Acute effects of exercise on affective responses, cravings and heart ...

Mental Health and Physical Activity 13 (2017) 68e76

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Acute effects of exercise on affective responses, cravings and heart rate variability in inpatients with alcohol use disorder e A randomized cross-over trial €ngle b, Carina Bichler a, *, Martin Niedermeier a, Anika Frühauf a, Nicole La c c W. Wolfgang Fleischhacker , Sergei Mechtcheriakov , Martin Kopp a a b c

Department of Sport Science, University of Innsbruck, Fuerstenweg 185, A-6020 Innsbruck, Austria Stiftung Maria Ebene, Maria Ebene 17, A-6820 Frastanz, Austria Department of Psychiatry and Psychotherapy, Medical University of Innsbruck, Anichstrasse 35, A-6020 Innsbruck, Austria

a r t i c l e i n f o

a b s t r a c t

Article history: Received 14 June 2017 Received in revised form 24 October 2017 Accepted 24 October 2017 Available online 11 November 2017

Problem: Exercise programs may increase abstinence rate in patients with alcohol use disorder (AUD). However, adherence to exercise programs is influenced by acute affective responses during the activity and preferences regarding the type of exercise. Thus, the aim of the present study was to assess the effects of two different exercise types on affective responses, cravings and heart rate variability (HRV). Method: Sixteen inpatients with diagnosed AUD were recruited during regular withdrawal treatment and took part in a randomized cross-over trial. Fifteen participants completed three 60-min interventions: a Nordic-walking condition (NW), a Yoga-Gymnastics condition (YG) and a passive control condition (PC). Affective responses, cravings and HRV were assessed before, during, immediately after, as well as 10 and 180 min after each intervention. Results: Repeated measures ANOVAs revealed a significantly higher increase in perceived activation during NW vs. PC (partial eta2 ¼ 0.34) as well as during YG vs. PC (partial eta2 ¼ 0.33). Affective valence significantly increased during NW vs. YG (partial eta2 ¼ 0.34). For cravings and HRV, no significant differences between treatment conditions were found. Conclusions: Results demonstrated that an acute exercise bout improved affective responses in inpatients with alcohol use disorder and indicated preferences towards NW compared to YG regarding affective valence during exercise. However, there were no differences after the interventions. Related to results of current literature, exercise bouts may provide some short-term motivation for abstinence in therapeutic settings and help preventing alcohol relapse through establishing alternative behavioural patterns. © 2017 Elsevier Ltd. All rights reserved.

Keywords: Physical activity Alcohol urges Affective valence Perceived activation

1. Introduction Alcohol is a potential dependence-producing, psychoactive substance, which is widely used among many cultures and considered a legally consumed drug applied throughout all socioeconomic groups (World Health Organization, 2014). Cravings for alcohol and negative mood can cause distress, discomfort and are

likely to contribute to heavy drinking, alcohol dependence and relapse following treatment (Kavanagh et al., 2013; Witkiewitz, Bowen, & Donovan, 2011). Reduced alcohol cravings therefore can lower consumption and decrease the risk of alcohol relapse in patients with alcohol use disorders (AUD) (Hallgren, Vancampfort, Giesen, Lundin, & Stubbs, 2017; Litt, Cooney, & Morse, 2000). 1.1. Exercise in the treatment of AUD

* Corresponding author. E-mail addresses: [email protected] (C. Bichler), martin.niedermeier@ uibk.ac.at (M. Niedermeier), [email protected] (A. Frühauf), nicole. €ngle), [email protected] (N. La wolfgang.fl[email protected] (W.W. Fleischhacker), [email protected] (S. Mechtcheriakov), martin. [email protected] (M. Kopp). https://doi.org/10.1016/j.mhpa.2017.10.002 1755-2966/© 2017 Elsevier Ltd. All rights reserved.

Exercise seems to be a cost-effective intervention without side effects in clinical rehabilitation programs with inpatients (World Health Organization, 2014). Within all ranges of substance use disorders, there is a growing body of evidence that supports the usage of exercise in the field of smoking- and illicit drug cessations

C. Bichler et al. / Mental Health and Physical Activity 13 (2017) 68e76

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(Linke & Ussher, 2015; Roberts et al., 2015; Zschucke, Heinz, & €hle, 2012). Regarding individuals with AUD, systematic reStro views showed beneficial exercise effects on physiological functioning and a trend for positive effects towards psychological outcomes such as anxiety, mood management, alcohol cravings and drinking behaviour (Giesen, Deimel, & Bloch, 2015). Correspondingly, exercise may as well positively influence consumption reduction, abstinence rates and lower the urge to drink (Manthou et al., 2016). The latest meta-analysis in the field of exercise treatment for individuals with AUD confirmed positive exercise effects towards health outcomes including depression and physical fitness, but in contrast concluded that exercise appeared not to reduce alcohol consumption (Hallgren et al., 2017). Until now, inconsistent findings regarding exercise effects on drinking behaviour are presented. In particular, aerobic exercise may help to minimize the relapse risk through its acute effects on affect and cravings (Brown, Prince, Minami, & Abrantes, 2016), since mood and the urge to drink have been identified as an important predictor of alcohol relapse (Witkiewitz et al., 2011). Exercise has shown to be accepted and innocuous within clinical settings for patients with AUD (Giesen et al., 2015; Hallgren et al., 2017). Interventions need to be suitable for the majority of patients on one hand (Read & Brown, 2003) but still need to be tailored to the unique preferences of individuals on the other hand (Abrantes et al., 2011).

relationship between the autonomic nervous system (such as reduced HRV) and cardiovascular mortality, including sudden cardiac death, is considered verified (Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology, 1996). Measuring HRV is a simple and non-invasive procedure and may provide psychophysiological information (Lackner et al., 2014; Sammito et al., 2015). Psychophysiological information through monitoring HRV, which is independent on the self-reported feedback (affective responses, cravings) of participants, may be considered as additional important information. Until now, there has been no prior work investigating acute exercise effects on HRV in patients with AUD. Prior data for healthy individuals was presented by Niedermeier and colleges showing that HRV did not differ in changes from baseline to follow up of a single exercise condition vs. a single sedentary €tter, Hartl, & Kopp, 2017). control condition (Niedermeier, Grafetsta However, previous findings in healthy individuals showed decreased HRV after exercise which is expected to increase again after recovery (Lakin, Notarius, Thomas, & Goodman, 2013). These results suggest similar cardiac sympathetic activation and parasympathetic deactivation regardless of training intensity (Rezk, Marrache, Tinucci, Mion, & Forjaz, 2006).

1.2. Effects of exercise on affective responses in patients with AUD

When exercise recommendations for inpatients with AUD are provided, an appropriate choice among various types of exercises has to be made. The following considerations have been identified as relevant for the selection of types of exercise interventions: Exercise interventions for patients with AUD should ideally correspond with individual preferences and positively influence affective responses (Ekkekakis & Petruzzello, 2002). Accordingly, a high dropout prevalence (Hallgren et al., 2017) may be reduced. Due to improved compliance, lifestyle can be modified positively after the intervention, which is an important component of relapse prevention (Marlatt & Donovan, 2008). Furthermore, from a clinical perspective, exercise should be feasible both in clinical settings and at home after hospital care to ensure that acquired exercise behaviour can be maintained and continued (Taylor & Faulkner, 2014). According to Abrantes et al. (2011), the top most preferred types of physical activity in substance abusing patients are walking and strength/resistance training. Yoga and stretching were popular especially in female participants (Abrantes et al., 2011). YogaGymnastics (YG) is a mix of various types of resistance training that contained elements of mind-body exercise of hatha yoga, gymnastics and stretching. There is some evidence to support popular believes about health-enhancing effects due to yogapractice. In a population of individuals with major psychiatric disorders, Balasubramaniam, Telles, and Doraiswamy (2012) reported a potential acute benefit of yoga in symptom reduction of depression, schizophrenia, attention deficit hyperactivity disorder and sleep complaints. Mind-body exercise such as yoga reduced depression symptoms in the long-term when applied as adjunctive therapy to regular treatment (Uebelacker et al., 2017). It also effectively improved abstinent rate and attenuated withdrawal and anxiety symptoms in individuals with substance use disorders in general (Wang, Wang, Wang, Li, & Zhou, 2014). In particular, yoga efficiently facilitated the treatment of AUD and showed beneficial effects on recovery (Raina, Chakraborty, & Basist, 2001), depression levels (Vedamurthachar et al., 2006), enhanced quality of life (Sareen, 2007) and reduced, but not statistically significant alcohol asson, 2014). consumption (Hallgren, Romberg, Bakshi, & Andre Nordic-walking (NW) is very similar to walking but additionally specially designed poles comparable to ski poles are used. Through the pole usage, muscles of the arms and upper body are activated

Affective responses originate in the body and can be characterized as “ ‘reflexes’ (such as the pleasure of physical rest or the displeasure of pain) or ‘physiological drives’ associated with periodic and, thus, predictable ‘homeostatic needs’ (such as the pleasure of eating after being hungry or the displeasure of starvation).” (Ekkekakis & Petruzzello, 2000, p. 79). It has been reported that negative affective responses increase alcohol cravings (Baker, Piper, McCarthy, Majeskie, & Fiore, 2004). Furthermore, affective responses are major factors in human decision-making (Deci & Ryan, 1996) and positive affective responses during exercise might help to increase long-term participation in exercise (Ekkekakis, Hall, & Petruzzello, 2004; Williams et al., 2008). As a consequence, it is important to know about the effects of exercise on affective responses, which might differ in different types of exercise (Abrantes et al., 2011). It has been shown previously, that a short bout of moderate intensity exercise significantly declined alcohol cravings compared to very low intensity exercise (Ussher, Sampuran, Doshi, West, & Drummond, 2004). Evidence for improvements in mood, decreases in anxiety and urges to drink in alcohol dependent individuals due to single exercise sessions were recently provided by Brown et al. (2016). Also, a short brisk walk acutely reduced alcohol cravings compared to a passive control condition and might be used as a self-help coping strategy to manage cravings for individuals with high alcohol consumption rates (Taylor, Oh, & Cullen, 2013). 1.3. Effects of exercise on physiological responses Beside effects of exercise on affective responses, there is growing interest in measuring corresponding psycho-physiological responses in order to investigate how biological markers are associated with affective responses in individuals (Gidlow et al., €inen et al., 2016; Seplaki, Goldman, Weinstein, & Lin, 2004; Tyrva 2014). Heart rate variability (HRV), defined as the beat-to-beat variation in heart rate (Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology, 1996), may illustrate acute affective responses (Lackner, Weiss, Hinghofer-Szalkay, & Papousek, 2014). The

1.4. Exercise feasibility for inpatients with AUD

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which are not used during a standard walk (Tschentscher, Niederseer, & Niebauer, 2013). NW has been recently used in the wider field of mental illnesses as an exercise treatment condition (Frühauf et al., 2016). Compared to brisk walking and jogging, NW showed further beneficial effects (e.g. enhanced quality of life) and can be recommended to a wide range of patients with various diseases (Tschentscher et al., 2013). There is some evidence that aerobic exercise and strength/ resistance training might produce different effects in patients with AUD (Hallgren et al., 2017), but research specifically addressed to the exercise types of NW and YG is needed to give evidence-based recommendations. . 1.5. Aim of the study The aims of the present study were to assess if (1) exercise can immediately improve affective responses (self-reported and objectively measured) and reduce cravings in inpatients with AUD and (2) which type of exercise elicits greater affective benefits, reduction in cravings and improved responses of HRV. To the best of our knowledge, no studies exist which aimed to compare affective responses, cravings and HRV using different types of exercise in inpatients with AUD. 2. Methods

2.2. Experimental design and procedure All participants were exposed to three experimental groupconditions in a randomized order (within-subject, cross-over design): Nordic-walking condition (NW), Yoga-Gymnastics condition (YG) and passive control condition (PC). The washout phase between the conditions was one week. The interventions were done on a fixed day of the week, each at the same time of day, to account for daytime fluctuations. The conditions were performed in small groups (n ¼ three to five). The instructor and the inpatients were identical throughout all conditions to control for social contact effects. Affective responses and cravings were assessed via self-reported questionnaire at five time points in each intervention: before (t1), during (t2), end (t3), 10 min post (t4) and approximately 180 min post (t5) intervention. Throughout the intervention time, heart rate was monitored using a heart rate watch (RS800CX, Polar, Finland) with a chest transmitter and participants were asked to estimate their perceived exertion at t2 to assess the intensity during the intervention. HRV was calculated for t1, t3, t4 and t5 (see Fig. 2). All interventions lasted 60 min and followed an identical procedure. After t4 was assessed, inpatients continued with their regular treatment. In order not to disturb further treatment programs, no standardized post-exercise period has been applied. However, inpatients reported their activity, number of cigarettes smoked and number of consumed drinks containing caffeine within the time period from t4 to t5.

2.1. Sample 2.3. Interventions Inpatients went through alcohol detoxification at first, followed by an eight-week addiction treatment in two psychiatric hospitals in Austria were selected by psychiatrists. Participants were eligible to enter the study if they were over 18 and up to 65 years old, diagnosed as alcohol dependent (F10.2: ICD-10; World Health Organization) with clinical observable cravings (>1 point for the subscale “thoughts” on the Obsessive Compulsory Drinking Scale (OCDS; Anton, Moak, & Latham, 1995)), but currently abstinent without relapse. We excluded legally incapable patients and those with acute affective or anxiety disorders, neurocognitive deficits, intake of benzodiazepine or antipsychotics and inpatients with any other contraindications for exercise. During their hospital stay, inpatients received standard treatment including psychotherapy, psychotropic drug therapy, occupational therapy, physiotherapy and social work care. No modifications to the regular treatment were made to minimize external influences for the inpatients. Study interventions were planned for days without other scheduled physical activity. Inpatients gathered to the condition appointments that took part in the psychiatric hospital or rather in the nearby clinical out-door area for the NW condition. Additionally to the regular treatment, 16 inpatients were recruited and took part in the present study. The 15 inpatients who completed the study were in their third to sixth week of hospital stay. The detailed participant flow is shown in Fig. 1. The sample size was estimated by G*Power analyses (Faul, Erdfelder, Lang, & Buchner, 2007) based on a study for acute exercise effects (Ussher et al., 2004). To detect a significant, mediumsized effect of partial h ¼ 0.124 (Ussher et al., 2004), alpha ¼ 0.05, 1beta ¼ 0.8 and epsilon ¼ 1 by using a 3 5 repeated measures ANOVA, 12 participants were required. Taking an estimated dropout-rate of 40% in account, a sample size of 17 participants was considered. The study was approved by the local medicine ethics committee according to the Declaration of Helsinki. Participation in the study was voluntary and all participants signed a consent form after obtaining written and spoken information about all study procedures.

2.3.1. Nordic-walking condition (NW) After a five-minute instruction for the correct usage of Nordicwalking sticks and a short warm-up, inpatients performed moderate intensity outdoor walking on uneven terrain in their group, led by the training therapist experimenter. Participants walked at a self-regulated pace with the instruction of “brisk walking” (corresponding approximately to 11 (fairly light) to 14 (somewhat) hard) on Rating of Perceived Exertion (RPE; Borg, 1998). If their walking pace was faster than the training therapist, they were told to overtake and turn around at a known position to stay within a certain distance of the group. Subsequently, inpatients completed an instructed, five-minute cool-down program. 2.3.2. Yoga-Gymnastics condition (YG) Inpatients took part in a Yoga-Gymnastics class collaborated in a gym, led by the training therapist experimenter. Instructions included hatha yoga-training, which is a practice of asanas (postures), practiced along with controlled breathing and meditation (Posadzki, Choi, Lee, & Ernst, 2014). When required, participants obtained feedback to correct postures. Inpatients were told to perform exercise within the intensity of 11 (fairly light) to 14 ((somewhat) hard) on RPE (Borg, 1998). To provide individual exercise intensity, graduation of postures were offered by the training therapist experimenter. 2.3.3. Passive control condition (PC) Inpatients were required to sit in a gym while reading magazines provided. The training therapist experimenter was present and instructed to keep conversation to other inpatients to a minimum. 2.4. Measures 2.4.1. Baseline profiling The baseline profiling included self-reported affective valence,


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Fig. 1. Participant flow.

Affective responses Craving

Affective responses

Craving

Affective responses

Affective responses

Affective responses

Craving

Craving

Craving

HRV

Intensity of physical activity

HRV

HRV

HRV

t1: before (0 min)

t2: during (30 min)

t3: end (60 min)

t4:10 min post

t5: 180 min post

Fig. 2. Measurements in all conditions. Note. HRV ¼ heart rate variability.

perceived activation and alcohol cravings, as well as measured HRV for the time point before intervention (t1). Thus was to control for same baseline levels on every of the three intervention days. 2.4.2. Affective responses Affective responses to exercise were measured by the two selfreport, single-item, dimensional scales, Feeling Scale (FS; Hardy & Rejeski, 1989) and Felt Arousal Scale (FAS; Svebak & Murgatroyd, 1985), commonly used combined. FS depicts affective valence within a range from ‘þ5’ (very good) above ‘0’ (neutral) to ‘-5’ (very bad). Perceived activation was quantified by FAS ranging from ‘1’ (low arousal) to ‘6’ (high arousal). These scales were frequently applied in measuring acute affective responses in exercise interventions and have been shown to be valid measurements (Hardy & Rejeski, 1989; Van Landuyt, Ekkekakis, Hall & Petruzzello, 2000). 2.4.3. Cravings Cravings concerning alcohol consumption were measured by the Alcohol Urge Questionnaire (AUQ; Bohn, Krahn, & Staehler, 1995), which has shown to be a valid and reliable instrument of measuring alcohol cravings (Drummond & Phillips, 2002; MacKillop, 2006). It was also used before by Ussher et al. (2004)

and Taylor et al. (2013) in exercise studies in patients with AUD. This eight-item, self-administered state measure is cumulatively scored on a seven-point Likert-type scale ranging from ‘strongly disagree’ to ‘strongly agree’. High values indicate strong cravings for alcohol. 2.4.4. Exercise intensity Heart rate was measured by wearing a heart rate watch (RS800CX, Polar, Finland) throughout the session and the post measurements to control for exercise intensity. Additionally, RPE was assessed at 30 min during exercise using the Borg Scale (Borg, 1998). The measurement ranges from ‘6’ (extremely light) to ‘20’ (extremely hard) and provides participant-rated exercise intensity. Information for validity and reliability has been provided (Borg, 1998). 2.4.5. Heart rate variability (HRV) Heart rate data was used to calculate HRV in selected domains as recommended to reflect the interplay between the sympathetic nervous system (dominant at times of stress) and the parasympathetic nervous system (dominant at times of relative safety and restoration) (Lackner et al., 2014; Roberts et al., 2015;

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Romanowicz, Schmidt, Bostwick, Mrazek, & Karpyak, 2011; Sammito et al., 2015; Task Force of The European Society of Cardiology and the North American Society of Pacing and Electrophysiology, 1996). Highest HRV-values are presented under vagal conditions, whereas HRV is reduced during times of stress (Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology, 1996; Thayer, Ahs, Fredrikson, Sollers, & Wager, 2012). Time domain measures of HRV were computed as the standard deviation of normal-to-normal beat (SDNN), the square root of the mean squared differences between adjacent R-R intervals (RMSSD) and the percentage of the number of adjacent R-R intervals that differed by more than 50 ms (pNN50). Frequency domains were computed by dividing low frequency (ranging from 0.040 to 0.150 Hz) through high frequency (ranging from 0.150 to 0.400 Hz) (LF/HF). Non-linear domains quantified the shape of the Poincare plot that reflects the balance between long- and short-term variability to infer to sympathetic activity (SD1/SD2). Ten-minute segments were assessed from time point t1, t3, t4, and t5 while resting in a seated position, whereof the last five minutes were used for analyses. Collected heart rate data were uploaded to the computer using ProTrainer 5 software (Version 5, Polar, Finland). Measures of HRV provide information regarding sympathetic or parasympathetic activity and may show psychological demands (Lackner et al., 2014; Sammito et al., 2015). Decreased HRV (HF, SDNN, RMSSD, pNN50) in reverse was discussed as a marker for susceptibility to alcoholism (Romanowicz et al., 2011). 2.5. Data analyses SPSS version 24 (IBM, New York, USA) was used for statistical analyses. Baseline ratings of self-reported affective valence, perceived activation and alcohol cravings, as well as measured HRV, were compared for the three conditions using separate repeated measures analysis of variance (ANOVA). To assess acute effects of exercise interventions on affective responses and cravings, a series of condition by time (3 5) fully repeated measures ANOVAs were conducted. Significant condition by time interactions were considered as different changes in affective responses or cravings. Significant results were checked by simple contrast analyses to identify differences due to the interventions. HRV was analysed using a conditions (NW, YG, PC) by time (t1, t3, t4, t5) repeated measures ANOVA. Therefore, single analyses of each parameter were conducted and then Bonferroni-corrections within the three domains applied. If the assumption of sphericity was not met in the ANOVA, Greenhouse-Geisser correction was applied. Partial h2 was reported as an effect size and values up to 0.05 were considered as small, between 0.06 and 0.13 as medium and above as large effects. Data are presented as mean (standard deviation). P-Values