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Psychological processes associated with insomnia in patients with multiple sclerosis

Psychological processes associated with insomnia in patients with multiple sclerosis Abstract Study Objectives Despite the high comorbidity of insomnia disorder (ID) with multiple sclerosis (MS), the relevance of psychological processes involved in the maintenance of insomnia is yet to be established in this neurological disorder. This study aimed to ascertain to what extent the suggested emotional, cognitive, and behavioral processes maintaining insomnia are relevant in people with insomnia and MS. Methods A between-subjects design was used to compare 26 patients with insomnia and MS, with 31 patients with MS only, and with 26 matched neurological disease-free individuals with insomnia. All patients participated in a standardized clinical interview and completed a battery of self-reported measures of cognitive and somatic presleep arousal experienced at bedtime, sleep- or insomnia-related unhelpful beliefs, and sleep-related safety behaviors. All patients with MS underwent a neurological examination. Results ID comorbid to MS was strongly associated with increased levels of cognitive and somatic arousal, higher endorsement of dysfunctional beliefs about the consequences of insomnia on daytime functioning, and worry about insomnia and more frequent engagement in sleep-related safety behaviors. Patients with MS with ID did not differ from neurological disease-free individuals with insomnia on these measures. No link was found between MS clinical peculiarities and ID diagnosis. Conclusions ID comorbid to MS is associated with the classical psychological factors perpetuating ID in neurological disease-free individuals with insomnia. Primary care providers and neurologists should consider target-oriented therapies like cognitive behavioral therapy for chronic insomnia as a treatment approach for ID comorbid to MS. insomnia, multiple sclerosis, emotion, cognition Statement of Significance Insomnia is the most common sleep disorder among adults affected by multiple sclerosis and is associated with a wide range of negative outcomes. In neurological disease-free individuals with insomnia, emotional, cognitive, and behavioral processes play a central role in the maintenance and treatment of insomnia. Originally, we clearly documented the high relevance of these psychological processes in the specific context of insomnia comorbid to multiple sclerosis. Considering insomnia symptoms to be secondary to medical disorder could lead to reluctance to expend resources to treat insomnia or denial of treatment for insomnia symptoms. Providers should consider target-oriented therapies like cognitive behavioral therapy for insomnia as a treatment approach for insomnia comorbid to multiple sclerosis. Introduction According to the International Classification of Sleep Disorders, 3rd ed. (ICSD-3) and the Diagnostic and Statistical Manual of Mental Disorders, 5th ed. (DSM-5), insomnia disorder (ID) is characterized by dissatisfaction with sleep quantity or quality related to one or more of the following symptoms: difficulty initiating sleep, difficulty maintaining sleep, and early-morning awakening. This dissatisfaction is accompanied by significant distress and/or impairment in daytime functioning [1, 2]. Symptoms should be present at least three nights per week for a minimum of three consecutive months. When these standardized criteria are used, it is estimated that 22%–25% of patients with multiple sclerosis (MS) meet the criteria for ID [3, 4]. This rate is two to three times as high as in the general population which indubitably makes ID one of the most prevalent sleep disorders in MS [5]. Despite its high prevalence, insomnia surprisingly remains underdiagnosed and, therefore, undertreated in MS [6]. Knowledge of factors associated with occurrence of ID in MS may provide clues for an increased understanding of underlying pathophysiology and contribute to developing targeted therapeutic interventions. However, this issue is hitherto poorly addressed in the literature. In fact, to the best of our knowledge, only one study has assessed factors associated with ID in MS [4]. Similar to the general population, female gender, medical comorbidities, anxiety, and fatigue were identified as independent factors for ID in MS outpatients. Over the last decades, there has been a range of theoretical advances in understanding insomnia [7–10], which have recognized the importance of emotional, behavioral, and cognitive processes. In this regard, the cognitive model of insomnia developed by Harvey has emphasized the central role played by arousal and distress arising from excessive negatively toned cognitive activity, both exacerbated by dysfunctional beliefs and attitudes about sleep and sleep-related safety behaviors, in the development and maintenance of chronic ID [10]. The cognitive approach to insomnia has provided researchers and clinicians with a framework for understanding and treating insomnia. In this respect, it is largely acknowledged that cognitive behavioral therapy for insomnia (CBT-I) is an effective treatment with long-term benefits and few side effects [11]. To the best of our knowledge, no study has examined the psychological processes involved in the maintenance of insomnia in the specific context of ID comorbid to MS. Consequently, the objective of the current study was to ascertain to what extent the suggested emotional, cognitive, and behavioral processes maintaining insomnia are relevant in insomniac people with MS. We more specifically hypothesized that ID comorbid to MS is associated with (1) increased levels of cognitive and somatic arousal; (2) higher endorsement of dysfunctional beliefs about the consequences of insomnia on daytime functioning and worry about insomnia; and (3) more frequent engagement in sleep-related safety behaviors. Methods Participants Eighty-three individuals participated in the study, with 57 consecutive outpatients with MS diagnosis according to the 2010 revision of the McDonald criteria for a minimum of 6 months. The Expanded Disability Status Scale (EDSS) was used to quantify disability in MS [12]. Among the MS group, 26 patients had ID as per to the ICSD-3 and DSM-5 diagnosis criteria (MS-ID) [1, 2], and 31 patients did not meet the diagnostic criteria for ID (MS-NID). Each patient with MS-ID was matched by gender and age (±1 year) to one neurological disease-free individual with ID diagnosis (NMS-ID). For all participants, the eligibility criteria included an age of 18 years or older and speaking French. Participants also had to be willing to voluntarily participate in the study, and no compensation was provided. Exclusion criteria for all participants were as follows: a history of schizophrenia spectrum or other psychotic disorder, bipolar-related disorder, substance-related and addictive disorder, and neurological disease other than MS for patient’s group including cerebrovascular disease and traumatic brain injury, active and unstable physical illness (e.g. cancer and renal failure). Also excluded were shift workers, pregnant women or breast-feeding mothers, parents with a baby less than 12 months. Note that all participants were screened for the two major diseases related to insomnia in adults, i.e. sleep apnea and the restless legs syndrome/Willis–Ekbom disease (RLS/WED). Sleep apnea was screened by using the Berlin Questionnaire [13] and RLS/WED was assessed based on the International Restless Legs Syndrome Study Group criteria [14]. Rapid eye movement sleep behavior disorder Single-Question Screen (RBD1Q) was applied to screen probable RBQ [15]. Participants with current anxiety and mood disorders were not excluded. Current psychotropic medication was not considered as exclusion criteria but was thoroughly recorded. Clinical interview The face-to-face clinical interview was conducted by trained licensed psychologists with expertise in sleep field. During clinical interview, we assessed insomnia, sleep history, medical and psychological states, psychotropic medication, and sociodemographic characteristics. Current insomnia, mood, and anxiety disorders were diagnosed as per to the DSM-5 criteria, using a local translation of the clinical version of the structured interview for DSM-5 (SCID-5-CV). The diagnosis of ID was established with a clinical interview covering items included in DSM-5 criteria for ID. Participants were diagnosed with ID [1, 2] when they reported (1) subjective difficulty in initiating and/or maintaining sleep and/or early morning awakening despite having adequate opportunity to sleep, (2) accompanied by significant distress and/or impairment in daytime functioning, and (3) for at least 3 months and at least 3 nights a week on the SCID-5-CV. Levels of depressive and anxious symptoms were respectively assessed by the Beck Depression Inventory (BDI-II) [16] and the Spielberger Trait Anxiety Inventory (STAI-trait) [17]. Questionnaires Insomnia Severity Index The Insomnia Severity Index (ISI) was used to evaluate insomnia complaint severity [18]. This 8-item self-rated questionnaire assesses the severity of sleep onset insomnia, sleep maintaining insomnia and early awakening insomnia, satisfaction with the current sleep patterns, interference with daytime functioning, noticeability of impairment to significant others, and level of distress caused by the sleep problem. Brief version of the dysfunctional beliefs and attitudes about sleep The DBAS-16 was used to assess various sleep- or insomnia-related cognitions (e.g. beliefs, attitudes, expectations, appraisals, and attributions), with higher scores indicating a stronger endorsement of dysfunctional beliefs [19]. The DBAS-16 is a 16-item self-reported questionnaire encompassing four subscales computed separately as follows: (1) attributions of the causes and appraisals of the consequences of insomnia (consequences), (2) issues of worry and helplessness about insomnia (worry/helplessness), (3) expectations about sleep requirements (expectations), and (4) sleep medication and biological attribution of insomnia (medication). Sleep-Related Behaviors Questionnaire The Sleep-Related behaviors Questionnaire (SRBQ) is a 32-item self-reported questionnaire reflecting behavioral strategies used to cope with insomnia during the day and at night [20]. For example, the items include as follows: “I try to keep all disturbing thoughts and images out of my mind while in bed”; “I avoid talking about my sleep”; “I look at the clock upon waking to calculate how many hours of sleep I got”; “I plan to get an early night.” The higher total score indicates higher engagement in unhelpful behavioral strategies to cope with insomnia. Presleep Arousal Scale The Presleep Arousal Scale (PSAS) contains 16 items referring to symptoms of cognitive (e.g. racing mind and worry about falling asleep) and somatic (e.g. muscle tension and heart racing) presleep arousal experienced at bedtime [21]. Two subscale scores were computed separately, i.e. cognitive arousal and somatic arousal. In taking the PSAS, participants were asked to describe how intensely they generally experienced each symptom as they attempted to fall asleep in their own bedroom. High scores for these scales are indicative of a higher intensity of the construct. Only patients with MS completed the Fatigue Impact Scale for multiple sclerosis (EMIF-SEP) to assess the severity of self-reported fatigue [22]. This self-administered questionnaire is composed of 40 items organized into four dimensions: (1) cognitive, (2) physical, (3) social role, and (4) psychological. Finally, an investigator-designed one question numeric rating scale was used to assess the impact of pain on sleep. Patients who reported pain were asked to indicate the unique number that best described the impact of pain on their sleep in the last 2 weeks on a scale ranging from 0 “sleep is not disturbed” to 10 “sleep is extremely disturbed.” Procedure Individuals from the NMS-ID group belong to a data base of Epsylon Laboratory. They were community-dwelling adults recruited by mean of advertisements, personal contacts, and snowballing techniques from December 2015 to April 2016. Patients with MS were recruited within the University Department of Neurology in Montpellier (France) from December 2015 to August 2016. At the time of the study, all patients with MS underwent a neurological examination. During a single session, all participants individually underwent a face-to-face clinical interview. By the end of the interview, each participant received a questionnaire booklet and was asked to fill it at home. Prepaid envelopes were provided for the return of the documents. The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008. All participants gave their informed consent to participate in the study, which was approved by the local university ethics committee. Statistical analyses All statistical analyses were performed with IBM SPSS software version 24.0. Data were tested for normal distribution and homogeneity of variance using the Kolmogorov–Smirnov test and the Levene test, respectively. One-way between-groups analysis of variance (ANOVA) and Student’s t test were used to assess group differences for continuous variables, and the chi-square test was used for categorical variables. In addition, we calculated the eta squared η2 and the Cohen’s d′ as measures of the effect size. The effect size was considered small (η2 = 0.01; d = 0.2), medium (η2 = 0.06; d = 0.5), or large (η2 = 0.14; d = 0.8) according to Cohen [23]. Given the sample size, 95% confidence of interval (CI) was reported when a statistical tendency was observed between MS-ID and MS MS-NID groups. All analyses were conducted with a significance threshold of α = 0.05, two-tailed. Results MS clinical characteristics Most patients (63.2%) were females, and ages varied between 20 and 67 years (Table 1). More than half (56.1%) were unemployed with handicapped status and 66.7% lived with their spouse or partner. One-third of patients (36.8%) had a relapsing–remitting form of MS and did not take any disease-modifying treatment (38.6%). The mean EDSS score was 4.79 ± 2.28 (all patients had EDSS score < 8). Mean duration of disease was 12.40 ± 10.02 years. In our study, 19.6% (n = 11; MS-ID = 6) of patients suffered from medical comorbidities. These included iatrogenic hypothyroidism controlled by medication (n = 4; MS-ID = 1), hypercholesterolemia (n = 3; MS-ID = 1), hypertension (MS-ID = 1), Crohn’s syndrome (MS-ID = 1), Raynaud’s syndrome (MS-ID = 1), and thalassemia (MS-ID = 1). Table 1. Demographic and clinical characteristics of multiple sclerosis patients with insomnia disorder, without insomnia disorder, and controls with insomnia disorder   MS-ID (n = 26)  MS-NID (n = 31)  NMS-ID (n = 26)  Statistics (ddl)  P-value  Demographic data   Age, y  47.5 ± 12.8  46.2 ± 11.3  47.0 ± 13.0  F(2.80) = 0.07  .94   Sex, female/male, n  19/7  17/14  19/7  χ2(2) = 2.89  .24   Education, y  13.1 ± 2.9  12.9 ± 2.2  14.1 ± 2.7  F(2.80) = 1.78  .18  MS clinical characteristics   Age at onset, y  34.1 ± 13.0  34.6 ± 9.7  —  t(45.4) = 0.16  .87   Duration of disease, y  13.5 ± 10.7  11.5 ± 9.5  —  t(55) = −0.74  .46   MS type      —  χ2(2) = 1.2  .55    Relapsing–Remitting  8  13  —        Primary progressive  9  7  —        Secondary progressive  9  11  —       EDSS  5.3 ± 1.9  4.3 ± 2.4  —  t(52) = −1.75  .09   MS treatment              None  12  10  —        Natalizumab  3  3  —  χ2(8) = 6.06  .64    Rituximab  4  3  —        Cyclophosphamide  1  4  —        Fingolimod  0  3  —        Methylprednisolone  2  1  —        Biotine  1  1  —        Glatiramere acetate  1  1  —        Other  2  4  —       Psychotropic intake (yes)  69.2%  35.5%  15.4%  χ2(2) = 16.12  <.001*   Average impact of pain on sleep  2.8 ± 3.4  0.68 ± 1.8  —  t(36) = −2.83  .008†  Fatigue impact scale dimensions   Cognitive  25.7 ± 6.4  23.6 ± 5.9    t(55) = −1.33  .19   Physical  37.9 ± 6.3  33.1 ± 9.5    t(55) = −2.24  .029†   Social role  33.9 ± 7.4  32.1 ± 8.6    t(55) = −0.85  .39   Psychological  10.5 ± 2.5  9.7 ± 2.5    t(55) = −1.23  .22  Mood and anxiety assessment   Beck depression inventory  19.4 ± 11.4  10.2 ± 9.7  12.4 ± 8.9  F(2.80) = 6.22  .003‡   Curent mood disorder  50.0%  35.5%  19.2%  χ2(2) = 5.42  .07   Spielberger Trait Anxiety inventory  50.2 ± 10.6  40.4 ± 11.8  26.2 ± 6.4  F(2.79) = 36.9  <.001§   Curent anxiety disorder  23.1%  9.7%  30.8%  χ2(2) = 4.02  .13    MS-ID (n = 26)  MS-NID (n = 31)  NMS-ID (n = 26)  Statistics (ddl)  P-value  Demographic data   Age, y  47.5 ± 12.8  46.2 ± 11.3  47.0 ± 13.0  F(2.80) = 0.07  .94   Sex, female/male, n  19/7  17/14  19/7  χ2(2) = 2.89  .24   Education, y  13.1 ± 2.9  12.9 ± 2.2  14.1 ± 2.7  F(2.80) = 1.78  .18  MS clinical characteristics   Age at onset, y  34.1 ± 13.0  34.6 ± 9.7  —  t(45.4) = 0.16  .87   Duration of disease, y  13.5 ± 10.7  11.5 ± 9.5  —  t(55) = −0.74  .46   MS type      —  χ2(2) = 1.2  .55    Relapsing–Remitting  8  13  —        Primary progressive  9  7  —        Secondary progressive  9  11  —       EDSS  5.3 ± 1.9  4.3 ± 2.4  —  t(52) = −1.75  .09   MS treatment              None  12  10  —        Natalizumab  3  3  —  χ2(8) = 6.06  .64    Rituximab  4  3  —        Cyclophosphamide  1  4  —        Fingolimod  0  3  —        Methylprednisolone  2  1  —        Biotine  1  1  —        Glatiramere acetate  1  1  —        Other  2  4  —       Psychotropic intake (yes)  69.2%  35.5%  15.4%  χ2(2) = 16.12  <.001*   Average impact of pain on sleep  2.8 ± 3.4  0.68 ± 1.8  —  t(36) = −2.83  .008†  Fatigue impact scale dimensions   Cognitive  25.7 ± 6.4  23.6 ± 5.9    t(55) = −1.33  .19   Physical  37.9 ± 6.3  33.1 ± 9.5    t(55) = −2.24  .029†   Social role  33.9 ± 7.4  32.1 ± 8.6    t(55) = −0.85  .39   Psychological  10.5 ± 2.5  9.7 ± 2.5    t(55) = −1.23  .22  Mood and anxiety assessment   Beck depression inventory  19.4 ± 11.4  10.2 ± 9.7  12.4 ± 8.9  F(2.80) = 6.22  .003‡   Curent mood disorder  50.0%  35.5%  19.2%  χ2(2) = 5.42  .07   Spielberger Trait Anxiety inventory  50.2 ± 10.6  40.4 ± 11.8  26.2 ± 6.4  F(2.79) = 36.9  <.001§   Curent anxiety disorder  23.1%  9.7%  30.8%  χ2(2) = 4.02  .13  Data are presented as means ± standard deviations. MS refers to multiple sclerosis; ID = insomnia disorder diagnosis; MS-ID = MS patients with ID; MS-NID = MS patients without ID; NMS-ID = neurological disease-free participants with ID; EDSS = Expanded Disability Status Scale. * MS-ID > MS-NID > NMS-ID. † MS-ID > MS-NID. ‡ MS-ID > [MS-NID = NMS-ID]. § MS-ID > MS-NID > NMS-ID. View Large MS-ID and MS-NID group comparisons As illustrated in Table 1, no significant differences were found between MS-ID and MS-NID groups in terms of age (p = .94), sex (p = .24), and years of education (p = .18). Note that the work status was not significantly different between the two groups (χ2 = 34.92, p = .57). In particular, the proportion of unemployed patients with handicapped status did not differ among MS-ID (61.5%) and MS-NID groups (58%). With regard to MS characteristics, age at onset (p = .87), duration of the disease (p = .46), and MS type (p = .46) did not differ between MS-ID and MS-NID groups (Table 1). On average, MS-ID group had a greater level of disability scored on the EDSS than did MS-NID group. This difference was not significant (p = .09, 95% CI [−2.29, 0.16]). With regard to MS characteristics, age at onset (p = .87), duration of the disease (p = .46), MS type (p = .46), and level of disability scored on the EDSS (p = .09, 95% CI [−2.29, 0.16]) did not differ between MS-ID and MS-NID groups. MS-ID group reported a higher level of fatigue on the physical EMIF-SEP dimension (p = .029, d′ = 0.59) and higher pain intensity in a relationship with disturbed sleep than did MS-NID group (p = .008, d′ = 0.78). These effects were medium to large. Finally, 14% of enrolled patients (n = 8) had a BMI score superior to 30, with no significant difference between patients with and without insomnia, respectively, 25.1 ± 5.4 versus 23.8 ± 3.8, t(55) = −1.06, p = .29. MS-ID, MS-NID, and NMS-ID group comparisons Mood and anxiety assessment A significant group effect was observed for both BDI-II and STAI-trait questionnaires (p = .003, η2 = 0.36; p < .001, η2 = 0.69). MS-ID group reported higher level of depressive symptoms compared with MS-NID group (p = .003) and NMS-ID group (p = .040). Both groups of patients with MS had higher levels of anxious symptoms comparatively to NMS-ID group (all p < .001). Nonetheless, MS-ID group reported higher levels of anxiety compared with MS-NID group (p = .001). Insomnia characteristics and sleep disorder screening The proportion of ID subtypes did not differ between MS-ID and NSM-ID groups (p = .55). The majority of participants with ID diagnosis had mixed insomnia (MS-ID = 69% and NMS-ID = 84%). As expected, insomnia complaint assessed by the ISI was significantly higher in MS-ID and NMS-ID groups than in MS-NID group (all p’s < .001). No significant difference was noted between MS-ID and NMS-ID groups on the ISI (p = 1). The proportion of individuals with RLS and probable SAS did not differ between the three groups (respectively, p = .76, p = .68). When considering the sample as a whole, none of participants had probable RBD. Questionnaires of psychological processes related to insomnia Globally, a same pattern of results was observed regarding group comparisons for DBAS-16, SRBQ, and PSAS questionnaires (Table 2). We observed significant group effects for the DBAS-16 consequences and worry/Helplessness subscales (p = .032, η2 = 0.28 and p = .002, η2 = 0.37, respectively). On these subscales, patients with MS-ID had a stronger endorsement of dysfunctional beliefs in comparison with patients with MS-NID (all p’s < .05), with no difference between MS-ID and NMS-ID groups (p = 1). A significant group effect was noted for the SRBQ total score, p = .013, η2 = 0.32. Contrast analyses indicated higher engagement in unhelpful behavioral strategies to cope with insomnia in patients with MS-ID compared with patients with MS-NID (p = .016), without any difference between MS-ID and NMS-ID groups (p = 1). Table 2. Sleep characteristics and psychological processes associated with insomnia disorder   MS-ID (n=26)  MS-NID (n=31)  NMS-ID (n=26)  Statistics (ddl)  P-Value  Sleep disorders screening  Insomnia disorder   Diagnosis of insomnia  100%  0%  100%  χ2(2) = 83  <.001*   Type of insomnia        χ2(3) = 2.27  .52    Sleep-onset insomnia  11.5%  —  8%        Sleep-maintenance insomnia  15.5%  —  8%        Terminal insomnia  4%  —  0%        Mixed insomnia  69%  —  84%       Insomnia duration (months)  70.6 ± 65.5  —  134.3 ± 157  t(50) = −1.91  .065   Frequency of sleep difficulties, days per week  6.2 ± 1.31  —  5.1 ± 1.7  t(50) = 2.75  .008†   Insomnia Severity Index  14.1 ± 6.9  6.0 ± 6.1  13.9 ± 4.9  F(2.80) = 16.9  <.001a  Restless legs syndrome  5  4  5  χ2(2) = 0.56  .76  Obstructive sleep apnea syndrome screening  1  1  2  χ2(2) = 0.77  .68  REM-sleep behavior disorder  0  0  0      Questionnaires of cognitive processes related to insomnia   Dysfunctional beliefs about sleep    Expectations  14.2 ± 5.2  12.9 ± 5.2  12.9 ± 3.9  F(2.80) = 0.57  .567    Medication  15.7 ± 8.1  11.3 ± 8.2  12.0 ± 6.7  F(2.80) = 2.58  .082    Consequences  28.4 ± 10.3  21.0 ± 13.1  26.7 ± 8.8  F(2.80) = 3.58  .032‡    Worry/helplessness  33.9 ± 12.0  23.29 ± 16.3  34.4 ± 14.1  F(2.80) = 6.54  .002§   Sleep-Related Behaviors Questionnaire  47.9 ± 22.6  30.1 ± 6.3  43.9 ± 20.0  F(2.80) = 4.60  .013§    Presleep Arousal Scale  45.9 ± 20.7  27.2 ± 10.2  33.1 ± 16.2  F(2.80) = 11.1  <.001    Somatic arousal  23.3 ± 14.5  13.5 ± 5.4  14.6 ± 5.9  F(2.79) = 8.94  <.001||    Cognitive arousal  22.7 ± 8.2  13.8 ± 7.2  18.1 ± 7.9  F(2.80) = 9.47  <.001‡    MS-ID (n=26)  MS-NID (n=31)  NMS-ID (n=26)  Statistics (ddl)  P-Value  Sleep disorders screening  Insomnia disorder   Diagnosis of insomnia  100%  0%  100%  χ2(2) = 83  <.001*   Type of insomnia        χ2(3) = 2.27  .52    Sleep-onset insomnia  11.5%  —  8%        Sleep-maintenance insomnia  15.5%  —  8%        Terminal insomnia  4%  —  0%        Mixed insomnia  69%  —  84%       Insomnia duration (months)  70.6 ± 65.5  —  134.3 ± 157  t(50) = −1.91  .065   Frequency of sleep difficulties, days per week  6.2 ± 1.31  —  5.1 ± 1.7  t(50) = 2.75  .008†   Insomnia Severity Index  14.1 ± 6.9  6.0 ± 6.1  13.9 ± 4.9  F(2.80) = 16.9  <.001a  Restless legs syndrome  5  4  5  χ2(2) = 0.56  .76  Obstructive sleep apnea syndrome screening  1  1  2  χ2(2) = 0.77  .68  REM-sleep behavior disorder  0  0  0      Questionnaires of cognitive processes related to insomnia   Dysfunctional beliefs about sleep    Expectations  14.2 ± 5.2  12.9 ± 5.2  12.9 ± 3.9  F(2.80) = 0.57  .567    Medication  15.7 ± 8.1  11.3 ± 8.2  12.0 ± 6.7  F(2.80) = 2.58  .082    Consequences  28.4 ± 10.3  21.0 ± 13.1  26.7 ± 8.8  F(2.80) = 3.58  .032‡    Worry/helplessness  33.9 ± 12.0  23.29 ± 16.3  34.4 ± 14.1  F(2.80) = 6.54  .002§   Sleep-Related Behaviors Questionnaire  47.9 ± 22.6  30.1 ± 6.3  43.9 ± 20.0  F(2.80) = 4.60  .013§    Presleep Arousal Scale  45.9 ± 20.7  27.2 ± 10.2  33.1 ± 16.2  F(2.80) = 11.1  <.001    Somatic arousal  23.3 ± 14.5  13.5 ± 5.4  14.6 ± 5.9  F(2.79) = 8.94  <.001||    Cognitive arousal  22.7 ± 8.2  13.8 ± 7.2  18.1 ± 7.9  F(2.80) = 9.47  <.001‡  Data are presented as means ± standard deviations. MS refers to multiple sclerosis; ID = insomnia disorder diagnosis; MS-ID = MS patients with ID; MS-NID = MS patients without ID; NMS-ID = neurological disease-free participants with ID; REM-sleep = rapid eye movement–sleep. * [MS-ID = NMS-ID] > MS-NID. † MS-ID > NMS-ID. ‡ [MS-ID = NMS-ID] > [MS-NID = NMS-ID], § [MS-ID = NMS-ID] > MS-NID. || MS-ID > [MS-NID = NMS-ID]. View Large Finally, between-group effects were reported for both cognitive and somatic arousal subscales of the PSAS (p < .001, η2 = 0.44; p < .001, η2 = 0.42, respectively). Post hoc multiple comparisons revealed that patients with MS-ID described higher cognitive and somatic manifestations of arousal than did patients with MS-NID, respectively, p < .001 and p = .001. In MS, insomnia diagnosis’ effect on somatic arousal subscale of the PSAS remained significant after controlling for pain intensity, F(1.57) = 5.33, p = .025. In both MS-ID and MS-NID groups, no association was found between pain intensity and somatic manifestations of arousal, respectively, r = –0.002, p = .99 and r = 0.11, p = .40. This lack of relationship was also observed on the whole sample of patients with MS, r = 0.11, p = .41. Finally, no significant group-difference was noticed between MS-ID and NMS-ID groups concerning cognitive arousal (p = .18). Nonetheless, patients with MS-NID reported a higher level of somatic arousal compared with NMS-ID individuals (p = .004). Discussion To the best of our knowledge, this is the first study especially assessing the relevance of psychological processes involved in the maintenance of insomnia, in the specific context of ID comorbid to MS. We specially hypothesized that ID comorbid to MS would be associated with the classical emotional, behavioral, and cognitive factors perpetuating ID in neurological disease-free individuals with insomnia. The relationships between sleep quality and clinical peculiarities of MS remain a matter of debate in literature. Although some studies described a positive association between level of disability as assessed by the EDSS and sleep disturbances [24, 25], others did not [6, 26–28]. One study reported that poor sleep quality was significantly more prevalent in patients with MS with longer disease duration [29] and another one documented that anxiety, pain discomfort, and nocturia had a deleterious effect on sleep. Braley and coworkers reported a positive association between insomnia complaint severity and a number of nocturnal symptoms interfering with sleep [28]. These latter included both psychological (feeling of restlessness, anxiety, and an inability to shut off the mind) and physical symptoms (pain, tingling, spasticity, urinary urgency, and muscle twitching). Unfortunately, the authors did not specify which of these symptoms (physical versus psychological) had a deleterious effect on sleep, in particular for sleep initiation and sleep maintenance. All of these studies had focused on sleep quality or insomnia severity, with various definitions and assessment methods: home-made questionnaires [26], Pittsburg Sleep Quality Index [25, 29], Insomnia Severity Index [28], Medical Outcome Study Sleep Scale [24], and Sleep Diary [27]. These methods have shown advantages in specific settings such as identifying good and bad sleepers or assessing changes in both nighttime and daytime components of insomnia after treatment [30, 31]. Nevertheless, none was designed to assess insomnia diagnosis based on the currently commonly used DSM-5 or ICSD-3. Furthermore, none has been formally validated in MS, and their measurement and structural invariance are also unknown in this neurological disease, as is the case for numerous neurological conditions. Capitalizing on the formal ID diagnosis [1, 2], our study found no link between MS clinical characteristics (i.e. age at onset, duration of the disease, MS type, EDSS, and MS treatment) and ID diagnosis. This lack of relationship corroborates the large Portuguese multicenter, hospital-based cross-sectional study performed by Viana and coworkers relying on ICSD-3 chronic ID [4]. All together, these results suggest that ID diagnosis is very poorly associated with MS clinical characteristics. It is now well admitted that predisposing, precipitating, and perpetuating factors all play a role in the formation of ID [32]. Following this theoretical approach, a primary medical disorder and its related clinical characteristics may be a precipitating factor in eliciting insomnia. Over time, perpetuating factors emerge to contribute and intensify insomnia. From this perspective, all patients with ID develop emotional, behavioral, and cognitive features that contribute to their insomnia. These features have been integrated in Harvey’s cognitive model for the maintenance of insomnia that was selected as the guide to the present research [10]. Our results are in line with this theoretical framework. Indeed, contrary to MS clinical peculiarities, we documented that ID comorbid to MS was strongly associated with increased levels of cognitive and somatic arousal, more frequent engagement in sleep-related safety behaviors, and higher endorsement of dysfunctional beliefs about the consequences of insomnia on daytime functioning and worry about insomnia. In this last respect, our findings are in accordance with the only study that has assessed insomnia in patients with MS using ICSD-3 standard diagnostic criteria and describing that patients with ID had a higher endorsement of maladaptive beliefs about sleep rated on the DBAS [4]. In this study, only DBAS total scores were reported. Otherwise, we originally reported that patients with MS with ID did not differ from sex-, age-, and insomnia severity–matched neurological disease-free individuals with insomnia regarding the intensity of emotional, behavioral, and cognitive processes involved in the maintenance of insomnia. This last observation is in accordance with evidences having emphasized the need to reconsider the traditional model of “secondary insomnia” and to propose new approaches to understand insomnia that is comorbid with another medical and/or psychiatric illness [33]. In this standpoint, DSM-5 and ICSD-3 nosological systems have both removed the distinction between “primary” and “secondary” insomnia [1, 2]. Furthermore, our results are in line with recently published studies that have shown the efficacy of CBT-I in patients with MS on sleep parameters [34, 35]. Unfortunately, these pioneering studies did not assess the impact of CBT-I on the variation of dysfunctional beliefs about sleep, sleep-related safety behaviors, and presleep cognitive arousal. In any event, taken together, these results pinpoint the need to consider ID comorbid to MS as a full-fledge clinical entity, underpinned by psychological factors, and requiring specific care. In the present study, the relationship found between ID diagnosis in patients with MS, and anxious and depressive symptoms are consistent with Viana and coworkers’ study capitalizing on the formal ID diagnosis [4]. It also substantiates several studies showing a robust association between poor sleep quality and severity of both depressive [24, 25, 36] and anxious symptoms [24] in MS. Pain and fatigue are key symptoms in MS and have been rated by patients as two of their most important symptoms [37, 38]. Studies examining relationships of MS-related fatigue to formal sleep disorders (i.e. obstructive sleep apnea, restless legs syndrome, periodic limb movement disorder, and nocturia) remain scarce though reporting inconsistent conclusions [3, 6, 25, 28, 39, 40]. By contrast, MS-related fatigue has been systematically associated with both self-reported sleep quality [26, 27, 36] and more recently with ID diagnosis [4]. Note that this last observation was also highlighted in our study. Similar to fatigue, pain intensity rated on specific instruments [4, 25, 26] or assessed by visual numeric scales [24] has been robustly related to sleep quality in MS. In accordance with this literature, we found that insomniac patients with MS reported that pain directly and negatively affected their sleep. Neuropathic and visceral painful symptoms frequently reported in MS are likely to mimic somatic arousal manifestations such as stomach upset, dry feeling in throat, or cold feeling [41]. This observation led us to consider pain intensity as a potential confounding factor on the relationship between insomnia diagnosis and presleep somatic arousal symptoms in patients with MS. Our results indicated that this relationship was independent of pain intensity, thus favoring the distressing nature of presleep somatic arousal experienced at bedtime. Pain in MS population is heterogeneous and includes several pain syndromes (i.e. headache, neuropathic extremity pain, back pain, painful spasms, Lhermitte sign, and trigeminal neuralgia) and mechanisms [41]. The interactions between this heterogeneity and sleep disturbances need to be addressed. Finally, 14% of enrolled patients in the present study had a BMI score superior to 30, with no significant difference between patients with and without insomnia. This observation is in accordance with the large multicenter study performed by Viana and coworkers who found no association between BMI and insomnia diagnosis with quasisimilar BMI scores between MS-ID and MS-NID groups. In contrast to what has been reported in general population [42], insomnia comorbid to MS is not associated with overweight. This may be related to the fact that overweight in itself is a risk factor for MS [43]. Although this study has several strengths such as the inclusion of patients with MS with formal diagnosis of insomnia and neurological disease-free individuals with insomnia, there are some limitations that must be mentioned. Firstly, owing to the small sample size, our results cannot be generalized to all individuals with MS. Furthermore, this small sample size did not allow us to apply more sophisticated statistical methodologies, e.g. structural equation modeling, to examine the complex relationships between psychological processes and ID in MS. Another limitation is the cross-sectional design of our study not allowing us to explore the causal pathways between ID comorbid to MS and psychological processes involved in the maintenance of insomnia. Thirdly, we did not extensively assess physical symptoms related to MS (e.g. nocturia, spasticity, and muscle twitching) that may negatively affect sleep and lead to chronic insomnia. In chronic insomnia comorbid to MS, this relationship has to be systematically explored. Note that, in this context, Viana and coworkers [4] found no association between chronic insomnia diagnosis and functional systems involved including pyramidal, brainstem, sensory, and sphincters. Finally, no polysomnography was performed to definitively exclude sleep breathing disorders, sleep-related motor disorders, or parasomnia. However, it is important to note that dysfunctional psychological processes, in particular sleep- or insomnia-related cognitions, have been documented in patients with comorbid sleep apnea syndrome or comorbid RLS and insomnia [44, 45]. This observation indicates that these “organic” sleep disorders deserve more diagnostic attention regarding possible insomnia-specific symptoms. In MS, it remains nevertheless an open question. Conclusion ID comorbid to MS is associated with the classical psychological factors perpetuating ID in neurological disease-free individuals with insomnia. Furthermore, very recent literature provided evidence that CBT-I is an effective treatment for ID comorbid to MS. Primary care providers and neurologists should consider target-oriented therapies like cognitive behavioral therapy for chronic insomnia as a treatment approach for ID comorbid to MS. Disclosure statement This was not an industry supported study. All authors have indicated no financial conflicts of interest. Notes Conflict of interest statement. None declared. References 1. American Academy of Sleep Medicine. International Classification of Sleep Disorders . 3rd ed. Darien, IL: American Academy of Sleep Medicine; 2014. 2. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders . 5th ed. Washington, DC: American Psychiatric Association; 2013. 3. Veauthier Cet al.  . Fatigue in multiple sclerosis is closely related to sleep disorders: a polysomnographic cross-sectional study. Mult Scler . 2011; 17( 5): 613– 622. Google Scholar CrossRef Search ADS PubMed  4. Viana Pet al.  . InMS: chronic insomnia disorder in multiple sclerosis – a Portuguese multicentre study on prevalence, subtypes, associated factors and impact on quality of life. Mult Scler Relat Disord . 2015; 4( 5): 477– 483. Google Scholar CrossRef Search ADS PubMed  5. Uhlig BLet al.  . Prevalence and associated factors of DSM-V insomnia in Norway: the Nord-Trøndelag Health Study (HUNT 3). Sleep Med . 2014; 15( 6): 708– 713. Google Scholar CrossRef Search ADS PubMed  6. Brass SDet al.  . The underdiagnosis of sleep disorders in patients with multiple sclerosis. J Clin Sleep Med . 2014; 10( 9): 1025– 1031. Google Scholar PubMed  7. Espie CA. Insomnia: conceptual issues in the development, persistence, and treatment of sleep disorder in adults. Annu Rev Psychol . 2002; 53: 215– 243. Google Scholar CrossRef Search ADS PubMed  8. Perlis MLet al.  . Psychophysiological insomnia: the behavioural model and a neurocognitive perspective. J Sleep Res . 1997; 6( 3): 179– 188. Google Scholar CrossRef Search ADS PubMed  9. Morin CMet al.  . Dysfunctional beliefs and attitudes about sleep among older adults with and without insomnia complaints. Psychol Aging . 1993; 8( 3): 463– 467. Google Scholar CrossRef Search ADS PubMed  10. Harvey AG. A cognitive model of insomnia. Behav Res Ther . 2002; 40( 8): 869– 893. Google Scholar CrossRef Search ADS PubMed  11. Mitchell MDet al.  . Comparative effectiveness of cognitive behavioral therapy for insomnia: a systematic review. BMC Fam Pract . 2012; 13: 40. Google Scholar CrossRef Search ADS PubMed  12. Kurtzke JF. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology . 1983; 33( 11): 1444– 1452. Google Scholar CrossRef Search ADS PubMed  13. Netzer NCet al.  . Using the Berlin Questionnaire to identify patients at risk for the sleep apnea syndrome. Ann Intern Med . 1999; 131( 7): 485– 491. Google Scholar CrossRef Search ADS PubMed  14. Allen RPet al.  . Restless legs syndrome/Willis-Ekbom disease diagnostic criteria: updated International Restless Legs Syndrome Study Group (IRLSSG) consensus criteria–history, rationale, description, and significance. Sleep Med . 2014; 15( 8): 860– 873. Google Scholar CrossRef Search ADS PubMed  15. Postuma RBet al.  . A single-question screen for rapid eye movement sleep behavior disorder: a multicenter validation study. Mov Disord . 2012; 27( 7): 913– 916. Google Scholar CrossRef Search ADS PubMed  16. Beck ATet al.  . Manual for the Beck Depression Inventory-II . Paris, France: Editions du Centre de Psychologie Appliquée; 1996. 17. Spielberger CD. State-Trait Anxiety Inventory: Bibliography  2nd ed. Palo Alto: Consulting Psychologists Press; 1989. 18. Chen PYet al.  . Validating the cross-cultural factor structure and invariance property of the Insomnia Severity Index: evidence based on ordinal EFA and CFA. Sleep Med . 2015; 16( 5): 598– 603. Google Scholar CrossRef Search ADS PubMed  19. Morin CMet al.  . Dysfunctional beliefs and attitudes about sleep (DBAS): validation of a brief version (DBAS-16). Sleep . 2007; 30( 11): 1547– 1554. Google Scholar CrossRef Search ADS PubMed  20. Ree MJet al.  . Investigating safety behaviours in insomnia: the development of the Sleep-Related Behaviours Questionnaire (SRBQ). Behav Change . 2004; 21( 1): 26– 36. Google Scholar CrossRef Search ADS   21. Nicassio PMet al.  . The phenomenology of the pre-sleep state: the development of the pre-sleep arousal scale. Behav Res Ther . 1985; 23( 3): 263– 271. Google Scholar CrossRef Search ADS PubMed  22. Debouverie Met al.  . Validity of a French version of the fatigue impact scale in multiple sclerosis. Mult Scler . 2007; 13( 8): 1026– 1032. Google Scholar CrossRef Search ADS PubMed  23. Cohen J. Statistical Power Analysis for the Behavioral Sciences . NY: Routledge Academic; 1988. 24. Leonavicius R. Peculiarities of sleep problems in multiple sclerosis. Neurol Psychiatry Brain Res . 2015; 21( 4): 148– 152. Google Scholar CrossRef Search ADS   25. Neau JPet al.  . Sleep disorders and multiple sclerosis: a clinical and polysomnography study. Eur Neurol . 2012; 68( 1): 8– 15. Google Scholar CrossRef Search ADS PubMed  26. Pokryszko-Dragan Aet al.  . Sleep disturbances in patients with multiple sclerosis. Neurol Sci . 2013; 34( 8): 1291– 1296. Google Scholar CrossRef Search ADS PubMed  27. Stanton BRet al.  . Sleep and fatigue in multiple sclerosis. Mult Scler . 2006; 12( 4): 481– 486. Google Scholar CrossRef Search ADS PubMed  28. Braley TJet al.  . Obstructive sleep apnea is an under-recognized and consequential morbidity in multiple sclerosis. J Clin Sleep Med . 2014; 10( 6): 709– 710. Google Scholar PubMed  29. Vitkova Met al.  . Factors associated with poor sleep quality in patients with multiple sclerosis differ by disease duration. Disabil Health J . 2014; 7( 4): 466– 471. Google Scholar CrossRef Search ADS PubMed  30. Moul DEet al.  . Self-report measures of insomnia in adults: rationales, choices, and needs. Sleep Med Rev . 2004; 8( 3): 177– 198. Google Scholar CrossRef Search ADS PubMed  31. Buysse DJet al.  . Recommendations for a standard research assessment of insomnia. Sleep . 2006; 29( 9): 1155– 1173. Google Scholar CrossRef Search ADS PubMed  32. Spielman AJet al.  . A behavioral perspective on insomnia treatment. Psychiatr Clin North Am . 1987; 10( 4): 541– 553. Google Scholar PubMed  33. Stepanski EJet al.  . Emerging research on the treatment and etiology of secondary or comorbid insomnia. Sleep Med Rev . 2006; 10( 1): 7– 18. Google Scholar CrossRef Search ADS PubMed  34. Clancy Met al.  . Outcomes of cognitive-behavioral treatment for insomnia on insomnia, depression, and fatigue for individuals with multiple sclerosis: a case series. Int J MS Care . 2015; 17( 6): 261– 267. Google Scholar CrossRef Search ADS PubMed  35. Abbasi SMset al.  . Effectiveness of cognitive behavioral therapy on the quality of sleep in women with multiple sclerosis: a randomized controlled trial study. Int J Community Based Nurs Midwifery . 2016; 4( 4): 320– 328. Google Scholar PubMed  36. Bøe Lunde HMet al.  . Poor sleep in patients with multiple sclerosis. PLoS One . 2012; 7( 11): e49996. Google Scholar CrossRef Search ADS PubMed  37. Fisk JDet al.  . The impact of fatigue on patients with multiple sclerosis. Can J Neurol Sci . 1994; 21( 1): 9– 14. Google Scholar CrossRef Search ADS PubMed  38. Kalia LVet al.  . Severity of chronic pain and its relationship to quality of life in multiple sclerosis. Mult Scler . 2005; 11( 3): 322– 327. Google Scholar CrossRef Search ADS PubMed  39. Veauthier Cet al.  . Sleep disorders in multiple sclerosis and their relationship to fatigue. Sleep Med . 2014; 15( 1): 5– 14. Google Scholar CrossRef Search ADS PubMed  40. Aydar Get al.  . Restless legs syndrome in multiple sclerosis. Eur Neurol . 2011; 65( 5): 302– 306. Google Scholar CrossRef Search ADS PubMed  41. Foley PLet al.  . Prevalence and natural history of pain in adults with multiple sclerosis: systematic review and meta-analysis. Pain . 2013; 154( 5): 632– 642. Google Scholar CrossRef Search ADS PubMed  42. Kalmbach DAet al.  . DSM-5 insomnia and short sleep: comorbidity landscape and racial disparities. Sleep . 2016; 39( 12): 2101– 2111. Google Scholar CrossRef Search ADS PubMed  43. Wesnes Ket al.  . Body size and the risk of multiple sclerosis in Norway and Italy: the EnvIMS study. Mult Scler . 2015; 21( 4): 388– 395. Google Scholar CrossRef Search ADS PubMed  44. Crönlein Tet al.  . Are dysfunctional attitudes and beliefs about sleep unique to primary insomnia? Sleep Med . 2014; 15( 12): 1463– 1467. Google Scholar CrossRef Search ADS PubMed  45. Yang CMet al.  . Psychological and behavioral factors in patients with comorbid obstructive sleep apnea and insomnia. J Psychosom Res . 2011; 70( 4): 355– 361. Google Scholar CrossRef Search ADS PubMed  © Sleep Research Society 2018. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. 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Oxford University Press
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© Sleep Research Society 2018. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.
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Abstract

Abstract Study Objectives Despite the high comorbidity of insomnia disorder (ID) with multiple sclerosis (MS), the relevance of psychological processes involved in the maintenance of insomnia is yet to be established in this neurological disorder. This study aimed to ascertain to what extent the suggested emotional, cognitive, and behavioral processes maintaining insomnia are relevant in people with insomnia and MS. Methods A between-subjects design was used to compare 26 patients with insomnia and MS, with 31 patients with MS only, and with 26 matched neurological disease-free individuals with insomnia. All patients participated in a standardized clinical interview and completed a battery of self-reported measures of cognitive and somatic presleep arousal experienced at bedtime, sleep- or insomnia-related unhelpful beliefs, and sleep-related safety behaviors. All patients with MS underwent a neurological examination. Results ID comorbid to MS was strongly associated with increased levels of cognitive and somatic arousal, higher endorsement of dysfunctional beliefs about the consequences of insomnia on daytime functioning, and worry about insomnia and more frequent engagement in sleep-related safety behaviors. Patients with MS with ID did not differ from neurological disease-free individuals with insomnia on these measures. No link was found between MS clinical peculiarities and ID diagnosis. Conclusions ID comorbid to MS is associated with the classical psychological factors perpetuating ID in neurological disease-free individuals with insomnia. Primary care providers and neurologists should consider target-oriented therapies like cognitive behavioral therapy for chronic insomnia as a treatment approach for ID comorbid to MS. insomnia, multiple sclerosis, emotion, cognition Statement of Significance Insomnia is the most common sleep disorder among adults affected by multiple sclerosis and is associated with a wide range of negative outcomes. In neurological disease-free individuals with insomnia, emotional, cognitive, and behavioral processes play a central role in the maintenance and treatment of insomnia. Originally, we clearly documented the high relevance of these psychological processes in the specific context of insomnia comorbid to multiple sclerosis. Considering insomnia symptoms to be secondary to medical disorder could lead to reluctance to expend resources to treat insomnia or denial of treatment for insomnia symptoms. Providers should consider target-oriented therapies like cognitive behavioral therapy for insomnia as a treatment approach for insomnia comorbid to multiple sclerosis. Introduction According to the International Classification of Sleep Disorders, 3rd ed. (ICSD-3) and the Diagnostic and Statistical Manual of Mental Disorders, 5th ed. (DSM-5), insomnia disorder (ID) is characterized by dissatisfaction with sleep quantity or quality related to one or more of the following symptoms: difficulty initiating sleep, difficulty maintaining sleep, and early-morning awakening. This dissatisfaction is accompanied by significant distress and/or impairment in daytime functioning [1, 2]. Symptoms should be present at least three nights per week for a minimum of three consecutive months. When these standardized criteria are used, it is estimated that 22%–25% of patients with multiple sclerosis (MS) meet the criteria for ID [3, 4]. This rate is two to three times as high as in the general population which indubitably makes ID one of the most prevalent sleep disorders in MS [5]. Despite its high prevalence, insomnia surprisingly remains underdiagnosed and, therefore, undertreated in MS [6]. Knowledge of factors associated with occurrence of ID in MS may provide clues for an increased understanding of underlying pathophysiology and contribute to developing targeted therapeutic interventions. However, this issue is hitherto poorly addressed in the literature. In fact, to the best of our knowledge, only one study has assessed factors associated with ID in MS [4]. Similar to the general population, female gender, medical comorbidities, anxiety, and fatigue were identified as independent factors for ID in MS outpatients. Over the last decades, there has been a range of theoretical advances in understanding insomnia [7–10], which have recognized the importance of emotional, behavioral, and cognitive processes. In this regard, the cognitive model of insomnia developed by Harvey has emphasized the central role played by arousal and distress arising from excessive negatively toned cognitive activity, both exacerbated by dysfunctional beliefs and attitudes about sleep and sleep-related safety behaviors, in the development and maintenance of chronic ID [10]. The cognitive approach to insomnia has provided researchers and clinicians with a framework for understanding and treating insomnia. In this respect, it is largely acknowledged that cognitive behavioral therapy for insomnia (CBT-I) is an effective treatment with long-term benefits and few side effects [11]. To the best of our knowledge, no study has examined the psychological processes involved in the maintenance of insomnia in the specific context of ID comorbid to MS. Consequently, the objective of the current study was to ascertain to what extent the suggested emotional, cognitive, and behavioral processes maintaining insomnia are relevant in insomniac people with MS. We more specifically hypothesized that ID comorbid to MS is associated with (1) increased levels of cognitive and somatic arousal; (2) higher endorsement of dysfunctional beliefs about the consequences of insomnia on daytime functioning and worry about insomnia; and (3) more frequent engagement in sleep-related safety behaviors. Methods Participants Eighty-three individuals participated in the study, with 57 consecutive outpatients with MS diagnosis according to the 2010 revision of the McDonald criteria for a minimum of 6 months. The Expanded Disability Status Scale (EDSS) was used to quantify disability in MS [12]. Among the MS group, 26 patients had ID as per to the ICSD-3 and DSM-5 diagnosis criteria (MS-ID) [1, 2], and 31 patients did not meet the diagnostic criteria for ID (MS-NID). Each patient with MS-ID was matched by gender and age (±1 year) to one neurological disease-free individual with ID diagnosis (NMS-ID). For all participants, the eligibility criteria included an age of 18 years or older and speaking French. Participants also had to be willing to voluntarily participate in the study, and no compensation was provided. Exclusion criteria for all participants were as follows: a history of schizophrenia spectrum or other psychotic disorder, bipolar-related disorder, substance-related and addictive disorder, and neurological disease other than MS for patient’s group including cerebrovascular disease and traumatic brain injury, active and unstable physical illness (e.g. cancer and renal failure). Also excluded were shift workers, pregnant women or breast-feeding mothers, parents with a baby less than 12 months. Note that all participants were screened for the two major diseases related to insomnia in adults, i.e. sleep apnea and the restless legs syndrome/Willis–Ekbom disease (RLS/WED). Sleep apnea was screened by using the Berlin Questionnaire [13] and RLS/WED was assessed based on the International Restless Legs Syndrome Study Group criteria [14]. Rapid eye movement sleep behavior disorder Single-Question Screen (RBD1Q) was applied to screen probable RBQ [15]. Participants with current anxiety and mood disorders were not excluded. Current psychotropic medication was not considered as exclusion criteria but was thoroughly recorded. Clinical interview The face-to-face clinical interview was conducted by trained licensed psychologists with expertise in sleep field. During clinical interview, we assessed insomnia, sleep history, medical and psychological states, psychotropic medication, and sociodemographic characteristics. Current insomnia, mood, and anxiety disorders were diagnosed as per to the DSM-5 criteria, using a local translation of the clinical version of the structured interview for DSM-5 (SCID-5-CV). The diagnosis of ID was established with a clinical interview covering items included in DSM-5 criteria for ID. Participants were diagnosed with ID [1, 2] when they reported (1) subjective difficulty in initiating and/or maintaining sleep and/or early morning awakening despite having adequate opportunity to sleep, (2) accompanied by significant distress and/or impairment in daytime functioning, and (3) for at least 3 months and at least 3 nights a week on the SCID-5-CV. Levels of depressive and anxious symptoms were respectively assessed by the Beck Depression Inventory (BDI-II) [16] and the Spielberger Trait Anxiety Inventory (STAI-trait) [17]. Questionnaires Insomnia Severity Index The Insomnia Severity Index (ISI) was used to evaluate insomnia complaint severity [18]. This 8-item self-rated questionnaire assesses the severity of sleep onset insomnia, sleep maintaining insomnia and early awakening insomnia, satisfaction with the current sleep patterns, interference with daytime functioning, noticeability of impairment to significant others, and level of distress caused by the sleep problem. Brief version of the dysfunctional beliefs and attitudes about sleep The DBAS-16 was used to assess various sleep- or insomnia-related cognitions (e.g. beliefs, attitudes, expectations, appraisals, and attributions), with higher scores indicating a stronger endorsement of dysfunctional beliefs [19]. The DBAS-16 is a 16-item self-reported questionnaire encompassing four subscales computed separately as follows: (1) attributions of the causes and appraisals of the consequences of insomnia (consequences), (2) issues of worry and helplessness about insomnia (worry/helplessness), (3) expectations about sleep requirements (expectations), and (4) sleep medication and biological attribution of insomnia (medication). Sleep-Related Behaviors Questionnaire The Sleep-Related behaviors Questionnaire (SRBQ) is a 32-item self-reported questionnaire reflecting behavioral strategies used to cope with insomnia during the day and at night [20]. For example, the items include as follows: “I try to keep all disturbing thoughts and images out of my mind while in bed”; “I avoid talking about my sleep”; “I look at the clock upon waking to calculate how many hours of sleep I got”; “I plan to get an early night.” The higher total score indicates higher engagement in unhelpful behavioral strategies to cope with insomnia. Presleep Arousal Scale The Presleep Arousal Scale (PSAS) contains 16 items referring to symptoms of cognitive (e.g. racing mind and worry about falling asleep) and somatic (e.g. muscle tension and heart racing) presleep arousal experienced at bedtime [21]. Two subscale scores were computed separately, i.e. cognitive arousal and somatic arousal. In taking the PSAS, participants were asked to describe how intensely they generally experienced each symptom as they attempted to fall asleep in their own bedroom. High scores for these scales are indicative of a higher intensity of the construct. Only patients with MS completed the Fatigue Impact Scale for multiple sclerosis (EMIF-SEP) to assess the severity of self-reported fatigue [22]. This self-administered questionnaire is composed of 40 items organized into four dimensions: (1) cognitive, (2) physical, (3) social role, and (4) psychological. Finally, an investigator-designed one question numeric rating scale was used to assess the impact of pain on sleep. Patients who reported pain were asked to indicate the unique number that best described the impact of pain on their sleep in the last 2 weeks on a scale ranging from 0 “sleep is not disturbed” to 10 “sleep is extremely disturbed.” Procedure Individuals from the NMS-ID group belong to a data base of Epsylon Laboratory. They were community-dwelling adults recruited by mean of advertisements, personal contacts, and snowballing techniques from December 2015 to April 2016. Patients with MS were recruited within the University Department of Neurology in Montpellier (France) from December 2015 to August 2016. At the time of the study, all patients with MS underwent a neurological examination. During a single session, all participants individually underwent a face-to-face clinical interview. By the end of the interview, each participant received a questionnaire booklet and was asked to fill it at home. Prepaid envelopes were provided for the return of the documents. The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008. All participants gave their informed consent to participate in the study, which was approved by the local university ethics committee. Statistical analyses All statistical analyses were performed with IBM SPSS software version 24.0. Data were tested for normal distribution and homogeneity of variance using the Kolmogorov–Smirnov test and the Levene test, respectively. One-way between-groups analysis of variance (ANOVA) and Student’s t test were used to assess group differences for continuous variables, and the chi-square test was used for categorical variables. In addition, we calculated the eta squared η2 and the Cohen’s d′ as measures of the effect size. The effect size was considered small (η2 = 0.01; d = 0.2), medium (η2 = 0.06; d = 0.5), or large (η2 = 0.14; d = 0.8) according to Cohen [23]. Given the sample size, 95% confidence of interval (CI) was reported when a statistical tendency was observed between MS-ID and MS MS-NID groups. All analyses were conducted with a significance threshold of α = 0.05, two-tailed. Results MS clinical characteristics Most patients (63.2%) were females, and ages varied between 20 and 67 years (Table 1). More than half (56.1%) were unemployed with handicapped status and 66.7% lived with their spouse or partner. One-third of patients (36.8%) had a relapsing–remitting form of MS and did not take any disease-modifying treatment (38.6%). The mean EDSS score was 4.79 ± 2.28 (all patients had EDSS score < 8). Mean duration of disease was 12.40 ± 10.02 years. In our study, 19.6% (n = 11; MS-ID = 6) of patients suffered from medical comorbidities. These included iatrogenic hypothyroidism controlled by medication (n = 4; MS-ID = 1), hypercholesterolemia (n = 3; MS-ID = 1), hypertension (MS-ID = 1), Crohn’s syndrome (MS-ID = 1), Raynaud’s syndrome (MS-ID = 1), and thalassemia (MS-ID = 1). Table 1. Demographic and clinical characteristics of multiple sclerosis patients with insomnia disorder, without insomnia disorder, and controls with insomnia disorder   MS-ID (n = 26)  MS-NID (n = 31)  NMS-ID (n = 26)  Statistics (ddl)  P-value  Demographic data   Age, y  47.5 ± 12.8  46.2 ± 11.3  47.0 ± 13.0  F(2.80) = 0.07  .94   Sex, female/male, n  19/7  17/14  19/7  χ2(2) = 2.89  .24   Education, y  13.1 ± 2.9  12.9 ± 2.2  14.1 ± 2.7  F(2.80) = 1.78  .18  MS clinical characteristics   Age at onset, y  34.1 ± 13.0  34.6 ± 9.7  —  t(45.4) = 0.16  .87   Duration of disease, y  13.5 ± 10.7  11.5 ± 9.5  —  t(55) = −0.74  .46   MS type      —  χ2(2) = 1.2  .55    Relapsing–Remitting  8  13  —        Primary progressive  9  7  —        Secondary progressive  9  11  —       EDSS  5.3 ± 1.9  4.3 ± 2.4  —  t(52) = −1.75  .09   MS treatment              None  12  10  —        Natalizumab  3  3  —  χ2(8) = 6.06  .64    Rituximab  4  3  —        Cyclophosphamide  1  4  —        Fingolimod  0  3  —        Methylprednisolone  2  1  —        Biotine  1  1  —        Glatiramere acetate  1  1  —        Other  2  4  —       Psychotropic intake (yes)  69.2%  35.5%  15.4%  χ2(2) = 16.12  <.001*   Average impact of pain on sleep  2.8 ± 3.4  0.68 ± 1.8  —  t(36) = −2.83  .008†  Fatigue impact scale dimensions   Cognitive  25.7 ± 6.4  23.6 ± 5.9    t(55) = −1.33  .19   Physical  37.9 ± 6.3  33.1 ± 9.5    t(55) = −2.24  .029†   Social role  33.9 ± 7.4  32.1 ± 8.6    t(55) = −0.85  .39   Psychological  10.5 ± 2.5  9.7 ± 2.5    t(55) = −1.23  .22  Mood and anxiety assessment   Beck depression inventory  19.4 ± 11.4  10.2 ± 9.7  12.4 ± 8.9  F(2.80) = 6.22  .003‡   Curent mood disorder  50.0%  35.5%  19.2%  χ2(2) = 5.42  .07   Spielberger Trait Anxiety inventory  50.2 ± 10.6  40.4 ± 11.8  26.2 ± 6.4  F(2.79) = 36.9  <.001§   Curent anxiety disorder  23.1%  9.7%  30.8%  χ2(2) = 4.02  .13    MS-ID (n = 26)  MS-NID (n = 31)  NMS-ID (n = 26)  Statistics (ddl)  P-value  Demographic data   Age, y  47.5 ± 12.8  46.2 ± 11.3  47.0 ± 13.0  F(2.80) = 0.07  .94   Sex, female/male, n  19/7  17/14  19/7  χ2(2) = 2.89  .24   Education, y  13.1 ± 2.9  12.9 ± 2.2  14.1 ± 2.7  F(2.80) = 1.78  .18  MS clinical characteristics   Age at onset, y  34.1 ± 13.0  34.6 ± 9.7  —  t(45.4) = 0.16  .87   Duration of disease, y  13.5 ± 10.7  11.5 ± 9.5  —  t(55) = −0.74  .46   MS type      —  χ2(2) = 1.2  .55    Relapsing–Remitting  8  13  —        Primary progressive  9  7  —        Secondary progressive  9  11  —       EDSS  5.3 ± 1.9  4.3 ± 2.4  —  t(52) = −1.75  .09   MS treatment              None  12  10  —        Natalizumab  3  3  —  χ2(8) = 6.06  .64    Rituximab  4  3  —        Cyclophosphamide  1  4  —        Fingolimod  0  3  —        Methylprednisolone  2  1  —        Biotine  1  1  —        Glatiramere acetate  1  1  —        Other  2  4  —       Psychotropic intake (yes)  69.2%  35.5%  15.4%  χ2(2) = 16.12  <.001*   Average impact of pain on sleep  2.8 ± 3.4  0.68 ± 1.8  —  t(36) = −2.83  .008†  Fatigue impact scale dimensions   Cognitive  25.7 ± 6.4  23.6 ± 5.9    t(55) = −1.33  .19   Physical  37.9 ± 6.3  33.1 ± 9.5    t(55) = −2.24  .029†   Social role  33.9 ± 7.4  32.1 ± 8.6    t(55) = −0.85  .39   Psychological  10.5 ± 2.5  9.7 ± 2.5    t(55) = −1.23  .22  Mood and anxiety assessment   Beck depression inventory  19.4 ± 11.4  10.2 ± 9.7  12.4 ± 8.9  F(2.80) = 6.22  .003‡   Curent mood disorder  50.0%  35.5%  19.2%  χ2(2) = 5.42  .07   Spielberger Trait Anxiety inventory  50.2 ± 10.6  40.4 ± 11.8  26.2 ± 6.4  F(2.79) = 36.9  <.001§   Curent anxiety disorder  23.1%  9.7%  30.8%  χ2(2) = 4.02  .13  Data are presented as means ± standard deviations. MS refers to multiple sclerosis; ID = insomnia disorder diagnosis; MS-ID = MS patients with ID; MS-NID = MS patients without ID; NMS-ID = neurological disease-free participants with ID; EDSS = Expanded Disability Status Scale. * MS-ID > MS-NID > NMS-ID. † MS-ID > MS-NID. ‡ MS-ID > [MS-NID = NMS-ID]. § MS-ID > MS-NID > NMS-ID. View Large MS-ID and MS-NID group comparisons As illustrated in Table 1, no significant differences were found between MS-ID and MS-NID groups in terms of age (p = .94), sex (p = .24), and years of education (p = .18). Note that the work status was not significantly different between the two groups (χ2 = 34.92, p = .57). In particular, the proportion of unemployed patients with handicapped status did not differ among MS-ID (61.5%) and MS-NID groups (58%). With regard to MS characteristics, age at onset (p = .87), duration of the disease (p = .46), and MS type (p = .46) did not differ between MS-ID and MS-NID groups (Table 1). On average, MS-ID group had a greater level of disability scored on the EDSS than did MS-NID group. This difference was not significant (p = .09, 95% CI [−2.29, 0.16]). With regard to MS characteristics, age at onset (p = .87), duration of the disease (p = .46), MS type (p = .46), and level of disability scored on the EDSS (p = .09, 95% CI [−2.29, 0.16]) did not differ between MS-ID and MS-NID groups. MS-ID group reported a higher level of fatigue on the physical EMIF-SEP dimension (p = .029, d′ = 0.59) and higher pain intensity in a relationship with disturbed sleep than did MS-NID group (p = .008, d′ = 0.78). These effects were medium to large. Finally, 14% of enrolled patients (n = 8) had a BMI score superior to 30, with no significant difference between patients with and without insomnia, respectively, 25.1 ± 5.4 versus 23.8 ± 3.8, t(55) = −1.06, p = .29. MS-ID, MS-NID, and NMS-ID group comparisons Mood and anxiety assessment A significant group effect was observed for both BDI-II and STAI-trait questionnaires (p = .003, η2 = 0.36; p < .001, η2 = 0.69). MS-ID group reported higher level of depressive symptoms compared with MS-NID group (p = .003) and NMS-ID group (p = .040). Both groups of patients with MS had higher levels of anxious symptoms comparatively to NMS-ID group (all p < .001). Nonetheless, MS-ID group reported higher levels of anxiety compared with MS-NID group (p = .001). Insomnia characteristics and sleep disorder screening The proportion of ID subtypes did not differ between MS-ID and NSM-ID groups (p = .55). The majority of participants with ID diagnosis had mixed insomnia (MS-ID = 69% and NMS-ID = 84%). As expected, insomnia complaint assessed by the ISI was significantly higher in MS-ID and NMS-ID groups than in MS-NID group (all p’s < .001). No significant difference was noted between MS-ID and NMS-ID groups on the ISI (p = 1). The proportion of individuals with RLS and probable SAS did not differ between the three groups (respectively, p = .76, p = .68). When considering the sample as a whole, none of participants had probable RBD. Questionnaires of psychological processes related to insomnia Globally, a same pattern of results was observed regarding group comparisons for DBAS-16, SRBQ, and PSAS questionnaires (Table 2). We observed significant group effects for the DBAS-16 consequences and worry/Helplessness subscales (p = .032, η2 = 0.28 and p = .002, η2 = 0.37, respectively). On these subscales, patients with MS-ID had a stronger endorsement of dysfunctional beliefs in comparison with patients with MS-NID (all p’s < .05), with no difference between MS-ID and NMS-ID groups (p = 1). A significant group effect was noted for the SRBQ total score, p = .013, η2 = 0.32. Contrast analyses indicated higher engagement in unhelpful behavioral strategies to cope with insomnia in patients with MS-ID compared with patients with MS-NID (p = .016), without any difference between MS-ID and NMS-ID groups (p = 1). Table 2. Sleep characteristics and psychological processes associated with insomnia disorder   MS-ID (n=26)  MS-NID (n=31)  NMS-ID (n=26)  Statistics (ddl)  P-Value  Sleep disorders screening  Insomnia disorder   Diagnosis of insomnia  100%  0%  100%  χ2(2) = 83  <.001*   Type of insomnia        χ2(3) = 2.27  .52    Sleep-onset insomnia  11.5%  —  8%        Sleep-maintenance insomnia  15.5%  —  8%        Terminal insomnia  4%  —  0%        Mixed insomnia  69%  —  84%       Insomnia duration (months)  70.6 ± 65.5  —  134.3 ± 157  t(50) = −1.91  .065   Frequency of sleep difficulties, days per week  6.2 ± 1.31  —  5.1 ± 1.7  t(50) = 2.75  .008†   Insomnia Severity Index  14.1 ± 6.9  6.0 ± 6.1  13.9 ± 4.9  F(2.80) = 16.9  <.001a  Restless legs syndrome  5  4  5  χ2(2) = 0.56  .76  Obstructive sleep apnea syndrome screening  1  1  2  χ2(2) = 0.77  .68  REM-sleep behavior disorder  0  0  0      Questionnaires of cognitive processes related to insomnia   Dysfunctional beliefs about sleep    Expectations  14.2 ± 5.2  12.9 ± 5.2  12.9 ± 3.9  F(2.80) = 0.57  .567    Medication  15.7 ± 8.1  11.3 ± 8.2  12.0 ± 6.7  F(2.80) = 2.58  .082    Consequences  28.4 ± 10.3  21.0 ± 13.1  26.7 ± 8.8  F(2.80) = 3.58  .032‡    Worry/helplessness  33.9 ± 12.0  23.29 ± 16.3  34.4 ± 14.1  F(2.80) = 6.54  .002§   Sleep-Related Behaviors Questionnaire  47.9 ± 22.6  30.1 ± 6.3  43.9 ± 20.0  F(2.80) = 4.60  .013§    Presleep Arousal Scale  45.9 ± 20.7  27.2 ± 10.2  33.1 ± 16.2  F(2.80) = 11.1  <.001    Somatic arousal  23.3 ± 14.5  13.5 ± 5.4  14.6 ± 5.9  F(2.79) = 8.94  <.001||    Cognitive arousal  22.7 ± 8.2  13.8 ± 7.2  18.1 ± 7.9  F(2.80) = 9.47  <.001‡    MS-ID (n=26)  MS-NID (n=31)  NMS-ID (n=26)  Statistics (ddl)  P-Value  Sleep disorders screening  Insomnia disorder   Diagnosis of insomnia  100%  0%  100%  χ2(2) = 83  <.001*   Type of insomnia        χ2(3) = 2.27  .52    Sleep-onset insomnia  11.5%  —  8%        Sleep-maintenance insomnia  15.5%  —  8%        Terminal insomnia  4%  —  0%        Mixed insomnia  69%  —  84%       Insomnia duration (months)  70.6 ± 65.5  —  134.3 ± 157  t(50) = −1.91  .065   Frequency of sleep difficulties, days per week  6.2 ± 1.31  —  5.1 ± 1.7  t(50) = 2.75  .008†   Insomnia Severity Index  14.1 ± 6.9  6.0 ± 6.1  13.9 ± 4.9  F(2.80) = 16.9  <.001a  Restless legs syndrome  5  4  5  χ2(2) = 0.56  .76  Obstructive sleep apnea syndrome screening  1  1  2  χ2(2) = 0.77  .68  REM-sleep behavior disorder  0  0  0      Questionnaires of cognitive processes related to insomnia   Dysfunctional beliefs about sleep    Expectations  14.2 ± 5.2  12.9 ± 5.2  12.9 ± 3.9  F(2.80) = 0.57  .567    Medication  15.7 ± 8.1  11.3 ± 8.2  12.0 ± 6.7  F(2.80) = 2.58  .082    Consequences  28.4 ± 10.3  21.0 ± 13.1  26.7 ± 8.8  F(2.80) = 3.58  .032‡    Worry/helplessness  33.9 ± 12.0  23.29 ± 16.3  34.4 ± 14.1  F(2.80) = 6.54  .002§   Sleep-Related Behaviors Questionnaire  47.9 ± 22.6  30.1 ± 6.3  43.9 ± 20.0  F(2.80) = 4.60  .013§    Presleep Arousal Scale  45.9 ± 20.7  27.2 ± 10.2  33.1 ± 16.2  F(2.80) = 11.1  <.001    Somatic arousal  23.3 ± 14.5  13.5 ± 5.4  14.6 ± 5.9  F(2.79) = 8.94  <.001||    Cognitive arousal  22.7 ± 8.2  13.8 ± 7.2  18.1 ± 7.9  F(2.80) = 9.47  <.001‡  Data are presented as means ± standard deviations. MS refers to multiple sclerosis; ID = insomnia disorder diagnosis; MS-ID = MS patients with ID; MS-NID = MS patients without ID; NMS-ID = neurological disease-free participants with ID; REM-sleep = rapid eye movement–sleep. * [MS-ID = NMS-ID] > MS-NID. † MS-ID > NMS-ID. ‡ [MS-ID = NMS-ID] > [MS-NID = NMS-ID], § [MS-ID = NMS-ID] > MS-NID. || MS-ID > [MS-NID = NMS-ID]. View Large Finally, between-group effects were reported for both cognitive and somatic arousal subscales of the PSAS (p < .001, η2 = 0.44; p < .001, η2 = 0.42, respectively). Post hoc multiple comparisons revealed that patients with MS-ID described higher cognitive and somatic manifestations of arousal than did patients with MS-NID, respectively, p < .001 and p = .001. In MS, insomnia diagnosis’ effect on somatic arousal subscale of the PSAS remained significant after controlling for pain intensity, F(1.57) = 5.33, p = .025. In both MS-ID and MS-NID groups, no association was found between pain intensity and somatic manifestations of arousal, respectively, r = –0.002, p = .99 and r = 0.11, p = .40. This lack of relationship was also observed on the whole sample of patients with MS, r = 0.11, p = .41. Finally, no significant group-difference was noticed between MS-ID and NMS-ID groups concerning cognitive arousal (p = .18). Nonetheless, patients with MS-NID reported a higher level of somatic arousal compared with NMS-ID individuals (p = .004). Discussion To the best of our knowledge, this is the first study especially assessing the relevance of psychological processes involved in the maintenance of insomnia, in the specific context of ID comorbid to MS. We specially hypothesized that ID comorbid to MS would be associated with the classical emotional, behavioral, and cognitive factors perpetuating ID in neurological disease-free individuals with insomnia. The relationships between sleep quality and clinical peculiarities of MS remain a matter of debate in literature. Although some studies described a positive association between level of disability as assessed by the EDSS and sleep disturbances [24, 25], others did not [6, 26–28]. One study reported that poor sleep quality was significantly more prevalent in patients with MS with longer disease duration [29] and another one documented that anxiety, pain discomfort, and nocturia had a deleterious effect on sleep. Braley and coworkers reported a positive association between insomnia complaint severity and a number of nocturnal symptoms interfering with sleep [28]. These latter included both psychological (feeling of restlessness, anxiety, and an inability to shut off the mind) and physical symptoms (pain, tingling, spasticity, urinary urgency, and muscle twitching). Unfortunately, the authors did not specify which of these symptoms (physical versus psychological) had a deleterious effect on sleep, in particular for sleep initiation and sleep maintenance. All of these studies had focused on sleep quality or insomnia severity, with various definitions and assessment methods: home-made questionnaires [26], Pittsburg Sleep Quality Index [25, 29], Insomnia Severity Index [28], Medical Outcome Study Sleep Scale [24], and Sleep Diary [27]. These methods have shown advantages in specific settings such as identifying good and bad sleepers or assessing changes in both nighttime and daytime components of insomnia after treatment [30, 31]. Nevertheless, none was designed to assess insomnia diagnosis based on the currently commonly used DSM-5 or ICSD-3. Furthermore, none has been formally validated in MS, and their measurement and structural invariance are also unknown in this neurological disease, as is the case for numerous neurological conditions. Capitalizing on the formal ID diagnosis [1, 2], our study found no link between MS clinical characteristics (i.e. age at onset, duration of the disease, MS type, EDSS, and MS treatment) and ID diagnosis. This lack of relationship corroborates the large Portuguese multicenter, hospital-based cross-sectional study performed by Viana and coworkers relying on ICSD-3 chronic ID [4]. All together, these results suggest that ID diagnosis is very poorly associated with MS clinical characteristics. It is now well admitted that predisposing, precipitating, and perpetuating factors all play a role in the formation of ID [32]. Following this theoretical approach, a primary medical disorder and its related clinical characteristics may be a precipitating factor in eliciting insomnia. Over time, perpetuating factors emerge to contribute and intensify insomnia. From this perspective, all patients with ID develop emotional, behavioral, and cognitive features that contribute to their insomnia. These features have been integrated in Harvey’s cognitive model for the maintenance of insomnia that was selected as the guide to the present research [10]. Our results are in line with this theoretical framework. Indeed, contrary to MS clinical peculiarities, we documented that ID comorbid to MS was strongly associated with increased levels of cognitive and somatic arousal, more frequent engagement in sleep-related safety behaviors, and higher endorsement of dysfunctional beliefs about the consequences of insomnia on daytime functioning and worry about insomnia. In this last respect, our findings are in accordance with the only study that has assessed insomnia in patients with MS using ICSD-3 standard diagnostic criteria and describing that patients with ID had a higher endorsement of maladaptive beliefs about sleep rated on the DBAS [4]. In this study, only DBAS total scores were reported. Otherwise, we originally reported that patients with MS with ID did not differ from sex-, age-, and insomnia severity–matched neurological disease-free individuals with insomnia regarding the intensity of emotional, behavioral, and cognitive processes involved in the maintenance of insomnia. This last observation is in accordance with evidences having emphasized the need to reconsider the traditional model of “secondary insomnia” and to propose new approaches to understand insomnia that is comorbid with another medical and/or psychiatric illness [33]. In this standpoint, DSM-5 and ICSD-3 nosological systems have both removed the distinction between “primary” and “secondary” insomnia [1, 2]. Furthermore, our results are in line with recently published studies that have shown the efficacy of CBT-I in patients with MS on sleep parameters [34, 35]. Unfortunately, these pioneering studies did not assess the impact of CBT-I on the variation of dysfunctional beliefs about sleep, sleep-related safety behaviors, and presleep cognitive arousal. In any event, taken together, these results pinpoint the need to consider ID comorbid to MS as a full-fledge clinical entity, underpinned by psychological factors, and requiring specific care. In the present study, the relationship found between ID diagnosis in patients with MS, and anxious and depressive symptoms are consistent with Viana and coworkers’ study capitalizing on the formal ID diagnosis [4]. It also substantiates several studies showing a robust association between poor sleep quality and severity of both depressive [24, 25, 36] and anxious symptoms [24] in MS. Pain and fatigue are key symptoms in MS and have been rated by patients as two of their most important symptoms [37, 38]. Studies examining relationships of MS-related fatigue to formal sleep disorders (i.e. obstructive sleep apnea, restless legs syndrome, periodic limb movement disorder, and nocturia) remain scarce though reporting inconsistent conclusions [3, 6, 25, 28, 39, 40]. By contrast, MS-related fatigue has been systematically associated with both self-reported sleep quality [26, 27, 36] and more recently with ID diagnosis [4]. Note that this last observation was also highlighted in our study. Similar to fatigue, pain intensity rated on specific instruments [4, 25, 26] or assessed by visual numeric scales [24] has been robustly related to sleep quality in MS. In accordance with this literature, we found that insomniac patients with MS reported that pain directly and negatively affected their sleep. Neuropathic and visceral painful symptoms frequently reported in MS are likely to mimic somatic arousal manifestations such as stomach upset, dry feeling in throat, or cold feeling [41]. This observation led us to consider pain intensity as a potential confounding factor on the relationship between insomnia diagnosis and presleep somatic arousal symptoms in patients with MS. Our results indicated that this relationship was independent of pain intensity, thus favoring the distressing nature of presleep somatic arousal experienced at bedtime. Pain in MS population is heterogeneous and includes several pain syndromes (i.e. headache, neuropathic extremity pain, back pain, painful spasms, Lhermitte sign, and trigeminal neuralgia) and mechanisms [41]. The interactions between this heterogeneity and sleep disturbances need to be addressed. Finally, 14% of enrolled patients in the present study had a BMI score superior to 30, with no significant difference between patients with and without insomnia. This observation is in accordance with the large multicenter study performed by Viana and coworkers who found no association between BMI and insomnia diagnosis with quasisimilar BMI scores between MS-ID and MS-NID groups. In contrast to what has been reported in general population [42], insomnia comorbid to MS is not associated with overweight. This may be related to the fact that overweight in itself is a risk factor for MS [43]. Although this study has several strengths such as the inclusion of patients with MS with formal diagnosis of insomnia and neurological disease-free individuals with insomnia, there are some limitations that must be mentioned. Firstly, owing to the small sample size, our results cannot be generalized to all individuals with MS. Furthermore, this small sample size did not allow us to apply more sophisticated statistical methodologies, e.g. structural equation modeling, to examine the complex relationships between psychological processes and ID in MS. Another limitation is the cross-sectional design of our study not allowing us to explore the causal pathways between ID comorbid to MS and psychological processes involved in the maintenance of insomnia. Thirdly, we did not extensively assess physical symptoms related to MS (e.g. nocturia, spasticity, and muscle twitching) that may negatively affect sleep and lead to chronic insomnia. In chronic insomnia comorbid to MS, this relationship has to be systematically explored. Note that, in this context, Viana and coworkers [4] found no association between chronic insomnia diagnosis and functional systems involved including pyramidal, brainstem, sensory, and sphincters. Finally, no polysomnography was performed to definitively exclude sleep breathing disorders, sleep-related motor disorders, or parasomnia. However, it is important to note that dysfunctional psychological processes, in particular sleep- or insomnia-related cognitions, have been documented in patients with comorbid sleep apnea syndrome or comorbid RLS and insomnia [44, 45]. This observation indicates that these “organic” sleep disorders deserve more diagnostic attention regarding possible insomnia-specific symptoms. In MS, it remains nevertheless an open question. Conclusion ID comorbid to MS is associated with the classical psychological factors perpetuating ID in neurological disease-free individuals with insomnia. Furthermore, very recent literature provided evidence that CBT-I is an effective treatment for ID comorbid to MS. Primary care providers and neurologists should consider target-oriented therapies like cognitive behavioral therapy for chronic insomnia as a treatment approach for ID comorbid to MS. Disclosure statement This was not an industry supported study. All authors have indicated no financial conflicts of interest. Notes Conflict of interest statement. None declared. References 1. American Academy of Sleep Medicine. International Classification of Sleep Disorders . 3rd ed. Darien, IL: American Academy of Sleep Medicine; 2014. 2. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders . 5th ed. Washington, DC: American Psychiatric Association; 2013. 3. Veauthier Cet al.  . Fatigue in multiple sclerosis is closely related to sleep disorders: a polysomnographic cross-sectional study. Mult Scler . 2011; 17( 5): 613– 622. Google Scholar CrossRef Search ADS PubMed  4. Viana Pet al.  . InMS: chronic insomnia disorder in multiple sclerosis – a Portuguese multicentre study on prevalence, subtypes, associated factors and impact on quality of life. Mult Scler Relat Disord . 2015; 4( 5): 477– 483. Google Scholar CrossRef Search ADS PubMed  5. Uhlig BLet al.  . Prevalence and associated factors of DSM-V insomnia in Norway: the Nord-Trøndelag Health Study (HUNT 3). Sleep Med . 2014; 15( 6): 708– 713. Google Scholar CrossRef Search ADS PubMed  6. Brass SDet al.  . The underdiagnosis of sleep disorders in patients with multiple sclerosis. J Clin Sleep Med . 2014; 10( 9): 1025– 1031. Google Scholar PubMed  7. Espie CA. Insomnia: conceptual issues in the development, persistence, and treatment of sleep disorder in adults. Annu Rev Psychol . 2002; 53: 215– 243. Google Scholar CrossRef Search ADS PubMed  8. Perlis MLet al.  . Psychophysiological insomnia: the behavioural model and a neurocognitive perspective. J Sleep Res . 1997; 6( 3): 179– 188. Google Scholar CrossRef Search ADS PubMed  9. Morin CMet al.  . Dysfunctional beliefs and attitudes about sleep among older adults with and without insomnia complaints. Psychol Aging . 1993; 8( 3): 463– 467. Google Scholar CrossRef Search ADS PubMed  10. Harvey AG. A cognitive model of insomnia. Behav Res Ther . 2002; 40( 8): 869– 893. Google Scholar CrossRef Search ADS PubMed  11. Mitchell MDet al.  . Comparative effectiveness of cognitive behavioral therapy for insomnia: a systematic review. BMC Fam Pract . 2012; 13: 40. Google Scholar CrossRef Search ADS PubMed  12. Kurtzke JF. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology . 1983; 33( 11): 1444– 1452. Google Scholar CrossRef Search ADS PubMed  13. Netzer NCet al.  . Using the Berlin Questionnaire to identify patients at risk for the sleep apnea syndrome. Ann Intern Med . 1999; 131( 7): 485– 491. Google Scholar CrossRef Search ADS PubMed  14. Allen RPet al.  . Restless legs syndrome/Willis-Ekbom disease diagnostic criteria: updated International Restless Legs Syndrome Study Group (IRLSSG) consensus criteria–history, rationale, description, and significance. Sleep Med . 2014; 15( 8): 860– 873. Google Scholar CrossRef Search ADS PubMed  15. Postuma RBet al.  . A single-question screen for rapid eye movement sleep behavior disorder: a multicenter validation study. Mov Disord . 2012; 27( 7): 913– 916. Google Scholar CrossRef Search ADS PubMed  16. Beck ATet al.  . Manual for the Beck Depression Inventory-II . Paris, France: Editions du Centre de Psychologie Appliquée; 1996. 17. Spielberger CD. State-Trait Anxiety Inventory: Bibliography  2nd ed. Palo Alto: Consulting Psychologists Press; 1989. 18. Chen PYet al.  . Validating the cross-cultural factor structure and invariance property of the Insomnia Severity Index: evidence based on ordinal EFA and CFA. Sleep Med . 2015; 16( 5): 598– 603. Google Scholar CrossRef Search ADS PubMed  19. Morin CMet al.  . Dysfunctional beliefs and attitudes about sleep (DBAS): validation of a brief version (DBAS-16). Sleep . 2007; 30( 11): 1547– 1554. Google Scholar CrossRef Search ADS PubMed  20. Ree MJet al.  . Investigating safety behaviours in insomnia: the development of the Sleep-Related Behaviours Questionnaire (SRBQ). Behav Change . 2004; 21( 1): 26– 36. Google Scholar CrossRef Search ADS   21. Nicassio PMet al.  . The phenomenology of the pre-sleep state: the development of the pre-sleep arousal scale. Behav Res Ther . 1985; 23( 3): 263– 271. Google Scholar CrossRef Search ADS PubMed  22. Debouverie Met al.  . Validity of a French version of the fatigue impact scale in multiple sclerosis. Mult Scler . 2007; 13( 8): 1026– 1032. Google Scholar CrossRef Search ADS PubMed  23. Cohen J. Statistical Power Analysis for the Behavioral Sciences . NY: Routledge Academic; 1988. 24. Leonavicius R. Peculiarities of sleep problems in multiple sclerosis. Neurol Psychiatry Brain Res . 2015; 21( 4): 148– 152. Google Scholar CrossRef Search ADS   25. Neau JPet al.  . Sleep disorders and multiple sclerosis: a clinical and polysomnography study. Eur Neurol . 2012; 68( 1): 8– 15. Google Scholar CrossRef Search ADS PubMed  26. Pokryszko-Dragan Aet al.  . Sleep disturbances in patients with multiple sclerosis. Neurol Sci . 2013; 34( 8): 1291– 1296. Google Scholar CrossRef Search ADS PubMed  27. Stanton BRet al.  . Sleep and fatigue in multiple sclerosis. Mult Scler . 2006; 12( 4): 481– 486. Google Scholar CrossRef Search ADS PubMed  28. Braley TJet al.  . Obstructive sleep apnea is an under-recognized and consequential morbidity in multiple sclerosis. J Clin Sleep Med . 2014; 10( 6): 709– 710. Google Scholar PubMed  29. Vitkova Met al.  . Factors associated with poor sleep quality in patients with multiple sclerosis differ by disease duration. Disabil Health J . 2014; 7( 4): 466– 471. Google Scholar CrossRef Search ADS PubMed  30. Moul DEet al.  . Self-report measures of insomnia in adults: rationales, choices, and needs. Sleep Med Rev . 2004; 8( 3): 177– 198. Google Scholar CrossRef Search ADS PubMed  31. Buysse DJet al.  . Recommendations for a standard research assessment of insomnia. Sleep . 2006; 29( 9): 1155– 1173. Google Scholar CrossRef Search ADS PubMed  32. Spielman AJet al.  . A behavioral perspective on insomnia treatment. Psychiatr Clin North Am . 1987; 10( 4): 541– 553. Google Scholar PubMed  33. Stepanski EJet al.  . Emerging research on the treatment and etiology of secondary or comorbid insomnia. Sleep Med Rev . 2006; 10( 1): 7– 18. Google Scholar CrossRef Search ADS PubMed  34. Clancy Met al.  . Outcomes of cognitive-behavioral treatment for insomnia on insomnia, depression, and fatigue for individuals with multiple sclerosis: a case series. Int J MS Care . 2015; 17( 6): 261– 267. Google Scholar CrossRef Search ADS PubMed  35. Abbasi SMset al.  . Effectiveness of cognitive behavioral therapy on the quality of sleep in women with multiple sclerosis: a randomized controlled trial study. Int J Community Based Nurs Midwifery . 2016; 4( 4): 320– 328. Google Scholar PubMed  36. Bøe Lunde HMet al.  . Poor sleep in patients with multiple sclerosis. PLoS One . 2012; 7( 11): e49996. Google Scholar CrossRef Search ADS PubMed  37. Fisk JDet al.  . The impact of fatigue on patients with multiple sclerosis. Can J Neurol Sci . 1994; 21( 1): 9– 14. Google Scholar CrossRef Search ADS PubMed  38. Kalia LVet al.  . Severity of chronic pain and its relationship to quality of life in multiple sclerosis. Mult Scler . 2005; 11( 3): 322– 327. Google Scholar CrossRef Search ADS PubMed  39. Veauthier Cet al.  . Sleep disorders in multiple sclerosis and their relationship to fatigue. Sleep Med . 2014; 15( 1): 5– 14. Google Scholar CrossRef Search ADS PubMed  40. Aydar Get al.  . Restless legs syndrome in multiple sclerosis. Eur Neurol . 2011; 65( 5): 302– 306. Google Scholar CrossRef Search ADS PubMed  41. Foley PLet al.  . Prevalence and natural history of pain in adults with multiple sclerosis: systematic review and meta-analysis. Pain . 2013; 154( 5): 632– 642. Google Scholar CrossRef Search ADS PubMed  42. Kalmbach DAet al.  . DSM-5 insomnia and short sleep: comorbidity landscape and racial disparities. Sleep . 2016; 39( 12): 2101– 2111. Google Scholar CrossRef Search ADS PubMed  43. Wesnes Ket al.  . Body size and the risk of multiple sclerosis in Norway and Italy: the EnvIMS study. Mult Scler . 2015; 21( 4): 388– 395. Google Scholar CrossRef Search ADS PubMed  44. Crönlein Tet al.  . Are dysfunctional attitudes and beliefs about sleep unique to primary insomnia? Sleep Med . 2014; 15( 12): 1463– 1467. Google Scholar CrossRef Search ADS PubMed  45. Yang CMet al.  . Psychological and behavioral factors in patients with comorbid obstructive sleep apnea and insomnia. J Psychosom Res . 2011; 70( 4): 355– 361. Google Scholar CrossRef Search ADS PubMed  © Sleep Research Society 2018. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.

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