Docket: EBSA-2009-0010 

Request for Information Regarding the Paul Wellstone and Pete Domenici Mental Health Parity and Addiction 

Equity Act of 2008 

Comment On: EBSA-2009-0010-0001 

Request for Information Regarding the Paul Wellstone and Pete Domenici Mental Health Parity and Addiction 

Equity Act of 2008 

Document: EBSA-2009-0010-DRAFT-0099 

Comment on FR Doc # E9-9629 

Submitter Information 

Name: Ronald Rosenthal 

Address: 

10691 N. Kendall Drive 

Suite 314 

Miami, FL, 33176 

Email: Rrosent710@aol.com 

Phone: 305-598-0013 

Organization: Association for Applied Psychophysiology and Biofeedback (AAPB) 

General Comment 

Comments regarding Regulatory Guidance USCG-2007-27022 

page 19157, II B 

I am writing on behalf of the Association for Applied Psychophysiology 

and Biofeedback. We are the national professional organization for biofeedback 

providers, educators and researchers. We welcome the opportunity to provide 

comments regarding the Mental Health Parity and Addiction Equity Act of 2008 

(MHPAEA). Biofeedback is often misunderstood by many health care 

professionals, so it is easy to understand how other groups may be ignorant about 

the benefits of biofeedback. I am taking the liberty of presenting the first two 

paragraphs of a monograph published by AAPB called, “Evidence Based Practice 

in Biofeedback and Neurofeedback.” It provides an excellent, brief description of 

biofeedback techniques. 

Biofeedback is a technique that enables an individual to learn how to 

change physiological activity for the purposes of improving health and performance 

(Gilbert & Moss, 2003; Schwartz &Andrasik, 2003; Shaffer & Moss, 2006). 

Biofeedback instruments are used to feed back information about physiological 

processes, assisting the individual to increase awareness of these processes and 

PUBLIC SUBMISSION 

As of: May 26, 2009 

Received: May 26, 2009 

Status: Pending_Post 

Tracking No. 809b5ea7 

Comments Due: May 28, 2009

Submission Type: Web
to gain voluntary control over body and mind. Biofeedback instruments measure 

muscle activity, skin temperature, electrodermal activity (sweat gland activity), 

respiration, heart rate, heart rate variability, blood pressure, brain electrical activity, 

and blood flow. Research shows that biofeedback, alone and in combination with 

other behavioral therapies, is effective for treating a variety of medical and 

psychological disorders, ranging from headache to hypertension to 

temporomandibular dysfunction to attentional disorders. The present publication 

surveys these applications and reviews relevant outcome research. Biofeedback is 

used by physicians, nurses, psychologists, counselors, physical therapists, 

occupational therapists, and others. Biofeedback therapies teach the individual to 

take a more active role in maintaining personal health and higher level mind-body 

health. 

Neurofeedback is a specialty field within biofeedback, which focuses on 

training people to gain control over electro-physiological processes in the human 

brain (Demos, 2005; Evans & Abarbanel, 1999; LaVaque, 2003; Thompson & 

Thompson, 2003). Neurofeedback uses information from the electroencephalogram 

(EEG) to show the trainee current patterns in his or her cortex. Many neurological 

and medical disorders are accompanied by abnormal patterns of cortical activity 

(Hammond, 2006). Neurofeedback assessment uses a baseline EEG, and 

sometimes a multi-site quantitative EEG (QEEG), to identify abnormal patterns 

(LaVaque, 2003). Clinical training with EEG feedback then enables the individual 

to modify those patterns, normalizing or optimizing brain activity. Neurofeedback 

practice is growing rapidly with the widest acceptance for applications for attention 

deficit hyperactivity disorder (ADHD), learning disabilities, seizures, depression, 

acquired brain injuries, substance abuse, and anxiety 

(Clinical EEG, 2000). 

Despite almost 40 years of research and clinical experience 

demonstrating the benefits of biofeedback and neurofeedback in the treatment of 

many disorders, many insurance companies continue to restrict access to these 

services. They claim that biofeedback is experimental and that the research does 

not adequately demonstrate the efficacy of biofeedback training. In doing so, they 

selectively review the published evidence and ignore many of the articles 

demonstrating the benefits of biofeedback. 

Biofeedback training is a teaching based approach to the management 

of symptoms. It requires the active participation of the individual getting 

biofeedback. Because of this, it is inappropriate to use a “double-blind” model of 

research, which is inherently designed for passive therapies. However, we 

continue to see criticisms of biofeedback based upon the lack of randomized 

controlled, double blind studies. There are numerous, well-designed studies that 

use randomized assignment of subjects that demonstrate the benefits of 

biofeedback. We respectfully request that all legislation written under the 

MHPAEA permit the fullest possible access to biofeedback. If the department 

wishes, we would be able to submit additional references and papers in support of 

our request. 

Respectfully yours, 

Ronald Rosenthal, Ph.D, BCIA Associate Fellow 

Chair, Insurance and Legislative Committee, AAPB 

10200 W. 44th Avenue, Suite 304 

Wheat Ridge, CO 80033-2840 

Phone: (303) 422-8436 

Fax: (303) 422-8894 

e-mail Rrosent710@aol.com 

Attachments 
EBSA-2009-0010-DRAFT-0099.1: Comment on FR Doc # E9-9629
Biofeedback Treatment for Headache Disorders:

A Comprehensive Efficacy Review

Yvonne Nestoriuc Æ Alexandra Martin Æ

Winfried Rief Æ Frank Andrasik

Published online: 26 August 2008

 Springer Science+Business Media, LLC 2008

Abstract The aim of the present review was to critically

evaluate the documented evidence regarding the efficacy

of biofeedback for the two most prevalent headache

conditions––migraine and tension-type headache. Drawing

upon two recently published meta-analyses, data from 150

outcome studies, including randomized controlled trials as

well as uncontrolled quasi-experimental designs, were

screened. Of these, 94 studies were selected for inclusion

according to predefined criteria. Meta-analytic integrations were carried out separately for the two conditions of

interest. The main results were medium-to-large mean

effect sizes for biofeedback in adult migraine and tensiontype headache patients. Treatment effects remained stable

over an average follow-up period of 14 months, both in

completer and intention-to-treat analyses. Headache frequency was the primary outcome variable and showed the

largest improvements. Further significant effects were

shown for perceived self-efficacy, symptoms of anxiety

and depression, and medication consumption. Reduced

muscle tension in pain related areas was observed in

electromyographic feedback for tension-type headache.

Biofeedback was more effective than waiting list and

headache monitoring conditions in all cases, while electromyographic feedback for tension-type headache

showed additional significant effects over placebo and

relaxation therapies. Levels of efficacy (migraine: efficacious, level 4; tension-type headache: efficacious and

specific, level 5) and recommendations for future research

are provided.

Keywords Migraine  Tension-type headache 

Biofeedback  Relaxation  Treatment efficacy 

Meta-analysis  White paper

Migraine and tension-type headache (TTH) are the two

most prevalent and disabling headache condition in adults

(Rasmussen et al. 1991) as well as in children and adolescents (Kroener-Herwig et al. 2007). In North America

migraine is experienced by 18% of women and 7% of men,

with at least one attack per year (Lipton et al. 2001). The

more common but less disabling episodic tension-type

headache (ETTH) is estimated with a one-year prevalence

of 38%, while the prevalence of chronic tension-type

headache (CTTH), defined as having a frequency of at least

This paper was prepared as a White Paper review, according to the

template guidelines developed by the Association for Applied

Psychophysiology and Biofeedback (AAPB) and the International

Society for Neurofeedback and Research (ISNR).

Y. Nestoriuc (&)

Department of Psychiatry, Brigham and Women’s Hospital,

Harvard Medical School, 1620 Tretmont Street, Boston, MA

02120, USA

e-mail: ynestoriuc@partners.org

Y. Nestoriuc  W. Rief

Department of Clinical Psychology and Psychotherapy, Philipps

University of Marburg, Gutenbergstr. 18, 35032 Marburg,

Germany

e-mail: rief@staff.uni-marburg.de

A. Martin

Department of Psychosomatic Medicine and Psychotherapy,

University of Erlangen-Nuernberg, Schwabachanlage 6, 91054

Erlangen, Germany

e-mail: alexandra.martin@uk-erlangen.de

F. Andrasik

Department of Psychology, University of West Florida, 11000

University Parkway, Pensacola, FL 32514, USA

e-mail: fandrasik@uwf.edu

123

Appl Psychophysiol Biofeedback (2008) 33:125–140

DOI 10.1007/s10484-008-9060-3
15 days per month, is estimated at 2–3% (Schwartz et al.

1998). Significant negative social and economic impacts

resulting from these headache conditions have been

reported (Stovner et al. 2007).

Headache patients frequently experience deteriorated

functional levels at home, work and school (Molarius and

Tegelberg 2006). Biofeedback treatments for pain

emphasize the patients’ active role in managing these

conditions, thereby establishing improved coping with the

psychological and psychosocial consequences of pain. For

the treatment of headache, several different feedback

modalities are being used, focussing on multiple psychophysiological parameters more or less directly

assumed to underlie the condition. To enhance efficacy,

biofeedback is often combined with relaxation and cognitive-behavioral elements such as stress management.

The measurement of treatment success, therefore, mostly

includes psychophysiological and behavioral variables in

addition to the symptom-related ones. Taking this diversity of treatment applications, components, and outcome

measures into account is one of the challenges of efficacy

reviews today. This comprehensive review will offer an

independent evaluation of the efficacy of biofeedback for

headache, including moderating effects of feedback

modalities, outcome categories, and trial design. Efficacy

recommendations, according to the guidelines jointly

established by the Association for Applied Psychophysiology and Biofeedback (AAPB) and the International

Society for Neurofeedback and Research (ISNR), will be

put forward.

Various biofeedback modalities are used for the

treatment of both migraine and TTH, building upon

different physiological and psychophysiological mechanisms that are assumed to be relevant for the conditions.

In migraine, peripheral skin temperature feedback

(TEMP-FB), blood-volume-pulse feedback (BVP-FB) and

electromyographic feedback (EMG-FB) are the most

prominent applications, while electroencephalographic

feedback (EEG-FB) and galvanic skin response training

(GSR-FB) are seldom used. The efficacy of biofeedback

in treating migraine has been established in earlier

reviews with improvement rates for pain from 40% to

65% (Blanchard and Andrasik 1987; Blanchard et al.

1980). Comparable treatment gains resulted for behavioral treatments and pharmacotherapies (Holroyd and

Penzien 1990). In a more recent review medium effect

sizes for EMG-FB and TEMP-FB in combination with

relaxation have been reported (Goslin et al. 1999). While

this was the first review providing standardized measures

of treatment effect, the number of integrated studies was

very small (n = 11) and confidence intervals for the

resulting effects were rather broad. Also, analyses were

limited to the two aforementioned feedback modalities,

only post-treatment data were analysed, and no moderator analyses were performed. BVP-FB was excluded

due to the technical difficulty in administering it. Further

meta-analytic data integrations are needed to determine

the short-term and long-term efficacy of BVP-FB and to

establish treatment moderators for migraine.

The most frequently applied behavioral treatment

option for TTH is EMG-FB, directed at reducing pericranial muscle activity. Previous quantitative reviews

assessing the outcome of various behavioral treatments

for TTH, including biofeedback, relaxation, cognitive

therapy, and hypnotherapy (Blanchard et al. 1980;

Bogaards and ter Kuile 1994; Haddock et al. 1997; Holroyd and Penzien 1986; McCrory et al. 2001) have shown

average improvement rates for pain from 46% (Holroyd

and Penzien 1986) to 61% (Blanchard et al. 1980),

exceeding those of no-treatment conditions (Bogaards and

ter Kuile 1994). Two meta-analyses investigating psychological headache treatments have provided

standardized measures of treatment success for pain.

McCrory et al. (2001) have reported medium-to-large

average effects for EMG-FB in adults, while Trautmann

et al. (2006) documented small-to-medium effect sizes for

the efficacy of psychological headache treatments in

children and adolescents. Specific comparisons of biofeedback for TTH to other behavioral headache treatments

have not yet been meta-analytically integrated. Likewise

the long-term effects of biofeedback for TTH, the efficacy

on different outcome measures, and treatment moderators

have not yet been systematically analysed. Notably, none

of the previous reviews for migraine or TTH have integrated effect sizes for outcome variables other than

headache or medication.

In the light of these limitations two recent metaanalyses have established scientifically sound evidence

supporting the utility of biofeedback for migraine and

TTH (Nestoriuc and Martin 2007; Nestoriuc et al. 2008).

The objective of this comprehensive review is to present

an up-to-date evaluation of the efficacy of biofeedback

for headache. Drawing upon the two most recent metaanalyses in the field, evidence was incorporated, assessed, and documented according to the guidelines for the

evaluation of the clinical efficacy of psychophysiological

interventions (LaVaque et al. 2002). Analysed were the

short- and long-term efficacy of biofeedback for migraine

and TTH, treatment specificity, differential treatment

effects in the form of pain measures, psychological,

behavioral, and physiological outcome categories, as well

as predictors of treatment success, such as patient characteristics and therapy features. Specific meta-analytic

techniques were applied to control for possible confounding effects of selective publication, dropout, and

study validity.

126 Appl Psychophysiol Biofeedback (2008) 33:125–140

123
Methods

Definitions and Operationalizations

Condition of Interest

This biofeedback efficacy review covers two conditions of

interest (COI), i.e., migraine and TTH. Diagnoses were

based on a standardized classification system (i.e., IHS

2004; IHS 1988; Ad Hoc Classification System 1962) or an

exact description of the disorder including characteristic

features of migraine (i.e., severe pain, throbbing character,

nausea, phono/photophobia or aura) or TTH (i.e., mild to

moderate pain intensity, bilateral, nonpulsating quality,

pressing or tightening, ‘‘band like’’ feeling, no exacerbation by exercise). Double diagnoses of TTH and migraine

(mixed or combination headache) were excluded.

Types of Interventions

This review focussed on individually administered biofeedback treatments (TEMP-FB, EMG-FB, BVP-FB, EEGFB, GSR-FB, or biofeedback in combination with other

behavioral therapies).

Outcome Variables

Frequency of pain measured with a structured headache

diary was considered the primary outcome variable for this

review, as recommended by the International Headache

Society (IHS 2000), the AHS Behavioral Clinical Trials

Workgroup (Penzien et al. 2005), and Andrasik et al.

(2005). Included as secondary outcome variables were

intensity and duration of pain as well as headache and

medication indices measured with headache diaries or pain

scales, anxiety, depression, self-efficacy, and physiological

parameters.

Study Inclusion Criteria

In addition to fulfilling the criteria mentioned before (COI,

treatment, outcome) studies included in this review had to

be published in English or German and report sufficient

statistical data to allow the calculation of effect sizes.

Excluded were studies with less than 4 patients per treatment arm and case studies.

Search Procedure

For the purpose of this review, the literature searches

conducted in the two meta-analyses by Nestoriuc and

Martin (2007) and Nestoriuc et al. (2008) were updated.

We used three international and one German databases

(Medline, PsycInfo, CENTRAL, and Psyndex from the first

available year to March 2008) using the search terms

biofeedback or behavioral treatment or cognitive therapy

or nonpharmacological or applied psychophysiology. For

the COI ‘‘migraine’’ these terms were paired with

migraine, vascular headache or mixed headache and for

‘‘TTH’’ with tension-type headache, muscle contraction

headache, tension headache or chronic headache. In

addition to the formerly reviewed studies this search

revealed 14 new studies, of which only two were treatment

outcome studies. Five studies were reviews or meta-analyses, another five described treatment and assessment of

headache conditions without evaluating them directly, and

two were experimental investigations. Of the two outcome

studies, one was included in the current review (Martin

et al. 2007), the other one was excluded because no

headache outcome variables were reported (Ciancarelli

et al. 2007). Finally, a total of 94 studies met our criteria

and were included this review (see Appendix A for a

complete reference list of the studies integrated in this

white paper).

Study Coding and Validity Assessment

For each study, clinical and methodological aspects were

coded with a structured coding scheme, including a 12-item

validity scale (see Appendix B for the Study Coding and

Validity Assessment Scale). After training in the use of the

coding system, all studies were coded by the first author

and two independent reviewers (graduate students). A

random sample of 20% of the migraine and all of the TTH

studies were coded twice to establish reliability of the

coding process. The reliability of the coding form as well

as the interrater-agreement for the validity scale were

proven satisfactory with mean reliability indices ranging

from .84 to .91. The evaluation of the randomization procedure (e.g., randomized or quasi-randomized according to

pre-existing criteria) or the therapy manual (e.g., provided

manual or brief description of procedures) led to more

disagreement than the coding of quantitative study aspects.

Coding discrepancies were discussed and resolved.

Meta-analytic Procedures

Effect Size Calculation and Integration

Standardized effect sizes using Hedges’ g (Hedges and

Olkin 1985) for controlled trials and its pre-post equivalent

for uncontrolled studies (Gibbons et al. 1993) were calculated for each outcome variable, treatment group and time

point. The correction for small samples was applied

(Hedges and Olkin 1985). Multiple effect sizes from a

Appl Psychophysiol Biofeedback (2008) 33:125–140 127

123
single study were averaged with covariance adjustment

prior to effect integration. Independent effect sizes were

weighted by their individual sample size. Separate integrations were carried out with respect to different treatment

comparisons, feedback modalities, outcome categories, and

time points. Contingent with the homogeneity statistic Q

(Shadish and Haddock 1994) fixed effect models or random

effect models (REM) were applied to compute average

effect sizes and confidence intervals. Moderating effects of

patient, treatment, and study characteristics were tested

with planned contrasts and weighted multiple regression

analysis.

Sensitivity Analyses

Meta-analytic results can be biased due to the fact that

studies with nonsignificant results are less likely to be

published than those with significant results. This potential

bias is called publication bias and can lead to an overestimation of treatment effects. To control for this bias, we

calculated the number of studies with effect sizes of zero

(i.e., fail-safe n rates) that would be needed to reduced the

established average effect to insignificance (Rosenthal

1979). Intention-to-treat-analyses with a modified lastobservation-carried-forward approach were applied to

control for potential biases due to treatment dropout.

Patients who dropped out of a study after treatment

assignment were considered nonresponders and henceforth

represented with zero effect sizes (i.e., no change in outcome variables). The individual completer effect sizes

were corrected with those intention-to-treat effects within

each study and then reintegrated.

Results

Characteristics of Included Studies

Included in this review were 94 studies, representing data

from over 3,500 headache patients, that have been published between 1973 and 2007. Included in the metaanalysis of biofeedback for migraine were 56 studies with a

mean of 40 patients per study. The meta-analysis on TTH

consisted of 45 studies with a mean of 29 patients per study.

In 7 of these studies treatment was provided for both

migraine and TTH patients, and results were scored and

presented independently. Key features of the integrated

studies are presented in Table 1. Age means and gender

distributions were similar for the two COI, with 37 and

38 years on average, and 88% and 73% percent women for

Migraine and TTH, respectively. The TTH sample additionally included 9 studies investigating the efficacy of

biofeedback for children and adolescents.1 In the studies

with adult headache patients, the average number of years

since headache diagnosis was 17.1 for migraine and 14.8 for

TTH. Diagnoses were made according to a standardized

diagnostic system in 80% of the migraine studies and in

50% of the TTH studies. Unstandardized exams and interviews applying characteristic features of the two COI were

used for diagnostic purposes in 7% of the migraine and in

34% of the TTH studies. In the remaining 13% of the

migraine and 16% of the TTH studies patients’ prior medical diagnoses were adopted from their records or

interviews. During biofeedback treatment, 14% of the

migraine and 8% of the TTH patients discontinued treatment. Information about attrition was provided in 76% of

the migraine and 61% of the TTH studies. During followup, an additional 6% of migraine patients and 25% of the

TTH patients ceased participation. Follow-up evaluations

took place 14 months after treatment termination on average. In total, 136 active biofeedback conditions were

investigated. For migraine, TEMP-FB in combination with

either relaxation or EMG-FB, was the most frequently

applied feedback modality, followed by TEMP-FB alone

and BVP-FB. Seldom used were EMG-FB alone, EEG-FB

and GSR-FB. For TTH, 92% of the biofeedback treatments

were EMG-FB. Of these 16% were applied in combination

with relaxation training. Other modalities were seldom

used. In 80% of the EMG-FB treatments electrodes were

placed bifrontal, in 12% multiple placements (i.e., frontal,

neck or jaw) were used, and in 8% electrodes were placed

on the neck. The number of biofeedback sessions ranged

from 3 to 24 with an average of 11 sessions for both

migraine and TTH. The duration of a treatment session

ranged from 20 to 95 minutes, averaging 43 minutes for the

two COI. In 78% of the migraine studies and 80% of the

TTH studies treatment manuals were utilized and described

in the publications. 78% of the integrated migraine studies

and 58% of the TTH studies were conducted with control

groups. The remaining 22% of the migraine studies and

42% of the TTH studies were uncontrolled pre-post evaluations. Within the controlled trials waiting list/no-treatment

control groups were applied in 15 of the migraine and 8 of

the TTH studies. Placebo control groups were applied in 12

of the migraine and 8 of the TTH studies. The placebo

treatments were mostly pseudofeedback conditions, where

patients were trained to influence psychophysiological

parameter under false or stable feedback or in the opposite

direction (e.g., increase of muscle tension). Active control

treatments included relaxation training in 18% of the

1 Studies with children and adolescents resulted in a significantly

different average effect size (see Nestoriuc et al. 2008) and were

therefore excluded from further analyses in this review. Hence, all

results presented in this white paper review apply to adult headache

patients.

128 Appl Psychophysiol Biofeedback (2008) 33:125–140

123
migraine and 11% of the TTH studies. Within the controlled

studies, 26% of the migraine and 22% of the TTH studies

incorporated single or double-blind designs. Outcome was

measured with headache parameters, and at least one other

outcome category, in 84% of the migraine and 68% of the

TTH studies. Means and standard deviations of the outcome

variables that can be directly used for the calculation of

effect sizes were presented in 73% of the migraine and 46%

of the TTH studies.

Efficacy of Biofeedback in Controlled Trials

For the analysis of general efficacy, the variables headache

frequency, duration, and intensity were integrated. These

outcome variables were consistently measured with a

structured headache diary in 92% of the migraine and 83%

of the TTH studies. Mean weighted effect sizes2 for all

controlled comparisons are presented in Table 2. In the

migraine studies, biofeedback yielded a significant smallto-medium effect size in comparison to waiting list control

groups. An average small-to-medium effect size was found

in comparison to placebo groups. However, this effect

missed formal significance. A small non-significant effect

Table 1 Characteristics of the integrated studies: demographics, diagnosis, treatment, validity

Characteristic Migraine TTH

n Descriptive statistics n Descriptive statistics

Total number of patients 56 2266 45 1289

Age, mean (range) 46 37.2 (28–67) 38 37.9 (20–67)

Sex (% female, mean ? range) 46 88.4 (21.2–100) 38 72.7 (42.9–100)

Years since diagnose, mean (range) 32 17.1 (8.5–37.6) 27 14.8 (3.0–42.4)

Use of standardized diagnostic system, % 45 80.4 23 51.0

Unstandardized exam (characteristic features) 4 7.2 15 34.1

Diagnose adopted from preceding medical exam 7 12.7 7 15.9

Dropout after treatment assignment, % 43 14.3 28 9.3

Dropout at follow-up, % 11 4.7 8 15.1

Duration of follow-up in month, mean (range) 16 14.3 (6–60) 17 14.0 (3–60)

Feedback modalities, number of treatment groups 56 85 45 51

EMG-FB 8 40

EMG-FB ? relaxation/TEMP-FB 35 7

TEMP-BF 19 2

BVP-FB 16 –

EEG-FB 3 1

Galvanic skin response feedback 4 1

Number of sessions, mean (range) 56 10.8 (3–24) 45 11.2 (6–20)

Duration of sessions in minutes, mean (range) 45 43.5 (20–95) 41 42.6 (20–90)

Description of a treatment manual, % 44 78.6 36 80.0

Control conditions, number of groups 40 35 28 38

Waiting list 15 8

Placebo 12 8

Relaxation 5 14

Pharmacotherapy 2 3

CBT/Stress management 1 3

Physical treatment – 2

Patient blinding, % calculated from controlled studies 10 25.6 6 22.2

Studies with C 2 outcome categories, % 47 83.9 31 68.9

Outcome depicted in means and standard deviations, % 41 73.2 21 46.7

Note: Numbers are frequencies unless described otherwise. N = number of studies, TTH = tension-type headache, EEG-FB = Electroencephalographic feedback, EMG/FB = Electromyographic feedback, TEMP-FB = peripheral temperature feedback, RT = Relaxation training,

BVP-FB = Blood-volume pulse feedback, CBT = cognitive behavioral therapy

2 Average effect sizes from .2 to .5 are considered small effects,

average effect sizes from .5 to .8 are considered medium and average

effects over .8 are considered large effects (Cohen 1988).

Appl Psychophysiol Biofeedback (2008) 33:125–140 129

123
in comparison to relaxation treatments was established. In

the TTH studies, biofeedback yielded a significant medium-to-large effect size as compared to untreated control

groups. A significant medium effect size was found in

comparison to placebo control groups and a significant

small effect size for biofeedback was obtained in comparison to relaxation control groups. For all reported

comparisons, effect sizes were homogeneous according to

the REM. The comparisons of biofeedback with pharmacotherapy, and physical and cognitive therapies, were

insignificant and consisted of too few studies to provide

reliable conclusions.

Efficacy in Pre-post and Follow-up Evaluations

Additional pre-post effect sizes were computed for all

controlled and uncontrolled comparisons. Weighted mean

effect sizes and confidence intervals for all pre-post and

follow-up integrations are presented in Table 3. For

migraine, 85 independent effect sizes ranging from -0.07

to 1.74 were computed. These effects were homogeneous

in the fixed effect model. For all biofeedback modalities, a

significant average effect size of medium magnitude

resulted. This effect was proven to be robust in intentionto-treat analysis. Over 14 months follow-up, on average, a

significant medium-to-large average effect size resulted.

Reliability of the follow-up effects was established in the

intention-to-treat analysis as well.

For TTH, the effect size calculation yielded 49 independent effect measures for headache relief from pre to

post-treatment, ranging from 0.06 to 1.99. Effect size

integration in the random effects model resulted in a significant large average effect size. In the intention-to-treat

analysis, this effect size was shown to be reliable. Over an

average 14 month follow-up, this effect was maintained

and somewhat enhanced with an average medium-to-large

effect size. Evaluation of the follow-up effect sizes in

intention-to-treat analysis resulted in a significant mediumto-large average effect size.

Efficacy of Different Feedback Modalities for Migraine

Effect sizes with confidence intervals for the feedback

modalities utilized in the biofeedback treatment of

migraine are shown in Fig. 1. All feedback modalities

showed significant effect sizes. The highest treatment gains

resulted for BVP-FB, with an average medium-to-large

effect size. An overall medium effect size resulted for

TEMP-FB in combination with relaxation and EMG-FB,

while small-to-medium effect sizes resulted for EMG-FB

and TEMP-FB alone. Differences between the modalities

were insignificant.

Table 2 Mean weighted effect sizes for headache reduction through biofeedback in different treatment comparisons

Comparison Migraine TTH

k n Effect size (95% CI) k n Effect size (95% CI)

BFB versus no treatment control 15 591 0.46 (0.27, 0.64) 8 147 0.79 (0.40, 1.17)

BFB versus placebo control 12 340 0.25 (0.00, 0.49) 8 135 0.50 (0.26, 0.75)

BFB versus relaxation 5 136 0.10 (-0.39, 0.50) 14 396 0.18 (0.06, 0.30)

Note: BFB = biofeedback, Placebo = non-pharmacological placebo treatment (e. g., pseudo/sham feedback, finger cooling), TTH = tension

type headache, k = number of effect sizes, n = number of headache patients, Effect Size = weighted mean effect size, 95% CI = confidence

interval for mean effect size

Table 3 Mean weighted effect sizes for headache reduction through biofeedback at post-treatment and follow-up in completer and intention-totreat analyses

Comparison Migraine TTH

k n Effect size (95% CI) k n Effect size (95% CI)

Pre versus post-treatment (Completer) 85 1489 0.58 (0.52, 0.65) 49 658 0.70 (0.57, 0.83)

Pre versus post-treatment (ITT) 85 1729 0.53 (0.45, 0.60) 49 712 0.59 (0.49, 0.70)

Pre-treatment versus follow-up (Completer) 25 475 0.67 (0.55, 0.79) 17 236 0.45 (0.28, 0.61)

Pre-treatment versus follow-up (ITT) 25 503 0.65 (0.47, 0.81) 17 313 0.31 (0.11, 0.45)

Note: BFB = biofeedback, TTH = tension type headache, k = number of effect sizes, N = number of headache patients, Effect Size =

weighted mean effect size, 95% CI = confidence interval for mean effect size, ITT = intention-to-treat analysis. For ITT dropouts were

considered as nonresponders and replaced with zero effects. Mean duration of follow-up for migraine studies is 14.3 (SD = 14.2) months, for

TTH studies 14.0 (SD = 16.1) months

130 Appl Psychophysiol Biofeedback (2008) 33:125–140

123
Effects of Biofeedback on Different Types of Outcome

Variables

Weighted average effect sizes and confidence intervals for

all outcome variables are depicted in Fig. 2a for the

migraine studies and in Fig. 2b for the TTH studies. In

migraine, frequency, intensity, duration, and the headacheindex were all reduced with significant medium effect sizes.

Differences between these outcome categories were insignificant. For medication consumption, a small-to-medium

effect size resulted. This effect was significantly smaller

than the reduction on headache frequency and duration.

Significant stronger improvements were shown for selfefficacy. Here a significant medium-to-large effect size

resulted. Depression and anxiety showed medium effects,

with confidence intervals ranging from small to large.

In the TTH studies, headache frequency, intensity, and

the headache-index were reduced with large average effect

sizes. Duration of headache episodes was reduced with a

small-to-medium effect size. Physiological outcome (i.e.,

muscle tension in microvolts) was assessed as changes in

muscle tension from baseline to post-treatment, and in

Fig. 1 Mean weighted effect sizes for the different feedback

modalities in the treatment of migraine. Outcome is measured in

headache pain. Mean effect sized are displayed with their individual

95% confidence intervals (k = number of independent effect sizes).

EEG-FB = Electroencephalographic feedback, EMG/FB = Electromyographic feedback, TEMP-FB = peripheral temperature feedback,

RT = Relaxation training, BVP-FB = Blood-volume pulse feedback

Fig. 2 (a) Mean weighted

effect sizes for the different

outcome variables in the

biofeedback treatment of

migraine. Outcome is measured

in headache pain over all

biofeedback modalities. Mean

effect sized are displayed with

their individual 95% confidence

intervals (k = number of

independent effect sizes). (b)

Mean weighted effect sizes for

the different outcome variables

in EMG-FB for tension-type

headache. Outcome is measured

in headache pain. Mean effect

sized are displayed with their

individual 95% confidence

intervals (k = number of

independent effect sizes). EMG

= reduction in muscle tension

measured in microvolt through

electromyography

Appl Psychophysiol Biofeedback (2008) 33:125–140 131

123
some studies, additional within-session changes were

reported. Muscle tension was reduced with a significant

medium-to-large effect size within treatment sessions and

with a significant small effect size (confidence interval

including medium effects) across sessions. Over the course

of all biofeedback sessions, reductions in headache-index

and frequency were significantly larger than the reductions

in muscle tension. Self-efficacy, anxiety, and depression all

yielded significant medium effect sizes, with corresponding

confidence intervals ranging from small to large effect

sizes. Medication intake was reduced with a significant

small-to-medium effect size. The average effect size for

headache-index was significantly higher than the effect size

for medication intake. The other symptom categories did

not show any significant differences.

Publication Bias

In addition to the graphical method (see funnel plots in

Nestoriuc and Martin 2007), we examined publication bias

by calculating fail-safe ks for the critical effect sizes 0.01

and 0.20. For migraine and TTH over 4,000 unpublished

studies with zero effects would be necessary to reduce the

observed average effect to zero. For a reduction to an

average effect size of small magnitude (0.20) 148 migraine

and 168 TTH studies with zero effects would be required.

In sum, publication bias seems rather unlikely.

Discussion

This white paper review provides an up-to date evaluation

of the efficacy of biofeedback as a behavioral treatment

option for headache. The integration of 102 studies with

over 140 active biofeedback treatment conditions allows us

to draw generalizable conclusions regarding the efficacy of

biofeedback. Depicted are data from over 3,500 headache

patients with an average chronicity of migraine and TTH of

over 14 years. The results apply for adult and geriatric

headache patients.

General Efficacy and Specificity

Overall robust treatment effects of medium magnitude

were established for migraine and TTH respectively.

Effects are clinically meaningful as they demonstrate

symptom improvements of over half a standard deviation

for migraine and almost one standard deviation for patients

suffering from TTH. The high chronicity of the sample

with over 14 years of headache on average further supports

the clinical significance of these results. With an overall

average of 11 sessions biofeedback treatments were altogether short and economical. Furthermore, the treatment

was generally very well accepted, as shown in the low

dropout rates.

For migraine, a medium average effect size resulted for

biofeedback in comparison to untreated control groups.

This effect size corresponds with symptom improvements

in headache scores exceeding those of 61% of the patients

in the untreated control groups (Rosenthal and Rubin

1982). As indicated by the confidence interval, migraine

patients treated with biofeedback will likely experience

symptom improvements of 56–65% over and above those

of an average patient in a waiting list control group.

Although a small effect size for biofeedback in comparison

to placebo was found, biofeedback treatment gains were

not reliably higher than improvements in placebo feedback

groups (i.e., psychological placebo for biofeedback

including TEMP-FB with finger cooling). The average

effect size found in comparison to placebo groups corresponds to a 56% success rate in biofeedback compared to

44% (38–50%) improvement in the placebo groups. Likewise differences between biofeedback and relaxation

showed no significance in migraine. Thus, there is strong

evidence for the efficacy, but only weak evidence for the

treatment specificity of biofeedback in migraine.

In TTH a large average effect size resulted for EMG-FB

in comparison to untreated control groups. This effect

corresponds with a 69% success rate under biofeedback as

opposed to a 31% (25–37%) chance of improvement in the

untreated control groups. Superior clinical results also

emerged for biofeedback compared to placebo control

groups and relaxation therapies. The effect size over placebo was robust and of medium magnitude, corresponding

with a 62% success rate versus 38% (34–43%) in the

placebo groups. Similar improvement rates for medication

placebo were documented by Blanchard, Andrasik et al.

(1980). However, the improvements in placebo groups

seemed to be higher in migraine than in TTH patients. The

effect size over relaxation was small but reliable, corresponding with a 55% success rate versus 45% (42–48%) in

the relaxation groups. Strong evidence regarding the efficacy as well as the specificity of biofeedback for TTH can

be drawn from these results. Further efficacy comparisons

of biofeedback to pharmacotherapy, physical therapy and

cognitive therapy included only very few studies and

cannot be interpreted reliably at this point.

Results of previous reviews have consistently shown

biofeedback to be more effective than headache monitoring

(Blanchard et al. 1980; Bogaards and ter Kuile 1994;

Holroyd and Penzien 1986; McCrory et al. 2001), but were

inconclusive about the specificity of biofeedback. Blanchard et al. (1980) pointed out nearly 30 years ago that

there were too few studies to draw conclusions about the

equivalence of alternative headache treatments. Holroyd

and Penzien (1986) reported significant differences

132 Appl Psychophysiol Biofeedback (2008) 33:125–140

123
between behavioral treatments and placebo conditions, but

no differences within the active treatments. Until today,

many studies have reported conflicting results with respect

to the comparative efficacy of biofeedback and relaxation

training, mostly due to underpowered statistical analyses

(Houle et al. 2005). The results of this review point to a

comparable efficacy of biofeedback and relaxation therapy

in the case of migraine and to a superiority of biofeedback

over relaxation in the treatment of TTH.

The efficacy findings from controlled comparisons were

subsequently replicated in pre-post treatment comparisons.

All available outcome data from the integrated randomized

controlled as well as uncontrolled studies were included in

the pre-post treatment comparisons. Robust medium average effect sizes resulted for the two COI, with a confidence

interval including large effects for TTH. This review is the

first to include intention-to-treat analyses for efficacy

evaluations in behavioral headache treatments. The inclusion of all patients who dropped out of the active

biofeedback groups during treatment resulted in slightly

diminished but still significant medium average effect sizes

for migraine and TTH. These results point to the robustness

and clinical meaningfulness of the established effects, even

when dropouts are considered as nonresponders.

Maintenance of Biofeedback Effects Over Time

In follow-up evaluations, the established effects were

shown to persist up to several years after treatment. One

study showed this to be the case whether additional treatment, in the form of booster sessions, was provided or not

(Andrasik et al. 1984). The average medium effect sizes

remained stable over follow-up intervals of 15 months for

migraine and TTH. Supporting prior results (Blanchard

et al. 1980) indicating the stability of biofeedback treatment gains, the presented results constitute the most

comprehensive meta-analytical confirmation of the longterm efficacy of biofeedback for headache disorders.

Intention-to-treat analysis showed that the established follow-up effects persisted even when dropouts were

considered as nonresponders.

Moderating Effects of Different Feedback Modalities

and Outcome Measures

The frequently applied feedback modalities in migraine all

showed comparable treatment effects with reasonable

confidence. The rarely investigated applications resulted in

medium effects as well but produced less stable results.

Among these, EEG-FB was applied in three studies only,

showing small and medium effect sizes. Due to the small

number of integrated studies, it is not possible to draw final

conclusions regarding the efficacy of EEG-FB for

migraine. It is both interesting and important to note that

BVP-FB, a modality that has been excluded from prior

efficacy reviews (Goslin et al. 1999), showed the highest

improvement rates; effect sizes ranged into large effects. In

TTH a differential analysis of feedback modalities is not

necessary, as the majority of studies used EMG-Feedback.

With respect to the different outcome variables that have

been evaluated, reliable effect sizes occurred for all headache variables. Headache frequency, the primary outcome

variable, yielded the highest treatment effects in migraine

and TTH. Also, consistently over both COI, the reduction in

medication consumption, though robustly present, yielded

the lowest effect sizes. In migraine, cognitive aspects, as

measured with changes in self-efficacy, yielded higher

effect sizes than the other outcomes. In TTH, the reductions

in muscle tension as a measure of physiological outcome

yielded similarly high effect sizes to the cognitive variables.

Anxiety and depression were less often evaluated, resulting

in rather imprecise estimated effects. It has to be noted that

these results cannot be used to analyze treatment mediators,

because the incorporated effect measures are only based on

pre-and post-treatment assessment. It is highly recommended to incorporate mediator analyses in future headache

trials (Penzien et al. 2005) in order to gain further insight

into treatment mechanisms. Promising variables in that

respect are self-efficacy and physiological changes, as well

as comorbid reductions in depression and anxiety. There are

some additional behavioral and socioecomic outcome categories that have seldom been assessed in the current

headache trials (i.e., lost work days, health service use,

general activity level, social and role functioning). Thus, in

future studies we recommend incorporating direct measures

of the functional, social, and socioeconomic burden of

headache (Andrasik 2001; Andrasik et al. 2005).

Influence of Treatment Features, Patient

Characteristics, and Study Validity

Analyses of treatment moderators are used to derive recommendations for the clinical utility of treatments. Our

moderator analyses in the two recently published metaanalyses on migraine and TTH have established important

treatment moderators, which we will briefly describe in the

following section.

In the biofeedback treatment of migraine, home training

was shown to be an essential component of the efficacy and

maintenance of treatment benefits. Treatment manuals

incorporating home training led to nearly 20% higher

treatment effects for headache reduction. Surprisingly,

headache chronicity turned out to be a positive treatment

predictor both in adult migraine and TTH patients. This

effect accounted for over 20% of the variability in the TTH

effect sizes and turned out to be a significant predictor for

Appl Psychophysiol Biofeedback (2008) 33:125–140 133

123
direct treatment efficacy and follow-up effects in migraine.

It might be partly due to particularly high effects in geriatric headache patients (Nicholson and Blanchard 1993).

However, the fact that more years with headache can lead

to higher treatment benefits emphasizes the treatment

possibilities inherent in biofeedback.

In the treatment of TTH, the combination of biofeedback

with relaxation training, and the use of biofeedback alone

can be recommended, especially for juvenile headache

patients. No moderating effects were found for different

training sites within the EMG-FB treatments, for study

setting (i.e., outpatient versus including home training),

treatment duration, or the diagnostic distinctions between

CTTH, ETTH, and TTH with pericranial tenderness.

Diagnostic distinctions between ETTH and the clinically

more meaningful CTTH were only seldom made. Hence it is

not yet possible to draw reliable conclusions regarding the

equal effectiveness of EMG-FB for both headache conditions. Further studies directly comparing the efficacy of

EMG-FB for episodic and chronic TTH are needed.

The validity levels of the integrated studies were

uncorrelated with the treatment effects for both COI at

post-treatment. Nevertheless, some validity issues seem

present in the field of biofeedback (Yucha 2002). In some

of the studies evaluated in this review, low sample sizes,

resulting in power problems, failure to describe basic

treatment and patient characteristics, as well as the use of

unstructured diagnostic systems had a negative impact on

validity levels. A number of excellent suggestions and

recommendations concerning behavioral headache research

have recently been put forward (Houle et al. 2005; Penzien

et al. 2005; Rains et al. 2005), and future studies would

undoubtedly benefit from adopting these standards.

Levels of Evidence of Efficacy

The evidence collected and presented in this comprehensive

efficacy review leads to the conclusion that biofeedback for

migraine can be supported as an efficacious treatment

option. This constitutes Level 4 evidence according to the

AAPB/ISNR criteria (LaVaque et al. 2002). Efficacy comparisons to no-treatment control groups favoring

biofeedback exist in studies from multiple independent

research teams, using clearly defined diagnostic criteria and

outcome measures as well as appropriate data analysis.

Biofeedback for TTH can be supported as an efficacious

and specific treatment option. According to the AAPB/

ISNR criteria this constitutes the highest level of evidence

(Level 5), reserved for psychophysiological interventions,

that have established Level 4 evidence and have shown

additional superior treatment results in comparisons to

credible sham therapy or alternative bona fide treatments.

Appendix A

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Appendix B

Study Coding Scheme

Identification: Identification number, coder, author, country, publishing journal, year of publication; Methodology:

design, number of BFB and control groups, measurement

points, type of outcome variables, use of a structured

headache diary, number of weeks of diary assessment at

pre, post and follow-up measurement, number of participants, number of dropouts, research hypothesis, statistical

data for the calculation of effect sizes; Subjects: diagnosis,

diagnostic instruments, additional diagnostic information,

patient characteristics (age, years with headache, gender);

Treatment: type of biofeedback intervention, additional

relaxation training during biofeedback, feedback modality,

type of control intervention, treatment setting, treatment

documentation (number and duration of sessions, treatment

manual), changes in medication.

Validity Assessment Scale

Internal Validity: Design, treatment allocation, dropout,

type of outcome variables; External validity: time points,

patient characteristics; Construct validity: treatment documentation, diagnose, medication status, blinding; Statistical

conclusion validity: number of participants, statistics for

effect size calculation.

138 Appl Psychophysiol Biofeedback (2008) 33:125–140

123
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