Biofeedback and cognitive behavioral therapy for Egyptian ... - IOS Press

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Journal of Pediatric Neurology 4 (2006) 161–169 IOS Press

Original Article

Biofeedback and cognitive behavioral therapy for Egyptian adolescents suffering from chronic fatigue syndrome Mohammad S. Al-Haggara,∗, Zienab A. Al-Naggarb and Mohammad A. Abdel-Salam c a

Department of Pediatrics, Faculty of Medicine, Mansoura University, Mansoura, Egypt Department of Psychiatry, Faculty of Medicine, Mansoura University, Mansoura, Egypt c Department of Neurology, Faculty of Medicine, Mansoura University, Mansoura, Egypt b

Received 1 August 2005 Revised 15 January 2006 Accepted 16 January 2006

Abstract. We aimed to evaluate the efficacy of cognitive behavioral therapy (CBT) aided by biofeedback in rehabilitating Egyptian adolescents who were suffering from chronic fatigue syndrome (CFS). Out of 298 screened individuals with chronic fatigue, only 159 adolescents were eligible for study; of them 63 cases lost follow up and four cases were further excluded because of switch leaving only 92 cases with complete database. Age range of enrolled cases was 10–14 years and male/female ratio (1/2.5). They were recruited from private schools and polyclinics in Eastern province, Saudi Arabia; some cases were referred by psychiatrists in private hospitals of the same area. All cases were diagnosed as CFS according to the recommendations of International CFS Study Group. Patients were randomly allocated to one of two groups; interventional group comprised 50 cases and underwent CBT aided with biofeedback over a period of 18 months applying two protocols according to patient’s activity pattern. Forty-two cases were followed and treated symptomatically and used as control group. Data were processed and analyzed using SPSS version 10.0. The most common symptoms were unrefreshing sleep, headache and myalgia (95.8%, 67.7% and 50% respectively). Patients of interventional group showed marked improvement manifested by decrement of checklist individual strength (decreased 23.1%; 95% confidence interval 19.2–25.4%) and better school attendance (increased 31.5%; 95% confidence interval 29.8–36.6 hours/month) with the disappearance of some self-rated CFS symptoms. CBT aided by biofeedback could be very effective in treatment of adolescents suffering from CFS taking in consideration the stressors and precipitating factors during settings of psychotherapy. Keywords: Biofeedback, cognitive behavioral therapy, chronic fatigue syndrome, adolescents

1. Introduction Chronic fatigue syndrome (CFS) is a troublesome fatigue lasting for more than six months, which is nei∗ Correspondence: M.S. Al-Haggar, MD, Department of Pediatrics, Faculty of Medicine, Mansoura University, Mansoura, Egypt. Postal address: P.O. 732 Al-Khobar 31952, Saudi Arabia. Tel.: +966 38982022; Fax: +966 38951196; E-mail: mhajjar2000@yahoo. co.uk.

ther caused by any organic disease or ongoing exertion nor alleviated by adequate sleep and rest. It may be accompanied with myalgia and other symptoms like headache, malaise, insomnia and appetite changes [1, 2]. CFS is not a single disease entity but rather a constellation of symptoms, which may be due to immune system dysfunction, slow viral reaction and effect of toxins, chemicals or psychiatric disease like depression; however, its exact cause is still controversial [3– 5]. CFS is underestimated among children because of

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M.S. Al-Haggar et al. / Cognitive behavioral therapy in chronic fatigue syndrome

the familial reluctance to report any minimal occasional symptoms and the unfamiliarity of doctors with this disease category [6]. Although the prognosis of CFS is not so bad, some cases would hardly be called “benign” since they even stay bedridden or wheel chaired. Biofeedback is a treatment technique in which people are trained to improve their health by using signals from their own bodies. It can be conducted by physiotherapists to learn paralyzed muscles, psychotherapists to relax tense anxious clients as well as different specialists for management of pains. With the help of some biofeedback machines one can get some internal body information from non-cooperative participants with far greater sensitivity and precision than could be provided by participants themselves; this information would be very useful adjuvant in sessions of cognitive behavioral therapy (CBT). Behavioral therapy is a trial to weaken connections between troublesome situations and person’s habitual reaction; however, cognitive therapy teaches patients how thinking patterns can cause these symptoms for no good reasons. CBT was deemed valuable in controlling such chronic benign problems being non-invasive and without medications or side effects; moreover, it reduced the frequency of emergency visits and physician consultations [7]. To the best of our knowledge, available data about the use of biofeedback for management of CFS in children and the experience with these machines in our culture are still scarce although reflexology rooting from Far East is widely used in our vicinity for the same reason. The aim of our work is to evaluate the efficacy of CBT aided with some biofeedback machines in treatment of Egyptian adolescents suffering from CFS, which may be related in part to some psychological factors like home sickness attempting to avoid prolonged school absence and to improve their life quality. 2. Materials and methods This controlled trial was completed on a cohort of 92 Egyptian adolescents (mean age 12.52 ± 3.32 years, with male/female ratio 1/2.5) who were left from 298 screened individuals using an official questionnaire over a period of almost 26 months started at October 2002 and terminated at January 2005. They were recruited from health records and attendance profiles of students in Egyptian schools of Eastern Province, Saudi Arabia, being checked by school health visitors and school physicians. Some chronic cases presented with vague symptoms without any evident organic disease were referred by family doctors, general practitioners and physicians for diagnostic approval.

2.1. Screening for chronic fatigue Adolescents were screened for chronic fatigue using a questionnaire; patients answered yes to any of the following four questions were considered high risk CFS for further evaluation (The American Academy of Family Physician; 1994–2005): (a) Did you feel tired (fatigued) for more than six months without hard work and despite of adequate sleep and rest? (b) Have your performance or school attendance decreased to the half? (c) Did you have persistent unexplained symptoms for more than six months e.g. headache, muscle soreness, joint pains, disturbed sleep or memory, tender glands? (d) Have been doctors unable to explain your symptoms in term of an organic disease? Further evaluation included detailed history taking, thorough clinical examination and routine laboratory investigations that included complete blood counts, sedimentation rate, urine, stool and chest X ray to rule out any organic disease underlying the chronic fatigue symptoms. No specific diagnostic test or neuroimaging studies are available for CFS; a minimum battery of routine laboratory tests should be ordered unless indicated by clinical suspicion on individual basis e.g. serology for viral infection should be done only in clinically suspected cases [1]. We applied the exclusionary criteria of Fukuda and his associates to improve the diagnostic accuracy of CFS; these criteria include the presence of any chronic systemic disease, the regular use of medications, manic-depressive illness, and morbid obesity with or without sleep apnea. Moreover, any unexplained physical or laboratory finding must be resolved before further classification [1]. Fatigue severity could be measured objectively by Checklist Individual Strength (CIS), individual’s performance and working hours (school attendance) as well as subjectively by self-rated fatigue symptoms reported in the patient’s own diary. As there are no available reference data for assessment of fatigue severity in pediatrics, we adopted a 10-item CIS called Fatigue Assessment Scale (FAS) that was used for assessment of adults with CFS [8]; it has been recently approved as an instrument for fatigue measurement [9]. 2.2. Diagnosis and enrollment of CFS Out of 298 screened individuals, only 159 were found eligible for study thus excluding 139 (72 cases did not fulfill the inclusion criteria of CFS, 39 cases had organic diseases, and 28 cases were excluded by the other exclusionary criteria of Fukuda). During subse-


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Fig. 1. Flow chart for the trial profile showing total screened individuals with chronic fatigue, definite cases of chronic fatigue syndrome as well as cases excluded from the trial and statistical analysis.

quent assessments 63 cases lost follow up due to noncompliance, travels, school examinations and other undetermined factors. So, the total number of cases left at the end of trial was 96 (32.2%) out of which four cases were further excluded from statistical analysis due to switch between groups (see flow chart of trial profile; Fig. 1). We adopted the revised case definition of CFS proposed by the US Centers for Disease Control [1]. Diagnosis of CFS could not be made without medical history, physical examination, mental status examination, and some laboratory tests. Cases were defined as CFS if they fulfilled the following two criteria: (a) Clinically evaluated, unexplained persistent or relapsing chronic fatigue that is of new or definite onset (i.e. not life long), not the result of ongoing exertion, not substantially alleviated by adequate sleep and rest, and with a substantial reduction in previous levels of occupational, education, social, or personal activities. (b) The concurrent occurrence of four or more out of total eight symptoms; 1) substantial impairment in short-term memory or concentration; 2) sore throat; 3) tender lymph nodes; 4) muscle pain; 5) multi-joint pain without swelling or redness; 6) headache of a new type, pattern, or severity; 7) unrefreshing sleep; and 8) post-exertional malaise lasting more than 24 hours. These symptoms must persist or recur during six or

more consecutive months of illness and should not be antecedent to fatigue. This strict case definition has been supported for research purposes by Laboratory Center for Disease Control (LCDC), Health Protection Branch (Wigle DT, Director of LCDC, November 12, 1996). All the enrolled CFS participants were more than 10 years old and complained of severe fatigue symptoms for more than six months, and had functional impairment of CIS more than 40%, without any of the exclusionary criteria of Fukuda. This crucial step had been undertaken by researchers themselves after full explanation of the plan and procedures of project, and then taking the written informed consents from parents. 2.3. Group allocation It was done by simple random method using a probability toss; psychotherapists as advised by statistician were the only persons aware of group assignment; however, researchers and statistician were kept unaware of group allocation. Cases randomly assigned to undergo CBT aided by biofeedback were called interventional group (IG) which comprised 50 cases; their families were informed to accept the issue of consulting only us during the whole study period and not to have any

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diagnostic or therapeutic intervention for the presenting symptoms anywhere. Other cases treated conservatively and symptomatically were used as a control group (CG); it comprised 46 cases out of which four were excluded because they switched to IG two weeks after the start of trial (see trial profile; Fig. 1). Researchers were kept unaware of group allocation till the end of trial to avoid selection bias at the start and ascertainment bias during assessment of outcome. Researchers followed participants indirectly through regular discussions with psychotherapists to solve any technical obstacles that might be encountered during the conduction of trial. 2.4. Treatment protocols Both groups were treated in a specifically designed CFS clinic held at Al-Jazira Polyclinic, Al-Khobar, Saudi Arabia; it was run by three well-trained pediatric psychotherapists and supervised by researchers. Psychotherapists were responsible for arrangement and formulation of all types of therapy; sometimes they consult family doctors for medical treatment of isolated systemic symptoms to keep all patients in a warm contact to that clinic. No psychotherapeutic drugs were used in our study. With biofeedback patients were trained to improve their health with the help of signals from their own bodies; the used machines gave some information about patient’s internal body functions, which might be valuable to direct the progress of CBT with far greater sensitivity and precision than could be provided by patients themselves. The most common biofeedback machines used were Muscle Monitors and Freeze Framer for treatment of muscle aches and chronic headache (Heart-Math LLC, 14700 West Park Avenue, Boulder Creek, California 95006 USA). These machines could be very useful adjuvant during CBT sessions especially in non-cooperative adolescents. Patients were trained to perform relaxation exercises, to identify circumstances that trigger their symptoms, to avoid or cope well with these stressful events, to change their habits, and even to have the ability of self-control. Behavioral therapy is a trial to weaken connections between troublesome situations and patient’s habitual reactions by teaching them to be calm, to think more clearly and to make better decisions (desensitization, behavior modification and activation). However cognitive therapy taught patients how thinking patterns could cause their troublesome symptoms for no good reasons using rational-emotive and Beck’s cognitive therapy.

When combined together CBT aided by biofeedback was carried out in official sessions over a period of 18 months, 40–60 sessions ranging from once up to twice weekly then tapered gradually depending upon the fatigue severity. These sessions usually included patients and their families. Warm contact between patients’ families and psychotherapists was maintained through phone calls and e-mails to answer their inquiries and frequently asked questions. For perfect follow up, every patient was asked to keep a personal diary to list times of fatigue, to analyze the stressors, if any, and to plan his/her activity with the help of psychotherapists. Also patients were asked to report the timing and duration of illness that necessitated the school absence. Patient’s activity pattern was frequently determined from history however it could be formally assessed in some cases by a specific device called actometer fixed above ankle for one week; patients showing lower activity scores were passive however others were relatively active [10]. According to patient’s activity pattern, we adopted two treatment protocols: relatively active patients who had periods of activity and periods of rest were advised to limit their activity then to build up gradually. However relatively passive patients who spent almost all times at home sleeping down were assured that activity will not aggravate their symptoms, then they were advised to undergo gradual building up by performing recreational exercises usually in the form of variable non-exhausting walks [11]. 2.5. Outcome parameters (assessment measures) All participants were assessed by researchers 18 months after the start of intervention using the following measures: (a) A ten-item CIS called FAS is the primary outcome parameter; it was developed in large samples of the Dutch workers and general population. Initially the items were 40, and then filtered to 10 items taken from the fatigue questionnaire; five representing physical activity and the other five for mental fatigue. A total score was calculated based on factorial and Mokken scale analyses. FAS instrument is directed at how a person usually feels; varying from one (never) to five (always) [8]. Although FAS seems to be unidimensional as it depends upon only one score analysis, it has been recently proven reliable and valid in comparison to six questionnaires (its reliability was 0.90) [9]. As FAS instrument did not measure emotional stability or depression, we excluded those patients having manic depressive illness from our trial. (b) Duration of school stay (in hours/month) is a simple precise measure and


can be a good index for improvement. However, as school absence may be related to many other factors, it was used as a secondary outcome. Duration of school stay was taken from school attendance profiles, patient’s own diary or reported roughly by families. (c) Some CFS symptoms were self-rated on four pointsLikert scale (from never to every day); patients indicated whether they became completely free (one), felt better (two), had the same complaints (three) or even became worse (four) [2]. These symptoms were also considered as secondary outcomes as they were merely subjective and each one was analyzed independently. 2.6. Statistical analysis Statistician was kept unaware of group assignment until the end of primary analyses. Data were explored, processed and analyzed using the statistical package of social science [12]. Power calculation was done before the trial conduction; it revealed a minimum sample size of 35 cases for each group based upon the tested multivariate fatigue severity score which was compatible with the number of cases ended the trial with a complete database ready for statistical analysis. This sample size produced 90% power to detect differences in the primary outcome with type I error less than 5%. The ten items of FAS were subjected to data reduction using factorial analysis to estimate a global score. Exploration of data by Kolmogrov Smirnov test revealed a preserved normality therefore analysis of difference between patients’ groups as regards parameters of fatigue severity was done by unpaired t-test, however changes within each group was determined by paired t-test. Descriptive statistics included mean ± SD for expression of central tendency and dispersion of quantitative parameters, number and percentage of categorical parameters. Sex distribution and activity pattern between the two groups were examined using cross tabulation and Chi-square test. The effect size (treatment effect) was estimated by the difference in means and its precision was evaluated by the 95% confidence interval (CI) in the estimated effect size. Post Hoc analysis of the CG ranks was done attempting to explain the low improvement rate in CG without any inferences to avoid the commonly met false positive rates in subgroup analyses. 3. Results Frequency of the different symptoms of CFS is shown in Table 1; some individuals showed two or more

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Table 1 Symptoms of adolescents suffering from chronic fatigue syndrome (n = 96) Symptoms Fatigue (unrefreshing sleep) Headache Myalgia Abdominal discomfort Sleep disturbances Others

n (%) 92 (95.8) 65 (67.7) 48 (50.0) 39 (40.6) 31 (32.3) 42 (43.8)

symptoms which occurred simultaneously or sequentially. Unrefreshing sleep was found in 95.8% of cases (92/96), the next common symptoms were headache in absence of any organic cause like refractive errors or hypertension (67.7%), myalgia without local tenderness or limited movement, with normal acute phase reactants and muscle enzymes (50%), abdominal discomfort (40.6%) which was mild in most cases but caused appetite inversion and even weight changes in some. Demographic data of patients showed mean age of more than 10 years (12.52 ± 3.32 years for all patients; 13.1 ± 3.2 years for IG and 11.9 ± 2.4 years for CG) to meet criteria of US Disease Control and Prevention of CFS, duration of fatigue symptoms was more than six months (27.9 ± 3.4 and 24.5 ± 4.2 weeks for IG and CG respectively) to fulfill CFS definition [1, 2]. CFS was predominantly occurring in adolescent females (male/female ratio is 1/2.5) with definite tendency to be active rather than passive (active/passive ratio 2.3/1). Proper group matching was assured by the lack of any statistical difference at the start of trial; neither in demographic data nor in severity parameters (Table 2). The primary outcome (CIS or FAS) was assessed blindly by researchers; however, duration of school stay and self-rated symptoms represented the secondary outcomes. At the end of trial, fatigue severity was found significantly lower and school attendance was significantly higher in IG compared to CG (32.2 and 92.8 for IG vs. 46.5 and 66.6 for CG with P 2 equal 0.02 and 0.004 respectively). This difference was due to the statistically significant drop in CIS (decreased by 23.1%; CI 19.2–25.4%) and the better school attendance (increased by 31.5%; from 64.4 to 92.8 hours/month; CI 29.8–36.6 hours/month) noticed among IG with P 1 < 0.001. Analyzing the changes in outcome parameters within CG revealed a small difference in means with a wide 95% CI (Table 3); this could be explained on the basis of rank analysis; there were three ranks within CG, the 1st rank included nine patients that showed an improvement lying within 95% CI of IG, another rank of 15 cases showed minor improvement and the last

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M.S. Al-Haggar et al. / Cognitive behavioral therapy in chronic fatigue syndrome Table 2 Demographic data and baseline severity parameters of chronic fatigue syndrome between patients’ groups Parameters

Age (years) Duration of symptoms (weeks) Male/female ratio Activity pattern number (active/passive) Fatigue severity (checklist score %) School attendance (hours/month)

Interventional group (n = 50) (mean ± SD) 13.1 ± 3.2 27.9 ± 3.4 14/36 32/18 54.8 ± 3.6 64.4 ± 13.2

Control group (n = 42) (mean ± SD)

Test statisticsa

P

11.9 ± 2.4 24.5 ± 4.2 11/31 32/10 51.9 ± 4.3 64.8 ± 14.5

0.82 1.15 0.19 1.55 1.72 0.96

0.55 0.31 0.72 0.29 0.28 0.46

a Test statistic is unpaired t-test for age, duration of symptoms, checklist score and school attendance, but for sex distribution and activity pattern, it is Chi-square test. P is statistically significant if less than 0.05.

Table 3 Severity parameters of chronic fatigue syndrome within each group; before and after trial as well as between both groups at the end of trial Parameters

Before trial (mean ± SD) Interventional group (n = 50) Fatigue severity 54.8 ± 3.6 (checklist score %) School attendance 64.4 ± 13.2 (hours/month) Control group (n = 42) Fatigue severity 51.9 ± 4.3 (checklist score %) School attendance 64.8 ± 14.5 (hours/month) Difference between groups at the end of trial Interventional group (n = 50) (mean ± SD) Fatigue severity 32.2 ± 3.8 (checklist score %) School attendance 92.8 ± 18.4 (hours/month)

After trial (mean ± SD)

Difference in means (95 % CI)a

P1

32.2 ± 3.8

23.1 (19.2–25.4) 34.46 (29.8–36.6)

< 0.001∗

4.46 (1.12–21.44) 3.44 (2.12–32.13)

0.62

Difference in means (95 % CI) 12.23 (7.4–14.8) 23.14 (20.6–26.8)

P2

92.8 ± 18.4 46.5 ± 14.2 66.6 ± 22.8

Control group (n = 42) (mean ± SD) 46.5 ± 14.2 66.6 ± 22.8

< 0.001∗

0.78

0.02∗ 0.004∗

P 1 is paired t-test for difference within each group (before and after) while P 2 is unpaired t-test for difference between both groups at the end of trial. a 95% CI; Confidence interval for difference in means. ∗ P is statistically significant if less than 0.05.

rank of 18 cases showed almost no changes or even worsening in outcome parameters (data are not shown in Table 3). This inconsistency in the outcome within CG could also explain the lack of statistically significant improvement within this group. A histogram illustrating the baseline fatigue severity parameters as well as changes at the end of trial among patients’ groups is shown in Fig. 2; data presented in the plot were based on the mean values. Some self-rated symptoms when analyzed independently showed statistically significant improvements e.g. unrefreshing sleep (fatigue), myalgia and headache with P 0.002, 0.005 and 0.03 respectively (Table 4).

4. Discussion CFS in children and adolescents has been uncommonly met, as it is usually mild however, it may be debilitating due to appetite inversion and sometimes anorexia and vomiting. Frequent school absence and even growth failure are the crucial threats in these young promising generations [1,2]. The innovation of potentially effective, non-invasive and safe therapy without the need for medications is very important for such chronic benign conditions in order to have normal school attendance and learning ability [13]. CBT aided by some biofeedback machines if approved as a thera-


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Table 4 Self-rated symptomsa of chronic fatigue syndrome in patients’ groups at the end of trial Symptoms

Fatigue (unrefreshing sleep) Headache Myalgia Joint pains Tender glands

Interventional group (n = 50) (mean ± SD) 2.12 ± 0.88 2.54 ± 0.84 2.16 ± 1.12 2.34 ± 1.14 1.81 ± 0.82

Control group (n = 42) (mean ± SD) 3.32 ± 1.14 2.86 ± 0.81 2.96 ± 0.92 2.34 ± 1.26 2.22 ± 0.92

t value

P

8.52 5.32 7.66 3.24 2.37

0.002∗ 0.03∗ 0.005∗ > 0.05 > 0.05

a Four

points-Likert scale: each symptom was self-scored by patients 1–4 depending upon its frequency (ranging from never to every day); patients indicated whether they became completely free (one), felt better (two), had the same complaints (three), or even became worse (four) [2]. ∗ P is statistically significant unpaired t-test if less than 0.05.

Fig. 2. Severity parameters of chronic fatigue syndrome in patients’ groups at the start and end of trial.

peutic option for CFS, it will improve the life quality and reduce the much costs and drawbacks associated with other conventional therapies. Up to the best of our knowledge, this is the first controlled trial studying the effect of CBT aided by biofeedback in Egyptian adolescents suffering from CFS. The studied population were school children living with their families outside the original country in Saudi Arabia, Eastern province; all school personnel and workers involved in the research were also Egyptians. Parents of most enrolled cases were attributing their symptoms to home sickness and/or the changed environment. A similar study was conducted towards the end of 2004 in Netherlands, University Medical Center Nijmegen; 71 consecutively referred adolescents with CFS were enrolled; 36 cases were randomly undergone CBT and the remainder 35 cases were left waiting for therapy and used as a control group [14]. Adolescents included in our current work were mostly active rather than staying at home in long sleep periods (active/passive ratio was 2.3/1) thus demonstrating how those children were unaware of their symptoms and could suggest a possible reason for the dis-

ease underestimation. We have found CBT to be very effective in reduction of fatigue severity and in improving school attendance up to the normal range (Table 3), provided that the contact between patient, family and therapy team remained very close as recommended by some authors [7]. These data are in agreement with that reported in literature although those authors neither ensured this tight contact nor explained their shortterm trial [14]. Recurrence risk of CFS had been documented to be very high if treatment whatever its nature is abruptly stopped or contact between patient, family and CBT team is lost [14,15]. Symptomatic treatment in our study showed unnoticeable changes in fatigue severity parameters possibly due to the heterogeneity of CFS symptoms and the different forms of medicine used in CG. The low improvement rate in CG could be explained statistically on basis of rank analysis by the lack of consistent trend in the outcome parameters as we observed three ranks within CG; the 1st rank of nine patients showed an improvement within 95% CI of difference in means noticed in IG, the 2nd rank of 15 cases showed minor improvements and the last rank of 18 cases showed almost no changes or even worsening

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thus leading to cancellation of power of the 1st rank. In a review and meta-analysis, the lower response of CFS to placebo had been proven compared to other conventional modalities and to placebo for other medical conditions [16]; results which are consistent with ours. Interestingly in the current study, some self-rated CFS symptoms [unrefreshing sleep (fatigue), myalgia and headache] showed statistically significant improvements among IG compared to CG. However as these isolated symptoms were analyzed independently serious bias might occur because participants were counted multiple times. This could be overcome either by counting each participant only once or by the use of more complex statistical procedures like multivariate regression analysis. For this reason, these self-rated symptoms should not be relied upon as primary outcomes and should be inferred with great caution. The improvement rate in our present study among IG was high compared to other studies regarding fatigue symptoms and school attendance irrespective of the treatment protocol whether for predominantly active or passive cases [11,14]. Despite school attendance was considered as a secondary outcome, it is a simple and precise index for improvement; it was found almost normalized among IG of our study. Differences in improvement rates between our study and others could be explained on the basis of different study designs, variable durations of intervention and/or the use of biofeedback aids in our study. The treatment protocol was individualized in the current work according to patient’s age and disease activity pattern. In other studies, the protocols used were those applied in adults and sometimes without reference to the patient’s activity pattern, moreover period of intervention was shorter compared to ours (6 vs. 18 months respectively). However, performance bias might occur in our work, as psychotherapists who conducted the interventional therapy were previously involved in the process of group allocation. As the CBT aided by biofeedback is a non-invasive method i.e. did not use any medications and lacked any potential drawbacks, it could be used for treatment of chronic benign problems like CFS to improve adolescents’ performance and to have a better life quality. However, there are some limitations for the generalizability (external validity) of our study; firstly because the enrolled participants were somewhat special (Egyptian adolescents studied on a foreign country), secondly, as psychotherapists who conducted the interventional therapy had been already involved in the process of group allocation, a factor that could produce some sort of performance bias and might add a further compromise for the genealizability of the current work.

We do not presume that biofeedback is magic but we aimed to remind physicians that cognition and behavior could profoundly influence physical health. Situations like CFS in adolescents could be treated effectively with CBT aided by biofeedback especially with the perfect initial evaluation and proper therapy plan.

Acknowledgments We acknowledge all pediatric psychotherapists Gamal A. Al-Mogi, Ahmad M. Zidan and Sawsan A. Nassar who confronted our cases in regular sessions and made strong relations with patients around the days of week. Special thanks are due to our adolescents who did not feel shame to attend the neuropsychiatric clinic on regular basis.

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