Feasibility and Treatment Effect of a Web-Based Cognitive Behavioral Therapy for Insomnia Program in Individuals with Multiple Sclerosis: A Pilot Randomized Controlled Trial

At least 40% of individuals with multiple sclerosis (MS) experience chronic insomnia,^1–3  defined as difficulty falling asleep, difficulty maintaining sleep, or waking up too early at least 3 nights per week for the past 3 months.⁴  However, the incidence is likely higher as one study found that only 11% of individuals with MS who screened positive for moderate-to-severe insomnia reported being diagnosed by a health care provider,⁵  suggesting that a large portion of individuals with MS and insomnia are not treated. Considering the high incidence of insomnia in individuals with MS, determining an optimally effective treatment for insomnia in individuals with MS is warranted.

Cognitive behavioral therapy for insomnia (CBT-I) is the recommended nonpharmacologic treatment for chronic insomnia.^6–9  It has been shown to be a more effective long-term treatment for insomnia than medication,⁹  and the positive effects have been shown to persist for at least 10 years after treatment.¹⁰  Although evidence overwhelmingly supports CBT-I as an effective treatment for chronic insomnia, only recently have studies examined the use of CBT-I to treat insomnia in individuals with MS. Those recent studies have shown that CBT-I effectively improves sleep outcomes in individuals with MS.^11–13  In addition, CBT-I also seems to improve comorbid symptoms, including depression and fatigue, in individuals with MS.^11–13 

Typically CBT-I is conducted in-person, one-on-one between the client and the trained professional. However, CBT-I can be successfully conducted via Web-based formats,^14,15  with improvements in sleep efficacy and insomnia severity maintained long-term and with similar efficacy as traditional in-person CBT-I.¹⁶  Importantly, these results were obtained with minimal or no contact with a trained professional.¹⁷  Also, the high adherence and satisfaction rates add to the appeal of Web-based CBT-I.¹⁷  Web-based CBT-I is highly structured and provides information on the same topics that would be covered during traditional in-person CBT-I. Furthermore, although highly structured, Web-based CBT-I allows continuous assessment through sleep diaries, and a daily sleep score and algorithms are used to guide treatment.

The traditional in-person delivery method may be problematic for individuals with MS who have mobility difficulties that make attending in-person sessions challenging. In addition, access to individuals trained in providing CBT-I is often limited, particularly in rural areas. Behavioral sleep medicine providers tend to be located in urban areas, although even large cities sometimes have an insufficient number of providers. Two of the 15 most populous cities in the United States have no identified behavioral sleep medicine providers, and four of the ten most populous cities have one provider for every 1 million or more people.¹⁸  A Web-based CBT-I program would provide nearly universal access to CBT-I for individuals with MS. Also, a Web-based program would allow individuals to complete the sessions at their own pace, which would be advantageous for individuals with fatigue. An effective Web-based CBT-I program would provide an innovative avenue to address the high prevalence of insomnia in individuals with MS. Furthermore, a standardized Web-based program would be a cost-effective method of delivering CBT-I compared with the time-consuming traditional one-on-one CBT-I. Considering the potential benefits of Web-based CBT-I, the purpose of this study was to assess the feasibility (primary purpose) and treatment effect (secondary purpose) of CBT-I delivered using a Web-based application with or without biweekly telephone calls to improve sleep quality and fatigue in individuals with MS and symptoms of insomnia.

This study was approved by the University of Kansas Medical Center’s (KUMC’s) institutional review board and was registered with clinicaltrials.gov (identifier: NCT03783585). Participants were recruited from the KUMC Frontiers Research Participant Registry, through the National Multiple Sclerosis Society’s (NMSS’s) website and newsletters, and from the MS specialty clinic at KUMC. Informed consent was obtained from all participants.

Individuals were eligible to participate in the study if they 1) were 18 to 80 years old; 2) were diagnosed as having relapsing-remitting or secondary progressive MS; 3) had mild-to-moderate disability (Patient-Determined Disease Steps [PDDS] scale score ≤4)¹⁹ ; 4) reported difficulty falling asleep, difficulty maintaining sleep, or waking up too early at least 3 nights per week for the past 6 months; 5) scored 10 or greater on the Insomnia Severity Index (ISI)²⁰ ; 6) were English speaking; 7) reported having daily access to internet service, 8) reported being comfortable with using computers, and 9) reported having a high school diploma, to serve as a proxy measurement of adequate reading ability to participate in the study. Individuals were excluded from participating if they 1) had a known untreated sleep disorder (such as sleep apnea or restless legs syndrome); 2) scored greater than 3 on the STOP BANG (snoring, tiredness, observed apnea, high blood pressure, BMI, age, neck circumference, and male gender) questionnaire²¹  (indicating an elevated risk of sleep apnea); 3) had an increased risk of restless legs syndrome on the Restless Legs Syndrome–Diagnostic Index²² ; 4) were diagnosed as having primary progressive MS due to possible unique neuropathology and clinical course^23,24 ; 5) had a Patient Health Questionnaire-9 (PHQ-9) score of 15 or greater, indicating severe depression, or endorsed any suicidal ideation²⁵ ; 6) reported having a nervous system disorder other than MS; 7) reported experiencing a relapse and/or corticosteroid use in the past 8 weeks; or 8) performed shift work.

Feasibility was assessed as 1) recruitment—the number of people enrolled of the number of people contacted, 2) retention—the number of participants who completed the study, 3) attrition—the number of individuals who dropped out of the study, 4) adherence—the number of Web-based CBT-I sessions completed, and 5) satisfaction with the intervention. Treatment satisfaction was assessed at the end of the intervention using a 5-point Likert scale (0 = very dissatisfied and 4 = very satisfied). Treatment effect on sleep quality and fatigue was assessed using the ISI,²⁰  the Pittsburgh Sleep Quality Index (PSQI),²⁶  and the Modified Fatigue Impact Scale (MFIS),²⁷  which were administered at baseline and after completing the Web-based CBT-I intervention. Because depression, anxiety, sleep self-efficacy, and motivation are known factors that may modulate the treatment effect, the PHQ-9,²⁵  the 7-item Generalized Anxiety Disorder Scale (GAD-7),²⁸  the Sleep Self-Efficacy Scale (SSES),²⁹  and Motivation to Change Sleep Behavior (MCSB; a 5-point Likert scale with 0 = not at all motivated and 4 = very motivated) were also assessed at baseline and after the intervention. Study data were collected and managed using the REDCap (Research Electronic Data Capture) tool³⁰  hosted at KUMC. REDCap is a secure, Web-based application designed to support data capture for research studies, providing 1) an intuitive interface for validated data entry, 2) audit trails for tracking data manipulation and export procedures, 3) automated export procedures for seamless data downloads to common statistical packages, and 4) procedures for importing data from external sources.

After completion of the consent document and baseline assessment, participants were randomized to one of two groups: 1) a group that participated in a 6-week interactive Web-based CBT-I program called Go! to Sleep³¹  (wCBT-I group) or 2) a group that participated in the same 6-week Web-based CBT-I program and also received one-on-one, semistructured telephone calls (wCBT-I + calls group; one call during week 2 and another during week 4). These calls were delivered by research personnel trained and experienced in motivational interviewing to help the participant problem solve as needed and provide supportive accountability. The Web-based CBT-I program delivered typical CBT-I treatment techniques of stimulus control, sleep restriction, behavioral modifications, and cognitive restructuring. The Go! to Sleep program has been previously well-described.^32,33  In brief, it is an interactive, Web-based, 6-week program that teaches cognitive and behavioral approaches with daily lessons (41 total) to manage sleep as well as mental and physiologic arousal. Participants receive a daily e-mail reminder to access the program. The program has been shown to produce clinically meaningful improvements in insomnia severity in adults with insomnia, both after completion of the intervention and at 4-month reassessment.³²  In addition, this Web-based application was shown to improve insomnia severity in adults with Parkinson disease.³³  The Web-based application was modified by the creator of the program (M.D.) to tailor the program to be more specific and applicable to people with MS to reduce the risk of exacerbating fatigue and falls.

All the participants received an e-mail from the study coordinator immediately after randomization containing 1) stepwise instructions on how to register for the Web-based CBT-I program, 2) encouragement to initiate the program as soon as possible and to develop a consistent routine to participate in the program each day, 3) the study coordinator’s e-mail and telephone number to be used in case of questions, and 4) instructions to complete the postassessment questionnaires that would be sent to them via e-mail at the end of their program. Participants in the wCBT-I + calls group were also asked to provide availability to receive the biweekly semistructured calls.

All the data were analyzed using SPSS Statistics for Windows, version 22.0 (IBM Corp). Only participants who completed at least 27 of the 41 modules were considered to have completed the Web-based CBT-I program and were included in the data analysis. One-way analyses of variance (ANOVAs) and χ² analyses were used to assess differences in demographic variables between the two groups at baseline. Feasibility was assessed using frequency analysis (recruitment, retention, attrition, and adherence) and one-way ANOVA (satisfaction). To assess within-group treatment effects, a repeated-measures ANOVA model generated parameter estimates to determine whether there was a significant change from baseline to reassessment for each outcome. Within-group effect sizes (Cohen’s d) were used to examine the magnitude of change in the outcome measures from baseline to reassessment. Cohen’s d was interpreted as small, d = 0.2; medium, d = 0.5; and large, d = 0.8.³⁴  Change scores were calculated (reassessment score – baseline score) for each outcome, and one-way ANOVAs were assessed for between-group differences. The number of participants who met the minimal clinically important difference (MCID) was also reported for the primary outcomes. The alpha level was set at 0.05.

The wCBT-I group consisted of ten women with a mean ± SD age of 50.1 ± 11.8 years. All of them had relapsing-remitting MS (mean ± SD PDDS scale score = 1.3 ± 1.5). The wCBT-I + calls group consisted of nine women and one man with a mean ± SD age of 53.8 ± 6.9 years. Nine of these individuals had relapsing-remitting MS and one had secondary progressive MS (mean ± SD PDDS scale score = 2.4 ± 1.3).

There were no statistically significant differences between the groups in sex, age, disease type, disease severity (as measured by the PDDS), marital status, working status, smoking status, consumption of alcohol, and number of years of education (Table 1). There were no differences between the groups in baseline performance on the ISI (P = .796), PSQI (P = .894), MFIS (P = .216), PHQ-9 (P = .466), GAD-7 (P = .267), SSES (P = .592), and MCSB (P = .567).

In total, 358 people were contacted to participate in the study (see Figure S1, which is published in the online version of this article at ijmsc.org, for a flow diagram). Of those contacted, 96 were assessed for eligibility. All eligible participants who agreed to enroll in the study were sent a link to complete the consent documents in REDCap by e-mail. Of these 43 individuals, two did not complete the consent documents and were not enrolled in the study. Therefore, 41 individuals enrolled in the study (recruitment rate, 11.5%). Of the 41 participants who completed informed consent, 21 were randomized to the wCBT-I group and 20 to the wCBTI-I + calls group. In total, 20 individuals completed the study (retention rate, 48.8%—10 of 21 [47.6%] for the wCBT-I group and 10 of 20 [50%] for the wCBT-I + calls group; attrition rate, 51.2%—11 of 21 [52.4%] for the wCBT-I group and ten of 20 [50%] for the wCBT-I + calls group). Eight of the ten individuals in the wCBT-I group completed all 41 lessons of the 6-week program, one individual completed 40 lessons, and another completed 37 lessons (adherence rate, 98.78%). Seven of the ten individuals in the wCBT-I + calls group completed all 41 lessons of the 6-week program, and one individual each completed 40, 39, and 29 lessons (adherence rate, 96.34%). Mean ± SD satisfaction with the intervention was significantly higher for the wCBT-I group (3.6 ± 0.52) compared with the wCBT-I + calls group (2.7 ± 1.1, P = .027).

See Table 2 for all baseline and reassessment values. Both groups demonstrated a significant improvement in the ISI (wCBT-I: P < .001, 9.1-point improvement, effect size = 2.154; wCBT-I + calls: P = .005, 4.9-point improvement, effect size = 0.908), although there was no significant between-group difference in the magnitude of change on the ISI (P = .068). Eight of the ten participants in the wCBT-I group and five in the wCBT-I + calls group showed an MCID of at least 6 points on the ISI.³⁵  The PSQI significantly improved from baseline to postassessment for both groups (wCBT-I: P < .001, 4.2-point reduction, effect size = 1.355; wCBT-I + calls: P = .028, 2.3-point reduction, effect size = 0.776), but there was no between-group difference (P = .178). Seven of the ten participants in the wCBT-I group and four of ten in the wCBT-I + calls group showed an MCID of 3 points or more on the PSQI.³⁶  Only the wCBT-I group demonstrated a significant improvement on the MFIS (P = .004, 11-point improvement, effect size = 1.199). There was no between- group difference in the magnitude of change on the MFIS (P = .242). Five individuals in both groups showed an MCID of at least 10 points on the MFIS.³⁷ 

The wCBT-I group demonstrated a significant improvement on the PHQ-9 (P = .004, effect size = 1.331) indicating improved depression, but the wCBTI + calls group did not (P = .111, effect size = 0.448); there was no between-group difference. Both groups demonstrated significant improvement on the GAD-7 (wCBT-I: P = .002; wCBT-I + calls: P < .001) and the SSES (wCBT-I: P = .014; wCBT-I + calls: P = .026), but there were no between-group differences in the magnitude of change (Table 2). The MCSB scores did not change for either group (Table 2).

To our knowledge, this is the first study to demonstrate that CBT-I provided through a Web-based format is feasible in individuals with MS. Furthermore, individuals with MS who participated in the Web-based CBT-I program experienced a significant improvement in insomnia severity, sleep quality, sleep self-efficacy, and anxiety. Those in the group without biweekly telephone calls also had improved depression and fatigue. Therefore, Web-based CBT-I may provide an option for a stepped-care approach to treating insomnia in individuals with MS.

The results of this study extend the findings from meta-analyses that reported Web-based CBT-I being effective in improving insomnia symptoms and sleep outcomes^16,17,38  to a unique sample. Other studies that specifically focused on samples with unique impairments and challenges (cancer survivors³⁹  and people with Parkinson disease³³ ) found Web-based CBT-I to be effective in improving sleep outcomes. The emerging evidence that Web-based CBT-I may be effective in individuals with various medical conditions is important because these individuals often have physical and/or cognitive impairments that make attending in-person sessions difficult. In addition, because fatigue is a common complaint in individuals with MS, Web-based CBT-I is advantageous to allow individuals to complete the sessions at a pace appropriate to their fatigue levels.

Interestingly, there was a nonsignificant (P = .068) difference in insomnia severity improvement for the wCBT-I group compared with the wCBT-I + calls group. Also, the wCBT-I group experienced a significant improvement in fatigue, whereas the wCBT-I + calls group did not. There were no group differences in demographic or baseline data to account for this difference in improvement between the groups. We expected that the biweekly calls with a trained counselor in motivational interviewing techniques would provide additional support, accountability, and problem-solving and would enhance outcomes compared with the group that did not participate in the calls, but this was not the case. Perhaps individuals in the wCBT-I + calls group relied on the counselor for support, and this was counterproductive to optimally learn and implement the CBT-I principles. However, sleep self-efficacy increased for both groups, which seems to negate or at least limit this supposition. Another possible explanation is that the biweekly calls were burdensome to the participants, potentially expressed by the lower satisfaction scores from individuals in the wCBT-I + calls group. Regardless of the rationale, the wCBT-I group having had improved outcomes suggests that calls from research personnel to provide support are not needed to optimize outcomes. A Web-based–only program is preferable due to reduced costs and burden to provider and participants.

The small sample size of this study limits the interpretation of the results. Also, this study included only individuals with MS with minimal-to-moderate depression and minimal disability, which limits the generalizability of the results. A third limitation is that the study did not include a group that received in-person CBT-I or another Web-based program, so we are unable to determine the treatment effect of CBT-I compared with another mode of CBT-I delivery or compared with another type of Web-based treatment. Although previous studies show that CBT-I delivered using Web-based formats have similar efficacy as traditional in-person CBT-I,¹⁶  this has yet to be shown in people with MS. Future studies are needed to compare in-person CBT-I with Web-based CBT-I in individuals with MS.

Another limitation is the high attrition rate. Results should be interpreted with caution because there is a high chance of attrition bias, with participants who complete the study being more likely to have good outcomes. The meta-analyses of Web-based CBT-I studies report an attrition rate of 22% to 25.5%,^16,17,38  which is lower than the 51.2% attrition rate in the present study. However, the attrition rate of CBT-I provided in a clinical setting is 14% to 40%.⁴⁰  The Web-based CBT-I study in cancer survivors reported a 7% attrition rate.³⁹  The Web-based CBT-I study in cancer survivors included an in-person screening session that included 15 minutes of instruction for how to use and navigate the Web-based platform.³⁹  Perhaps this in-person instruction contributed to a low attrition rate. The present study did not include any in-person sessions; instructions on how to use the Web-based platform were e-mailed to participants, the individuals in the wCBT-I group did not receive contact from research personnel after being contacted for consent and baseline assessment, and the individuals in the wCBT-I + calls group were called only two times during the intervention. We conducted a post hoc analysis to determine whether there were group differences in demographic factors or performance on baseline assessment for those who completed the study (“completers”; n = 20) and those who dropped out (“noncompleters”; n = 19). There were no significance differences between completers and noncompleters in sex (P = .517), age (P = .664), disease type (P > .99), disease severity (P = .208), marital status (P = .485), working status (P = .927), smoking status (P = .547), consumption of alcohol (P = .429), and number of years of education (P = .126). There was no difference between completers and noncompleters in baseline performance on the ISI (P = .881), MFIS (P = .911), PHQ-9 (P = .376), GAD-7 (P = .641), SSES (P = .118), and MCSB (P = .298), but the noncompleters did have a statistically significantly higher mean ± SD PSQI (13.5 ± 3.9) at baseline assessment compared with the “completers (10.2 ± 3.2, P = 0.006), which may have influenced completion of the study. One might hypothesize that those with poorer sleep quality would be more likely to complete an intervention to improve sleep; however, perhaps the poorer sleep quality was a hindrance to participation.

A Web-based CBT-I study in individuals with Parkinson disease reported an attrition rate of 43%,³³  which is similar to the attrition rate in the present study. It does not seem that the individuals with Parkinson disease were provided in-person instructions on how to use and navigate the Web-based program, but they did receive weekly phone reminders to participate in the program they were randomized to (Web-based CBT-I or standard sleep hygiene education). This seems to put into question whether contact from research personnel is an effective addition to Web-based CBT-I, particularly considering the additional cost and burden to staff and participants. However, the type of contact (therapeutic vs reminder to participate) and the experience of the provider (research assistant vs certified behavioral sleep medicine provider) presumably influence the effectiveness of the contact. In addition, future studies should consider the type and amount of instruction that is optimal for retention and adherence, for implementing in a clinical setting as well as remotely. Ideally, the instruction could be provided remotely (ie, via recorded video) to increase the accessibility of the Web-based CBT-I program. If implemented in a clinical setting, in-person instruction on how to use and navigate the Web-based program might enhance adherence and, thus, lead to better outcomes.

This study provides an interesting possibility that Web-based CBT-I may be an effective delivery mode of CBT-I for individuals with MS. Future studies should investigate whether there are specific characteristics of individuals with MS who are more likely to experience improvement of sleep outcomes and concomitant symptoms with Web-based delivery and those who are more likely to need in-person–delivered CBT-I (such as motivation, social support, depression, fatigue, and comfort with technology). The meta-analysis by Cheng and Dizon¹⁷  estimated that one of every four individuals with chronic insomnia will recover using Web-based CBT-I, so it seems that even in the general population there are individuals who are more likely to experience improvement with Web-based CBT-I and those who likely need more individualized, supportive, in-person CBT-I. A recent study reported that individuals with some subtypes of insomnia experienced improvement in sleep outcomes with CBT-I, whereas individuals with other subtypes did not,⁴¹  suggesting that there are variables that influence the likelihood that CBT-I will be effective for a given individual. Future studies are needed to determine which variables influence likelihood to experience improvement in sleep outcomes with use of Web-based CBT-I,⁴²  particularly in populations with unique challenges and needs, including individuals with MS.

In conclusion, this study provides initial evidence that Web-based CBT-I is feasible and effective in improving sleep outcomes and concomitant symptoms in individuals with MS. Future studies are needed to determine which individuals with MS are more likely to experience improvement in sleep outcomes using Web-based CBT-I and which individuals are more likely to need CBT-I delivered in-person by an experienced provider. This study provides an exciting possibility that Web-based CBT-I may increase the accessibility of CBT-I treatment and provide a stepped-care approach to treating chronic insomnia in individuals with MS.

We thank our participants; Rhonda Vansuch, Tom Gubanc, and Tiffany Brown at Cleveland Clinic for their technical support and reporting; Alexis Hawks, MPH, for performing the biweekly phone calls; and the NMSS for assistance with recruitment.

Dr Siengsukon is owner and CEO of Sleep Health Education LLC and has received funding support from the American Heart Association, the NMSS, and the National Institutes of Health. Dr Drerup receives salary support for a development/consultant role for the Go! to Sleep program from the Wellness Institute at Cleveland Clinic. Dr Beck declares no conflicts of interest.

This study was supported in part by a National Institutes of Health Clinical and Translational Science Award (grant UL1 TR002366) to the University of Kansas Medical Center.