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Abstract

Background

Cluster headache (CH) is clinically associated with considerable psychosocial burden. However, instruments to assess and characterize psychosocial factors in cluster headache more specifically are lacking. This study aimed to develop a self-report questionnaire, which assesses the broadest possible spectrum of psychosocial factors in cluster headache, the Cluster Headache Scales (CHS).

Method

Items of the Cluster Headache Scales were constructed based on a literature review and semi-structured interviews with several experts (including persons with cluster headache). A cross-sectional online survey was conducted to determine the psychometric properties and the factor structure of the Cluster Headache Scales. Data was analyzed using exploratory factor analysis as well as exploratory structural equation modelling (ESEM).

Results

In total, n = 342 subjects with cluster headache (mean age 47.8, 63% male, 51% with episodic cluster headache) were included. Factor analysis yielded eight clearly interpretable factors: Medical care, medication side effects, fear of attacks, disability, (auto)aggression, coping, physical activity, and financial burden, which are assessed via 36 items. The internal consistencies of the subscales were acceptable to excellent and ranged between Cronbach’s alpha = .76 and .93. The pattern of correlations with related instruments provides first evidence for convergent validity.

Conclusion

The CHS represents a reliable and valid self-report instrument for the assessment of psychosocial factors in persons with cluster headache, which appears useful for both clinical practice as well as research.

Trial registration: The study was registered at the German Clinical Trials Register (www.drks.de, ID-Number: DRKS00016502).

Keywords

Cluster headache psychosocial factors coping disability questionnaire

Introduction

Cluster headache (CH) is associated with high burden of disease and with several psychosocial factors such as psychological distress, disability, and different ways of coping (1 –3). Presumably, the relation of psychosocial factors and disease activity is bidirectional, in that psychosocial factors may affect the course of the disease, and vice versa. For example, dysfunctional coping strategies or a comorbid mental disorder could have an adverse effect on the course of the disease, and a high disease activity or a high frequency of CH attacks could lead to more disability or a greater reduction of quality of life (QoL). Pohl and colleagues showed in a current, cross-sectional survey (the EUROLIGHT Cluster Headache Project), that higher headache frequencies were related to more burden in different factors (e.g. impaired autonomy or impairment of career options), whereas only few aspects of burden (e.g. worrying about future attacks) were not associated with attack frequency or disease duration (4). Schenk and colleagues conclude in a recent review, that in persons with CH QoL is reduced and disability increased to a larger degree than in persons with other headache disorders (2). Another finding is that persons with CH have a higher risk of depressive or anxiety disorders compared to controls (5,6) and that persons with active episodic CH and chronic CH are more affected than persons with inactive CH or migraine (7). However, there is only sparse data on these relationships and more research is needed (2).

A major drawback of previous studies on psychosocial factors in CH is that instruments were used that hardly address the specific aspects of this disorder. For instance, using assessment instruments developed for migraine is not adequate in the exploration of factors associated with CH. Specifically, item no. 3 from the six-item Headache Impact Test (HIT-6) (8) “When you have a headache, how often do you wish you could lie down?” is not suitable for persons with CH who are known to show a pattern of restlessness, anger, and self-injury during CH attacks. Another example is the Migraine Disability Assessment (MIDAS) (9), which focuses on days with headache, but does not record the frequency and duration of attacks per day. Thus, one of the characteristic aspects of CH (the relatively short duration of attacks), cannot be adequately assessed with the MIDAS. Nevertheless, the MIDAS was used in some studies to assess headache related disability in persons with CH (2), since no specific instruments existed.

Actually, there are only two CH-specific questionnaires known, the Cluster Headache Severity Scale (CHSS) (10), and the Cluster Headache Quality of life scale (CHQ) (11). The CHSS allows grading of the severity of CH by building a total score, which includes (i) typical frequency of CH attacks per day, (ii) CH attack duration in minutes, and (iii) period (bout) duration in months. Since the CHSS reflects the severity of the disease only by assessing the attacks themselves and not by assessing the QoL or burden of disease, which includes psychosocial factors, sleep disturbances and altered mood, there is a further need for a suitable instrument to determine the total burden of CH. The CHQ aims to assess QoL in persons with CH. It consists of four subscales, labelled “restriction of activities of daily living”, “impact on mood and interpersonal relationships”, “pain and anxiety”, and “lack of vitality”, with the first subscale explaining by far the largest variance (43.11%). Although the CHQ does encompass some important aspects of disability, some relevant psychosocial factors such as coping with the disorder or self-efficacy may not be covered with this questionnaire. Schenck and colleagues conclude that “the need for ‘cluster’-specific measures of QoL, disability, and impact is readily apparent” (p. 181) (2).

The primary objective of this study was therefore to develop a self-report questionnaire, which assesses the broadest possible spectrum of psychosocial aspects in CH, the Cluster Headache Scales (CHS). Further, our aim was to determine the factor structure and psychometric properties of this instrument.

Methods

Procedure

The study was designed as a cross-sectional online survey. Inclusion criteria were (i) age of at least 18 years, and (ii) pre-diagnosed CH (according to ICHD 3.1 or ICD-10 G44.0) (12,13). Participants were recruited via the German Association of the Cluster Headache Self-help Groups. In doing so, the members of the CH self-help groups received an email with information about the study and a link to the online survey. The survey was conducted from January to February 2019 via the online portal SoSci-Survey (14). When activating the link to the survey, the participants first received brief information (e.g. study goals). After participants had agreed to the informed consent, the survey began. The survey contained a battery of measures, including the CHS. The study protocol was approved by the local ethics committee of the department of psychology, University of Mainz, Germany (2018-JGU-psychEK-016). The study was registered at the German Clinical Trials Register (www.drks.de, ID-Number: DRKS00016502).

Construction of the questionnaire

The items of the CHS were constructed based on a literature review, and semi-structured interviews with seven experts in total. The literature review was done by using the keywords: Cluster, cluster headache, episodic, chronic, trigeminal autonomic cephalalgias AND diagnostic, sleep, depression, suicide, anxiety, treatment, trigger, alcohol, smoking, restlessness, psychological burden, management, impairment, lifestyle, quality of life, comorbidities, in the databases Web of Science, PubMed, and Google Scholar, and limited in time from the year 2000. Moreover, the reference list of specific textbooks or reviews were checked (15 –18). In addition, the website of the German Association of the Cluster Headache Self-help Groups (www.clusterkopf.de) was searched for relevant information. Further, in order to capture as many different points of view as possible, three types of experts were interviewed: Two experienced practitioners (one neurology specialist, one licensed psychotherapist, both practicing in the Migraine and Headache Clinic Königstein), two officials of the German Association of the Cluster Headache Self-help Groups, and three patients with CH (Migraine and Headache Clinic Königstein). The questionnaire consisted of three parts, namely (i) socio-demographic data (e.g. family status), (ii) disorder characteristics (e.g. type, duration, triggers), and (iii) psychosocial aspects (95 items with the assumed core areas of distress, disability, and coping). Part (iii) is regarded as the CHS in a narrow sense. We conducted a pre-test with eight CH patients (Migraine and Headache Clinic Königstein, six men; seven with chronic CH; mean age 50.4, SD = 7.2). Participants in the pre-test were requested to additionally assess the comprehensibility and the relevance of the items of part (iii). Further, the participants were given the possibility to give an informal feedback for each item. Taking the feedback into account, the prototype was revised. In doing so, we optimized the wording of some items. Each item from part (iii) is to be answered on a 5-point scale (1 = strongly disagree, 2 = disagree, 3 = neither agree or disagree, 4 = agree, 5 = strongly agree).

Measures

In order to assess the validity of the CHS, we used the following self-report measures in our survey (each in the German version): (i) German short form (HMSE-G-SF) (19) of the Headache Management Self-efficacy Scale (HSME) (20); (ii) Epworth Sleepiness Scale (ESS) (21), the German version of the German Sleep Research Society (22); (iii) Depression Anxiety Stress Scales (DASS) (23), German short version (24); (iv) Cluster Headache Severity Scale (CHSS) (10); (v) Headache Disability Inventory (HDI (25), German version: Inventar zur Beeinträchtigung durch Kopfschmerzen, IBK) (26). The above-mentioned instruments were selected in order to cover the assumed core areas of distress, disability, and coping in an appropriate way. To assess depression and anxiety, we preferred the DASS over the more commonly used Hospital Anxiety and Depression Scale (HADS) (27). The advantages of the DASS over the HADS are better specificity and sensitivity, as well as a clearer factor structure (24). For the determination of discriminant validity, we applied the German Version (28) of the Social Interaction Anxiety Scale (SIAS) (29).

The HMSE-G-SF comprises six items (e.g. “There are things I can do to reduce headache pain”), and has a satisfying internal consistency (Cronbach’s alpha = .72) (19). Therefore, the HMSE-G-SF can be regarded as a suitable instrument to asses self-efficacy beliefs in the context of coping with headache. Since CH attacks oftentimes appear during sleep, the quality of sleep is often affected in persons with CH. The ESS aims to measure the general level of daytime sleepiness (21). It describes eight situations (e.g. “Watching TV”), for which the subject has to assess his chance of dozing. The ESS has a good internal consistency (Cronbach’s alpha = .88) (30). The DASS consists of three scales: Depression (DASS-D), Anxiety (DASS-A), and Stress (DASS-S). Thus, the DASS provides a measure of the emotional state. Each scale comprises seven items (short version). Every item (e.g. “I felt sad and depressed”, DASS-D) requires an answer on a 4-point scale. Overall, the scales showed good internal consistency (Cronbach’s alpha = .78 to .92) (24). The CHSS was constructed to grade the severity of CH. We translated the three core items (that is the specification of attacks/day, attack duration in minutes, bout duration in months) into German (a retrospective back-translation into English by a professional native English speaking translator showed no substantial deviations). Each item is classified into four scores, and by summing up the scores, a total score is built (from 3 = minimal severity to 12 = maximal severity) (10). The HDI (German version: IBK) has two subscales (functional and emotional disability) and comprises 25 items (e.g. “due to my headaches, I have fewer social contacts”). The internal consistency of the total scale (German version) is high (Cronbach’s alpha = .90) (26). The IBK allows quantification of the impact of headaches on daily living. The SIAS is a self-report instrument to assess anxiety in social interactions; for example, in conversations with friends, strangers, or potential partners. The SIAS has good internal consistency (Cronbach’s alpha = .94) (28).

Statistical analysis

To reduce the number of items in the final version of the questionnaire (Supplementary Material 1), item statistics were investigated. Items with skewness > 2, kurtosis > 7, item difficulty <.10 or > .90, and item intercorrelations >.7 were excluded. In a next step, items with low communality (<.35) and factor loadings <.4 in a principal axis analysis were excluded.

Suitability for factor analysis was determined with Kaiser-Meyer-Olkin (KMO) criterion and Bartlett test. The number of factors was determined with parallel analysis and Velicer Minimum Average Partial (MAP) criterion (31). Exploratory Structural Equation Modelling (ESEM) was performed by applying the weighted least squares‐mean and variance‐adjusted estimator (WLSMV) and geomin (oblique) rotation. Model fit was evaluated with χ², root mean square error of approximation (RMSEA), comparative fit index (CFI), Tucker-Lewis fit index (TFI), and weighted root mean‐square residual (WRMR).

Convergent validity was assessed with Spearman correlations between the subscales of the CHS and questionnaire scores (cf. above) as well as clinical characteristics (number of cluster headache attacks in the past week, mean pain intensity during headache attacks, and mean duration of a headache attack).

Analyses were calculated with Mplus (32), R version 3.5.0 (33), and SPSS (V23).

Results

Sample description

The majority of the participants (Figure 1, Table 1) were male (63%, n = 215) and on average participants were 47.8 years old (SD = 11.8, min = 19, max = 78 years). The average duration of illness was 16.6 years (SD = 10.9, min = 1, max = 51 years). At about half of the participants reported being diagnosed with episodic (51%, n = 174) or with chronic CH (49%, n = 167; n = 1 missing). Most participants indicated that their diagnosis was made by a neurologist (n = 254, 74.3%). The remaining participants indicated that their diagnosis was made by a general practitioner (n = 31, 9.1%), by a medical doctor specialized in pain medicine (n = 21, 6.1%), an unspecific clinic or institution (n = 11, 3.2%) or by more than one of the above (n = 25, 7.3%).

Figure 1:

Flowchart of attrition.

Table 1.

Sample description and clinical characteristics.

	sample (N = 342 subjects)
Currently in a partnership	83 % (n = 283)
Marital status
Single	25 % (n = 85)
Married	59 % (n =202)
Divorced	15 % (n = 50)
Widowed	2 % (n = 5)
Education
No school-leaving qualification	1 % (n = 2)
Lower secondary education	13 % (n = 44)
Secondary school	38 % (n = 129)
High school	23 % (n = 77)
University	26 % (n = 90)
Employment status
Full-time job	51 % (n = 175)
Part-time job	15 % (n = 51)
School/training	2 % (n = 6)
Retirement pension	9 % (n = 31)
Part-time job & disability pension (partial)	1 % (n = 4)
Disability pension (full)	13 % (n =45)
Disability pension (partial)	2 % (n =6)
Unemployed	5 % (n =17)
Missing value	2 % (n = 5)
Accompanying symptoms
Red eyes	67 % (n = 228)
Watery eyes	86 % (n = 295)
Swollen eye lid	33 % (n = 112)
Nasal congestion	75 % (n = 257)
Running nose	61 % (n = 207)
Physical agitation	80 % (n = 272)
Restlessness	78 % (n = 268)
Sweating in the face	41 % (n = 139)
Ptosis	48 % (n = 165)
Miosis	25 % (n = 87)
Other	27 % (n = 91)
Acute treatment
Oxygen	75 % (n = 257)
Sumatriptan	68 % (n = 232)
Zolmitriptan	26 % (n = 90)
Lidocaine/procain	5 % (n = 16)
Ergotamine	2 % (n = 6)
None	6 % (n = 19)
Prophylactic medication
Verapamil	54 % (n = 186)
Lithium	9 % (n = 30)
Corticosteroids	9 % (n = 32)
Valproate	2 % (n = 5)
Topiramate	11 % (n = 38)
Triptans	11 % (n = 37)
Melatonin	2 % (n = 6)
None	31 % (n = 107)
Course of disease
Change from episodic to chronic CH	31.3 % (n = 107)
Change from chronic to episodic CH	4.7 % (n = 16)
Episodic CH from the beginning	38.9 % (n = 133)
Chronic CH from the beginning	15.2 % (n = 52)
Another kind of change (e.g. multiple changes)	9.6 % (n = 33)
Trigger of CH attacks
Alcohol	51.2 % (n = 175)
Emotional distress	43.0 % (n = 147)
Weather/weather change	39.2 % (n = 134)
Flickering light	34.2 % (n = 117)
Heat	28.9 % (n = 99)
Lack of sleep	26.9 % (n = 92)
Histamine	22.5 % (n = 77)
Other triggers	21.6 % (n = 74)
Other food	21.1 % (n = 72)
None	18.1 % (n = 62)
Menstruation (from n = 127 females)	12.6 % (n = 16)
Nicotine	6.7 % (n = 23)
Caffeine	2.3 % (n = 8)

CH: Cluster Headache.

Item selection

No item had to be excluded due to skewness, kurtosis, and item difficulty. Eighteen items were excluded due to high item intercorrelation and another 18 items due to low communality or low factor loading. The final questionnaire consisted of 36 items. Items 1–4, 21–24, 29–33, and 36 were recoded so that higher scores mirror higher burden.

Items 73–95 had to be excluded due to missing data. These items were initially developed to address potential psychosocial aspects, such as the relationship to one’s own children, to seniors, or to workmates. Since there were missing values for each of these items (not every person has their own children, workmates, and so on), it was not possible to include these items into further calculations or the factor analysis.

Factorial structure and model fit

The data proved suitable for factor analyses, according to KMO criterion (KMO = 0.90; “marvelous”; Kaiser, 1975) and Bartlett test (χ²(2556) = 18115.53, p < .001). Following Velicer MAP as well as results from parallel analysis, eight factors were extracted.

The eight factors were clearly interpretable (Table 2). Four items loaded on a factor that was interpreted as “medical care”, three items loaded on a factor “medication side effects”, four items on a factor “fear of attacks”, eleven items on a factor “disability”, five items on a factor “(auto)aggression”, three items on a factor “coping”, three items on a factor “physical activity”, and three items on a factor “financial burden”. Although some significant cross-loadings appeared, the factor loadings were mostly distinct so that the items could be allocated to a single factor. Exceptions were item 03 (“I tolerate my cluster headache medication well.”), which showed substantial (>.40) loadings on the factor “medical care” and “medication side effects” as well as item 25 (“I am not active enough”), which showed substantial loadings on the factor “physical activity” and “disability”.

Table 2.

Standardized model results with significant loadings (p < .01), explained variance (R²), item difficulty (pi), and item selectivity (rit).

Item	Scale	Factor loadings								R²	p_i	r_it
Item	Scale	F1	F2	F3	F4	F5	F6	F7	F8	R²	p_i	r_it
01	Medical care	0.69								.52	.30	.51
02	Medical care	0.91								.86	.35	.71
03	Medical care	0.61	0.41							.53	.38	.47
04	Medical care	0.61								.51	.29	.55
05	Medication side effects		0.91							.88	.57	.72
06	Medication side effects		0.72							.56	.58	.60
07	Medication side effects		0.66		0.21					.57	.55	.63
08	Fear of attacks			0.70	0.15					.60	.80	.66
09	Fear of attacks			0.92						.84	.80	.79
10	Fear of attacks			0.77						.73	.60	.74
11	Fear of attacks			0.83						.78	.69	.77
12	Disability			0.14	0.73					.65	.63	.72
13	Disability			0.27	0.74					.78	.76	.72
14	Disability			0.25	0.69		0.11			.73	.58	.75
15	Disability				0.66					.56	.57	.70
16	(Auto)aggression				0.18	0.64				.56	.57	.58
17	(Auto)aggression					0.70				.50	.33	.60
18	(Auto)aggression					0.76				.66	.52	.63
19	(Auto)aggression					0.70				.54	.15	.51
20	(Auto)aggression			0.14		0.65				.57	.40	.60
21	Coping	.13			0.16		0.69			.62	.62	.64
22	Coping						0.93			.87	.63	.74
23	Coping					0.17	0.77			.61	.66	.65
24	Disability				0.67			0.34		.73	.62	.74
25	Physical activity				0.38			0.52		.54	.57	.50
26	Disability			0.21	0.78					.76	.72	.77
27	Disability			0.21	0.78				−.13	.65	.67	.69
28	Disability				0.71		−.18			.54	.55	.62
29	Disability		0.22		0.73	−0.16		0.22	0.17	.84	.53	.76
30	Disability		0.20		0.70	−0.13		0.25	.16	.81	.48	.73
31	Physical activity							0.90		.84	.44	.74
32	Physical activity							0.79		.68	.52	.65
33	Disability			−0.14	0.49			0.31	0.16	.53	.41	.58
34	Financial burden								0.59	.45	.39	.55
35	Financial burden								0.70	.57	.42	.58
36	Financial burden								0.88	.78	.42	.68
Cronbach’s alpha		.76	.80	.88	.93	.80	.82	.79	.77

The factors were partly correlated (see Supplementary Table 1): “Fear of attacks” and “disability”, “fear of attacks” and “(auto)aggression”, “disability” and “(auto)aggression”, as well as “disability” and “financial burden” especially showed correlations > .3.

Goodness of fit of the model was acceptable to good (χ²(370) = 883.52, p < .001, χ²/df = 2.39, RMSEA = .07, CFI = .96, TLI = .92, WRMR = .64).

Reliability and item statistics

The internal consistencies of the subscales were acceptable to excellent and ranged between Cronbach’s alpha = .76 and .93 and item selectivity was ≥ .47 for all items (Table 2). Item difficulty ranged between .15 and .80, thus allowing differentiation in a broad spectrum.

Validity

Demonstrating convergent validity (Table 3), all subscales of the CHS correlated with the subscales of the DASS and HDI, whereby the subscales “disability”, “(auto)aggression”, and “fear of attacks” showed the largest correlations with medium to large effect sizes. The CHSS correlated with all subscales of the CHS except “medical care” and “fear of attacks” and showed largest correlations with the “disability” subscale. As expected, HMSE-G-SF showed the largest correlation with the “coping” subscale of the CHS and also significantly correlated with “disability”, “medical care”, “fear of attacks”, and “(auto)aggression”.

Table 3.

Measures of validity. Spearman correlations of questionnaires scores and clinical characteristics with the subscales of the Cluster Headache Scales.

Subscale	Discriminant validity	Convergent validity								Number attacks/last week	Mean pain intensity/attack	Mean duration/attack
Subscale	SIAS	HMSE-G-SF	ESS	DASS-D	DASS-A	DASS-S	CHSS	HDI-E	HDI-F	Number attacks/last week	Mean pain intensity/attack	Mean duration/attack
Medical care	.20***	−.12*	<.01	.20***	.19***	.24***	.08	.36***	.32***	.10	.10	.19*
Medication side effects	.02	−.03	.02	.18**	.19**	.21***	.31***	.24***	.29***	.13	.01	.08
Fear of attacks	.16**	−.25***	.12*	.41***	.36***	.41***	.06	.51***	.40***	−.02	−.02	.06
Disability	.21***	−.19***	.08	.57***	.43***	.48***	.40***	.60***	.76***	.24**	.07	.27**
(Auto)aggression	.21***	−.11*	.13*	.42***	.40***	.49***	.25***	.57***	.42***	.15	.11	.13
Coping	.02	−.56***	.08	.17**	.15**	.16**	.17**	.24***	.20***	.10	.04	.13
Physical activity	.14*	−.07	.06	.29***	.22***	.21***	.13*	.20***	.29***	.05	−.07	.02
Financial burden	.25***	−.05	−.02	.31***	.27***	.27***	.18***	.31***	.32***	.19*	.07	.14

Abbreviations of measures (each used the German version): SIAS: Social Interaction Anxiety Scale; HMSE-G-SF: Headache Management Self-Efficacy Scale, short-form; ESS: Epworth Sleepiness Scale; DASS-D: Depression Anxiety Stress Scale, subscale Depression; DASS-A: subscale Anxiety; DASS-S: subscale Stress; CHSS: Cluster Headache Severity Scale; HDI-E: Headache Disability Inventory, subscale Emotion; HDI-F, subscale Function. *p < .05, **p < .01, ***p < .001.

With regards to clinical characteristics (Table 3), the subscale “medical care” showed a significant correlation with mean duration of attacks, and the subscale “disability” significantly correlated with mean duration of attacks and number of attacks in the past week. The subscale “financial burden” further correlated with number of attacks in the past week.

The SIAS, which was used to determine divergent validity, showed low but significant correlations with the subscales “medical care”, “fear of attacks”, “disability”, “(auto)aggression”, “physical activity”, and “financial burden”.

Interpretation for clinical use

Both the scores of the eight subscales and a total score (“global psychosocial burden”) of the CHS can be used to interpret the psychosocial burden of persons with CH. First the values per item (1 = strongly disagree, 2 = disagree, 3 = neither agree or disagree, 4 = agree, 5 = strongly agree) are determined, whereby the items 1–4, 21–24, 29–33, and 36 are inverted. Thus, higher values mirror higher burden or lower coping/self-efficacy. A score is calculated for each of the eight subscales by adding up the values of the respective items (scale 1: items 1–4, scale 2: items 5–7, scale 3: items 8–11, scale 4: items 12–15, 24, 26–30, 33, scale 5:items 16–20, scale 6: items 21–23, scale 7: items 25, 31, 32, scale 8: items 34–36). Further, a total score is calculated by adding up the values of all items. The percentile ranks and t-values for each subscale and the global psychosocial burden are presented in Supplementary Table 2 or Table 3. Percentile ranks >84 or a t-value > 60 indicates an above-average level of burden or below-average coping/self-efficacy compared to other persons with CH.

Comparing persons with episodic and chronic CH (Supplementary Table 4), the latter show larger means in the subscales medication side effects, disability, (auto)aggression, financial burden, and the total score. Persons with episodic CH show a larger mean score in the subscale “fear of attacks”.

Discussion

Despite the well-known high burden of disease and severe psychosocial consequences of cluster headache, an instrument for the disease-specific assessment of those aspects is missing. Due to the unique character of the disorder (e.g. more than one attack per day) migraine-specific questionnaires do not fit for cluster headache. Therefore, a CH-specific self-report questionnaire (the CHS) was developed. The CHS is supposed to cover the broadest possible spectrum of CH-specific psychosocial factors. Item selection led to 36 items in part three of the questionnaire (part three covers the psychosocial factors). Factor analysis with data of a large sample of subjects with CH yielded eight clearly interpretable factors: “medical care”, “medication side effects”, “fear of attacks”, “disability”, “(auto)aggression”, “coping”, “physical activity”, and “financial burden”. Model fit was acceptable to good. The psychometric properties of the questionnaire were adequate; that is, the internal consistencies of the eight subscales were acceptable to excellent, and the pattern of correlations with other (sub)scales indicated mainly good convergent validity (e.g. the correlation of the subscale “coping” with the HMSE-G-SF was medium-sized and statistically significant, and the correlation of the subscale “disability” with the HDI was large and statistically significant). Moreover, there were statistically significant correlations between the subscale “disability” and the headache activity (number of attacks and mean duration/attack); that is, more headache activity appears to be associated with more disability.

Existing psychometric questionnaires that are recommended for use in headache disorders can be assigned to three areas, which are (i) psychosocial/emotional distress, (ii) disability, and (iii) coping (34). However, there is a lack of specific instruments to assess psychosocial factors in persons with CH. The only CH-specific questionnaires known to us are the CHSS (which aims to grade the severity of CH), and the CHQ (which primarily aims to assess QoL in persons with CH). Our results show that the pattern of psychosocial factors in CH is more complex and more differentiated than the above-mentioned three areas, in that the CHS contains the additional subscales “medical care”, “medication side effects”, “(auto)aggression”, and “financial burden”. With these scales, the CHS also provides an important addition to the CHQ. Even though the CHQ also contains an item each on self-harm or aggressiveness, it has no separate subscale for this area. However, in contrast to the CHS, the CHQ does address more explicitly the aspect of impairment in interpersonal relationships with the subscale “impact on mood and interpersonal relationships”. Another difference between these two questionnaires is that the CHQ asks about the frequency of a specific disability or complaint (e.g. “felt tense or anxious”) by having five possible answers from “never” to “always”, whereas the CHS asks about the level of agreement with a statement (e.g. “the treatment costs are a financial burden for me”) by having five possible answers from “strongly disagree” to “strongly agree”. We conclude that the developed CHS is a valuable additional tool to assess psychosocial factors in CH, in that the CHS covers several other important psychosocial factors of CH, and in that the answer options for the items of the CHS are different in terms of content.

However, some of the findings were rather unexpected: First, there was no independent factor “sleep quality”, although sleep is often impaired in CH. Accordingly, the correlations of our subscales with the ESS were mainly small and not statistically significant. Thus, the CHS does not cover this aspect of the disorder, and it may be reasonable, to apply the ESS in clinical practice and research additionally to the CHS. Second, the correlational analyses yielded small, but statistically significant correlations between the SIAS and several subscales of the CHS. We initially applied the SIAS to determine discriminant validity, but retrospectively we assume that aspects of social interaction might be significantly affected in persons with CH. Thus, we conclude that the SIAS was not the best choice to measure discriminant validity.

A major strength of the study is the large sample of participants. Our sample is heterogeneous (e.g. 51% episodic and 49% chronic persons with CH) and the sample characteristics are similar to those of a sample of an outpatient headache center (35). Accordingly, the mean age (47.8 vs. 44.7 years) was comparable in both samples. Further, the vast majority were male, and taking oxygen and/or medication as attack-aborting treatment, and in both samples 69% were taking prophylactic medication. However, it can be assumed that the psychosocial burden on participants in a self-help group tends to be somewhat higher than the burden of the “average” person with CH, since a higher burden may motivate a person to join a self-help group. As the study participants in our survey were recruited via the German Association of the Cluster Headache Self-help Groups, their psychosocial burden may be slightly higher than the entire population of persons with CH. This consideration is supported in that the proportion of persons with chronic CH is somewhat higher in our sample compared to the above-mentioned outpatient sample (49% vs. 40%), and the mean duration of the disease is somewhat longer (16.6 vs. 12.9 years). Thus, one limitation of our study might be a selection bias. Another limitation is that the CH diagnosis was based on a self-assessment only. Due to the character of the survey it was not possible to objectify the diagnosis through own specialist staff. However, since the vast majority of subjects reported that their diagnosis was made by a medical specialist, we assume that the accuracy was acceptable. The fact that the participants were recruited through the German Association of the Cluster Headache Self-help Groups may also have contributed to a sufficient level of accuracy.

The most commonly reported trigger in our sample was “alcohol”, which is in line with a survey about CH in the United States of America (36), and which is a generally recognized trigger (37). However, the second most commonly reported trigger in our sample was “emotional stress”, which was not named in the USA survey. In general, emotional stress as a trigger seems to be neglected in the literature.

As expected, the comparison between the participants with episodic and chronic CH tended to show a higher burden on the latter. Only the scale “fear of attacks” was significantly higher among the persons with episodic CH. An explanation may be, that the more frequent confrontation with attacks among the persons with chronic CH could have led to an anxiety reduction (which is in accordance with current fear coping models, e.g. as described by Craske and colleagues) (38). The finding, that more headache frequency (here: chronic CH) tends to be associated with more psychosocial burden, is in line with the results from the EUROLIGHT Cluster Headache Project (4). However, the finding that persons with episodic CH have significantly more fear of attacks is novel.

Taken together, the CHS could be applied in clinical practice as well as in research. In clinical practice, the assessment of psychosocial factors could provide important information for scheduling an individual behavioral intervention. For example, a high score in the scale (auto)aggression could be a strong indication to develop skills in coping with aggression or agitation during an ongoing CH attack. In interventional studies, the assessment of psychosocial factors could lead to more meaningful results. Outcome measures in clinical trials should not only include headache activity, but also psychosocial factors such as disability and QoL (39,40). Both, the CHQ and the CHS are brief and easy to use, and the processing time of the CHS is suitable, as it usually does not exceed 25 minutes. Thus, we recommend that an assessment of psychosocial factors in persons with CH should be made with the CHQ and the CHS, both in clinical practice and in research.

Future research should aim to detect the sensitivity of the CHS to change, and to develop CH-specific behavioral interventions. Currently, the evidence of behavioral interventions in CH is very low. Blanchard and colleagues showed in an uncontrolled, single-group study with 11 subjects with episodic CH, that progressive muscle relaxation in combination with biofeedback has potential benefits (41). However, randomized controlled-trials are lacking. Certain specific lifestyle factors (especially increased tobacco consumption) are observed in persons with CH (42), and it may be of value to address unhealthy behavior patterns with targeted interventions. A behavioral approach should (i) comprise education about the disease, (ii) promote a healthy lifestyle and coping with stress or triggers (iii) support coping with CH attacks, (iv) address comorbid mental disorders, and (v) enhance the management of relevant social areas (e.g. work, finance, partnership, family, medical care). The application of the CHQ and the CHS in behavioral treatment studies could help to shape suitable behavioral interventions.

Clinical implications

We identified eight psychosocial factors, which are relevant to CH sufferers: “medical care”, “medication side effects”, “fear of attacks”, “disability”, “(auto)aggression”, “coping”, “physical activity”, and “financial burden”.

The developed Cluster Headache Scales (CHS) are a self-report questionnaire in order to asses these eight psychosocial factors. The CHS comprise 36 items and show good psychometric properties, thus they may be used in clinical practice and research.

Future research should aim to develop suitable behavioral interventions for CH sufferers, and the Cluster Headache Scales (CHS) as well as the Cluster Headache Quality of life scale (CHQ) are useful instruments to evaluate CH specific treatments.

Supplemental Material

sj-pdf-1-cep-10.1177_0333102420928076 - Supplemental material for Determination of psychosocial factors in cluster headache – construction and psychometric properties of the Cluster Headache Scales (CHS)

Supplemental material, sj-pdf-1-cep-10.1177_0333102420928076 for Determination of psychosocial factors in cluster headache – construction and psychometric properties of the Cluster Headache Scales (CHS) by Timo Klan, Anne-Kathrin Bräscher, Annabella Vales, Eva Liesering-Latta, Michael Witthöft and Charly Gaul in Cephalalgia

Supplemental Material

sj-pdf-2-cep-10.1177_0333102420928076 - Supplemental material for Determination of psychosocial factors in cluster headache – construction and psychometric properties of the Cluster Headache Scales (CHS)

Supplemental material, sj-pdf-2-cep-10.1177_0333102420928076 for Determination of psychosocial factors in cluster headache – construction and psychometric properties of the Cluster Headache Scales (CHS) by Timo Klan, Anne-Kathrin Bräscher, Annabella Vales, Eva Liesering-Latta, Michael Witthöft and Charly Gaul in Cephalalgia

Footnotes

Acknowledgements

The authors would like to thank all the persons who participated in this study. Also, we would like to thank Dr. Harald Müller and Jakob C. Terhaag from the German Association of the Cluster Headache Self-help Groups (CSG e.V.) for the support in recruiting persons with cluster headache. Further, the authors would like to thank Ms. M.Sc. Hülya Kilic who conducted a pretest of the questionnaire in the context of her master thesis.

Declaration of conflicting interests

The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Timo Klan: None.

Anne-Kathrin Bräscher: None.

Annabella Vales: None.

Eva Liesering-Latta received honoraria for lectures within the past 2 years from Allergan Pharma, and Eli Lilly.

Michael Witthöft: None.

Charly Gaul received honoraria for consulting and lectures within the past 3 years from Allergan Pharma, Ratiopharm, Boehringer Ingelheim Pharma, Eli Lilly, Novartis Pharma, Desitin Arzneimittel, Cerbotec, Hormosan Pharma, electroCore, Sanofi Reckitt Benckiser, and Teva.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Timo Klan

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