Original article

An Internet-Based Intervention for Chronic Pain

A three-arm randomized controlled study of the effectiveness of guided and unguided acceptance and commitment therapy

Dtsch Arztebl Int 2017; 114(41): 681-8; DOI: 10.3238/arztebl.2017.0681

Lin, J; Paganini, S; Sander, L; Lüking, M; Ebert, D D; Buhrman, M; Andersson, G; Baumeister, H

Background: Persons with chronic pain can be treated effectively with acceptance and commitment therapy (ACT). In this trial, we examined the effectiveness of guided and unguided ACT-based online treatment (ACTonPain) for chronic pain patients.

Methods: 302 individuals were randomly assigned to ACTonPain with or without guidance (n = 100/101) or to a waiting-list control group (n=101). The primary outcome was pain interference as measured by the Multidimensional Pain Inventory. The secondary outcomes were physical and emotional functioning, pain intensity, ACT process variables, quality of life, satisfaction with the intervention, adherence, and participants’ rating of overall improvement. The online measurements were carried out before randomization (T0) and 9 weeks and 6 months after randomization (T1 and T2, respectively). Intention-to-treat (ITT) data analysis was supplemented with additional per-protocol analyses.

Results: The guided ACTonPain group showed significantly less pain interference than the control group in the ITT analysis (p = 0.01), with a moderate effect size at T1 and T2 (d = 0.58 respectively), corresponding to a number needed to treat (NNT) of 3.14 for both time points. Participants in the guided ACTonPain group also indicated higher pain acceptance (T1: d = 0.59; T2: d = 0.76). The unguided ACTonPain group showed to be significantly less depressed in comparison to the control group at at time T2 (d = 0.50). No significant differences with respect to effectiveness were found between the two ACTonPain groups (p>0.05).

Conclusion: The online intervention ACTonPain is effective for persons with chronic pain when the program is guided. Further research in a variety of settings of health care is needed in order to determine whether and how ACTonPain can be implemented.

Chronic pain is widespread (13) and is associated with direct and indirect costs as well as adverse social, physical, and mental effects (25). In a cross-sectional survey conducted in Germany, 28.3 % of the respondents stated that they had chronic pain and 7.3 % fulfilled the criteria for chronic, non-tumor-related debilitating pain (6). Multimodal interdisciplinary therapy is acknowledged as the gold standard for evidence-based treatment of chronic pain (7). Psychological interventions such as acceptance and commitment therapy (ACT), a recent development in the field of cognitive behavioral therapy (CBT), represent a key element of such treatment (8).

The goal of ACT is for the affected person to accept unpleasant, unalterable experiences such as pain and lead a value-oriented life in open contact with their thoughts and feelings; this is summarized as “psychological flexibility” (9, 10). ACT represents an alternative to CBT, showing equivalent efficacy (small to moderate effects). People with chronic pain are, however, often confronted with limited accessibility and availability of established treatments (3, 13, 14), and according to a large European survey almost half of those affected are treated inadequately, e.g., only by medication (3).

Against this backdrop, Internet- and mobile-based interventions (IMIs) (15) for chronic pain could be an effective and cost-effective way of overcoming the above-mentioned barriers of face-to-face psychotherapy. Furthermore, IMIs may offer additional advantages over face-to-face treatments, e.g., shorter waiting times, anonymity, and flexibility of time and place (1517).

A recent meta-analysis of 19 randomized controlled trials (RCTs) on the efficacy of IMIs in various groups of people with pain found an effect size of Hedge’s g = 0.41 for pain interference, comparable to the small to moderate effects of face-to-face treatments. Once established, guidance of patients in the form of regular feedback, explanations, motivation, and reminders to adhere to the treatment not only improves treatment effects (19) but also is a central cost factor. Unguided IMIs may therefore be of particular interest for healthcare policy (20). However, little is known about the effectiveness of ACT-based IMIs for chronic pain in general (21) or the effectiveness of guided and unguided IMIs for chronic pain in particular (18).

Therefore, the aim of this study was to investigate the effectiveness of a guided and unguided ACT-based IMI for persons with chronic pain (ACTonPain) in comparison with a waiting-list control group (CG).

Method

Design

The study protocol with a detailed description of this three-armed pragmatic RCT with parallel design has been published (22). The participants were assigned to one of three groups: guided ACTonPain, unguided ACTonPain, or CG.

Participants

Recruitment took place during the period from October 2014 to August 2015. The participants were recruited via a broad-based online and offline advertising strategy involving cooperation with a health insurance provider. The inclusion and exclusion criteria, outlined in the Box, were based on online self report. All measurements (eligibility screening and assessments) were carried out online. The assessments were performed at baseline (T0; pre-treatment) and at 9 weeks (T1; post-treatment) and 6 months (T2; follow-up) after randomization.

Inclusion and exclusion criteria
Box
Inclusion and exclusion criteria

The ACTonPain program comprises an introduction and seven successive modules. The participants were advised to complete one module per week, spending around 60 min on each module.

In the guided ACTonPain group, e-coaches (psychologists) under the supervision of an experienced psychological psychotherapist (HB) provided personalized and standardized (preformulated) feedback by e-mail within two working days after completion of each module. Guidance took an average of 105 min per participant.

Control group

The participants in the CG were given access to the unguided version of ACTonPain after completion of the T2 assessments.

Instruments

The participants’ clinical characteristics were documented using the pain-relevant items of the German Pain Questionnaire (Deutscher Schmerzfragebogen) (23). The study outcomes were selected based on the recommendations of the Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials (IMMPACT) (24, 25). The instruments are described in detail in the study protocol (22) and thus merely outlined in brief here.

Primary outcome

The primary outcome was pain interference, assessed with the interference subscale of the Multidimensional Pain Inventory (MPI) (26, 27). This subscale comprises 10 questions about daily activities with responses on a 7-point scale ranging from 0 (“no interference”) to 6 (“extreme interference”).

Secondary outcomes

The secondary outcomes were related to:

  • Physical and emotional functioning
  • Pain intensity
  • Health-related quality of life
  • ACT-related variables
  • Participants’ satisfaction
  • Participants’ rating of overall improvement
  • Intervention adherence

Randomization

To obtain groups of the same size, an independent statistician performed permuted-block randomization with variable block sizes of 6, 9, and 12 (randomly ordered) and an allocation ratio of 1 : 1 : 1 with an automated web-based program (www.sealedenvelope.com).

Statistical analyses

Missing data were imputed using the expectation–maximization algorithm of the Statistical Package for the Social Sciences (SPSS, Version 22). All analyses were carried out with SPSS 22.

The effectiveness of the intervention was analyzed on an intention-to-treat (ITT) basis. The data of those participants who completed at least five of the seven modules and all assessments were additionally included in per-protocol (PP) analyses. In contrast to the originally planned multivariate analysis of covariance (MANCOVA), we used a multivariate analysis of variance (MANOVA) with repeated measures as there were no baseline group differences concerning the potential covariables sex and age. Use of MANOVA also maximized the degrees of freedom of the model. In this model, the interaction effects of group × time for the three groups and the three assessment times with regard to the primary and secondary outcomes were of particular interest. Whenever significant interaction effects were found, univariate post-hoc tests with repeated measures were carried out to further examine the interaction effect for the corresponding outcome between the groups and between the assessment times (T0 versus T1 and T0 versus T2).

For significant group × time interactions in each comparison, the corresponding effect sizes (Cohen’s d) and number needed to treat (NNT) were calculated with regard to the group differences at T1 and T2.

A further repeated measures MANOVA was carried out in respect of intervention satisfaction and adherence between the intervention groups, because these variables were only assessed in the two intervention groups at T1 and T2. An additional ANOVA was performed with post-treatment and follow-up data for participants’ rating of overall improvement.

Further information on the methods with regard to participants, intervention, study instruments, and statistical analyses, together with study registration, can be found in the eBox and in eTables 1 and 2.

Method
eBox
Method

Results

All study participants completed the baseline survey. Little’s Missing Completely at Random (MCAR) test indicates that the data is missing at random. (χ2[1779] = 604.73; p = 0.99). Table 1 summarizes the participants’ demographic and clinical characteristics at baseline, with no clinically relevant differences among the groups. 24% of the participants dropped out of the study at T1, 39 % at T2 (Figure). The PP sample consisted of 43 participants from the guided ACTonPain group, 30 from the unguided ACTonPain group, and 71 from the CG.

Flow chart of inclusion and exclusion
Figure
Flow chart of inclusion and exclusion
The participants’ demographic and clinical characteristics at baseline*1
Table 1
The participants’ demographic and clinical characteristics at baseline*1

Efficacy of interventions

MANOVA with repeated measures revealed a significant interaction effect for group × time (value [V] = 0.13, F[36.237] = 2.24, p <0.01; PP: V = 0.18, F[36.1108] = 1.49, p = 0.03). Table 2 shows the means (M) and standard deviations (SD) of the primary outcomes and summarizes the results of the univariate variance analyses with repeated measures of the group × time effects for each comparison between T0 and T1 and between T0 and T2 of the ITT sample. (M and SD for the secondary outcomes are presented in eTable 1.) These analyses showed significant (p <0.05) group × time effects for pain interference, pain intensity, and pain acceptance, as well as depression, in the comparisons T0 versus T1 and T0 versus T2.

Means and standard deviations for the primary outcome: pain interference*
Table 2
Means and standard deviations for the primary outcome: pain interference*
Means and standard deviations for the secondary outcomes at pre-treatment, post-treatment, and follow-up, F values for univariate follow-up tests with repeated measures, intention to treat sample
eTable 1
Means and standard deviations for the secondary outcomes at pre-treatment, post-treatment, and follow-up, F values for univariate follow-up tests with repeated measures, intention to treat sample

Furthermore, there were significant (p <0.05) group × time effects in the comparison T0 versus T1 for health-related quality of life—mental health subscale—and in the comparison T0 versus T2 for physical functioning (Brief Pain Inventory, BPI) and psychological flexibility (Acceptance and Action Questionnaire, German version: Fragebogen zu Akzeptanz und Handeln-II, FAH). Analysis of the PP sample yielded comparable findings. The post-hoc group effects of the comparisons T0 versus T1 and T0 versus T2, the corresponding effect sizes, and the equivalent NNT for T1 and T2 of the ITT sample are listed in Table 3 (see eTable 2 for the secondary outcomes).

Post-hoc group effects of the comparisons between pre-treatment and post-treatment and between pre-treatment and follow-up*
Table 3
Post-hoc group effects of the comparisons between pre-treatment and post-treatment and between pre-treatment and follow-up*
Post-hoc group effects of the comparisons between pre-treatment and post-treatment and between pre-treatment and follow-up for the second - ary outcomes, corresponding effect sizes and number needed to treat (NNT) data for post-treatment and follow-up, intention to treat sample
eTable 2
Post-hoc group effects of the comparisons between pre-treatment and post-treatment and between pre-treatment and follow-up for the second - ary outcomes, corresponding effect sizes and number needed to treat (NNT) data for post-treatment and follow-up, intention to treat sample

Primary outcome

In the post-hoc group comparisons, pain interference was significantly (p = 0.01) lower in the guided ACTonPain group than in the CG for both T0 versus T1 and T0 versus T2. Based on Cohen’s d, these were moderate to large effects. No significant differences were found between the two ACTonPain groups or between the unguided ACTonPain group and the CG. No significant group differences were found in the PP sample (p <0.05).

Secondary outcomes

In the post-hoc group comparisons, the guided ACTonPain group showed significantly higher pain acceptance than the CG for both T0 versus T1 and T0 versus T2; these were moderate to large effects. In the PP sample, this finding was confirmed only for T0 versus T2. The participants of the unguided ACTonPain group showed to be significantly less depressed than the CG in the comparison T0 versus T2, and this was confirmed in the PP sample. With regard to the remaining secondary outcomes, no significant (p >0.05) group differences for physical and emotional functioning (BPI; Generalized Anxiety Disorder Screener [GAD-7]), pain intensity, physical and mental quality of life, and psychological flexibility (FAH) were found in the post hoc analyses. The additional ANOVA showed that the intervention groups, compared with the CG, reported higher overall improvement (Patient Global Impression of Change [PGIC]) at T1 and T2 in the ITT and PP analyses; the two intervention groups did not differ from one another.

Comparison between guided and unguided ACTonPain groups and negative effects

While the above-mentioned analyses showed no differences between the guided and unguided ACTonPain groups, the participants of the guided ACTonPain group completed more modules (number of modules: 0–8) than those in the unguided ACTonPain group (M = 5.94, SD = 2.80 versus M = 4.74, SD = 2.89; F[1.99] = 8.92; p <0.01). The attrition rate was 40% in the guided ACTonPain group and 61% in the unguided ACTonPain group. There were no significant differences between the groups with regard to participants’ satisfaction (V = 0.01, F[2.198] = 0.81, p = 0.45; PP: V = 0.00, F[2.70] = 0.04, p = 0.96). The participants’ overall degree of satisfaction can be interpreted as high, and the majority of participants (81.6 % in both groups) stated at T1 that they would recommend the intervention to a friend who needed psychological assistance (item 4: response “yes, probably” or “yes, definitely”).

In response to the question about possible negative effects—as recommended by Rozetal and colleagues (28, 29)—the participants reported no negative events.

Discussion

This study is the first to investigate the effectiveness of online-based acceptance and commitment therapy for chronic pain (ACTonPain) in Germany. The results show that people with chronic pain can considerably benefit from ACTonPain if the program is guided. The participants of the guided ACTonPain group reported significantly less pain interference and higher pain acceptance at post-treatment and follow-up assessments than persons on the waiting list, which demonstrates the long-term effect of the intervention. Moreover, the participants of both ACTonPain groups stated a high level of satisfaction with the program.

These results are in line with the findings of other guided, ACT-based IMIs for chronic pain, which revealed effect sizes of d = 0.33 (30) and d = 0.56 (31) for pain interference in comparison with active control groups (e.g., expressive writing [30] and participation in online forums [31]). The results of our study are also comparable with the treatment effects of face-to-face therapies, for which weak to moderate effects on pain interference, pain intensity, depression, anxiety, and disability were reported (standardized mean difference [SMD] = 0.62, 0.24, 0.43, and 0.40 respectively) (12).

The present study makes an important contribution to the growing body of evidence on IMIs for chronic pain and emphasizes the benefit of guided ACTonPain. The effect-facilitating impact of guidance may be attributable to monitoring of treatment adherence rather than to the provision of therapeutic content (19). With regard to unguided IMIs, only one other study has directly compared the efficacy of guided and unguided interventions (32). In contrast to the results of Dear et al. (32), the findings of our study do not confirm the efficacy of unguided ACTonPain, despite its positive effect on depressive symptoms in comparison with the CG and between T0 and T2. This may be partly attributable to the high drop-out rate. However, due to the cost-saving provision, unguided ACTonPain could beclinically important at population level. This aspect is currently being examined in the context of the cost-effectiveness analyses of guided ACTonPain and unguided ACTonPain in comparison with the CG.

Limitations

One limitation of this study lies in the pragmatic implementation of the diagnostic process, which exclusively took place only based on self-reports. We regarded chronic pain as a disease in its own right (2) in a heterogeneous population that need not be documented in detail. To conduct additional moderator and mediator analyses,, the German Pain Questionnaire (23) assesses pain-related variables. These serve to examine which persons benefit most and least from ACTonPain. Furthermore, the external validity of our study seems to be high for well-educated women, who form a high proportion of the sample. The proportion of women with a high level of education is comparable with that in earlier IMI studies (18, 33) and with the uptake rates for face-to-face psychotherapy (34). This appears to be the target group that is particularly interested in this kind of intervention.

Summary

In view of the high prevalence of chronic pain (3) and the challenges related to the availability and accessibility of evidence-based treatments (3, 14), it is crucial to take active steps to implement new, effective treatments such as ACTonPain in the health care system. To date, however, the acceptance of IMIs in various patient populations seems to be ambivalent (3537). IMIs might be far less effective in the health care context (38) than reported in the efficacy studies, where the high level of administrative support potentially increases adherence to the intervention (39). For successful dissemination and implementation of ACTonPain in various areas of the healthcare system, there is a need for acceptance- and adherence-facilitating strategies focussing on contact initialization and the participants’ utilization patterns.

Within the health care system ACTonPain can be used a stand-alone treatment or as an adjunct to psychotherapy (“blended care”). Because single treatment measures fail to adequately treat chronic pain, future studies should examine the role of ACTonPain in a bio-psycho-social context. ACTonPain could be implemented in disease management and collaborative care programs and in integrated pain care plans.

The findings of this study suggest the advisability of implementing ACTonPain with therapeutic guidance into the health care system. ACTonPain can help to shorten waiting times, improve access to pain treatment, and possibly lower treatment costs. Further investigations are required to establish in which routine health care settings ACTonPain can easily be integrated and how it can be best disseminated and implemented.

Acknowledgments
We are grateful to Laura Klatt, Susanne Stollewerk, Lasse Bartels, Magdalena Wanner, Anne Helmecke, Manuel Massell, and Bianca Faust for their assistance in recruitment, study administration, and data processing. We thank Julian Mack for his help with the methodology.

Conflict of interest statement

Dr. Lin, M.Sc. Psych, Dipl.-Psych. Lüking, Buhrmann, PhD, Prof. Andersson, and Prof. Baumeister are authors and developers of ACTonPain.

Dr. Ebert possesses shares in the GET.On Instituts GesundheitsTrainings.Online, which works to transfer research findings on Internet- and mobile phone-based health interventions into routine care. He has received payments from several companies and health insurance providers (Lantern Inc., Minddistrict Holding, BARMER, Techniker Krankenkasse, Schön Kliniken, Agaplesion Kliniken, Ebel Kliniken) for advice on the use of Internet-based interventions. He has received payments for lectures from the Federal Psychotherapy Association (Bundes­psycho­therapeuten­kammer) and the psychotherapy associations of the states of Hesse and Lower Saxony, and has been the beneficiary of third-party funding from the health insurance provider BARMER, the German Statutory Pension Insurance Scheme (DRV), Social Insurance for Agriculture, Forestry, and Horticulture (SVLFG), and the Accident Insurance Fund of the state of North Rhine–Westphalia (Unfallkasse NRW).

Dipl.-Psych. Sander has received payments for lectures on the topic of online-based psychotherapy from the Freiburg Institute for Training in Cognitive Therapy (Freiburger Ausbildungsinstitut für Verhaltenstherapie, FAVT GmbH) and the Institute for Training in Psychotherapy, Saarland University (Weiterbildungsinstitut für Psychotherapie an der Universität des Saarlandes, WIPS GmbH).

Prof. Baumeister has received a consultancy fee from the Federal Psychotherapy Association (Bundes­psycho­therapeuten­kammer). He has received reimbursement of congress attendance and travel costs as well as payments for lectures from the Federal Psychotherapy Association, the psychotherapy association of the state of Baden-Württemberg, and the Community Psychiatry Confederation (Dachverband für Gemeindepsychiatrie). He has been the beneficiary of study support (third-party funding) from the health insurance provider BARMER GEK, Social Insurance for Agriculture, Forestry, and Horticulture (SVLFG), and the German Statutory Pension Insurance Scheme (DRV) Moreover, he has received payments for lectures on the topic of online-based psychotherapy from the Freiburg Institute for Training in Cognitive Therapy (Freiburger Ausbildungsinstitut für Verhaltenstherapie, FAVT GmbH).

Dipl.-Psych. Paganini declares that no conflicts of interest exist.

Manuscript submitted on 7 December 2016, revised version accepted on
14 June 2017

Translated from the original German by David Roseveare

Corresponding author
Dr. phil. Jiaxi Lin, M.Sc. Psych.
King’s College London
Health Psychology Section
Psychology Department
Institute of Psychiatry, Psychology & Neuroscience (IoPPN)
5th Floor Bermondsey Wing, Guy’s Campus
London SE1 9RT, UK
jiaxi.lin@kcl.ac.uk

Supplementary material
For eReferences please refer to:
www.aerzteblatt-international.de/ref4117

eBox, eTables:
www.aerzteblatt-international.de/17m0681

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Bond FW, Hayes SC, Baer RA, et al.: Preliminary psychometric properties of the Acceptance and Action Questionnaire-II:
a revised measure of psychological inflexibility and experiential avoidance. Behav Ther 2011; 42: 676–88 CrossRef MEDLINE
e13.
Wicksell RK, Olsson GL, Melin L: The Chronic Pain Acceptance Questionnaire (CPAQ)-further validation including a confirmatory factor analysis and a comparison with the Tampa Scale of Kinesiophobia. Eur J Pain 2009; 13: 760–8 CrossRef MEDLINE
e14.
Schmidt J, Lamprecht F, Wittmann WW: Satisfaction with inpatient management. Development of a questionnaire and initial validity studies. Psychother Psych Med 1989; 39: 248–55.
e15.
Attkisson CC, Zwick R: The client satisfaction questionnaire. Psychometric properties and correlations with service utilization and psychotherapy outcome. Eval Program Plann 1982; 5: 233–7 CrossRef
e16.
Guy W: Clinical global impression scale. The ECDEU assessment manual for psychopharmacology-revised. DHEW Publ (No ADM 76) 1976; 338: 218–22.
e17.
Finch WH: Missing data and multiple imputation in the context of multivariate analysis of variance. J Exp Educ 2015; 84: 356–72.
e18.
van Ginkel, Joost R, Kroonenberg PM: Analysis of variance of multiply imputed data. Multivariate Behav Res 2014; 49: 78–91 CrossRef MEDLINE PubMed Central
e19.
Verma JP: Repeated measures design for empirical researchers. Hoboken, New Jersey, USA: John Wiley & Sons 2015.
e20.
Field A: Discovering statistics using SPSS. os Angeles, London, New Delhi, Singapur und Washington D.C.: Sage publications 2009.
e21.
Bender R, Lange S: Adjusting for multiple testing—when and how? J Clin Epidemiol 2001; 54: 343–9 CrossRef
Department of Rehabilitational Psychology and Psychotherapy, Institute of Psychology, University of Freiburg: Dr. Lin, M.Sc. Psych; Dipl.-Psych. Paganini, Dipl.-Psych. Sander
Psychology Department, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK: Dr. Lin, M.Sc. Psych.
Private Practice, Freiburg: Dipl.-Psych. Lüking
Clinical Psychology and Psychotherapy, Institute of Psychology, University of Erlangen-Nürnberg: Dr. Ebert
Department of Psychology, Uppsala University, Sweden: Buhrman, PhD
Linnaeus Centre HEAD, Swedish Institute for Disability Research, Department of Behavioural Sciences and Learning, Linköping University, and Department of Clinical Neuroscience, Division of Psychiatry, Karolinska Institutet, Stockholm, Sweden: Prof. Andersson, PhD
Department of Clinical Psychology and Psychotherapy, Institute of Psychology and Education Science, University of Ulm: Prof. Baumeister
Inclusion and exclusion criteria
Box
Inclusion and exclusion criteria
Flow chart of inclusion and exclusion
Figure
Flow chart of inclusion and exclusion
Key messages
The participants’ demographic and clinical characteristics at baseline*1
Table 1
The participants’ demographic and clinical characteristics at baseline*1
Means and standard deviations for the primary outcome: pain interference*
Table 2
Means and standard deviations for the primary outcome: pain interference*
Post-hoc group effects of the comparisons between pre-treatment and post-treatment and between pre-treatment and follow-up*
Table 3
Post-hoc group effects of the comparisons between pre-treatment and post-treatment and between pre-treatment and follow-up*
Method
eBox
Method
Means and standard deviations for the secondary outcomes at pre-treatment, post-treatment, and follow-up, F values for univariate follow-up tests with repeated measures, intention to treat sample
eTable 1
Means and standard deviations for the secondary outcomes at pre-treatment, post-treatment, and follow-up, F values for univariate follow-up tests with repeated measures, intention to treat sample
Post-hoc group effects of the comparisons between pre-treatment and post-treatment and between pre-treatment and follow-up for the second - ary outcomes, corresponding effect sizes and number needed to treat (NNT) data for post-treatment and follow-up, intention to treat sample
eTable 2
Post-hoc group effects of the comparisons between pre-treatment and post-treatment and between pre-treatment and follow-up for the second - ary outcomes, corresponding effect sizes and number needed to treat (NNT) data for post-treatment and follow-up, intention to treat sample
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e1.Buhrman M, Skoglund A, Husell J, et al.: Guided internet-delivered acceptance and commitment therapy for chronic pain patients:
a randomized controlled trial. Behav Res Ther 2013; 51: 307–15 CrossRef MEDLINE
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e11.Luo X, George ML, Kakouras I, et al.: Reliability, validity, and responsiveness of the short form 12-item survey (SF-12) in patients with back pain. Spine 2003; 28: 1739–45 CrossRef CrossRef MEDLINE
e12.Bond FW, Hayes SC, Baer RA, et al.: Preliminary psychometric properties of the Acceptance and Action Questionnaire-II:
a revised measure of psychological inflexibility and experiential avoidance. Behav Ther 2011; 42: 676–88 CrossRef MEDLINE
e13.Wicksell RK, Olsson GL, Melin L: The Chronic Pain Acceptance Questionnaire (CPAQ)-further validation including a confirmatory factor analysis and a comparison with the Tampa Scale of Kinesiophobia. Eur J Pain 2009; 13: 760–8 CrossRef MEDLINE
e14.Schmidt J, Lamprecht F, Wittmann WW: Satisfaction with inpatient management. Development of a questionnaire and initial validity studies. Psychother Psych Med 1989; 39: 248–55.
e15.Attkisson CC, Zwick R: The client satisfaction questionnaire. Psychometric properties and correlations with service utilization and psychotherapy outcome. Eval Program Plann 1982; 5: 233–7 CrossRef
e16.Guy W: Clinical global impression scale. The ECDEU assessment manual for psychopharmacology-revised. DHEW Publ (No ADM 76) 1976; 338: 218–22.
e17.Finch WH: Missing data and multiple imputation in the context of multivariate analysis of variance. J Exp Educ 2015; 84: 356–72.
e18.van Ginkel, Joost R, Kroonenberg PM: Analysis of variance of multiply imputed data. Multivariate Behav Res 2014; 49: 78–91 CrossRef MEDLINE PubMed Central
e19.Verma JP: Repeated measures design for empirical researchers. Hoboken, New Jersey, USA: John Wiley & Sons 2015.
e20.Field A: Discovering statistics using SPSS. os Angeles, London, New Delhi, Singapur und Washington D.C.: Sage publications 2009.
e21.Bender R, Lange S: Adjusting for multiple testing—when and how? J Clin Epidemiol 2001; 54: 343–9 CrossRef

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