Psychological determinants for behavioral problems in people with multiple sclerosis: a patient control pilot study

Abstract

Although multiple sclerosis (MS) is a common disease of the central nervous system, little is known about behavioral problems, like signs of rigidity, increased disinhibition and apathy. The aim of the present study is to examine whether people with MS (PwMS) report more behavioral problems compared to people with a non-CNS-involved chronic disease (people with rheumatoid arthritis (PwRA)) and the relationship with depression, anxiety, coping and fatigue. Forty-five PwMS and thirty PwRA and informants filled in questionnaires assessing behavioral problems (NPI-Q, BRIEF-A), depression and anxiety (HADS), acceptance (ICQ) and fatigue (CIS-20). Compared to PwRA, PwMS reported significantly more apathy, irritability and aimless repetitive behavior. PwMS also reported higher levels of fatigue and more helplessness. Higher levels of depressive symptoms and lower levels of acceptance were related to higher levels of self-reported apathy. Higher levels of irritability were related to more helplessness and less acceptance. This study indicates that there is a specific pattern of self-reported behavioral problems in PwMS regarding apathy, irritability and repetitive behavior. These results may not solely be explained by psychological factors, but it is hypothesized that this could result from MS related executive disorders.

Keywords:

• Multiple sclerosis
• behavioral problems
• psychological factors
• cognition
• neuropsychology

Reviewing Editor:

• Stephanie Rossit, University of East Anglia, United Kingdom

Subjects:

• Cognitive Psychology
• Health Psychology
• Neuropsychology
• Psychological Science

Introduction

Multiple sclerosis (MS) is a prevalent, chronic progressive inflammatory and degenerative disease of the central nervous system that leads to demyelination and neuronal and axonal loss. Cognitive deficits impair about 43% to 72% of the MS population (Ferreira, 2010; Glanz et al., 2012) and occurs in all disease subtypes, irrespective of disease duration. However, cognitive deficits might be more prevalent in people with MS (PwMS) with progressive courses (Chiaravalloti & DeLuca, 2008; Denney et al., 2005) and are thought to be more severe in PwMS with a higher level of physical disability (Amato et al., 2001; Ruano et al., 2017). There is an overall consensus of the nature of cognitive deficits observed in PwMS, which include deficits in speed of information processing, memory, spatial perception and executive functioning (EF) (Chiaravalloti & DeLuca, 2008; Ferreira, 2010). Regarding EF, deficits in planning and organization skills, working memory, fluency and shifting are described (Roman & Arnett, 2016). In addition to EF and other cognitive deficits, subtle behavioral problems are regularly observed in clinical practice, in particular behavioral problems that could result from executive dysfunction, i.e. signs of rigidity, increased disinhibition and apathy. However, little is known about these behavioral problems in PwMS.

In contrast, there is extensive research in people with traumatic brain injury (PwTBI), reporting behavioral changes in 49% to 80% of the cases (Koponen et al., 2002). These behavioral changes could often be directly linked to executive disorders due to brain dysfunction (i.e. frontal lobes). For instance, PwTBI in the ventral frontal region often show reduced anger control, aggressiveness (Tateno et al., 2003; Ylvisaker et al., 2005), disinhibition, impulsiveness, lability, sexual acting out, perseveration, inefficient learning from consequences, and generally poor social judgment (Ylvisaker et al., 2005). Dorsal prefrontal lesions have been linked to problems regarding theory of mind deficits, reduced initiation, apathy, lack of drive, loss of interest, lethargy, slowness, inattentiveness, reduced spontaneity, unconcern, lack of emotional reactivity, dullness, poor grooming and perseveration (Ylvisaker et al., 2005). Multiple studies showed that MS pathology is multifaceted, with cortical, deep grey matter and white matter structures being significantly impacted (Deluca et al., 2015; Calabrese et al., 2013; Pirko et al., 2007; Popescu & Lucchinetti, 2012). Lesions are present in the gray matter, including the cortex, the basal ganglia, brain stem and the gray matter of the spinal cord. Neurodegeneration affects the brain and spinal cord in a global sense, resulting in a diffuse neurodegeneration in the entire gray matter (Lassmann, 2018). Although white matter lesions are found in all white matter structures, some studies suggest that white matter lesions show a propensity for frontal and parietal regions (Sperling et al., 2001), with also demyelination of the temporal and frontal cortices (Calabrese et al., 2013). It is overall assumed that the before mentioned regions play an important role in EF, although also other neural networks such as different posterior cortical areas and (the connectivity with) subcortical regions are important (Snyder, 2013).

A few studies addressed the topic of self-awareness of executive deficits and dysexecutive behavioral problems in PwMS (Chiaravalloti & DeLuca, 2003; Smith & Arnett, 2010; van der Hiele et al., 2012). These studies found that self-reported data of executive functioning in PwMS are generally reliable, but did not specify what kind of executive behavioral problems were reported by PwMS (Chiaravalloti & DeLuca, 2003; Smith & Arnett, 2010; van der Hiele et al., 2012). A study by Hanssen et al. (2014) used a reliable and valid self-report measure for self-reported behavioral problems (BRIEF-A), but merely focused on predictors and did not report the prevalence and types of behavioral problems. Regarding predictors for self-reported executive problems, they found that depression was the strongest predictor of self-reported behavioral complaints that indicate executive deficits. Other studies showed that clinically significant depression in PwMS results in more impaired executive functioning (Arnett et al., 1997, 2001) and more overreporting of executive dysfunction (Carone et al., 2005; Hanssen et al., 2014). Considering the fact that half of the PwMS is diagnosed with a depressive disorder somewhere during the course of their lifetime (Feinstein, 2011), depression seems to be an important confounder when studying EF. Apart from depression, physical and cognitive fatigue is one of the most common symptoms of MS, with a negative impact on general functioning and quality of life (Asano & Finlayson, 2014). Fatigue might affect cognitive performance and EF negatively (Chiaravalloti & DeLuca, 2008; Krupp & Elkins, 2000), making fatigue also an important confounder when studying EF.

The lack of knowledge regarding the prevalence of behavioral problems in PwMS is striking, especially because of the detrimental consequences for functional capacities and the quality of life in PwMS (Amato et al., 2019; Chiaravalloti & DeLuca, 2008; Cutajar et al., 2000). This, together with the young age of disease onset, underlines the importance of understanding cognitive deficits in general and more specific behavioral problems in PwMS.The aim of the present study is therefore 1) to examine whether PwMS report more often behavioral problems compared to another patient group diagnosed with a non CNS-involved chronic disease (e.g. PwRA), 2) to investigate whether informants report the same behavioral problems as PwMS or whether they differ, and 3) to explore potential psychological determinants of behavioral problems in PwMS. We want to include PwRA because of overlapping clinical features with MS, such as problems with (fine) motor skills and relapses, but with different underlying pathology (no CNS involvement but an auto-immune disease). By using PwRA as a control group, it is possible to control for nonspecific effects of having a chronic disease on possible behavioral problems. We expect that PwMS and their informants report more behavioral problems when compared to the RA group because of the lack of significant CNS involvement in the RA group. This study is the first step towards understanding a clinically significant problem, providing a foundation for future work to identify which aspects of behavioral problems may be specifically associated with MS. With a better understanding of behavioral problems in PwMS, rehabilitation programs can be more accurately developed and/or adjusted, quality of life can be improved, as well as overall social and employment status.

Materials and method

Participants

PwMS were invited for study participation during clinical visits at the department of medical psychology or the outpatient department of neurology of the Canisius Wilhelmina Hospital. After informed consent, PwMS were asked to fill out five self-report questionnaires. Furthermore, with the permission of the participant, an adult informant who is familiar with the rated individual’s everyday functioning (e.g. a spouse, a close family member or close friend) was asked to fill out two questionnaires. PwMS met inclusion criteria when they were diagnosed with MS according to the revised McDonald criteria (Thompson et al., 2018). PwMS were excluded if they had an exacerbation of MS four weeks prior to taking part in the study, if they had a psychiatric and/or personality disorder that preceded the onset of MS, had a history of substance abuse or any neurological disease besides MS. PwMS who had other long term health conditions like cardiac, pulmonary of musculo-skeletal problems, were not excluded.

To control for nonspecific effects of a chronic disease, a control group of 30 people from the outpatient rheumatology clinic of the Sint Maartenskliniek, Nijmegen, the Netherlands, was included for comparison. PwRA were informed about the study by a mailing from their treating rheumatologist, which they could respond to if they were willing to participate. After informed consent, PwRA were asked to fill out five self-report questionnaires. Furthermore, with the permission of the RA participant, an adult informant who is familiar with the rated individual’s everyday functioning (e.g. a spouse, a close family member or close friend) was asked to fill out two questionnaires. The questionnaires could be returned using a stamped envelope. Participants in the control group were all clinically diagnosed with RA according to either 2010 ACR RA (Kay & Upchurch, 2012) and/or clinical diagnosis of the treating rheumatologist (fulfilled at any time point between the start of the disease and inclusion). Controls were excluded if they had an exacerbation of RA four weeks prior before taking part in the study, if they had a psychiatric and/or personality disorder that preceded the onset of RA, had a history of substance abuse or an neurological disease. PwRA who had other long term health conditions like cardiac, pulmonary of musculo-skeletal problems, were not excluded.

Material

Questionnaires

Dysexecutive behavioral problems

To assess self-reported dysexecutive behavioral problems, levels of anxiety, depression, fatigue and illness cognitions, five questionnaires were used in both MS and RA group. In both informant groups, only two questionnaires were used. The following self-reported dysexecutive behavioral problems were assessed: agitation, euphoria, apathy, disinhibition, irritability and repetitive behavior using the Dutch version of the Neuropsychiatric Inventory Questionnaire (NPI-Q), and inhibition, cognitive flexibility and emotion regulation using the Dutch version of the Behavior Rating Inventory of Executive Function-Adult Version (BRIEF-A). The NPI-Q is a caregiver-based rating scale of established validity and reliability. It assesses 12 neuropsychiatric domains, including delusions, hallucinations, agitation, anxiety, euphoria, apathy, disinhibition, irritability, and aberrant motor activity such as pacing and stereotyped behaviors. NPI-Q scores are based on behaviors present in the past month (Kaufer et al., 2000). The minimum score is 0, the maximum is 36. The BRIEF-A consists of a patient questionnaire and an informant-questionnaire. A total of 75 questions have to be answered, resulting in nine subscales: Inhibition, Self-Monitoring, Planning/Organizing, Cognitive flexibility, Initiating, Task Monitoring, Emotional Regulation, Working Memory, and Organization of Materials.

Depression and anxiety

The Dutch version of the Hospital Anxiety and Depression Scale (HADS) was used to measure depressive and anxiety symptoms. The HADS is a 14-item self-report screening scale that was originally developed to screen for the possible presence of anxiety and depressive states in the setting of a medical outpatient clinic (Zigmond & Snaith, 1983). It contains two 7-item scales: one for anxiety and one for depression, both with a score range of 0–21. The total score of the combined subscales can be classified in the following four categories: 0–7 (minimal symptoms), 8–10 (possible depression and/or anxiety disorder), 11-21 (presumably depression and/or anxiety disorder.

Illness cognitions

The Illness Cognition Questionnaire (ICQ) for Chronic Diseases (Evers et al., 2001) was used to assess illness cognitions. The ICQ consists of three subscales. The Acceptance subscale was used in this study, to assess patients’ recognition of the need to adapt to the chronic illness and the ability to tolerate the unpredictable and uncontrollable nature of the disease. The Helplessness subscale was used as a way of emphasizing the aversive meaning of a chronic disease. The Perceived Benefits subscale was used as a way of adding a positive meaning to the disease. For all subscales, the scores can range from 6 to 24, with higher scores reflecting, respectively, more acceptance, more helplessness and more perceived disease benefits. There are no cutoff points available. In a study by Lauwerier et al. (2010), it is advised to use the upper quartile cutoff scores of the illness cognitions for screening and diagnostic purposes, resulting in cutoff scores of ≥14 (helplessness), ≤19 (acceptance) and ≤15 (perceived benefits) (Lauwerier et al., 2010).

Fatigue

The Checklist Individual Strength (CIS) was used to assess fatigue. The CIS is a 20-item self-report scale on a 7-point Likert scale. It is divided into four subscales: subjective fatigue, concentration, motivation, and physical activity. A total score of ≥76 indicates severe and abnormal fatigue (Vercoulen et al., 1994).

Cognitive functioning

We analyzed cognitive functioning by multiple neuropsychological tests. Because of readability purposes and to overcome a multiple testing problem and a heightened Type I error rate, we did not use measures of cognitive functioning in the current manuscript.

Neurological assessment

All PwMS underwent—as care as usual—a neurological examination. The neurological impairment, the disability, and the independence of the PwMS were measured by an Expanded Disability Status Scale (EDSS). The scale has a score range from 0.0 to 10.0 in 0.5-unit increment, with 0.0 meaning a normal neurological exam and 10.0 meaning death due to MS (Kurtzke, 1983). The EDSS score was used to quantify disability in MS.

Statistical analyses

Descriptives were computed. T-tests were used to evaluate differences in demographic and clinical characteristics. To compute the frequencies of self-reported behavioral problems, BRIEF-A scores were firstly transformed into categorical variables in which a z-score of −1,5 or lower (in comparison with normative data) was defined as a behavioral problem. Because answers on the NPI-Q were already categorical (e.g. ‘yes’ or ‘no’), scores on the NPI-Q were not transformed. A ‘yes’ answer on one or more items was defined as a behavioural problem. Chi square tests were used to examine differences between PwMS/PwRA and both informantgroups on BRIEF-A scores and NPI-Q scores. Pearson correlations were calculated to investigate the relationship between demographic and clinical characteristics and self-reported behavioral problems (reported on the BRIEF-A and NPI-Q). We used both univariate and multiple logistic and linear regression analyses to examine the association between dependent (behavioural problems on BRIEF-A and NPI-Q) and independent variables (anxiety, depression, fatigue and different covariables: age, sex and level of education). To investigate whether differences on NPI-Q subscales were related to psychological factors within the group of MS participants (e.g. scores on CIS, HADS and ICQ), a multiple logistic regression analyses was used. In all analyses, we controlled for different covariables (age, sex and level of education). For all further analyses, multicollinearity testing showed tolerance and VIF values within the normal range. The SPSS version 25 was used to analyse the data. The level of significance was set at 5%.

Results

Demographic data

Table 1 displays the demographic and clinical characteristics of the MS and RA group. Both groups did not differ significantly according to gender (p = .27). PwMS were significantly younger (p < .001), higher educated (p = .00) and had a shorter disease duration (p <.05) compared to PwRA.

Table 1. Descriptive statistics of the sample (MS N = 45; RA N = 30).

	MS (Mean, SD)	RA (Mean, SD)	t
Age (years)	49.3 ± 10.5	62.5 ± 10.9	−5.3*
Male (%)	24.4	36.7	1.1
Education	5.7 ± 0.9	5.0 ± 1.0	3.4*
Disease course
% RR	53.3
% SP	22.2
% PP	24.4
EDSSa	3.2 ± 1.3
Disease duration (years)	9.2 ± 9.0	16.6 ± 10.9	−3.2*

^a Expanded Disability Status Scale (higher score represents more physical impairment).

*p <.05.

Frequency of behavioral problems reported by PwMS and informants

Table 2 shows the behavioral problems reported by PwMS group and MS informants. Irritability, emotion regulation problems and problems with cognitive flexibility were reported frequently by PwMS, i.e. 53%, 47% and 36%, respectively.

Table 2. Frequency (%) and total number (N) of self-reported behavioral problems on BRIEF-A and NPI-Q in PwMS and informants (N = 45) and PwRA and informants (N = 30).

	MS (%, N)	Informants MS(%, N)	RA (%, N)	Informants RA (%, N)	PwMS vs. PwRA X^2(p)	MS informants vs. RA informants X^2(p)
BRIEF-A
Inhibition	13.3 (6)	22.2 (10)	26.7 (8)	16.7 (5)	2.0 (ns)	0.1 (ns)
Cognitive Flexibility	35.6 (16)	26.7 (12)	16.7 (5)	20 (6)	3.4 (ns)	0.1 (ns)
Emotion Regulation	46.7 (21)	35.6 (16)	33.3 (10)	16.7 (5)	1.5 (ns)	2.4 (ns)
NPI-Q
Agitation	20 (9)	11.1 (5)	6.7 (2)	6.7 (2)	3.2 (ns)	0.6 (ns)
Euphoria	11.1 (5)	6.7 (3)	13.3 (4)	10 (3)	0.0 (ns)	0.1 (ns)
Apathy	26.7 (12)	17.8 (8)	6.7 (2)	20 (6)	5.7 (.02)	0.1 (ns)
Disinhibition	13.3 (6)	6.7 (3)	10 (3)	10 (3)	0.5 (ns)	0.1 (ns)
Irritability	53.3 (24)	37.8 (17)	23.3 (7)	33.3 (10)	5.6 (.02)	0.0 (ns)
Repetitive Behavior	11.1 (5)	2.2 (1)	0 (0)	6.7 (2)	4.3 (.04)	0.3 (ns)

Significantly more PwMS reported apathy (X² = 5.7, p = .02), irritability (X² = 5.6, p = .02) and aimless repetitive behavior (X² = 4.3, p = 0.04) compared to the RA group. Especially irritability was reported frequently, i.e. in 53% of the cases. No other significant differences between MS and RA group were found. No significant differences were found between both informant groups on all subscales of the NPI-Q and BRIEF-A.

Differences in depression, anxiety, illness cognitions, and fatigue between PwMS and PwRA

The mean levels of distress, fatigue and differences in coping in MS and RA group are presented in Table 3. PwMS reported higher levels of feelings of helplessness with regard to their chronic disease when compared to PwRA, adjusted for age, level of education and disease duration (β = −3.9; t (68) = −2.476; p = .02). Levels of disease acceptance and disease benefits were not significantly different between the two groups, as was the level of psychological distress (e.g. levels of depression and anxiety). In both groups, levels of anxiety and depression did not exceed the clinical cutoff-point ≥8, which indicates that both groups reported low levels of depression and anxiety.

Table 3. Mean fatigue (CIS), depression and anxiety (HADS) and illness perceptions (ICQ) in people with MS and RA, adjusted for age, level of education and disease duration.

	MS (Mean, SD, N above cut-off)	RA (Mean, SD, N above cut-off)	β (SD)	p
CIS^a
Total	83.1 ± 22.0 (29)	65.3 ± 24.9 (8)	−18.0 (-0.4)	.01
Subjective Feeling	39.0 ± 10.5	33.6 ± 13.4	−3.7 (3.4)	.28
Concentration	18.7 ± 8.7	16.8 ± 23.0	−1.6 (4.8)	.74
Motivation	13.6 ± 5.6	10.7 ± 5.9	−3.8 (1.7)	.03
Activity	11.6 ± 4.7	8.0 ± 4.5	−4.8 (1.4)	<0.001
HADSb
Total	11.0 ± 6.1 (20)	9.7 ± 7.5 (10)	−0.6 (1.9)	.76
Depression	4.9 ± 3.0 (6)	4.6 ± 3.8 (5)	0.2 (1.0)	.81
Anxiety	6.1 ± 3.7 (13)	5.1 ± 4.4 (8)	−0.8 (1.1)	.48
ICQc
Helplessness	13.9 ± 6.1 (21)	11.5 ± 6.1 (10)	−3.9 (1.6)	.02
Acceptance	15.3 ± 4.3 (38)	17.5 ± 4.1 (18)	1.5 (1.2)	.19
Disease Benefits	14.8 ± 4.4 (24)	14.0 ± 4.4 (150)	−1.5 (1.2)	.20

^a Checklist Individual Strength (higher score represents more fatigue; Total cutoff score: ≥76 indicates severe and abnormal fatigue).

^b Hospital Anxiety and Depression Scale (higher score represents more anxiety/depression; Total cutoff score: ≥12, Subscale cutoff score: ≥8).

^c Illness Cognition Questionnaire (higher scores on subscales acceptance and disease benefits represents more acceptance and experiencing disease benefits, higher scores on helplessness indicates higher levels of helplessness; Helplessness cutoff score: ≥14, Acceptance cutoff score: ≤19, Disease Benefits cutoff score: ≤15.).

PwMS also reported significantly higher levels of fatigue when compared to PwRA, adjusted for age, level of education and disease duration (β = −18.0; t (67) = −2.675; p = .01). They reported especially more motivational problems for undertaking activities and a reduced level of activity due to fatigue.

Behavioral problems and the relationship with psychological variables in PwMS

To investigate whether Apathy, Irritability and Repetitive Behavior are related to psychological factors in PwMS, a multi variable logistic regression analysis was conducted, adjusted for age, level of education, disease duration. Results are presented in Table 4.

Table 4. Potential determinants of apathy, irritability and repetitive behavior in people with MS, adjusted for age, level of education and disease duration.

	Apathy		Irritability		Repetitive Behavior
	β (SD)	p	β (SD)	p	β (SD)	p
CIS
Subjective Feeling	0.0 (0.0)	.34	0.0 (0.0)	.23	0.1 (0.1)	.26
Concentration	0.0 (0.1)	.71	0.0 (0.0)	.56	0.1 (0.1)	.18
Activity	−0.1 (0.1)	.54	0.0 (0.1)	.91	−0.4 (0.2)	.07
Motivation	0.1 (0.1)	.31	0.0 (0.1)	.67	0.1 (0.1)	.33
HADS
Anxiety	0.1 (0.1)	.68	0.1 (0.1)	.32	−0.0 (0.2)	.91
Depression	0.3 (0.2)	.05	0.3 (0.2)	.10	0.3 (0.1)	.14
ICQ
Helplessness	−0.0 (0.1)	.82	0.2 (0.1)	.04	0.0 (0.1)	.76
Acceptance	−0.2 (0.1)	.05	−0.4 (0.1)	.01	−0.5 (0.2)	.04
Disease Benefits	−0.0 (0.1)	.88	0.3 (0.1)	.03	0.3 (0.2)	.13

Depressive symptoms and the level of acceptance were significantly related to apathy in the MS group. More specifically, more depressive symptoms and lower levels of acceptance were related to higher levels of apathy. Furthermore, more helplessness, less disease acceptance and more disease benefits were significantly related to irritability. Less disease acceptance was significantly related to repetitive behavior.

Discussion

To our knowledge, this is one of the first explorative studies to investigate if self-reported behavioral problems occur more frequently in PwMS compared to a group of people with a non-CNS-involved chronic disease (rheumatoid arthritis) and to explore potential psychological determinants of behavioral problems. We found that on the NPI-Q, the MS group indeed reported significantly more apathy, irritability and aimless repetitive behavior when compared to the RA group, despite the fact that the RA group had longer disease duration and were older than the MS group. Irritability (i.e. in 53%), emotion regulation problems (43%) and decreased cognitive flexibility (35%), were frequently reported. The MS group, furthermore, tended to report more fatigue and higher levels of feelings of helplessness compared to the RA group. The MS group did not significantly differ from the RA group regarding depressive symptoms and anxiety, where overall anxiety and depression scores were low and did not exceed clinical thresholds. Nor did both groups differ in coping strategies or illness perceptions. Surprisingly, informants of the MS group did not report more behavioral problems than informants of the RA group, but still reported irritability and emotion regulation problems in quite a large proportion of the MS group (i.e. 38% and 37%, respectively). The behavioral problems we report on in this study may however be subtle.

Of note, in contrast to what we expected, both participants and informants reported no significant behavioral problems on the BRIEF-A. A possible explanation for this finding could be that both questionnaires investigate different aspects of behavioral functioning. The BRIEF-A mainly focusses on measuring different aspects of executive functions in everyday activities and focusses less on concrete behavior like aimless repetitive behavior and irritability.

Within the MS group, there were some significant psychological predictors for self-reported behavioral problems. The relationship between apathy and depression is extensively reported before (Steffens et al., 2022; Groeneweg-Koolhoven et al., 2017), and—as was expected—we found that higher levels of depressive symptoms were related to higher levels of self-reported apathy. Also, lower levels of acceptance were related to higher levels of self-reported apathy, which shows that it is important to have a broad diagnostic view when investigating behavioral problems as well as other neuropsychological problems within PwMS. Higher levels of irritability were related to less adequate coping, i.e. more helplessness and less acceptance.

While the present explorative study shows a significant relationship between some psychological variables and self-reported behavioral problems, the results also show that these psychological variables cannot fully explain all self-reported behavioral problems. By using another participant group without CNS-involvement instead of a healthy control group, it is possible to distinguish chronic disease-related behavioral changes and more CNS determined behavioral changes. Due to the fact that neither psychological variables nor differences between groups could fully explain differences in self-reported behavioral problems, it might be possible that other disease specific factors are responsible for the self-reported behavioral problems in the MS group. One hypothesis may be that executive dysfunction, due to a specific pattern of lesion distribution within the brain, might account for differences in self-reported behavioral problems. Mainly lesions in the frontal and parietal lobes are linked to executive functions and dysexecutive behavioral problems. Lesions in these regions are regularly found in PwMS (Calabrese et al., 2013; Pirko et al., 2007; Popescu & Lucchinetti, 2012), which could lead to executive dysfunction in which executive behavioral problems such as apathy, irritability and aimless repetitive behavior can occur.

Previous research showed that executive self-report questionnaires are a reliable and valid instrument in PwMS (Smith & Arnett, 2010; van der Hiele et al., 2012). However, it was notable that the MS group and MS proxies reported different amounts of behavioral problems, with the MS participants tending to report more behavioral problems. It could be that due to the often subtle behavioral changes and executive dysfunction in the early stages of the disease, PwMS experience more behavioral problems than informants can observe in the daily activities of PwMS. Informants may therefore underreport behavioral problems in PwMS. Furthermore, research has shown that depression can increase the subjective nature of self-reported executive problems, in which people with both MS and depression reporting more often subjective executive complaints (Cerezo García et al., 2015). In this study, however, the overall score on the HADS depression scale is low and showed no indication for possible depressive symptoms within the study population. Furthermore, analysis showed that depression was only significantly related to self-reported apathy. Therefore, a bias in the data where self-reported executive behavioral problems can fully be explained by depressive symptoms, is not a plausible hypothesis for the difference between self and informant reported behavioral problems.

Despite its strengths, such as the use of multiple questionnaires and a patient and a control group, this study also has some limitations. Although 45 MS participants and 30 RA participants were included, a larger sample size would strengthen the current results. Furthermore, the RA group was significantly older, was less educated and had a shorter disease duration. Despite the fact that analyses showed that there was no significant effect of age, level of education and disease duration on self-reported behavioral problems, for further studies, it is advised to use a matched control group. In addition, we did not control for disease severity nor limitation of activity. This is also a limitation of the current study. To better control for the heterogeneous nature of both MS and RA, we would also advise to better match for disease severity by using, for instance, a measure of limitation of activity or a specific measure for disease severity in itself. Furthermore, the use of the NPI-Q has some disadvantages, such as the lack of normative data, which makes it impossible to compare scores with the general population. Furthermore, the dichotomous nature of the NPI-Q (e.g. answers are ‘yes’ or ‘no’) leaves little room for more varied answer options. Lastly, we would like to note that—although we suspect a relationship between cognitive functioning and behavioral problems—we did not use cognitive functioning in our analysis in order to overcome a multiple testing problem and a heightened Type I error rate.The results of this explorative study show that in clinical practice, it is important to evaluate behavioral problems like apathy, irritability and repetitive behavior in PwMS. Furthermore, it is important to evaluate these problems from a broad biopsychosocial viewing point, where apart from cognitive disorders, fatigue and psychological well-being (e.g. depression and anxiety) and coping strategies (levels of acceptance, feelings of helplessness) are taken into account as possible and treatable contributing factors. Due to possible differences in disease characteristics within specific subtypes of MS, such as level of physical and cognitive impairment and lesion distribution within the brain, it is interesting to know whether psychological factors and more disease specific factors and cognitive functioning contribute differently to behavioral problems for each of the MS subtypes. If so, this could have further clinical implications for diagnosis and treatment.

To the best of our knowledge, there is no literature available on treating behavioral problems in PwMS. However, in PwTBI, there is an overall consensus to use Cognitive Behavioral Therapy (CBT) to improve behavioral problems such as irritability (Wiart et al., 2016). The highly structured nature of CBT, together with concrete objectives and the focus on the ‘here and now’, makes it a very appropriate treatment option for PwTBI (PwTBI). In PwTBI whose behavioral problems are more severe, one might consider an interpersonal and adaptive approach in which the patients close circle and environment is adjusted to eliminate possible triggers for the behavioral disturbances (Wiart et al., 2016). Based on our current findings, in which we advocate for the use of a broad biopsychosocial viewing point, we would advise the same treatment approach in PwMS as in PwTBI.

Conclusion

This explorative study shows a specific pattern of self-reported behavioral problems in PwMS regarding apathy, irritability and repetitive behavior. These results cannot solely be explained by psychological factors (e.g. depression, anxiety, acceptance), nor fatigue or differences in patient characteristics between both patient groups, but may be related to disease specific executive problems. This is one of the first steps towards understanding a clinically significant problem and providing a basis for future work to identify which aspects of behavioral problems may be specifically associated with MS. With a better understanding of behavioral problems in PwMS, rehabilitation programs can be more accurately developed and/or adjusted, quality of life can be improved, as well as overall social and employment status.

Acknowledgements

We are grateful to the neurology department of the Canisius Wilhelmina Hospital and the Sint Maartenskliniek for their help in recruitment. Furthermore, we want to thank all participants for their voluntary contribution in the current study.

Disclosure statement

The authors declare no financial or other conflict of interests.

Availability of data

The data that support the findings of this study are available from the corresponding author [I. Kooi, MSc), upon reasonable request.

Additional information

Notes on contributors

Inga Kooi

Inga Kooi is a clinical neuropsychologist at the department of medical psychology at Canisius Wilhelmina Hospital. Research of interest: neuropsychology, multiple sclerosis.

Sofie Geurts

Sofie Geurts is a clinical neuropsychologist at the department of medical psychology at Canisius Wilhelmina Hospital. Research of interest: neuropsychology, multiple sclerosis.

Gert van Dijk

Gert van Dijk is a neurologist at the neurology department of Canisius Wilhelmina Hospital. His expertise lies within the field of multiple sclerosis.

Johanna E. Vriezekolk

Johanna E. Vriezekolk, PhD, is a researcher and psychologist at the department of Research and Innovation of the Sint Maartenskliniek. Research interest: to study the impact of psychosocial and behavioral factors on the course of the disease, treatment outcomes and well-being of people with a chronic (pain) condition.

Iris van Oostrom

Iris van Oostrom, PhD, is a clinical neuropsychologist at neurocare clinics. Research of interest: As a senior researcher, she conducts research on the effects of stress-related disorders and their treatment on the brain and on cognitive and behavioral functioning.