Using Technology to Support Evidence-Based Behavioral Health Practices

A Clinician's Guide

Michael A. Cucciare, Kenneth R. Weingardt, Michael A. Cucciare, Kenneth R. Weingardt

• Publisher: Routledge
• Year: 2009
• eBook ISBN: 9781135269166
• Topic: Psychology
• Subtopic: Mental Health in Psychology
• Index: Psychology

The use of technology to provide cost-effective behavioral healthcare is emerging as a crucial aspect of treating a wide variety of behavioral health problems. However, many behavioral health providers lack the knowledge and skills necessary to effectively integrate technology-based behavioral tools into their practice. In Using Technology to Support Evidence-Based Behavioral Health Practices, the authors help providers implement technology-based behavioral health practices in various healthcare settings and with various mental health disorders. Divided into two parts, the text first addresses specific disorders or problem areas, then presents issues concerning implementation and evaluating such tools in clinical practice and important ethical issues to consider when doing so.

section one

Technology and behavioral health

chapter one

Mood Disorders

Judith A. Callan and Jesse H. Wright

Introduction

Mood disorders are disabling and common conditions. The lifetime prevalence of major depression (major depressive disorder, MDD) and bipolar disorder together is approximately 21% (Kessler, Berglund, Demler, Jin, & Walters, 2005). The negative impact of mood disorders on functional, emotional, occupational, and social functioning is even greater than many debilitating physical disorders (Kessler & Frank, 1997; Mintz, Mintz, Arruda, & Hwang, 1992; Wells et al., 1989), and the economic burden of depression is also excessive with estimates as high as $83.1 billion per year (Greenberg et al., 2003). Depression is the highest predictor of suicide in adults aged 30 to 65 years (Maris, 1992). Because information technology efforts have been directed to date almost completely on MDD, the focus of this chapter is primarily on this form of mood disorder.

Traditional treatment for MDD has primarily included medication and psychotherapy. However, there are many problems in the provision of these treatments. Over 60% of individuals with MDD in the United States receive no treatment in the year after they first develop this disorder (Wang et al., 2005). There are multiple and complex reasons for delays in treatment, including lack of access to different types of therapy, or failure to receive any treatment (Regier et al., 1993; Wang et al. 2005). One of the possible barriers that has been suggested is lack of sufficient numbers of therapists who are trained in evidence-based psychotherapies such as cognitive-behavior therapy (CBT) or interpersonal psychotherapy (IPT; Wilson, 1996; Wright et al., 2005). Information technology would appear to have the potential to improve access to effective psychotherapy for MDD by assisting clinicians, improving the efficiency of treatment, and/or reducing the cost of treatment (Wright, 2004). However, large-scale adoption of computer-assisted therapy, telepsychiatry, and other technological advances has not yet occurred.

In this chapter we examine the use of technology in five principal applications: diagnostic and symptom assessment, computer-assisted psychotherapy, self-help via the Internet, telepsychiatry, and symptom monitoring. The topic of online psychotherapy is covered within the computer-assisted psychotherapy and telepsychiatry sections. Because the emphasis of this book is on technology that supports clinical practice, we only briefly discuss the various self-help materials and programs available on the Internet. Some of these resources are listed so that clinicians can tap them for self-help assignments for their patients.

Computer-Aided Diagnostic and Symptom Assessment

The use of technology to assist in diagnostic evaluation, depression screening, and severity assessment began in the late 1960s and 1970s. However, these early programs were typically not made available to practicing clinicians and were found to be of limited value (Das, 2002; Sletten, Altman, & Ulett, 1971). Farvolden and coworkers (Farvolden, Denisoff, Selby, Babgy, & Rudy, 2005), more recently used a Web-based anxiety and depression test (Structured Clinical Interview for DSM-IV Axis 1 Disorders [SCID-I]), which was able to provide diagnoses equivalent to most anxiety and depressive diagnoses with good sensitivity and specificity. At present, there is no widespread use of computer-assisted psychiatric diagnostic software. Nevertheless, Emmelkamp (2005) concluded that online assessment can have psychometric properties comparable to in-person evaluation and may have the advantage of promoting self-disclosure.

Attempts to improve evaluation of depression symptom severity have led to the use of interactive voice response (IVR) technology. Kobak et al. (2000) reported on the use of IVR to evaluate the use of the Hamilton Depression Rating Scale (HDRS) in 10 studies with a total of 1,761 subjects. Patients access the system by calling a toll-free number and then entering a password. Each item of the HDRS is evaluated by multiple queries. Cronbach’s alpha, as the measure of internal consistency, yielded ranges of .60 to .91 compared to clinician-rated values of –.41 to .91. Test–retest reliability was examined after 24 hours with the IVR and clinician-rated HDRS. The IVR method for the HDRS had a test–retest reliability of .74 compared to .98 for the clinician-rated HDRS. The overall correlation between the clinician-rated assessments and the IVR system was .81 (p < .001). There was a strong level of satisfaction with the use of these technologies to evaluate depression severity. However, 75% of subjects still preferred in-person evaluation.

A method of screening the public for depression on the Internet was accomplished by using the CES-D adapted for online screening and placed on the Intelihealth Web site (Houston et al. 2001). Over an 8-month period, 24,479 people completed the Center for Epidemiologic Studies Depression Scale (CES-D). A total of 58% of those completing the online evaluation screened positive for depression. Less than half of those screening positive had never been treated for depression. A follow-up evaluation found that 56% of those who screened positive for depression did seek a subsequent evaluation for treatment. The authors concluded that this platform for anonymous screening for depression was an effective method, especially for younger age groups who have not been typically reached by traditional methods. The Web site is available at http://www.intelihealth.com.

Computer-Assisted Psychotherapy for Depression

Computer-assisted therapy (CAT) can be defined as “psychotherapy that utilizes a computer program to deliver a significant part of the therapy content or uses a computer program to assist the work of a therapist” (Wright, 2008, p. 14). In CAT, a clinician evaluates the patient, prescribes the therapy program, and provides at least minimal supervision and guidance for use of the computer-delivered portion of treatment. In some applications, there is a highly integrated human–computer team that maximizes the use of technology to improve the efficiency of treatment delivery. In addition to potential advantages of efficiency and cost reduction, computer-assisted therapy may enhance learning, reduce the burden on therapists to perform repetitive tasks, provide systematic delivery of core therapy concepts and skills, deliver effective feedback to users, store and analyze patient responses, and promote use of homework (Wright, 2004).

Initially, CAT was only delivered in clinical settings. But more recently, some programs have been available on the Internet or in DVD-ROM editions that patients can use at home or wherever they prefer. As Internet delivery has become more common, the definition of computer-assisted therapy has become blurred. How much clinician involvement is required if the program is to be considered true psychotherapy? If a clinician simply recommends that a patient use an educational Web site for self-help, is this psychotherapy? If a person with depression finds a Web site by browsing and spends a few minutes looking at the program, is this psychotherapy? Although some developers of Web sites that are used without a clinician’s supervision may consider the learning experience to be psychotherapy, we believe that a more traditional definition should be retained.

Although self-help programs have some definite advantages (e.g., available 24 hours a day, low cost or no cost, able to reach people who have no access to trained clinicians), research has shown that they are less effective than CAT in reducing symptoms of depression. A meta-analysis of 12 studies of Internet-delivered programs that used cognitive-behavior therapy principles found that when therapist support was provided, the effect size was d = 1.00 as compared with d = .27 when therapist support was not involved (Spek et al., 2007). Another problem with Internet-delivered self-help programs is that relatively few people complete the full program. The completion rate can be lower than 1% when there is open access to therapeutic Web sites, a research study is not being conducted, and there is no clinician contact (Christiansen, Griffiths, Groves, & Korten, 2006; Eysenbach, Powell, Rizo, & Stern, 2004). In contrast, completion rates for CAT with significant clinician involvement, either in clinical offices or over the Internet, is typically 70% or higher (Litz, Engel, Bryant, & Papa, 2007; Wright et al., 2002).

In reviewing studies of CAT and self-help computer programs, we conclude that the mode of delivery (i.e., CD-ROM, DVD-ROM, or Internet) is not the critical determinant in success—the key feature is clinician involvement. Thus, we focus most of our effort on describing computer-assisted therapy for depression as compared to programs that have been designed to be incorporated into clinical practice.

Early Programs for CAT for Depression

Efforts to develop and test computer programs for treatment of depression began in the 1980s with the work of Selmi and coworkers (Selmi, Klein, Greist, & Harris, 1982; Selmi, Klein, Greist, Sorrell, & Endman, 1990), who introduced software that instructed patients on the basic concepts of cognitive-behavior therapy (CBT). The Selmi group’s software used text on computer screens to educate patients, perform depression ratings, and participate in simple interactive exercises. Although this software did not have a sophisticated interface, advanced graphics, or multimedia elements, which are standard components of contemporary programs for computer-assisted CBT (CCBT) of depression, the program fared well in a randomized, controlled trial. Patients with MDD treated with the Selmi and coworkers’ program for both CCBT or standard CBT both had significantly greater improvement in depression ratings than a wait list control, and there were no significant differences found between the two active therapies (Selmi et al., 1990). This program is now obsolete and is no longer available for clinical use.

Another early program for computer-assisted therapy of depression was developed by Colby and Colby (1990). As with the Selmi et al. program (1982, 1990), the software is text based and contains no multimedia components. The Colby and Colby program (“Overcoming Depression”) has two main elements: a psychoeducational module loosely based on CBT and a “natural language” section that attempts to conduct a nondirective therapeutic interview. The latter feature of the Colby and Colby software has roots in much earlier efforts to program a computer to perform like a human therapist—asking and responding to questions, understanding the meaning of the patient’s responses, and giving empathic and insightful comments (O’Dell & Dickson, 1984; Weizenbaum, 1996). Such programs have not yet been able to reliably replicate therapeutic communication between therapists and patients (Wright, 2004).

Problems with the natural language module may have contributed to the negative findings of a study of the Colby and Colby software for depression (Bowers, Stuart, MacFarlane, & Gorman, 1993; Stuart & LaRue, 1996). In a small investigation with 22 depressed inpatients, subjects assigned to therapy with the Colby and Colby program (1990) had less symptomatic improvement than those treated with standard CBT (Bowers et al., 1993). This is the only study of computer-assisted CBT for depression in clinical settings that did not show a positive effect for the computerized treatment intervention.

Currently Available Programs for CAT for Depression

More contemporary programs for computer-assisted therapy of depression have moved away from natural language applications and have focused instead on using multimedia to enhance learning and skill acquisition. All of the newer computer programs for psychotherapy of depression utilize a CBT approach. CBT is well suited for computer-assisted therapy because of its information processing theories, psychoeducational emphasis, practical methods, skill-based approach, and use of homework (Wright, 2004).

Several uncontrolled trials of multimedia forms of CCBT have shown excellent patient acceptance (Cavanaugh et al., 2006; Whitfield, Winshelwood, Pashely, Williams, & Campsie, 2006; Wright et al., 2002). For example, Wright and coworkers (2002) reported that 78.1% of a series of 96 outpatients and inpatients treated with a multimedia program for CBT (later named Good Days Ahead: The Multimedia Program for Cognitive Therapy) completed the entire program, while 93.4% reached at least the midpoint.

The affinity of patients for using the Good Days Ahead software was assessed with a scale including responses such as “I liked the program,” “The program helped me,” and “I would recommend the program to others.” The range for mean scores for individual questions was 4.3 +/− 0.6 to 4.5 +/− 0.6 (five = highest possible rating). Mean scores on a measure of knowledge of cognitive therapy (Cognitive Therapy Awareness Scale [CTAS]) increased significantly from 24.2 +/− 4.2 to 32.5 +/− 3.7 in study completers (Wright et al., 2002). Although, this uncontrolled study was not designed to measure the effectiveness of using the Good Days Ahead program, symptoms of depression and anxiety were measured to obtain information on possible effects of the software when used along with other treatments. Beck Depression Inventory (BDI), Beck Anxiety Inventory (BAI), and Automatic Thoughts Questionnaire (ATQ) scores all dropped significantly (Wright et al., 2002).

Two research groups (Proudfoot et al., 2003; Wright et al., 2005) have performed randomized, controlled trials to investigate the efficacy of modern forms of computer-assisted CBT that employ multimedia technology and have been used in clinical settings. Proudfoot and coworkers (Proudfoot et al., 2003, 2004; McCrone et al., 2004) have examined the usefulness of computer software (called Beating the Blues) developed in the United Kingdom in a large sample (n = 274) of primary care patients with mixed depression and anxiety. Subjects who scored 4 or more on the General Health Questionnaire and 12 or more on the Clinical Interview Schedule-Revised were randomly assigned to CCBT plus treatment as usual (TAU) or TAU alone. Treatment with antidepressants was not controlled. Baseline BDI-II scores were similar in both groups (CCBT = 24.9; TAU = 24.9), but CCBT patients had lower BDI-II scores 3 months after treatment (CCBT = 12.1; TAU = 16.4).

The Beating the Blues software uses video simulations to educate patients on symptoms of depression and anxiety. It also includes a variety of animations, audio instructions, and interactive exercises to help patients learn to use CBT to reduce symptoms. A limited amount of clinician assistance was provided for the computer-assisted component of the Proudfoot et al. study (2003, 2004). Nurses could spend up to 10 minutes in each of 8 sessions assisting primary care patients with the computerized therapy.

Wright and coworkers (2005) have conducted a randomized, controlled trial of CCBT using the Good Days Ahead software in patients with major depressive disorder (...

Table of contents

• Cover
• Half Title
• Title Page
• Copyright
• Contents
• Editors’ introduction
• Contributors
• Section I: Technology and behavioral health
• Section II: Issues concerning implementation and evaluation
• Index