Implementing Computer-Based Psychotherapy Among Veterans in Outpatient Treatment for Substance Use Disorders
Abstract
Objective:
Computer-based psychotherapy interventions (CBPIs) are increasingly offered as first-level access to evidence-based mental health treatment. However, their implementation has not been evaluated in public-sector outpatient settings.
Methods:
An evidence-based CBPI for insomnia was implemented with provider and patient education sessions, on-site Internet access, and clinician telephone support. Persons receiving care at a Veterans Health Administration substance abuse treatment clinic were screened for chronic insomnia and offered CBPI access. The feasibility of this strategy was evaluated in a pre-post design, which assessed engagement and completion rates, participant-reported acceptability, and clinical outcomes.
Results:
Of 100 veterans referred, 51 enrolled in the program, of whom 22 (43%) completed all sessions, 13 (26%) partially completed the program, and 16 (31%) did not engage. There were no statistically significant differences between these three groups in baseline characteristics. In the total sample, Insomnia Severity Index (ISI) scores decreased (improved) by 32% (mean±SD of 6.3±6.2 points, t=6.82, df=44, p<.001). Veterans who completed all six sessions displayed clinically and statistically significant improvements on the ISI compared with those who did not engage, as shown in a regression analysis that controlled for baseline insomnia severity, time between assessments, and sedative-hypnotic medication use (F=3.87, df=4 and 40, p≤.004). Among all participants, 67% agreed that they would engage in another CBPI in the future. When questioned about potential barriers, 36% of the full sample endorsed a preference for face-to-face therapy.
Conclusions:
A strategy of brief provider and patient education, on-site Internet access, and telephone support was feasible and effective for implementing CBPIs in outpatient substance abuse treatment settings for veterans.
Internet-based technology is increasingly used to deliver a broad spectrum of health interventions. One of the fastest growing segments of this technology involves computer-based psychotherapy interventions (CBPIs), consisting primarily of self-guided, Internet-based programs that use cognitive-behavioral therapy (CBT) techniques to improve knowledge, manage symptoms, or induce behavior change (1). CBPIs present standardized yet individualized material in rich formats, including audio, video, and text.
The potential health service benefits of CBPIs are considerable. They can reduce transportation barriers, reduce barriers associated with the stigma of seeking mental health care, accommodate deficiencies in the number of trained therapists, and promote self-efficacy (2–4). CBPIs may also increase clinic productivity and reduce costs (5–7).
Such interventions have the potential to improve care for common mental disorders such as depression, anxiety, and especially insomnia. Insomnia is one of the most common complaints of veterans from recent conflicts and is strongly associated with trauma, problematic alcohol use, decreased quality of life, and use of significantly more health services (8–13). Sedative-hypnotics, many of which are associated with abuse potential and a host of side effects, are the current mainstay of treatment (14,15).
Face-to-face CBT has been shown in multiple studies, including meta-analyses, to be superior to both placebo and active pharmacologic agents for the treatment of insomnia, prompting the American Academy of Sleep Medicine to recommend its use as a first-line treatment (16,17). This therapy is being actively disseminated throughout the Veterans Health Administration (VHA) but requires extensive provider training and in-person client attendance (18). These barriers can be overcome through the use of self-help CBPI versions as the first-line treatment, with referral to face-to-face therapy if the CBPI fails. Such CBPIs for insomnia have shown efficacy (19).
As the development and use of evidence-based self-help CBPIs grow, it will be important to understand how current outpatient treatment programs can benefit from implementing this mode of service delivery. To date, work in this area has focused on efficacy testing through controlled trials in selected populations. Strategies for implementing self-help CBPIs in outpatient treatment settings serving populations with extensive comorbidity and that include provider referral and support have not been developed or evaluated. The objective of this study was to assess the feasibility of a six-session self-help CBPI for insomnia as well as the strategy used to implement it among users of VHA outpatient substance use treatment services, including an exploration of the level of assistance required to support participants in the program.
Methods
Study Design and Intervention
This study explored the feasibility of implementing a self-help CBPI for insomnia in a VHA substance use disorder outpatient care site using an uncontrolled pre-post intervention format evaluating program engagement, completion, acceptability, and clinical response. The CBPI, called Restore, is a six-session, Internet-based, self-administered therapy consisting of interactive instruction on sleep hygiene, stimulus control, relaxation, sleep restriction, and cognitive distortions. Therapeutic tools include videos, questions, a sleep log, and homework. Providers can follow treatment progress electronically. The program has shown efficacy in a controlled trial involving 118 persons with chronic insomnia (20).
The Replicating Effective Programs (REP) framework for implementation, developed by the Centers for Disease Control and Prevention, provides extensive guidance in all phases of implementation, from the identification of quality gaps in mental health services to the maintenance of newly implemented interventions. This study was patterned after the REP concept of piloting the intervention before full implementation efforts. The four core components of the implementation strategy used in this study were drawn from the many concepts described in the preimplementation phase of REP (training, facilitation, technical assistance, and the identification of a “program champion”).
In this study, the core components were as follows. First, all clinic providers attended an education session about Restore and its implementation in which they were introduced to recommended treatments for insomnia and the efficacy of CBT for treating it, as well as to the format, content, and efficacy of the program. Second, engagement and completion were facilitated through the use of an optional Internet-connected computer set up in a private part of the clinic. Third, prior to using the program, enrollees participated in a 45-minute face-to-face education session and discussion covering insomnia, its behavioral components, and treatment, as well as the content, format, and technical aspects of Restore. Fourth, support was provided through facilitation and technical assistance from a “program champion,” who contacted patients once a week, primarily over the phone, and provided face-to-face help sessions when requested by the participant. Goals of support were to provide encouragement for engagement and completion and to answer clinical and technical questions regarding either insomnia treatment or the program. For this pilot study, the amount, format, and content of these contact sessions were exploratory and performed by the principal investigator (EH), who was not a provider at the clinic. The goal was to use data from these interactions to modify the implementation strategy for future implementation efforts to where the support role would be accomplished by individuals within the clinic. The institutional review boards of the Veterans Affairs Connecticut Health Care System and the Yale University School of Medicine approved this study.
Sample
The target population was veterans with chronic insomnia who were receiving outpatient substance abuse treatment. Entry criteria were consistent with general diagnostic criteria for insomnia disorder: a delay in sleep onset, delay in return to sleep after awakening, or early morning awakening longer than 30 minutes for three or more nights a week for three months or longer with at least one symptom of daytime impairment (including fatigue and difficulty concentrating) (21). Participants were English speaking and had no evidence of diagnosed sleep apnea or restless leg syndrome by self-report or medical record review; no past-month psychiatric emergency department or inpatient admissions, nor active suicidal or homicidal ideation; no concurrent treatment with buprenorphine, methadone, or CBT for insomnia; and no engagement in evening or night shift work. All medications were allowed, including sedative-hypnotics.
Measures
Feasibility was operationalized as participant engagement in or completion of the program; acceptability, as assessed in a series of follow-up survey questions; and positive clinical response, measured by improvement on the Insomnia Severity Index (ISI), an assessment of sleep dissatisfaction and daytime impairment (22,23). Secondary outcomes included the number of sedative-hypnotic medication doses taken weekly and the 12-Item Short-Form (SF-12) health-related quality-of-life measure (24). Additional measures included sociodemographic characteristics, Internet use, psychiatric diagnoses, profile of current substance use, and the number and content of CBPI support contacts. Participants completed measures before program initiation, after completion or after a decision either to discontinue or to not engage, and three months after the follow-up assessment for those who completed the program.
Analysis
Using the provider supervisory function of the program, participants were categorized as “completers” if they completed all six active modules, “partial completers” if they completed fewer than six, and “nonengagers” if they did not complete any modules. Bivariate analysis of differences between the engagement and completion groups and baseline variables were tested with chi square tests and analysis of variance.
Acceptability questions used a 7-point Likert scale, and responses were analyzed with chi square tests in three categories according to engagement or completion status. For general CBPI acceptability questions, the entire sample was used. For Restore-specific questions, only persons who fully or partially completed the program were used. For questions regarding early dropout, responses of only those who partially completed or did not engage in the program were analyzed.
Pre- and postintervention clinical outcomes, including ISI and SF-12 scores (24) and the total weekly number of sedative-hypnotic doses, were compared by using paired t tests and chi square. The follow-up ISI score was compared in linear regression models. This analysis was by completion or engagement status, with adjustment for baseline ISI score, days between baseline and follow-up measurement (in order to adjust for spontaneous improvement), as well as the number of sedative-hypnotic doses used in the week before assessment at baseline and follow-up. Effect sizes for the ISI were calculated with dichotomous dummy codes for intervention completers and partial completers compared with those who did not engage.
Results
Engagement, Completion, and Sample Characteristics
One hundred individuals were screened, and 51 were enrolled. [Reasons for exclusion are described in a CONSORT diagram provided as an online supplement to this article.] Of enrollees, 43% completed the program, 26% completed part of the program, and 31% did not engage (Table 1). The population enrolled was largely male (88%) and older (mean age of 52.2±10.4 years) with 98% reporting a history of an alcohol or a drug use disorder or combination, whereas 49% reported current problematic alcohol or drug use and 46 (90%) reported a psychiatric diagnosis. The mean insomnia level for the sample represented moderate to severe insomnia (ISI score=20 out of 28, with higher scores indicating more severe insomnia), and 39 (77%) veterans reported using at least one sedative-hypnotic regularly. There were no statistically significant differences between groups of completers, partial completers, and nonengagers for baseline characteristics (Table 1).
| Characteristic | Total sample (N=51) | Completers (N=22, 43%)a | Partial completers (N=13, 26%)a | Did not engage (N=16, 31%)a | ||||
|---|---|---|---|---|---|---|---|---|
| N | % | N | % | N | % | N | % | |
| Sociodemographic | ||||||||
| Age (M±SD) | 52.2±10.4 | 54.7±6.4 | 52.2±9.6 | 48.7±14.4 | ||||
| Gender (male) | 45 | 88 | 20 | 44 | 10 | 22 | 15 | 33 |
| Race-ethnicity | ||||||||
| White | 27 | 53 | 8 | 30 | 8 | 30 | 11 | 41 |
| African American | 19 | 37 | 10 | 53 | 5 | 26 | 4 | 21 |
| Other | 5 | 10 | 4 | 80 | 0 | — | 1 | 20 |
| Education level | ||||||||
| High school completion or less | 17 | 33 | 7 | 41 | 6 | 35 | 4 | 24 |
| At least some college | 34 | 67 | 15 | 44 | 7 | 21 | 12 | 35 |
| Diagnostic | ||||||||
| Substance use disorder | ||||||||
| Alcohol and drug related | 24 | 47 | 10 | 42 | 7 | 29 | 7 | 29 |
| Alcohol only | 7 | 14 | 2 | 29 | 2 | 29 | 3 | 43 |
| Drug only | 19 | 37 | 9 | 47 | 4 | 21 | 6 | 32 |
| None | 1 | 2 | 1 | 100 | 0 | — | 0 | — |
| Schizophrenia and psychosis | 10 | 20 | 4 | 40 | 3 | 30 | 3 | 30 |
| Major depression | 22 | 43 | 10 | 46 | 6 | 27 | 6 | 27 |
| Bipolar disorder | 11 | 22 | 5 | 46 | 3 | 27 | 3 | 27 |
| PTSD | 23 | 45 | 7 | 30 | 8 | 35 | 8 | 35 |
| Other anxiety disorder | 22 | 43 | 9 | 41 | 5 | 23 | 8 | 36 |
| Comorbid general medical diagnosis | ||||||||
| None | 9 | 18 | 2 | 22 | 1 | 11 | 6 | 67 |
| 1 or 2 | 22 | 43 | 8 | 36 | 8 | 36 | 6 | 27 |
| ≥3 | 20 | 39 | 12 | 60 | 4 | 20 | 4 | 20 |
| Current problematic substance use | ||||||||
| Drug and alcohol | 8 | 16 | 6 | 75 | 2 | 25 | 0 | — |
| Alcohol only | 6 | 12 | 2 | 33 | 1 | 17 | 3 | 50 |
| Drug only | 11 | 22 | 5 | 46 | 5 | 46 | 1 | 9 |
| None | 26 | 51 | 9 | 35 | 5 | 19 | 12 | 46 |
| Total days of drug or alcohol use (or combination) in past month | 6.6 | 17.0 | 3.9 | 7.6 | 8.3 | 17.0 | 9.1 | 25.1 |
| Internet use | ||||||||
| At least once a day | 20 | 39 | 10 | 50 | 5 | 25 | 5 | 25 |
| Less than once a day, at least weekly | 16 | 31 | 8 | 50 | 2 | 13 | 6 | 38 |
| Less than once a week | 15 | 29 | 4 | 27 | 6 | 40 | 5 | 33 |
| Uses Internet only in clinic (not at home or elsewhere) | 20 | 39 | 9 | 45 | 4 | 20 | 7 | 35 |
| Clinical | ||||||||
| Insomnia Severity Index score (M±SD)b | 20.0±4.0 | 20.6±3.9 | 20.7±3.2 | 20.6±4.9 | ||||
| Sedative-hypnotic doses per week (M±SD)c | 8.2±7.0 | 8.4±7.4 | 8.1±6.6 | 8.1±7.0 | ||||
a
Between-group comparisons were tested with chi square for categorical variables and analysis of variance for continuous variables. Bonferroni-corrected alpha level for statistical significance was set at .003, corresponding to 18 variables tested. In no test was α<.05. Proportions displayed are based on the row, and the percentage may not sum to 100 due to rounding.
b
Possible scores range from 0 to 28, with higher scores indicating more severe insomnia.
c
For self-report data on sedative-hypnotic use, participants reported the total number of doses of selected sedative hypnotics used in the preceding week.
Acceptability
When asked about the acceptability of CBPI, 67% of enrolled veterans agreed that they would participate in another CBPI, whereas only 11% disagreed (Table 2). When asked if they would have preferred meeting in person, only 16 participants (36%) agreed (Table 2). For Restore-specific questions, 68% agreed that the program was helpful in reducing insomnia, with a higher, but not statistically significant, proportion of completers (74%) agreeing compared with partial completers (26%) (Table 3). On questions regarding nonengagement and noncompletion, agreement with any of the presented reasons was not strong (>50% agreeing or strongly agreeing), and differences between partial completers and nonengagers were not statistically significant (Table 4). Specifically, for the statement, “Access to a computer . . . was too difficult,” only 35% of the total sample agreed, 63% of whom were nonengagers.
| Item | Total sample (N=45)a | Engaged and completed (N=21)a | Engaged, did not complete (N=13)a | Did not engage (N=11)a | χ2b | p | ||||
|---|---|---|---|---|---|---|---|---|---|---|
| N | % | N | % | N | % | N | % | |||
| “I would participate in another computer-based therapy for another mental health, physical or other problem.” | 1.23 | .873 | ||||||||
| Strongly agree, agree | 30 | 67 | 15 | 50 | 9 | 30 | 6 | 20 | ||
| Somewhat agree or disagree, neutral | 10 | 22 | 4 | 40 | 3 | 30 | 3 | 30 | ||
| Strongly disagree, disagree | 5 | 11 | 2 | 40 | 1 | 20 | 2 | 40 | ||
| “I prefer meetings with a person rather than a computer-based or online therapy.” | 10.82 | .029 | ||||||||
| Strongly agree, agree | 16 | 36 | 3 | 19 | 9 | 56 | 4 | 25 | ||
| Somewhat agree or disagree, neutral | 23 | 51 | 14 | 61 | 3 | 13 | 6 | 26 | ||
| Strongly disagree, disagree | 6 | 13 | 4 | 67 | 1 | 17 | 1 | 17 | ||
| “I would be more likely to participate in a computer-based or online therapy if I had more instruction on the use of a computer and/or the Internet.” | 2.07 | .722 | ||||||||
| Strongly agree, agree | 13 | 29 | 7 | 54 | 4 | 31 | 2 | 15 | ||
| Somewhat agree or disagree, neutral | 17 | 38 | 9 | 53 | 4 | 24 | 4 | 24 | ||
| Strongly disagree, disagree | 15 | 33 | 5 | 33 | 5 | 33 | 5 | 33 | ||
| “I would be more likely to participate in computer-based or online therapy if I had more support from a clinician to help me use the intervention and work on the homework.” | 4.41 | .036 | ||||||||
| Strongly agree, agree | 11 | 24 | 8 | 73 | 2 | 18 | 1 | 9 | ||
| Somewhat agree or disagree, neutral | 21 | 47 | 9 | 43 | 7 | 33 | 5 | 24 | ||
| Strongly disagree, disagree | 13 | 29 | 4 | 31 | 4 | 31 | 5 | 39 | ||
| “I would be more likely to participate in computer-based or online therapy if the program was more user friendly.” | 1.78 | .777 | ||||||||
| Strongly agree, agree | 12 | 27 | 6 | 50 | 4 | 33 | 2 | 17 | ||
| Somewhat agree or disagree, neutral | 19 | 42 | 10 | 53 | 5 | 26 | 4 | 21 | ||
| Strongly disagree, disagree | 14 | 31 | 5 | 36 | 4 | 29 | 5 | 36 | ||
| “I would be more likely to participate in a computer-based or online therapy if the content could be accessed on a phone or other handheld device.” | 6.17 | .187 | ||||||||
| Strongly agree, agree | 9 | 20 | 1 | 11 | 4 | 44 | 4 | 44 | ||
| Somewhat agree or disagree, neutral | 21 | 47 | 11 | 52 | 6 | 29 | 4 | 19 | ||
| Strongly disagree, disagree | 15 | 33 | 9 | 60 | 3 | 20 | 3 | 20 | ||
a
A total of six participants were lost to follow-up and are missing follow-up measures. Percentages may not equal 100 due to rounding.
b
Between-group comparisons were tested with chi square tests, where df=1. The Bonferroni-corrected alpha level for statistical significance was set at .003, corresponding to 16 acceptability variables tested. Degrees of freedom for all tests equaled 4. Proportions displayed are based on the row, and percentages may not sum to 100 due to rounding. Percentages may not equal 100 due to rounding.
| Item | Engaged (N=34)a | Completed (N=21)a | Partially completed (N=13)a | χ2b | p | |||
|---|---|---|---|---|---|---|---|---|
| N | % | N | % | N | % | |||
| The Restore program was useful for reducing insomnia and/or improving sleep. | 4.44 | .035 | ||||||
| Strongly agree, agree | 23 | 68 | 17 | 74 | 6 | 26 | ||
| Somewhat agree or disagree, neutral | 11 | 32 | 4 | 36 | 7 | 64 | ||
| Strongly disagree, disagree | 0 | — | 0 | — | 0 | — | ||
| The content of the Restore program (not the homework) was easy to understand. | .81 | .369 | ||||||
| Strongly agree, agree | 19 | 56 | 13 | 68 | 6 | 32 | ||
| Somewhat agree or disagree, neutral | 15 | 44 | 8 | 53 | 7 | 47 | ||
| Strongly disagree, disagree | 0 | — | 0 | — | 0 | — | ||
| The homework prescribed by the Restore program was easy to complete.c | .35 | .554 | ||||||
| Strongly agree, agree | 16 | 49 | 11 | 69 | 5 | 31 | ||
| Somewhat agree or disagree, neutral | 17 | 52 | 10 | 59 | 7 | 41 | ||
| Strongly disagree, disagree | 0 | — | 0 | — | 0 | — | ||
a
Six participants were lost to follow-up and are missing follow-up measures. Percentages may not equal 100 due to rounding.
b
Between-group comparisons were tested with chi square tests, where df=1. Bonferroni-corrected alpha level for statistical significance was set at .003, corresponding to a total of 16 acceptability variables tested. Degrees of freedom for all tests equaled 4. Proportions displayed are based on the row, and percentages may not sum to 100 due to rounding.
c
An additional individual did not complete this question.
| Item | Noncompleters (N=23)a | Engaged but did not complete (N=13)a | Did not engage (N=10)a | χ2b | p | |||
|---|---|---|---|---|---|---|---|---|
| N | % | N | % | N | % | |||
| “I did not feel I would receive any more benefit.” | .80 | .669 | ||||||
| Strongly agree, agree | 1 | 4 | 1 | 100 | 0 | — | ||
| Somewhat agree or disagree, neutral | 11 | 48 | 6 | 55 | 5 | 46 | ||
| Strongly disagree, disagree | 11 | 48 | 6 | 55 | 5 | 46 | ||
| “Working with the online content (i.e., the mechanics of the website) was too difficult.” | .12 | .941 | ||||||
| Strongly agree, agree | 4 | 17 | 2 | 50 | 2 | 50 | ||
| Somewhat agree or disagree, neutral | 10 | 44 | 6 | 60 | 4 | 40 | ||
| Strongly disagree, disagree | 9 | 39 | 5 | 56 | 4 | 44 | ||
| “I had a difficult time understanding the online content.” | 1.43 | .492 | ||||||
| Strongly agree, agree | 1 | 4 | 0 | — | 1 | 100 | ||
| Somewhat agree or disagree, neutral | 8 | 35 | 5 | 63 | 3 | 38 | ||
| Strongly disagree, disagree | 14 | 61 | 8 | 57 | 6 | 43 | ||
| “The homework was too difficult.” | 5.76 | .056 | ||||||
| Strongly agree, agree | 2 | 9 | 1 | 50 | 1 | 50 | ||
| Somewhat agree or disagree, neutral | 10 | 44 | 3 | 30 | 7 | 70 | ||
| Strongly disagree, disagree | 11 | 48 | 9 | 82 | 2 | 18 | ||
| “I did not have enough time to complete the homework.” | 5.57 | .062 | ||||||
| Strongly agree, agree | 3 | 13 | 0 | — | 3 | 100 | ||
| Somewhat agree or disagree, neutral | 11 | 48 | 6 | 55 | 5 | 46 | ||
| Strongly disagree, disagree | 9 | 39 | 7 | 78 | 2 | 22 | ||
| “I did not feel I had enough support from my treatment team at the VA.” | .48 | .785 | ||||||
| Strongly agree, agree | 5 | 22 | 3 | 60 | 2 | 40 | ||
| Somewhat agree or disagree, neutral | 12 | 52 | 6 | 50 | 6 | 50 | ||
| Strongly disagree, disagree | 6 | 26 | 4 | 67 | 2 | 33 | ||
| “Access to a computer with an Internet connection was too difficult.” | 2.42 | .298 | ||||||
| Strongly agree, agree | 8 | 35 | 3 | 38 | 5 | 63 | ||
| Somewhat agree or disagree, neutral | 4 | 17 | 2 | 50 | 2 | 50 | ||
| Strongly disagree, disagree | 11 | 48 | 8 | 73 | 3 | 27 | ||
a
A total of six participants were lost to follow-up and are missing follow-up measures. In addition, one individual did not complete questions about reasons for nonengagement. Percentages may not equal 100 due to rounding.
b
Between-group comparisons were tested with chi square. Bonferroni-corrected alpha level for statistical significance was set at .003, corresponding to a total of 16 acceptability variables tested. Degrees of freedom for all tests equaled four. Proportions displayed are based on the row, and percentages may not sum to 100 due to rounding.
Clinical Outcomes
In the total sample, total ISI scores decreased by a mean of 6.3 points (32% decrease) from baseline to follow-up (t=6.82, df=44, p<.001). Among completers, ISI scores decreased from 20.1 to 10.2 (49% decrease; t=8.14, df=20, p<.001) and further, to 9.9 (51%) at three-month follow-up (t=7.40, df=20, p<.001). Partial completers also experienced a statistically significant decrease in the ISI score of 27%, from 19.9 to 14.6 (t=2.64, df=12, p=.022). Those who did not engage showed only a nonsignificant decrease of 3%, from 19.9 to 14.6. In adjusted linear regression analysis, statistically significant differences were observed in mean follow-up ISI scores between engagement and completion groups (F=3.87, df=4 and 40, p≤.004). Differences corresponded to an effect size of 1.2 for completers and .7 for partial completers, compared with nonengagers. No clinically meaningful or statistically significant differences were observed in either component (physical or mental health) of the SF-12.
There were no statistically significant changes in the number of sedative-hypnotic doses ingested per week for the entire sample or in any of the engagement and completion groups. Likewise, there were no statistically significant differences in the number of new sedative-hypnotic starts or stops between engagement and completion groups.
In analysis of follow-up clinical support contacts, completers and partial completers had 9.0±4.5 and 9.6±4.2 contacts, respectively, whereas those who did not engage had 7.8±4.6 contacts. Among these contacts, 36 (8%) dealt with computer- and Internet-related questions such as username and password loss, and only six (1%) were related to program content or clinical questions. A majority (N=410, 91%) were either phone messages or short conversations of a motivational nature. In the sample, 20 individuals (39%) accessed the program from the clinic, and 31 (61%) used a computer in a different location. Neither engagement and completion status nor the number of clinical support contacts varied significantly by location of computer use.
Discussion
This study evaluated the feasibility of implementing a self-help CBPI for insomnia among individuals in outpatient VHA substance abuse treatment using an implementation strategy that offers provider education, optional on-site Internet availability, a patient education session, and facilitation through weekly telephone support. Results suggest that implementation of the Restore program using this strategy is feasible, which is supported by evidence in three areas: reasonable engagement and completion rates in comparison with those found in other studies of CBPIs, positive self-report of satisfaction, and a dose-response type of association between engagement in the program and insomnia improvement, independent of sedative-hypnotic use. Moreover, an exploration of the amount and content of support provided indicates that in future CBPI implementation efforts, support can be easily provided by clinicians or potentially support personnel within a practice setting.
Although there have been many efforts within the VHA to develop and test CBPIs for a number of common clinical problems, efforts to implement them in current VHA care models have not been documented. Similar efforts outside the VHA have focused on implementing CBPIs for depression or anxiety by using similar care management strategies in the United Kingdom’s National Health Service, with evidence that they have improved access and outcomes and decreased costs (6,7). Self-help CBPIs, it should be noted, are first-line treatments that can be followed by face-to-face intervention if they do not achieve the desired goals.
The acceptability of CBPIs, as measured by program engagement and completion and participant feedback, is a useful indicator of the platform’s feasibility (25). In this study, 69% of veterans engaged in the intervention and 43% completed it, compared with 68% who completed Restore in a university-based controlled trial and rates of between 57% and 95% in trials of other CBPIs for insomnia (20,26–29). These comparisons are with completion rates in controlled trials, which typically recruited homogeneous uncomplicated samples and used rigorous research protocols with staff to facilitate engagement. In contrast, this sample was drawn from a population seeking treatment for drug and alcohol use in a public mental health setting, and participants had high levels of psychiatric comorbidity and concomitant sedative-hypnotic use. Reduced engagement and completion in such treatment settings may be the rule rather than an exception (30). For example, trials of clinician-assisted computerized interventions for depression have reported dropout rates of between 30% and 50% (31). This relatively low engagement and completion rate may also be associated with the relatively high proportion of individuals using the computer station within the clinic (40%), requiring them to come to the clinic to participate. Similarly, a recent study of the implementation within the VHA of face-to-face CBT for insomnia reported that only 52% of veterans who engaged completed six sessions (32).
Participant self-report data from this study suggest that both CBPIs in general and Restore specifically were acceptable to between one-half to two-thirds of veterans in outpatient substance abuse treatment. These findings mirror other literature on research that used patient self-report data, which showed general acceptability of Internet-based self-care resources for veterans (33–35). Moreover, our finding that no baseline factors predicted engagement and completion is similar to that of other studies showing few such predictors (36,37).
The program was associated with clinically and statistically significant changes in insomnia severity among individuals who engaged in or completed the program. Although most efficacy studies have reported data from sleep logs, including sleep onset latency and sleep efficiency, such data were not available in our study for those who did not engage or who dropped out. Prior studies of CBPIs for insomnia have shown small to medium effect sizes for patient report of insomnia severity, disrupted sleep, and sleep efficiency (20,26–29). This study showed large effect sizes on the ISI among both completers and partial completers compared with those who did not engage. The strong effect for partial completers may indicate that insomnia levels of those individuals either improved on their own or after only minimal engagement with modules addressing the subjects of sleep hygiene or behavioral anxiolytic techniques, perhaps leading individuals to drop out after what they regarded as sufficient clinical improvement. An alternative explanation would be that a placebo effect of trying the program was responsible for improved sleep. Studies of sedative-hypnotic medication treatment for insomnia have shown strong placebo effects (38).
A secondary objective was to evaluate the program’s association with a decrease in sedative-hypnotic medication use. Results showed only small changes in such use. Three prior studies of CBPIs for insomnia have found similarly small changes in sedative-hypnotic use (26–28). These findings underscore the difficulty that patients with insomnia face in stopping such dependence-inducing medications. Additional explanations for this limited impact include the brief duration of the study and the fact that the education component of the strategy did not include an explicit discussion of decreasing sedative-hypnotic use during the program.
Additional limitations of this study deserve comment. This was an open pilot trial to evaluate initial feasibility of the program and implementation strategy. The untreated comparison group was self-selected and not identified by random assignment; thus causal inferences are not conclusive. However, the evaluation of baseline characteristics and engagement and completion status did not reveal any factors that may have accounted for these differences. Moreover, the clinical site for this study, like most outpatient mental health clinics, does not screen for the presence of insomnia among patients, and the penetration of this program’s use among potential insomnia sufferers is unknown. However, a small survey for a different project at the same clinic suggested that over 50% of patients suffer from clinically significant sleep problems (39), signifying that only 10% of potentially eligible patients were referred. Future studies investigating these findings are planned. Similarly, the sample size of 51 participants was relatively small, especially given the number of individuals who did not engage. Also, three-month follow-up measures were accomplished only by those who competed the program, which limited statistical power, making results susceptible to type II statistical error. Finally, although we collected information from participants on acceptability of treatment, the validity of these assessments has not been evaluated, and we do not have systematic data on provider response to the program. However, we feel that the acceptability questions have strong face validity given that this was a pilot project, and semistructured interviews of providers were conducted for qualitative analysis, which will be reported in future articles.
Conclusions
Whereas multiple past studies have documented the development and testing of CBPI programs for mental health problems, a strategy for their implementation in large public health care systems treating numerous patients facing multiple chronic conditions had not been devised or piloted, which is the major accomplishment of this study (40). Results suggest that the implementation of a CBPI for insomnia using a strategy consisting of provider and patient education sessions, clinic-based Internet access, and telephone-based support is feasible in VHA outpatient mental health and substance abuse treatment settings. Future studies of CBPI effectiveness, implementation, and use should focus on the integration of such programs into current clinical care, strategies for increasing engagement and completion, and the recruitment and training of individuals within the practice setting to educate and support participants.
Footnote
The funding sources had no role in the design, analysis, or interpretation of data or in the preparation of the report or decision to publish.
Supplementary Material
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Cover: Print table, by Frank Lloyd Wright (maker: William E. Nemmers), 1902–1903. White oak. Purchase, Emily Crane Chadbourne Bequest, 1972, the Metropolitan Museum of Art, New York City. Image copyright © The Metropolitan Museum of Art. Image source: Art Resource, New York City.
History
Received: 18 November 2014
Revision received: 17 March 2015
Accepted: 20 May 2015
Published online: 1 December 2015
Published in print: February 01, 2016
Authors
Competing Interests
The authors report no financial relationships with commercial interests.
Funding Information
U.S. Department of Veterans Affairs10.13039/100000738: VISN 1 Career Development Award V1CDA2012-15
This research was supported by a Veterans Integrated Service Network 1 career development award V1CDA2012-17 to Dr. Hermes and by the VA New England MIRECC. The Restore program was provided through a contract and data use agreement with Cobalt Therapeutics, LLC, and the authors are grateful for its support and encouragement.Metrics & Citations
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