The Efficacy and Effectiveness of Online CBT - Jeroen Ruwaard
The Efficacy and Effectiveness of Online CBT - Jeroen Ruwaard The Efficacy and Effectiveness of Online CBT - Jeroen Ruwaard
110 Chapter 6. Online CBT in Routine Clinical Practicemeasures were identical to those used in the clinical trials. Full descriptions of thequestionnaires, which are often used in mental health outcome research, can be foundin the reports of these trials (Lange et al., 2001; Lange, van de Ven, & Schrieken,2003; Knaevelsrud & Maercker, 2007, 2009; Wagner et al., 2006; Wagner & Maercker,2007; Ruwaard et al., 2007, 2009, 2010). The psychometric characteristics of thesequestionnaires are satisfactory (PDSS-SR, OLBI) to good (DASS, BDI, IES). In thepresent sample, Cronbach’s alpha’s ranged from α = .73 (OLBI) to α = .95 (DASSDepression).Secondary outcomes. Secondary outcomes were pre-to-post-treatment changes ingeneral psychopathology, and patient satisfaction. General psychopathology wasassessed through the total score of the DASS (42 items; range: 0-126), which providesa global measure of negative emotional symptoms (Lovibond & Lovibond, 1995). Inthe present sample, the internal consistency of this measure was excellent (Cronbach’salpha: α = .97). Patient satisfaction was assessed through a brief evaluationquestionnaire, which was administered at posttest. Patients rated the contact withtheir therapists (on a 1-10 scale), and stated whether they perceived the treatment aseffective, whether they had missed the face to face contact, and whether they wouldrecommend the treatment to others (Yes/No/Don’t know).6.1.5 Statistical analysesStatistical significance and effect size We estimated treatment effects throughmulti-level mixed-model repeated measures regression (MMRM) (Verbeke & Molenberghs,2000), using the statistical software package R (R Development Core Team,2008). Time of measurement was coded to contrast mean baseline scores to a) meanscores at the short-term posttreatment assessments (i.e., the post-test and the 6-weekfollow-up), and b) mean scores at one-year follow-up. Separate analyses were conductedon data from each treatment and each outcome measure, using two-sided testsand Bonferroni corrections to ensure a family-wise significance level of α = .05. Wefitted three-level regression models, with repeated measurements nested in patientsat level 1, patients nested in therapists at level 2, and therapists at level 3 (Wampold& Serlin, 2000). Conditional intraclass correlations (ICC; Bickel, 2007) revealed that
6.2. Results 1112% of the variance in outcome was attributable to differences between therapists(mean ICC = .02; range: .001 - 0.13). To express effect sizes as Cohen’s d d (J. Cohen,1988), fixed effect regression estimates and associated 95% confidence intervals weredivided by pretest standard deviations.Reliable and clinically significant change Following principles set out by Jacobsonand Truax (1991), pre- to post-treatment change scores of each patient were classifiedas follows: a) deterioration (change was negative and statistically reliable, i.e., itexceeded 1.96 times the standard error of the difference, b) no change (changewas not statistically reliable), c) improvement (change was positive and statisticallyreliable), or d) recovery (change was positive, statistically reliable, and involved achange from a score above clinical cut-off to a score below this cut-off). Analyses wereconducted on observed data of the full sample (i.e., N = 1500, assuming no change inthe patients, who did not complete post-test measurements) as well as the completersample (i.e., those patients, who completed the full treatment and post-treatmentassessment).6.2 Results6.2.1 Sample selectionTo obtain 1500 records of patients who started treatment, 3003 patient records wereretrieved from the database. Figure 6.1 shows that 507 (17%) of the applicants didnot start baseline assessment, 843 (28%) withdrew during assessment, 153 (5%)were referred to other mental health institutions, while 50% (N = 1500) startedtreatment. The available data did not allow for a systematic analysis of the reasonsof voluntary pre-treatment withdrawal. Of the 1500 accepted patients, 413 (28%)started Web-CBT for depression, 139 (9%) started Web-CBT for panic disorder, 478(32%) started Web-CBT for posttraumatic stress, and 470 (31%) started Web-CBT forburnout. Patients were treated by a total of 135 therapists (depression: n = 74; panicdisorder: n = 24; posttraumatic stress: n = 65; burnout: n = 51).
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6.2. Results 1112% <strong>of</strong> the variance in outcome was attributable to differences between therapists(mean ICC = .02; range: .001 - 0.13). To express effect sizes as Cohen’s d d (J. Cohen,1988), fixed effect regression estimates <strong>and</strong> associated 95% confidence intervals weredivided by pretest st<strong>and</strong>ard deviations.Reliable <strong>and</strong> clinically significant change Following principles set out by Jacobson<strong>and</strong> Truax (1991), pre- to post-treatment change scores <strong>of</strong> each patient were classifiedas follows: a) deterioration (change was negative <strong>and</strong> statistically reliable, i.e., itexceeded 1.96 times the st<strong>and</strong>ard error <strong>of</strong> the difference, b) no change (changewas not statistically reliable), c) improvement (change was positive <strong>and</strong> statisticallyreliable), or d) recovery (change was positive, statistically reliable, <strong>and</strong> involved achange from a score above clinical cut-<strong>of</strong>f to a score below this cut-<strong>of</strong>f). Analyses wereconducted on observed data <strong>of</strong> the full sample (i.e., N = 1500, assuming no change inthe patients, who did not complete post-test measurements) as well as the completersample (i.e., those patients, who completed the full treatment <strong>and</strong> post-treatmentassessment).6.2 Results6.2.1 Sample selectionTo obtain 1500 records <strong>of</strong> patients who started treatment, 3003 patient records wereretrieved from the database. Figure 6.1 shows that 507 (17%) <strong>of</strong> the applicants didnot start baseline assessment, 843 (28%) withdrew during assessment, 153 (5%)were referred to other mental health institutions, while 50% (N = 1500) startedtreatment. <strong>The</strong> available data did not allow for a systematic analysis <strong>of</strong> the reasons<strong>of</strong> voluntary pre-treatment withdrawal. Of the 1500 accepted patients, 413 (28%)started Web-<strong>CBT</strong> for depression, 139 (9%) started Web-<strong>CBT</strong> for panic disorder, 478(32%) started Web-<strong>CBT</strong> for posttraumatic stress, <strong>and</strong> 470 (31%) started Web-<strong>CBT</strong> forburnout. Patients were treated by a total <strong>of</strong> 135 therapists (depression: n = 74; panicdisorder: n = 24; posttraumatic stress: n = 65; burnout: n = 51).
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