complete withdrawal from analgesics in the past 3 months; changes in prophylactic or psychological treatment in the past 2 months; severe mental illness; severe memory deficits; poor Dutch language fluency; not in the possession of a smartphone with internet connection.
In total, 247 patients were contacted about the study. Of the 159 patients who were screened for eligibility, 71 were found eligible. The most common reasons for non-eligibility were having less than 15 headache days or less than 8 migraine days per month (n=64) and recent changes in pharmacological or psychological treatment that may influence the study results (n=18). Finally, 67 patients provided informed consent. Six patients dropped out during the study; reasons for drop out included illness (N=2), too many technical issues with the smartphone diary (N=2), and finding the study protocol too burdensome (N=2).
The final sample consisted of 61 participants. The mean age of participants was 41.25 (SD = 13.24) and the large majority (95.1%) was female. Three quarters (75.5%) of participants had a partner. Educational level was high in 45.9% of participants, middle in 44.3%, and low in 9.8%. About one-third (45.9%) of participants was either full-time or part-time (self-)employed, 29.5% received disability benefits, and 24.6% had another main activity (e.g., studying).
Procedure
The Experience Sampling Method (ESM) (Csikszentmihalyi & Larson, 1987; de Vries, 1992) was used to collect diary assessments of momentary pain intensity, positive affect, and negative affect nine times a day, for seven consecutive days. An end-of-day diary was used to assess relevant contextual variables (e.g., stressful events). Prior to the ESM period, participants completed an online baseline questionnaire including a standardized measure for mindfulness. During a telephonic briefing session with the researcher (YC) participants were instructed about the procedure and completed a practice diary.
ESM diaries were completed via a web-based application (Online Digital Assistance; (Sorbi, Mak, Houtveen, Kleiboer, & van Doornen, 2007) that operated on participants’ own smartphone. At each assessment point, participants received a text message with a link to the diary questionnaire which they were requested to fill out within the next 30 minutes. Paper-and-pencil diaries were available in case of technical problems (e.g., no internet connection). The ESM diaries were sent during waking hours at random moments within 90-minute time frames. End-of-day diaries were sent at a fixed time-point after the last ESM diary. To promote compliance with the protocol, participants received a financial reward of €50 if they completed at least 80% of the diaries. Participants were excluded from analyses if they completed less than 30% of the diaries. All participants gave written informed consent. The medical ethical committees of the University Medical Center Groningen and the Martini Hospital Groningen approved of the study protocol (NL49506.042).
Affective reactivity in chronic migraine
_________________________________________________________________________ Another factor that may explain individual differences in affective reactivity to pain is trait mindfulness, in particular a non-judgmental and non-reactive orientation towards experience (e.g., pain, emotions) (Bishop et al., 2004). The ability to experience pain without judging or reacting to it may help to reduce maladaptive cognitive and behavioral responses to pain (e.g., catastrophizing, worrying) and subsequent increases in negative affect (Davis, Zautra, Wolf, Tennen, & Yeung, 2015; Garland et al., 2012). Studies in chronic pain have indeed found that higher trait mindfulness is associated with lower catastrophizing and negative affect, but these studies did not focus specifically on non-judging and non-reactivity (Cassidy, Atherton, Robertson, Walsh, & Gillett, 2012; McCracken, Gauntlett-Gilbert, & Vowles, 2007; Schutze, Rees, Preece, & Schutze, 2010). Moreover, they did not examine the role of trait mindfulness in the moment-to-moment associations between pain and negative affect in daily life, which limits ecological validity of findings.
In sum, while the DMA assumes that positive affect during a pain episode buffers affective reactivity to pain, other theories suggest that these associations could depend on individual differences in average positive affect and mindfulness. The aim of this study was to conduct a first examination of these assumptions in individuals with chronic migraine. The Experience Sampling Method (Csikszentmihalyi & Larson, 1987; de Vries, 1992) was used to obtain ecologically valid assessments of pain (i.e., the intensity of headache) and affect in daily life, as well as to examine both concurrent and prospective (i.e., time lagged) relationships between these variables. We hypothesized that increases in pain would be less strongly associated with negative affect (at the same and the next moment in time) when individuals experienced higher levels of positive affect at the moment of pain. Furthermore, we expected lower affective reactivity to pain in individuals with higher average levels positive affect and mindfulness (i.e., non-judging and non-reactivity).
METHODS Participants
Patients with chronic migraine were recruited via i) two neurology outpatient clinics, ii) the Dutch Society for Headache Patients, and iii) local newspapers. Interested patients were called by the researcher to provide further information and screening. Patients were eligible if they were 18 years or older, currently fulfilled ICHD-III criteria for chronic migraine (Headache Classification Committee of the International Headache Society (IHS, 2013). Exclusion criteria were: diagnosis of a secondary headache disorder (i.e., headache
attributed to a structural lesion), with exception of medication-overuse headache; pregnancy in the past year; complete withdrawal from analgesics in the past 3 months; changes in prophylactic or psychological treatment in the past 2 months; severe mental illness; severe memory deficits; poor Dutch language fluency; not in the possession of a smartphone with internet connection.
Affective reactivity in chronic migraine _________________________________________________________________________
In total, 247 patients were contacted about the study. Of the 159 patients who were screened for eligibility, 71 were found eligible. The most common reasons for non-eligibility were having less than 15 headache days or less than 8 migraine days per month (n=64) and recent changes in pharmacological or psychological treatment that may influence the study results (n=18). Finally, 67 patients provided informed consent. Six patients dropped out during the study; reasons for drop out included illness (N=2), too many technical issues with the smartphone diary (N=2), and finding the study protocol too burdensome (N=2).
The final sample consisted of 61 participants. The mean age of participants was 41.25 (SD = 13.24) and the large majority (95.1%) was female. Three quarters (75.5%) of participants had a partner. Educational level was high in 45.9% of participants, middle in 44.3%, and low in 9.8%. About one-third (45.9%) of participants was either full-time or part-time (self-)employed, 29.5% received disability benefits, and 24.6% had another main activity (e.g., studying).
Procedure
The Experience Sampling Method (ESM) (Csikszentmihalyi & Larson, 1987; de Vries, 1992) was used to collect diary assessments of momentary pain intensity, positive affect, and negative affect nine times a day, for seven consecutive days. An end-of-day diary was used to assess relevant contextual variables (e.g., stressful events). Prior to the ESM period, participants completed an online baseline questionnaire including a standardized measure for mindfulness. During a telephonic briefing session with the researcher (YC) participants were instructed about the procedure and completed a practice diary.
ESM diaries were completed via a web-based application (Online Digital Assistance; (Sorbi, Mak, Houtveen, Kleiboer, & van Doornen, 2007) that operated on participants’ own smartphone. At each assessment point, participants received a text message with a link to the diary questionnaire which they were requested to fill out within the next 30 minutes. Paper-and-pencil diaries were available in case of technical problems (e.g., no internet connection). The ESM diaries were sent during waking hours at random moments within 90-minute time frames. End-of-day diaries were sent at a fixed time-point after the last ESM diary. To promote compliance with the protocol, participants received a financial reward of €50 if they completed at least 80% of the diaries. Participants were excluded from analyses if they completed less than 30% of the diaries. All participants gave written informed consent. The medical ethical committees of the University Medical Center Groningen and the Martini Hospital Groningen approved of the study protocol (NL49506.042).
Measures
Pain intensity – At each ESM assessment, momentary pain intensity was rated in
response to the item ‘At this moment, I’m having a headache’. All ESM items were answered on a 7-point Likert scale ranging from 0 (not at all) to 6 (very).
Positive and negative affect – At each ESM assessment, positive and negative mood
adjectives were rated on a 7-point Likert scale ranging from 0 (not at all) to 6 (very). For the purpose of this study, we used items that i) showed sufficient within-person variation over time, and ii) loaded onto a factor representing positive affect (PA) or negative affect (NA). Two NA items (‘I feel lonely’ and ‘I feel anxious’) were excluded because they showed insufficient within-person variation. Principal component factor analysis with oblique rotation indicated that the mood adjectives ‘content’, ‘enthusiastic’, ‘relaxed’, ‘cheerful’ and ‘strong’ loaded onto one factor representing PA (alpha = .88) and ‘sad’, ‘gloomy’, ‘irritable’, ‘tense’, and ‘worried’ onto a factor representing NA (alpha = .80). Hence, we used these items to obtain a mean score for (state) PA and NA at each
assessment. Trait PA was represented by the average of an individual’s PA scores across all assessments.
Mindfulness – At the baseline assessment, two subscales of the Five Facet Mindfulness
Questionnaire (FFMQ) (Baer, Smith, Hopkins, Krietemeyer, & Toney, 2006; Veehof, Peter, Taal, Westerhof, & Bohlmeijer, 2011) were used to assess two dimensions of mindfulness: non-judging and non-reactivity. The ‘non-judging’ subscale measures the extent to which one is judgmental towards inner experience and contains items such as “I criticize myself for having irrational or inappropriate emotions”. The non-reactivity subscale measures the extent to which one tends to react on inner experiences and includes items such as: ”I watch my feelings without getting lost in them”. All items were answered on a 5-point Likert scale ranging from 1 ‘never or very rarely true’ to 5 ‘very often or always true’ (Baer et al., 2006). Mean scores were calculated for each subscale; items of the nonjudging subscale were reverse coded so that higher scores represent a more nonjudgmental stance towards experience. Cronbach’s alpha for the FFMQ in this sample was .89 for non-judging and .86 for non-reactivity.
Statistical analyses
Since the ESM data had a hierarchical two-level structure (i.e., ESM assessments nested within individuals), data were analyzed with multilevel modelling using the XTMIXED command in Stata 14 (StataCorp, 2015). In all models, the dependent variable was negative affect at time ‘t’. In the concurrent models, level 1 (‘assessment level’) predictors were time (i.e., a continuous variable ranging from the first assessment (0) till the last assessment (63), while inserting a missing observation between the last observation on one day and the first on the next day), pain intensity and positive affect at time ‘t’. In the time-lagged models, level 1 predictors were time, pain intensity and positive affect time ‘t-1’ as well as
negative affect at ‘t-1’. In both concurrent and time-lagged models, level 2 (‘person level’) predictors were average positive affect, non-judging, and non-reactivity. To test our hypotheses, interaction terms were added to the concurrent and time-lagged models. The hypothesis that state positive affect buffers the impact of pain intensity on negative affect was tested by modelling the interaction between momentary pain intensity and positive affect. The buffering effect of trait positive affect was modelled as the cross-level interaction between the person average of positive affect and momentary pain intensity. Finally, the protective role of mindfulness was examined with the cross-level interaction between non-judging and pain intensity and the interaction between non-reactivity and pain intensity.
In all models, we controlled for medication use since the last assessment, sleep quality in the previous night, and the extent to which stressful events occurred during the day. Time-varying predictors were first grand-mean centered and then person-mean centered to separate within-subject effects from between-subject effects (Bolger & Laurenceau, 2013). All models included a random intercept. Random slopes for the time-varying predictors were included if they improved model fit (as indicated by lower AIC and BIC values). Models with different co-variance structures were compared; the best fitting model was selected based on AIC and BIC criteria.
RESULTS
Descriptive statistics
We collected 3349 ESM observations in total. Participants completed on average 56 out of 63 (89%) assessments. The number of completed assessments ranged from 23 to 63 (37 – 100%). Table 1 presents means and standard deviations for the variables of interest. All ESM items were scored on a scale of 0 (i.e., not at all present) to 6 (i.e., very much present). Average levels of negative affect (NA) were relatively low, while average levels of positive affect and pain intensity were moderate. Negative affect, positive affect, and pain intensity showed considerable variation across measurements, as shown by the Mean Squared Successive Difference (MSSD) scores. Total scores for the FFMQ subscales non-judging and non-reactivity were comparable to those previously reported in non-meditating students (de Bruin, Topper, Muskens, Bögels, & Kamphuis, 2012) and patients with fibromyalgia (Veehof et al., 2011).
Affective reactivity in chronic migraine
_________________________________________________________________________
Measures
Pain intensity – At each ESM assessment, momentary pain intensity was rated in
response to the item ‘At this moment, I’m having a headache’. All ESM items were answered on a 7-point Likert scale ranging from 0 (not at all) to 6 (very).
Positive and negative affect – At each ESM assessment, positive and negative mood
adjectives were rated on a 7-point Likert scale ranging from 0 (not at all) to 6 (very). For the purpose of this study, we used items that i) showed sufficient within-person variation over time, and ii) loaded onto a factor representing positive affect (PA) or negative affect (NA). Two NA items (‘I feel lonely’ and ‘I feel anxious’) were excluded because they showed insufficient within-person variation. Principal component factor analysis with oblique rotation indicated that the mood adjectives ‘content’, ‘enthusiastic’, ‘relaxed’, ‘cheerful’ and ‘strong’ loaded onto one factor representing PA (alpha = .88) and ‘sad’, ‘gloomy’, ‘irritable’, ‘tense’, and ‘worried’ onto a factor representing NA (alpha = .80). Hence, we used these items to obtain a mean score for (state) PA and NA at each
assessment. Trait PA was represented by the average of an individual’s PA scores across all assessments.
Mindfulness – At the baseline assessment, two subscales of the Five Facet Mindfulness
Questionnaire (FFMQ) (Baer, Smith, Hopkins, Krietemeyer, & Toney, 2006; Veehof, Peter, Taal, Westerhof, & Bohlmeijer, 2011) were used to assess two dimensions of mindfulness: non-judging and non-reactivity. The ‘non-judging’ subscale measures the extent to which one is judgmental towards inner experience and contains items such as “I criticize myself for having irrational or inappropriate emotions”. The non-reactivity subscale measures the extent to which one tends to react on inner experiences and includes items such as: ”I watch my feelings without getting lost in them”. All items were answered on a 5-point Likert scale ranging from 1 ‘never or very rarely true’ to 5 ‘very often or always true’ (Baer et al., 2006). Mean scores were calculated for each subscale; items of the nonjudging subscale were reverse coded so that higher scores represent a more nonjudgmental stance towards experience. Cronbach’s alpha for the FFMQ in this sample was .89 for non-judging and .86 for non-reactivity.
Statistical analyses
Since the ESM data had a hierarchical two-level structure (i.e., ESM assessments nested within individuals), data were analyzed with multilevel modelling using the XTMIXED command in Stata 14 (StataCorp, 2015). In all models, the dependent variable was negative affect at time ‘t’. In the concurrent models, level 1 (‘assessment level’) predictors were time (i.e., a continuous variable ranging from the first assessment (0) till the last assessment (63), while inserting a missing observation between the last observation on one day and the first on the next day), pain intensity and positive affect at time ‘t’. In the time-lagged models, level 1 predictors were time, pain intensity and positive affect time ‘t-1’ as well as
Affective reactivity in chronic migraine _________________________________________________________________________ negative affect at ‘t-1’. In both concurrent and time-lagged models, level 2 (‘person level’) predictors were average positive affect, non-judging, and non-reactivity. To test our hypotheses, interaction terms were added to the concurrent and time-lagged models. The hypothesis that state positive affect buffers the impact of pain intensity on negative affect was tested by modelling the interaction between momentary pain intensity and positive affect. The buffering effect of trait positive affect was modelled as the cross-level interaction between the person average of positive affect and momentary pain intensity. Finally, the protective role of mindfulness was examined with the cross-level interaction between non-judging and pain intensity and the interaction between non-reactivity and pain intensity.
In all models, we controlled for medication use since the last assessment, sleep quality in the previous night, and the extent to which stressful events occurred during the day. Time-varying predictors were first grand-mean centered and then person-mean centered to separate within-subject effects from between-subject effects (Bolger & Laurenceau, 2013). All models included a random intercept. Random slopes for the time-varying predictors were included if they improved model fit (as indicated by lower AIC and BIC values). Models with different co-variance structures were compared; the best fitting model was selected based on AIC and BIC criteria.
RESULTS
Descriptive statistics
We collected 3349 ESM observations in total. Participants completed on average 56 out of 63 (89%) assessments. The number of completed assessments ranged from 23 to 63 (37 – 100%). Table 1 presents means and standard deviations for the variables of interest. All ESM items were scored on a scale of 0 (i.e., not at all present) to 6 (i.e., very much present). Average levels of negative affect (NA) were relatively low, while average levels of positive affect and pain intensity were moderate. Negative affect, positive affect, and pain intensity showed considerable variation across measurements, as shown by the Mean Squared Successive Difference (MSSD) scores. Total scores for the FFMQ subscales non-judging and non-reactivity were comparable to those previously reported in non-meditating students (de Bruin, Topper, Muskens, Bögels, & Kamphuis, 2012) and patients with fibromyalgia (Veehof et al., 2011).
Table 1 – Mean scores of ESM measures across all assessments and of baseline
mindfulness
MSSD: mean squared successive difference; FFMQ: Five Facet Mindfulness Questionnaire
Concurrent associations
Parameter estimates of the multilevel models examining the concurrent associations between pain and negative affect are presented in Table 2. When controlling for PA, medication use, sleep, and negative events, within-person fluctuations in pain intensity were significantly associated with within-person fluctuations in NA. A one-unit increase in pain intensity was accompanied by a .07 increase in NA.
Hypothesis 1 ‘buffering effect of state positive affect’ – Following the proposition of the
Dynamic Model of Affect (Zautra et al., 1997), it was hypothesized that pain intensity would be less strongly related to negative affect at moments when positive affect was higher. The interaction parameter modelling this effect was significant (p<.01). For each unit increase in positive affect, the association between pain intensity and negative affect weakened with .02 (see Figure 1).
Figure 1 – Average marginal effects of pain intensity on concurrent negative affect for
different levels of positive affect.
Hypothesis 2 ‘buffering effect of trait positive affect’ – Based on the Broaden-and-Build
model (Fredrickson, 1998), the within-person associations between pain intensity and negative affect were expected to be weaker for individuals with higher average ‘trait’ positive affect. The results did not support this hypothesis as average positive affect did not significantly moderate the associations between pain intensity and negative affect.
Hypothesis 3 ‘buffering effect of mindfulness’ – The hypothesis that level of
mindfulness (i.e., non-judging and non-reactivity) would moderate the associations between pain intensity and negative affect was not supported. Contrary to expectations, the
association between pain intensity and negative affect did not depend on levels of non-judging. The interaction effect between pain intensity and non-reactivity was significant, but not in the expected direction (p = .037). With each unit increase in non-reactivity, the strength of the association between pain intensity and negative affect increased with .04.
Affective reactivity in chronic migraine
_________________________________________________________________________
Table 1 – Mean scores of ESM measures across all assessments and of baseline
mindfulness
MSSD: mean squared successive difference; FFMQ: Five Facet Mindfulness Questionnaire
Concurrent associations
Parameter estimates of the multilevel models examining the concurrent associations between pain and negative affect are presented in Table 2. When controlling for PA, medication use, sleep, and negative events, within-person fluctuations in pain intensity were significantly associated with within-person fluctuations in NA. A one-unit increase in pain intensity was accompanied by a .07 increase in NA.
Hypothesis 1 ‘buffering effect of state positive affect’ – Following the proposition of the
Dynamic Model of Affect (Zautra et al., 1997), it was hypothesized that pain intensity would be less strongly related to negative affect at moments when positive affect was higher. The interaction parameter modelling this effect was significant (p<.01). For each unit increase in positive affect, the association between pain intensity and negative affect weakened with .02 (see Figure 1).
Figure 1 – Average marginal effects of pain intensity on concurrent negative affect for
different levels of positive affect.
Affective reactivity in chronic migraine _________________________________________________________________________
Hypothesis 2 ‘buffering effect of trait positive affect’ – Based on the Broaden-and-Build
model (Fredrickson, 1998), the within-person associations between pain intensity and negative affect were expected to be weaker for individuals with higher average ‘trait’ positive affect. The results did not support this hypothesis as average positive affect did not significantly moderate the associations between pain intensity and negative affect.
Hypothesis 3 ‘buffering effect of mindfulness’ – The hypothesis that level of
mindfulness (i.e., non-judging and non-reactivity) would moderate the associations between pain intensity and negative affect was not supported. Contrary to expectations, the
association between pain intensity and negative affect did not depend on levels of non-judging. The interaction effect between pain intensity and non-reactivity was significant, but not in the expected direction (p = .037). With each unit increase in non-reactivity, the strength of the association between pain intensity and negative affect increased with .04.
Ta bl e 2 – C on cu rr en t m ul til ev el m od el s p red ict in g s am e m om en t n eg at iv e a ff ect Time-lagged associations
Parameter estimates of the multilevel models examining the time-lagged associations between pain and negative affect are presented in Table 3. Within-person fluctuations in NA were significantly predicted by within-person fluctuations in pain intensity, when controlling for the influence of PA, medication use, sleep, and negative events. A one-unit increase in pain intensity was predicted by a .05 increase in NA at the next timepoint. Of note, within-person fluctuations in pain intensity were in turn not significantly predicted by within-person fluctuations in NA (.03 (SE=.04), p = .39), when controlling for the influence of PA, medication use, sleep, and negative events.
Hypothesis 1 ‘buffering effect of state positive affect’ – There was a significant
interaction between pain intensity and positive affect in predicting next-moment negative affect (- .02, p = .04). This implies that the association between pain intensity and negative affect the next moment in time was slightly weaker when individuals had higher levels of positive affect on the moment they experienced pain.
Hypothesis 2 ‘buffering effect of trait positive affect’ – In contrast to findings for the
concurrent associations, average positive affect interacted significantly with pain intensity in predicting next-moment negative affect (p = .03). For each unit difference between individuals in average positive affect, the association between pain intensity and negative affect weakened with .03.
Hypothesis 3 ‘buffering effect of mindfulness’ – Both non-judging and non-reactivity
significantly interacted with pain intensity in predicting next-moment negative affect. With each unit difference in non-judging between individuals, the association between pain intensity and negative affect was .04 smaller (p = .03). Contrary to expectations, the association between pain intensity and negative affect was again stronger for individuals with higher levels of non-reactivity (.03, p = .02).
Affective reactivity in chronic migraine _________________________________________________________________________ Ta bl e 2 – C on cu rr en t m ul til ev el m od el s p red ict in g s am e m om en t n eg at iv e a ff ect
Affective reactivity in chronic migraine _________________________________________________________________________
Time-lagged associations
Parameter estimates of the multilevel models examining the time-lagged associations between pain and negative affect are presented in Table 3. Within-person fluctuations in NA were significantly predicted by within-person fluctuations in pain intensity, when controlling for the influence of PA, medication use, sleep, and negative events. A one-unit increase in pain intensity was predicted by a .05 increase in NA at the next timepoint. Of note, within-person fluctuations in pain intensity were in turn not significantly predicted by within-person fluctuations in NA (.03 (SE=.04), p = .39), when controlling for the influence of PA, medication use, sleep, and negative events.
Hypothesis 1 ‘buffering effect of state positive affect’ – There was a significant
interaction between pain intensity and positive affect in predicting next-moment negative affect (- .02, p = .04). This implies that the association between pain intensity and negative affect the next moment in time was slightly weaker when individuals had higher levels of positive affect on the moment they experienced pain.
Hypothesis 2 ‘buffering effect of trait positive affect’ – In contrast to findings for the
concurrent associations, average positive affect interacted significantly with pain intensity in predicting next-moment negative affect (p = .03). For each unit difference between individuals in average positive affect, the association between pain intensity and negative affect weakened with .03.
Hypothesis 3 ‘buffering effect of mindfulness’ – Both non-judging and non-reactivity
significantly interacted with pain intensity in predicting next-moment negative affect. With each unit difference in non-judging between individuals, the association between pain intensity and negative affect was .04 smaller (p = .03). Contrary to expectations, the association between pain intensity and negative affect was again stronger for individuals with higher levels of non-reactivity (.03, p = .02).
Ta
bl
e 3
–
T
ime
-la
gge
d m
ultile
ve
l mo
de
ls p
re
dic
tin
g
nex
t m
om
en
t n
eg
at
iv
e af
fect
DISCUSSIONThis study aimed to test two complementary models regarding the possible buffering role of positive affect and mindfulness in the dynamic associations between pain and negative affect in chronic migraine (CM). Multilevel models showed significant concurrent and time-lagged associations between pain intensity and negative affect (NA), indicating affective reactivity to chronic migraine-related pain. In accordance with the Dynamic Model of Affect (DMA; (Zautra et al., 1997)), concurrent and time-lagged associations between pain intensity and NA were weaker when individuals experienced higher levels of positive affect (PA) at the moment of pain. Higher average PA predicted only the time-lagged, but not the concurrent associations between pain intensity and NA, providing partial support for the Broaden-and-Build model (BBM; (Fredrickson, 1998; Fredrickson, 2001). Finally, higher non-judging was found to predict weaker time-lagged pain-NA associations while, against expectations, higher non-reactivity predicted stronger time-lagged pain-NA associations.
Our findings correspond with earlier studies examining affect dynamics in the context of arthritis and fibromyalgia (Strand et al., 2006; Zautra et al., 2005; Zautra et al., 2001). Together, these findings suggest that higher positive affect during a pain episode buffers affective reactivity to pain. Extending earlier studies focusing only on concurrent associations, we found that positive affect also moderated the time-lagged associations between pain and negative affect. Our findings therefore provide stronger support for the role of PA in reducing affective reactivity, as the time-lagged associations reflect a reaction of NA later in time on an increase in pain intensity. The ability to access positive emotions during pain episodes may thus help protect mental well-being in the context of chronic pain.
In addition, the finding that average PA moderated the time-lagged associations between pain and NA suggests that not only state PA, but also trait PA may be a protective factor. However, it should be noted that average PA did not interact with the concurrent pain-NA associations. Findings of earlier studies investigating the role of trait PA in the context of chronic pain have also reported inconsistent findings. While one study (Zautra et al., 2005) found that fibromyalgia and osteoarthritis sufferers with higher average PA reported lower NA during weeks with high pain, another study (Zautra et al., 2001) did not find such an effect in women with rheumatoid arthritis and osteoarthritis. According to the BBM, trait PA promotes the acquisition of personal resources that can be utilized in stressful circumstances (Fredrickson, 2001). It is however possible that the effect of trait PA depends on whether individuals are indeed able to mobilize these resources when in pain (e.g., ask for help, use pain-management techniques). As it might take some time to mobilize personal resources, this might explain why we only found that trait PA moderated the lagged association and not the concurrent association between pain and NA. This hypothesis however needs testing in future research.
Affective reactivity in chronic migraine _________________________________________________________________________
Ta
bl
e 3
–
T
ime
-la
gge
d m
ultile
ve
l mo
de
ls p
re
dic
tin
g
nex
t m
om
en
t n
eg
at
iv
e af
fect
Affective reactivity in chronic migraine _________________________________________________________________________
DISCUSSION
This study aimed to test two complementary models regarding the possible buffering role of positive affect and mindfulness in the dynamic associations between pain and negative affect in chronic migraine (CM). Multilevel models showed significant concurrent and time-lagged associations between pain intensity and negative affect (NA), indicating affective reactivity to chronic migraine-related pain. In accordance with the Dynamic Model of Affect (DMA; (Zautra et al., 1997)), concurrent and time-lagged associations between pain intensity and NA were weaker when individuals experienced higher levels of positive affect (PA) at the moment of pain. Higher average PA predicted only the time-lagged, but not the concurrent associations between pain intensity and NA, providing partial support for the Broaden-and-Build model (BBM; (Fredrickson, 1998; Fredrickson, 2001). Finally, higher non-judging was found to predict weaker time-lagged pain-NA associations while, against expectations, higher non-reactivity predicted stronger time-lagged pain-NA associations.
Our findings correspond with earlier studies examining affect dynamics in the context of arthritis and fibromyalgia (Strand et al., 2006; Zautra et al., 2005; Zautra et al., 2001). Together, these findings suggest that higher positive affect during a pain episode buffers affective reactivity to pain. Extending earlier studies focusing only on concurrent associations, we found that positive affect also moderated the time-lagged associations between pain and negative affect. Our findings therefore provide stronger support for the role of PA in reducing affective reactivity, as the time-lagged associations reflect a reaction of NA later in time on an increase in pain intensity. The ability to access positive emotions during pain episodes may thus help protect mental well-being in the context of chronic pain.
In addition, the finding that average PA moderated the time-lagged associations between pain and NA suggests that not only state PA, but also trait PA may be a protective factor. However, it should be noted that average PA did not interact with the concurrent pain-NA associations. Findings of earlier studies investigating the role of trait PA in the context of chronic pain have also reported inconsistent findings. While one study (Zautra et al., 2005) found that fibromyalgia and osteoarthritis sufferers with higher average PA reported lower NA during weeks with high pain, another study (Zautra et al., 2001) did not find such an effect in women with rheumatoid arthritis and osteoarthritis. According to the BBM, trait PA promotes the acquisition of personal resources that can be utilized in stressful circumstances (Fredrickson, 2001). It is however possible that the effect of trait PA depends on whether individuals are indeed able to mobilize these resources when in pain (e.g., ask for help, use pain-management techniques). As it might take some time to mobilize personal resources, this might explain why we only found that trait PA moderated the lagged association and not the concurrent association between pain and NA. This hypothesis however needs testing in future research.
Finally, we examined whether individual differences in the way in which people react to negative experiences (e.g., pain) played a role. To our knowledge, our study was the first to examine the influence of trait mindfulness on the within-day dynamic associations between pain and NA. The finding that the association between pain and next-moment NA was weaker when individuals scored higher on non-judging suggests a mechanism through which mindfulness may protect against adverse mental health outcomes in chronic pain. Indeed, earlier studies found that chronic pain patients with higher levels of trait mindfulness report lower negative mood (Cassidy et al., 2012; McCracken et al., 2007; Veehof et al., 2011). We can only speculate about an explanation for the unexpected finding that individuals with higher non-reactivity showed stronger, rather than weaker associations between pain and NA. An explanation could be that individuals who are better at allowing negative thoughts and feelings to be present, without reacting to them, are also more likely to recognize and thus report negative emotions during a pain episode because they are more mindful.
To our knowledge, this study was the first to examine affective reactivity to pain in individuals with CM. CM can be a highly stressful condition due to its fluctuating nature (Viana et al., 2016) and high interference with daily activities (Lanteri-Minet, Duru, Mudge, & Cottrell, 2011). Our results indeed show that CM patients may respond to pain with heightened NA, even though NA was on average not high in our sample. Importantly, positive affect seems to protect against the negative effects headache may have on mental wellbeing in CM. A unique characteristic of migraine, as opposed to most other types of pain, is the presence of concomitant symptoms such as nausea and sensitivity to light or sounds. These symptoms were beyond the scope of the current study, but may nevertheless influence the experience of a pain episode. Future studies may therefore take these
symptoms into account.
This study had strengths as well as limitations. An important strength of this study was the used experience sampling method (ESM) that provides insight into affective reactivity to pain experience in daily life. Besides the enhanced ecological validity of this design (Myin-Germeys et al., 2009), the intensive longitudinal nature of ESM allowed us to examine both concurrent and temporal associations between pain and NA. Despite the intensive measurement schedule, adherence was on average high. A limitation was the relatively small sample size which may have precluded the detection of smaller interaction effects of the between-subject variables (i.e., average PA and mindfulness). Furthermore, the large majority of the sample was female. Findings are therefore not fully generalizable to males with chronic migraine.
Notwithstanding these limitations, the findings may have implications for clinical practice. Together with findings of earlier studies in other pain conditions, results of this study suggest that interventions promoting positive affect, and potentially non-judging, may reduce affective reactivity to pain. These interventions should focus on the ability to access positive emotions during and in between pain episodes, given that both state and trait PA appeared to buffer affective reactivity. Interventions that have been shown to have an effect
on PA and non-judging are, for instance, Acceptance-based Cognitive Therapy and Mindfulness-based Cognitive Therapy (Day & Thorn, 2016; Geschwind, Peeters, Drukker, van Os, & Wichers, 2011; Nyklícek & Kuijpers, 2008). Pilot studies have shown
acceptability and feasibility of these interventions in patients with migraine (Dindo, Recober, Marchman, O'Hara, & Turvey, 2014; Mo'tamedi, Rezaiemaram, & Tavallaie, 2012).
Affective reactivity in chronic migraine
_________________________________________________________________________ Finally, we examined whether individual differences in the way in which people react to negative experiences (e.g., pain) played a role. To our knowledge, our study was the first to examine the influence of trait mindfulness on the within-day dynamic associations between pain and NA. The finding that the association between pain and next-moment NA was weaker when individuals scored higher on non-judging suggests a mechanism through which mindfulness may protect against adverse mental health outcomes in chronic pain. Indeed, earlier studies found that chronic pain patients with higher levels of trait mindfulness report lower negative mood (Cassidy et al., 2012; McCracken et al., 2007; Veehof et al., 2011). We can only speculate about an explanation for the unexpected finding that individuals with higher non-reactivity showed stronger, rather than weaker associations between pain and NA. An explanation could be that individuals who are better at allowing negative thoughts and feelings to be present, without reacting to them, are also more likely to recognize and thus report negative emotions during a pain episode because they are more mindful.
To our knowledge, this study was the first to examine affective reactivity to pain in individuals with CM. CM can be a highly stressful condition due to its fluctuating nature (Viana et al., 2016) and high interference with daily activities (Lanteri-Minet, Duru, Mudge, & Cottrell, 2011). Our results indeed show that CM patients may respond to pain with heightened NA, even though NA was on average not high in our sample. Importantly, positive affect seems to protect against the negative effects headache may have on mental wellbeing in CM. A unique characteristic of migraine, as opposed to most other types of pain, is the presence of concomitant symptoms such as nausea and sensitivity to light or sounds. These symptoms were beyond the scope of the current study, but may nevertheless influence the experience of a pain episode. Future studies may therefore take these
symptoms into account.
This study had strengths as well as limitations. An important strength of this study was the used experience sampling method (ESM) that provides insight into affective reactivity to pain experience in daily life. Besides the enhanced ecological validity of this design (Myin-Germeys et al., 2009), the intensive longitudinal nature of ESM allowed us to examine both concurrent and temporal associations between pain and NA. Despite the intensive measurement schedule, adherence was on average high. A limitation was the relatively small sample size which may have precluded the detection of smaller interaction effects of the between-subject variables (i.e., average PA and mindfulness). Furthermore, the large majority of the sample was female. Findings are therefore not fully generalizable to males with chronic migraine.
Notwithstanding these limitations, the findings may have implications for clinical practice. Together with findings of earlier studies in other pain conditions, results of this study suggest that interventions promoting positive affect, and potentially non-judging, may reduce affective reactivity to pain. These interventions should focus on the ability to access positive emotions during and in between pain episodes, given that both state and trait PA appeared to buffer affective reactivity. Interventions that have been shown to have an effect
Affective reactivity in chronic migraine _________________________________________________________________________ on PA and non-judging are, for instance, Acceptance-based Cognitive Therapy and
Mindfulness-based Cognitive Therapy (Day & Thorn, 2016; Geschwind, Peeters, Drukker, van Os, & Wichers, 2011; Nyklícek & Kuijpers, 2008). Pilot studies have shown
acceptability and feasibility of these interventions in patients with migraine (Dindo, Recober, Marchman, O'Hara, & Turvey, 2014; Mo'tamedi, Rezaiemaram, & Tavallaie, 2012).
References
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(1), 27-45.
Bishop, S. R., Lau, M., Shapiro, S., Carlson, L., Anderson, N. D., Carmody, J., . . . Velting, D. (2004).
Mindfulness: A proposed operational definition. Clinical Psychology: Science and Practice, 11(3), 230-241. Bolger, N., & Laurenceau, J. (2013). Intensive longitudinal methods: An introduction to diary and experience
sampling research. New York: Guilford Press.
Cassidy, E. L., Atherton, R. J., Robertson, N., Walsh, D. A., & Gillett, R. (2012). Mindfulness, functioning and catastrophizing after multidisciplinary pain management for chronic low back pain. Pain, 153(3), 644-650. Csikszentmihalyi, M., & Larson, R. (1987). Validity and reliability of the experience-sampling method. The
Journal of Nervous and Mental Disease, 175(9), 526-536.
Davis, M. C., Zautra, A. J., Wolf, L. D., Tennen, H., & Yeung, E. W. (2015). Mindfulness and cognitive-behavioral interventions for chronic pain: Differential effects on daily pain reactivity and stress reactivity.
Journal of Consulting and Clinical Psychology, 83(1), 24-35.
Day, M. A., & Thorn, B. E. (2016). The mediating role of pain acceptance during mindfulness-based cognitive therapy for headache. Complementary Therapies in Medicine, 25, 51-54.
de Bruin, E. I., Topper, M., Muskens, J. G., Bögels, S. M., & Kamphuis, J. H. (2012). Psychometric properties of the five facets mindfulness questionnaire (FFMQ) in a meditating and a non-meditating sample. Assessment,
19(2), 187-197.
de Vries, M. W. (1992). The experience of psychopathology in natural settings: Introduction and illustration of variables. In M. W. DeVries (Ed.), The experience of psychopathology: Investigating mental disorders in their
natural settings (pp. 3-26). Cambridge, UK: Cambridge University Press.
Dindo, L., Recober, A., Marchman, J., O'Hara, M. W., & Turvey, C. (2014). One-day behavioral intervention in depressed migraine patients: Effects on headache. Headache, 54(3), 528-538.
Fredrickson, B. L. (1998). What good are positive emotions? Review of General Psychology, 2(3), 300-319. Fredrickson, B. L. (2001). The role of positive emotions in positive psychology: The broaden-and-build theory of
positive emotions. American Psychologist, 56(3), 218-226.
Garland, E. L., Gaylord, S. A., Palsson, O., Faurot, K., Mann, J. D., & Whitehead, W. E. (2012). Therapeutic mechanisms of a mindfulness-based treatment for IBS: Effects on visceral sensitivity, catastrophizing, and affective processing of pain sensations. Journal of Behavioral Medicine, 35(6), 591-602.
Geschwind, N., Peeters, F., Drukker, M., van Os, J., & Wichers, M. (2011). Mindfulness training increases momentary positive emotions and reward experience in adults vulnerable to depression: A randomized controlled trial. Journal of Consulting and Clinical Psychology, 79(5), 618-628.
Headache Classification Committee of the International Headache Society (IHS. (2013). The international classification of headache disorders, (beta version). Cephalalgia, 33(9), 629-808.
Lanteri-Minet, M., Duru, G., Mudge, M., & Cottrell, S. (2011). Quality of life impairment, disability and economic burden associated with chronic daily headache, focusing on chronic migraine with or without medication overuse: A systematic review. Cephalalgia, 31(7), 837-850.
McCracken, L. M., Gauntlett-Gilbert, J., & Vowles, K. E. (2007). The role of mindfulness in a contextual cognitive-behavioral analysis of chronic pain-related suffering and disability. Pain, 131(1), 63-69. Mo'tamedi, H., Rezaiemaram, P., & Tavallaie, A. (2012). The effectiveness of a group-based acceptance and
commitment additive therapy on rehabilitation of female outpatients with chronic headache: Preliminary findings reducing 3 dimensions of headache impact. Headache, 52(7), 1106-1119.
Myin-Germeys, I., Oorschot, M., Collip, D., Lataster, J., Delespaul, P., & van Os, J. (2009). Experience sampling research in psychopathology: Opening the black box of daily life. Psychological Medicine, 39(9), 1533-1547. 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(3), 331-340.
O'Neill, S. C., Cohen, L. H., Tolpin, L. H., & Gunthert, K. C. (2004). Affective reactivity to daily interpersonal stressors as a prospective predictor of depressive symptoms. Journal of Social and Clinical Psychology, 23(2), 172-194.
Piazza, J. R., Charles, S. T., Sliwinski, M. J., Mogle, J., & Almeida, D. M. (2013). Affective reactivity to daily stressors and long-term risk of reporting a chronic physical health condition. Annals of Behavioral Medicine,
45(1), 110-120.
Rost, S., Van Ryckeghem, D. M. L., Koval, P., Suetterlin, S., Voegele, C., & Crombez, G. (2016). Affective instability in patients with chronic pain: A diary approach. Pain, 157(8), 1783-1790.
Schutze, R., Rees, C., Preece, M., & Schutze, M. (2010). Low mindfulness predicts pain catastrophizing in a fear-avoidance model of chronic pain. Pain, 148(1), 120-127.
Sin, N. L., Graham-Engeland, J. E., Ong, A. D., & Almeida, D. M. (2015). Affective reactivity to daily stressors is associated with elevated inflammation. Health Psychology, 34(12), 1154-1165.
Sorbi, M., Mak, S., Houtveen, J., Kleiboer, A., & van Doornen, L. (2007). Mobile web-based monitoring and coaching: Feasibility in chronic migraine. Journal of Medical Internet Research, 9(5), e38.
StataCorp. (2015). Stata statistical software: Release 14College Station, TX: StataCorp LP.
Strand, E. B., Zautra, A. J., Thoresen, M., Ødegård, S., Uhlig, T., & Finset, A. (2006). Positive affect as a factor of resilience in the pain—negative affect relationship in patients with rheumatoid arthritis. Journal of
Psychosomatic Research, 60(5), 477-484.
van Middendorp, H., Lumley, M. A., Moerbeek, M., Jacobs, J. W. G., Bijlsma, J. W. J., & Geenen, R. (2010). Effects of anger and anger regulation styles on pain in daily life of women with fibromyalgia: A diary study.
European Journal of Pain, 14(2), 176-182.
van Winkel, M., Nicolson, N., Wichers, M., Viechtbauer, W., Myin-Germeys, I., & Peeters, F. (2015). Daily life stress reactivity in remitted versus non-remitted depressed individuals. European Psychiatry, 30(4), 441-447. Veehof, M. M., Peter, M., Taal, E., Westerhof, G. J., & Bohlmeijer, E. T. (2011). Psychometric properties of the
dutch five facet mindfulness questionnaire (FFMQ) in patients with fibromyalgia. Clinical Rheumatology,
30(8), 1045-1054.
Viana, M., Sances, G., Ghiotto, N., Guaschino, E., Allena, M., Nappi, G., . . . Tassorelli, C. (2016). Variability of the characteristics of a migraine attack within patients. Cephalalgia, 36(9), 825-830.
Watson, D., Clark, L., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect - the panas scales. Journal of Personality and Social Psychology, 54(6), 1063-1070. Zautra, A. J., Potter, P. T., & Reich, J. W. (1997). The independence of affects is context-dependent: An
integrative model of the relationship between positive and negative affect”. In K. Warner Schaie, & M. Powel Lawton (Eds.), Annual review of gerontology and geriatrics (17th ed., pp. 75-102). New York, United States: Springer Publishing Company.
Zautra, A. J., Smith, B., Affleck, G., & Tennen, H. (2001). Examinations of chronic pain and affect relationships: Applications of a dynamic model of affect. Journal of Consulting and Clinical Psychology, 69(5), 786-795. Zautra, A. J., Johnson, L. M., & Davis, M. C. (2005). Positive affect as a source of resilience for women in chronic
pain. Journal of Consulting and Clinical Psychology, 73(2), 212-220.
Zautra, A. J., & Smith, B. W. (2001). Depression and reactivity to stress in older women with rheumatoid arthritis and osteoarthritis. Psychosomatic Medicine, 63(4), 687-696.
