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Recent studies provide evidence for the effectiveness of Internet-based maintenance treatments for mental disorders. However, it is still unclear which participants might or might not profit from this particular kind of treatment delivery.
The study aimed to identify moderators of treatment outcome in a transdiagnostic Internet-based maintenance treatment (TIMT) offered to patients after inpatient psychotherapy for mental disorders in routine care.
Using data from a randomized controlled trial (N=400) designed to test the effectiveness of TIMT, we performed secondary analyses to identify factors moderating the effects of TIMT (intervention) when compared with those of a treatment-as-usual control condition. TIMT involved an online self-management module, asynchronous patient–therapist communication, a peer support group, and online-based progress monitoring. Participants in the control condition had unstructured access to outpatient psychotherapy, standardized outpatient face-to-face continuation treatment, and psychotropic management. Self-reports of psychopathological symptoms and potential moderators were assessed at the start of inpatient treatment (T1), at discharge from inpatient treatment/start of TIMT (T2), and at 3-month (T3) and 12-month follow-up (T4).
Education level, positive outcome expectations, and diagnoses significantly moderated intervention versus control differences regarding changes in outcomes between T2 and T3. Only education level moderated change differences between T2 and T4. The effectiveness of the intervention (vs control) was more pronounced among participants with a low (vs high) education level (T2-T3: B=–0.32, SE 0.16,
This transdiagnostic Internet-based maintenance treatment might be suitable for a wide range of participants differing in various clinical, motivational, and demographic characteristics. The treatment is especially effective for participants with low education levels. These findings may generalize to other Internet-based maintenance treatments.
International Standard Randomized Controlled Trial Number (ISRCTN): 28632626; http://www.controlled-trials.com/isrctn/pf/28632626 (Archived by WebCite at http://www.webcitation.org/6IqZjTLrx).
Despite strong evidence for the efficacy of psychotherapy for common mental health disorders [
The use of the Internet to provide guided self-help maintenance phase treatments may help to overcome this unmet maintenance need. Internet-based guided self-help strategies for the maintenance phase of psychotherapies have several advantages over face-to-face maintenance approaches. These include (1) greater potential for the integration of acquired skills in daily life because of an emphasis on the patient’s active role in (guided) self-help treatment [
Several studies have shown promising results with delivering maintenance phase treatments over the Internet [
Although there is evidence for the general effectiveness of Internet-based maintenance phase treatments, little is known about which patients might or might not benefit from this particular kind of treatment delivery. Investigating the moderating effects of patient characteristics on Internet-based maintenance phase treatment effectiveness is crucial for identifying appropriate populations and for customizing interventions to the specific needs of patient subgroups. More knowledge regarding who is likely or unlikely to profit from these interventions should also help in identifying relevant mechanisms of change as well as allocating health care resources on an evidence-based level [
Only a few studies to date have investigated moderators of Internet-based intervention outcomes for mental health problems. In 1 of these studies, Warmerdam and colleagues [
The aim of the present study was to identify moderating factors on the effects of TIMT after inpatient psychotherapy. Using data from a pragmatic RCT on the effectiveness of TIMT (ISRCTN:28632626) [
Given the current lack of data on moderators of Internet-based continuation phase treatment effects, we used an exploratory approach including a wide range of potential pretreatment moderators [
The primary research questions of this study were:
Do any of the pretreatment factors included in this study moderate the effectiveness of TIMT compared with TAU?
If moderating effects are found, do participants characterized by disadvantageous scores on identified moderators still benefit from TIMT?
We performed secondary analyses using data from a pragmatic RCT comparing TIMT in addition to TAU following inpatient psychotherapy to TAU only (N=400) [
We recruited potential participants from 2189 patients treated for a variety of mental disorders between July 2008 and October 2009 in the study hospital. Patients were eligible for the study if they (1) were age 18 years or older, (2) met criteria for a mental disorder according to the
Participants who gave full written informed consent were randomly assigned to receive TAU only (control) or TAU plus TIMT (intervention). In total, 58 of 400 (14.5%) participants did not complete the T3 assessment and 113 (28.5%) did not complete the T4 assessment. Participants who did not provide data at 1 of the follow-ups did not differ from participants without missing data on baseline psychopathological symptom severity scores or any other clinical characteristics (all
Inpatient treatment was based on CBT [
Following inpatient treatment, all participants had unstructured access to outpatient psychotherapy and standardized outpatient group-based, face-to-face, maintenance treatment [
In addition to TAU, the intervention group had TIMT for 12 weeks. The main focus of TIMT is to support patients in the sustained utilization of skills acquired during treatment. For this purpose, TIMT works to help participants identify activities that they have found helpful and systematically integrate these into their daily life routines. Because TIMT aims to enhance whatever strategy patients experienced as helpful, it can be used to maintain treatment outcome regardless of which psychopathology the patient is suffering from and regardless of the kind of treatment the patient received before. TIMT consists of 5 core components. The first component is the generation of a personal development plan. This process is conducted during the last 10 days of inpatient treatment in which TIMT participants complete 3 sessions of blended (face-to-face and online) standardized goal-setting and action planning instead of inpatient TAU. Participants develop a detailed plan including (1) highly relevant personal goals they want to achieve during the intervention phase, and (2) implementation intentions [
The intervention and control group did not differ in types of treatment received except for frequency of sedatives taken. Participants in the intervention group were less likely to take sedatives than controls (
In total, we included 11 pretreatment participant characteristics: age, sex, education, main diagnosis, comorbid personality disorder, remission status at the end of inpatient treatment, reliable change in the primary outcome during inpatient treatment, years since first disorder onset, Internet/computer literacy, positive outcome expectations, and health-related self-efficacy.
Information on sex, age, and education were extracted from the inpatient clinic patient files. All self-report data were assessed using an online-based assessment tool. Diagnoses and year of first disorder onsets were assessed during the intake interview. All interviewers were experienced psychotherapists who were either psychologists or physicians with a master’s degree or higher, trained extensively in administering the structured clinical interviews of the German version of the
Positive outcome expectations were assessed by using the respective subscale of the Patient Questionnaire on Therapy Expectation and Evaluation (PATHEV) [
Health-related self-efficacy was assessed by using the self-efficacy subscale of the 49-item short form of the Hamburg Modules for the Assessment of Psychosocial Health (HEALTH-49) questionnaire [
The primary outcome from the effectiveness trial was change in general psychopathological symptom severity (symptom severity) from discharge (T2) to 3- and 12-month follow-ups (T3, T4). Symptom severity was assessed by using the HEALTH-49, a widely used measure of symptom severity in Germany [
Group differences regarding baseline characteristics were compared via chi-square tests for categorical variables and
To increase interpretability and allow for testing nonlinear effects, categorical variables with more than 2 categories (ie, diagnosis, years since first disorder onset, education) were recoded into a maximum of 3 meaningful categories. Because of low prevalence rates, we excluded diagnoses other than depression, anxiety disorders, and adjustment disorders. All continuous moderators (ie, age, self-efficacy, positive outcome expectations) were standardized so that regression coefficients refer to participants with average scores on each moderator.
Aiming at an intention-to-treat (ITT) design, we included all participants randomly assigned to conditions. We employed a full information maximum likelihood (FIML) estimation, which allows for all available data to be included without replacement or imputation of missing values. The FIML estimation for mixed models is especially robust with respect to missing data [
Additionally, we conducted follow-up simple slope analyses for each significant 3-way interaction effect [
Effect sizes for each significant moderator were calculated based on comparing the effect of control versus intervention groups on symptom severity scores, with participants grouped by the significant moderator variable. Cohen’s
To verify whether the results of the ITT analyses would be sustained among the intervention completers sample only, we subsequently repeated all mixed-effects models with participants who stayed within key treatment parameters (completed at least 6 of 12 Web diary entries or more than 25 posts, n=177).
To clarify the generalizability of our findings, we assessed all potential moderators also from patients who were treated during the recruitment period in the study center, but did not participate in the trial (not invited, declined to participate, not fulfilling inclusion criteria) but gave informed consent to use their data for research purposes (n=1789). Study participants and nonparticipants were compared using chi-square tests for categorical variables and
Finally, if a significant moderator effect contradicted our a priori expectations, we conducted post hoc simple slope analyses for the control and intervention groups separately to identify the reasons for the effect. All analyses were performed with SPSS 19 (IBM Corp, Armonk, NY, USA).
Participant flow and study dropouts at each stage of the study.
Descriptives for primary trial main outcome, psychopathological symptom severity as measured by the general psychopathological symptom severity subscale of the HEALTH-49 questionnaire.
Assessment points | Time of Assessment | Intervention |
Control |
||
|
|
Mean | SD | Mean | SD |
T1 | Inpatient admission | 1.50 | 0.69 | 1.49 | 0.71 |
T2 | Inpatient discharge | 0.83 | 0.64 | 0.83 | 0.66 |
T3 | 3-month follow-up | 0.71 | 0.61 | 0.96 | 0.69 |
T4 | 12-month follow-up | 0.78 | 0.69 | 1.12 | 0.84 |
Descriptives for pretreatment moderator variables.
Variables | Intervention |
Control |
Nonparticipantsa
|
|
Age, mean (SD) | 45.09 (8.88) | 45.45 (9.80) | 47.12 (9.45) | |
Sex (female), n (%) | 147 (73.5) | 151 (75.5) | 1360 (76.0) | |
|
|
|
|
|
|
High | 80 (40.0) | 78 (39.0) | 498 (27.8) |
|
Medium | 93 (46.5) | 91 (45.5) | 779 (43.5) |
|
Low | 26 (13.0) | 31 (15.5) | 509 (28.5) |
Existing Internet literacy (%) | 178 (89.0) | 167 (83.5) | 1132 (67.5)b | |
|
|
|
|
|
|
Mood disorder | 108 (54.0) | 113 (56.5) | 918 (51.3) |
|
Anxiety | 19 (9.5) | 18 (9.0) | 206 (11.5) |
|
Adjustment | 53 (26.5) | 38 (19.0) | 405 (22.6) |
|
Other | 20 (10.0) | 31 (15.5) | 260 (14.5) |
Comorbid personality disorder, n (%) | 20 (10.0) | 22 (11.0) | 175 (9.8) | |
|
|
|
|
|
|
< 1 | 44 (22.0) | 47 (23.5) | 430 (24.2) |
|
1-5 | 55 (27.5) | 44 (22.0) | 444 (24.9) |
|
> 5 | 96 (48.0) | 105 (52.5) | 906 (50.9) |
Reliable change during inpatient treatment, n (%) | 100 (50.0) | 90 (45.0) | 1052 (58.8) | |
Remission at discharge, n (%) | 94 (47.0) | 93 (46.5) | 787 (44.0) | |
Self-efficacy, mean (SD) | 1.47 (0.83) | 1.49 (0.87) | 1.58 (0.90) | |
Positive outcome expectations, mean (SD) | 3.86 (0.74) | 3.92 (0.66) | 3.72 (0.78) |
aAll differences between conditions were nonsignificant. If percentages do not reach 100, it is due to missing data.
bn=1676.
The subsequent tables show the mixed-effect model results based on ITT for the interactions between pretreatment participant characteristics (moderators), intervention condition, and changes in symptom severity. Intercepts represent the estimated level of symptom severity at baseline (discharge, T2). The regression coefficient of the moderator represents differences in symptom severity between participants differing in 1 unit of the hypothesized moderator at baseline. The regression coefficient of T1-T2 represents the average difference in symptom severity between inpatient admission (T1) and inpatient discharge (T2) in the control group, the regression coefficient of T2-T3 represents the average difference in symptom severity between discharge (T2) and 3-month follow-up (T3) in the control group, and the regression coefficient of T2-T4 represents the average difference in symptom severity between discharge (T2) and 1-year follow-up (T4) in the control group. The regression coefficient of the condition represents differences in symptom severity between the intervention and the control condition at discharge (T2). The cross-level interactions condition × T1-T2, T2-T3, T2-T4 represent intervention versus control group differences in changes over time.
As expected, we found (1) a significant decrease in symptom severity between T1 and T2 in both conditions (T1-T2), (2) no interaction between T1-T2 and the intervention condition, (3) a significant condition × T2-T3 interaction effect showing that symptom severity remained low in the intervention group between T2 and T3 but increased in the control group, and (4) a significant T2-T4 × condition interaction effect showing that symptom severity remained low in the intervention group between T2 and T4 but increased in the control group (
Multilevel results of the interactions between pretreatment participant characteristics (dichotomic moderator variables), intervention condition, and change in psychopathological symptom severity (dummy coded) for the intention-to-treat sample (N=400) using full maximum likelihood estimation.
Interaction terms | Sexa | Internet literacyb | Reliable changec | Comorbid PDd | Remission statuse | ||||||||||
|
B | SE |
|
B | SE |
|
B | SE |
|
B | SE |
|
B | SE |
|
Interceptf | 0.94 | 0.09 | <.001 | 0.91 | 0.11 | <.001 | 0.98 | 0.06 | <.001 | 0.78 | 0.05 | <.001 | 0.30 | 0.04 | <.001 |
Moderator | –0.16 | 0.11 | .13 | –0.11 | 0.12 | .39 | –0.34 | 0.09 | <.001 | 0.42 | 0.15 | .004 | 0.98 | 0.06 | <.001 |
T1-T2 (dummy 1)g | 0.60 | 0.08 | <.001 | 0.69 | 0.10 | <.001 | 0.25 | 0.03 | <.001 | 0.66 | 0.04 | <.001 | 0.84 | 0.06 | <.001 |
T2-T3 (dummy 2)h | 0.20 | 0.08 | .008 | 0.19 | 0.09 | .04 | 0.00 | 0.05 | .99 | 0.16 | 0.04 | <.001 | 0.36 | 0.05 | <.001 |
T2-T4 (dummy 3)i | 0.48 | 0.10 | <.001 | 0.40 | 0.12 | .001 | 0.12 | 0.06 | .05 | 0.30 | 0.05 | <.001 | 0.44 | 0.07 | <.001 |
Conditionj | –0.35 | 0.13 | .006 | –0.13 | 0.18 | .48 | 0.05 | 0.09 | .58 | 0.02 | 0.07 | .78 | 0.01 | 0.06 | .90 |
Condition×T1-T2 | 0.04 | 0.12 | .750 | 0.07 | 0.16 | .66 | –0.06 | 0.05 | .25 | 0.04 | 0.06 | .53 | –0.04 | 0.08 | .61 |
Condition×T2-T3 | –0.24 | 0.11 | .03 | –0.30 | 0.14 | .04 | –0.22 | 0.07 | .002 | –0.24 | 0.06 | <.001 | –0.30 | 0.07 | <.001 |
Condition×T2-T4 | –0.45 | 0.14 | .001 | –0.65 | 0.18 | <.001 | –0.41 | 0.10 | <.001 | –0.34 | 0.07 | <.001 | –0.30 | 0.10 | .002 |
Moderator×T1-T2 | 0.09 | 0.10 | .35 | –0.03 | 0.11 | .80 | 0.92 | 0.05 | <.001 | 0.02 | 0.13 | .87 | –0.31 | 0.08 | <.001 |
Moderator×T2-T3 | –0.04 | 0.09 | .61 | –0.02 | 0.10 | .83 | 0.36 | 0.07 | <.001 | 0.04 | 0.12 | .75 | –0.37 | 0.07 | <.001 |
Moderator×T2-T4 | –0.22 | 0.11 | .05 | –0.11 | 0.13 | .41 | 0.41 | 0.09 | <.001 | 0.08 | 0.16 | .61 | –0.25 | 0.10 | .01 |
Condition×moderator | 0.46 | 0.15 | .002 | 0.14 | 0.19 | .47 | –0.07 | 0.13 | .57 | –0.23 | 0.21 | .28 | –0.02 | 0.09 | .83 |
Cond×mod×T1-T2k | –0.03 | 0.14 | .84 | –0.06 | 0.17 | .72 | 0.05 | 0.07 | .47 | –0.25 | 0.19 | .20 | 0.11 | 0.12 | .36 |
Cond×mod×T2-T3k | –0.02 | 0.12 | .89 | 0.06 | 0.15 | .71 | –0.08 | 0.10 | .46 | –0.12 | 0.18 | .49 | 0.12 | 0.10 | .22 |
Cond×mod×T2-T4k | 0.12 | 0.16 | .47 | 0.34 | 0.20 | .09 | 0.06 | 0.14 | .67 | –0.22 | 0.23 | .34 | –0.11 | 0.14 | .41 |
aSex (0=female; 1=male).
bExisting Internet literacy (0=no; 1=yes).
cReliable change: reliable change during inpatient treatment (0=no; 1=yes).
dComorbid PD: comorbid personality disorder (0=no; 1=yes).
eRemission status: remission status at baseline (T2) (0=in remission; 1=not in remission).
fIntercept: general psychopathological symptom severity in control at baseline (T2).
gT1-T2: dummy-coded change in general psychopathological symptom severity from T1 to T2.
hT2-T3: dummy-coded change in general psychopathological symptom severity from T2 to T3.
iT2-T4: dummy-coded change in general psychopathological symptom severity from T2 to T4.
jCondition (0=control; 1=intervention).
kCond × mod: condition × moderator.
Moreover, diagnoses dummy 1 (mood disorders vs anxiety disorders) interacted with condition × T2-T3. Participants diagnosed with an anxiety disorder showed a larger intervention versus control group difference on changes in symptom severity between discharge and 3-month follow-up than participants diagnosed with a mood disorder (see
Years since disorder onset did not moderate the effect of treatment on any intervention versus control group differences on change scores. Thus, transdiagnostic Internet-based maintenance treatment is effective irrespective of years since first disorder onset.
Estimated course of symptoms based on simple slope mixed-effect model analysis for significant moderators effect of education (0=high education, n=159; 1=low education, n=57) at inpatient admission (T1), inpatient discharge/begin transdiagnostic Internet-based maintenance treatment (T2), 3-month follow-up/end transdiagnostic Internet-based maintenance treatment (T3), and 12-month follow-up (T4).
Estimated course of symptoms based on simple slope mixed-effect model analyses for significant moderator effect of diagnoses (0=mood disorder, n=221; 1=anxiety disorder, n=37) at inpatient admission (T1), inpatient discharge/begin transdiagnostic Internet-based maintenance treatment (T2), 3-month follow-up/end transdiagnostic Internet-based maintenance treatment (T3), and 12-month follow-up (T4).
Multilevel results for interactions between pretreatment participant characteristics (trichotomous moderator variables), intervention condition, and change in psychopathological symptom severity (dummy coded) for the intention-to-treat sample (N=400) using full maximum likelihood estimation.
Interaction terms | Education levela | Diagnosesb | Years since onsetc | ||||||
|
B | SE |
|
B | SE |
|
B | SE |
|
Interceptd | 0.88 | 0.07 | <.001 | 0.87 | 0.06 | <.001 | 0.88 | 0.09 | <.001 |
Moderator dummy 1 | –0.16 | 0.10 | .11 | 0.44 | 0.16 | .005 | –0.04 | 0.11 | .687 |
Moderator dummy 2 | 0.08 | 0.14 | .55 | –0.34 | 0.12 | .004 | –0.13 | 0.13 | .313 |
T1-T2e | 0.63 | 0.07 | <.001 | 0.73 | 0.06 | <.001 | 0.64 | 0.09 | <.001 |
T2-T3f | 0.17 | 0.06 | .005 | 0.16 | 0.05 | .002 | 0.10 | 0.08 | .18 |
T2-T4g | 0.22 | 0.08 | .004 | 0.36 | 0.06 | <.001 | 0.31 | 0.10 | .002 |
Conditionh | –0.14 | 0.10 | .17 | –0.02 | 0.08 | .82 | –0.28 | 0.13 | .02 |
Condition×T1-T2 | 0.03 | 0.09 | .76 | –0.02 | 0.08 | .85 | 0.09 | 0.12 | .43 |
Condition×T2-T3 | –0.17 | 0.08 | .04 | –0.21 | 0.07 | .004 | –0.20 | 0.10 | .06 |
Condition×T2-T4 | –0.25 | 0.11 | .03 | –0.38 | 0.09 | <.001 | –0.33 | 0.14 | .02 |
Moderator dummy 1×T1-T2 | 0.03 | 0.09 | .72 | –0.04 | 0.15 | .80 | –0.04 | 0.11 | .70 |
Moderator dummy 1×T2-T3 | –0.04 | 0.08 | .64 | 0.02 | 0.15 | .89 | 0.04 | 0.09 | .68 |
Moderator dummy 1×T2-T4 | 0.07 | 0.11 | .48 | 0.01 | 0.19 | .96 | –0.03 | 0.12 | .80 |
Moderator dummy 2×T1-T2 | 0.17 | 0.13 | .17 | –0.09 | 0.11 | .40 | 0.20 | 0.12 | .10 |
Moderator dummy 2×T2-T3 | 0.10 | 0.11 | .35 | 0.03 | 0.10 | .75 | 0.14 | 0.11 | .19 |
Moderator dummy 2×T2-T4 | 0.35 | 0.14 | .02 | –0.19 | 0.13 | .14 | 0.02 | 0.14 | .88 |
Cond×mod×dummy 1i | 0.22 | 0.14 | .11 | –0.07 | 0.22 | .74 | 0.36 | 0.15 | .02 |
Cond×mod×dummy 2i | 0.19 | 0.20 | .34 | 0.08 | 0.16 | .63 | 0.27 | 0.18 | .13 |
Cond×mod×dummy 1×T1-T2i | –0.03 | 0.13 | .82 | –0.07 | 0.22 | .75 | –0.07 | 0.15 | .63 |
Cond×mod×dummy 1×T2-T3i | –0.08 | 0.11 | .50 | –0.43 | 0.21 | .04 | –0.03 | 0.13 | .82 |
Cond×mod×dummy 1×T2-T4i | –0.12 | 0.15 | .42 | –0.24 | 0.26 | .37 | 0.01 | 0.17 | .93 |
Cond×mod×dummy 2×T1-T2i | 0.05 | 0.18 | .77 | 0.10 | 0.15 | .52 | –0.14 | 0.17 | .43 |
Cond×mod×dummy 2×T2-T3i | –0.32 | 0.16 | .049 | –0.03 | 0.14 | .83 | –0.09 | 0.15 | .56 |
Cond×mod×dummy 2×T2-T4i | –0.42 | 0.21 | .049 | 0.15 | 0.18 | .41 | 0.03 | 0.19 | .89 |
aEducation level dummy 1 (0=high education level; 1=medium education level), education level dummy 2 (0=high education level; 1=low education level).
bDiagnoses dummy 1 (0=mood disorder; 1=anxiety disorder), diagnoses dummy 2 (0=mood disorder; 1=adjustment disorder).
cYears since onset: years since disorder onset dummy 1 (0=1-5 years; 1=>5 years), years since disorder onset dummy 2 (0=1-5 years; 1=<1 year).
dIntercept: general psychopathological symptom severity in control at baseline (T2).
eT1-T2: dummy-coded change in general psychopathological symptom severity from T1 to T2.
fT2-T3: dummy-coded change in general psychopathological symptom severity from T2 to T3.
gT2-T4: dummy-coded change in general psychopathological symptom severity from T2 to T4.
hCondition (0=control; 1=intervention).
iCond × mod × dummy: condition × moderator × dummy.
Multilevel results for interactions between pretreatment participant characteristics (continuous moderator variables), intervention condition, and change in psychopathological symptom severity (dummy coded) for intention-to-treat sample (N=400) using full maximum likelihood estimation.
Interaction terms | Agea | Self efficacya | Positive outcome expectationsa |
|
||||||
|
B | SE |
|
B | SE |
|
B | SE |
|
|
Interceptb | 0.83 | 0.05 | .<001 | 0.82 | 0.04 | <.001 | 0.84 | 0.04 | <.001 | |
Moderatorc | –0.12 | 0.04 | .004 | 0.44 | 0.03 | <.001 | –0.23 | 0.05 | <.001 | |
T1-T2d | 0.67 | 0.04 | <.001 | 0.67 | 0.04 | <.001 | 0.66 | 0.04 | <.001 | |
T2-T3e | 0.17 | 0.04 | <.001 | 0.17 | 0.04 | <.001 | 0.16 | 0.04 | <.001 | |
T2-T4f | 0.31 | 0.05 | <.001 | 0.31 | 0.05 | <.001 | 0.30 | 0.05 | <.001 | |
Conditiong | –0.01 | 0.06 | .85 | 0.01 | 0.05 | .89 | –0.01 | 0.06 | .84 | |
Condition×T1-T2 | 0.02 | 0.06 | .79 | 0.01 | 0.06 | .88 | 0.02 | 0.06 | .75 | |
Condition×T2-T3 | –0.24 | 0.05 | <.001 | –0.25 | 0.05 | <.001 | –0.25 | 0.05 | <.001 | |
Condition×T2-T4 | –0.35 | 0.07 | <.001 | –0.36 | 0.07 | <.001 | –0.35 | 0.07 | <.001 | |
Moderator×T1-T2 | 0.01 | 0.04 | .79 | –0.18 | 0.04 | <.001 | 0.08 | 0.04 | .08 | |
Moderator×T2-T3 | 0.07 | 0.04 | .07 | –0.16 | 0.04 | .002 | 0.07 | 0.04 | .08 | |
Moderator×T2-T4 | 0.05 | 0.05 | .26 | –0.05 | 0.05 | .26 | 0.03 | 0.05 | .62 | |
Condition×moderator | 0.03 | 0.06 | .60 | –0.04 | 0.05 | .42 | 0.12 | 0.06 | .06 | |
Condition×moderator×T1-T2 | 0.03 | 0.06 | .60 | 0.05 | 0.06 | .39 | –0.10 | 0.06 | .09 | |
Condition×moderator×T2-T3 | 0.04 | 0.05 | .50 | 0.07 | 0.05 | .22 | –0.12 | 0.05 | .02 | |
Condition×moderator×T2-T4 | 0.00 | 0.07 | .98 | –0.10 | 0.07 | .15 | 0.03 | 0.07 | .65 |
aAll continuous variables standardized.
bIntercept: general psychopathological symptom severity in control at baseline (T2).
cModerators (0=mean; 1=mean + 1 SD).
dT1-T2: dummy-coded change in general psychopathological symptom severity from T1 to T2.
eT2-T3: dummy-coded change in general psychopathological symptom severity from T2 to T3.
fT2-T4: dummy-coded change in general psychopathological symptom severity from T2 to T4.
gCondition (0=control; 1=intervention).
Estimated course of symptoms based on simple slope mixed-effect model analyses for significant moderator positive outcome expectations (mean vs mean – 1 SD vs mean + 1 SD) at inpatient admission (T1), inpatient discharge/begin transdiagnostic Internet-based maintenance treatment (T2), 3-month follow-up/end transdiagnostic Internet-based maintenance treatment (T3), and 12-month follow-up (T4).
Effect sizes (Cohen’s
The results of the following intervention completers analyses closely paralleled those of the ITT analyses. Most of the significant 3-way interactions were also significant in the completers sample (B=–0.45 to –0.12, SE 0.05-0.21,
As shown in
The moderator effect of education contradicted our a priori expectation of higher educated participants benefiting to a greater extent from the Internet-based intervention than lower educated participants. Thus, we conducted further post hoc simple slope analyses for the control group and the intervention group separately to identify possible explanations for this effect. For participants in the control group, we found no significant interaction between education and changes in symptom severity from discharge to 3-month follow-up (education dummy 2 × T2-T3 interaction, B=0.10, SE 0.11,
In the present study, we aimed to identify moderators of treatment outcome for TIMT following inpatient psychotherapy. Education level, positive outcome expectations, and mental health diagnoses were identified as significant moderators of TIMT’s effects on psychopathological symptom severity. Findings indicate that the effects of TIMT on general psychopathological symptom severity were more pronounced among participants with a low (vs high) education level. Participants with high positive outcome expectations profited in the short term (until 3-month follow-up) more than participants with low positive outcome expectations. However, this effect was not significant at 1-year follow-up. Moreover, participants with a mood disorder benefited less from the intervention than did participants with an anxiety disorder; however, this effect was also not significant at 1-year follow-up. Simple slope analyses revealed that even when some groups profited less from participating, treatment effects in these subgroups were still significant, except for the subgroup of participants with low positive outcome expectation at 3-month follow-up.
Other pretreatment variables did not interact with TIMT’s effects indicating that TIMT might be superior to TAU only with regard to outcome sustainability irrespective of age, gender, comorbid personality disorder, years since disorder onset, self-efficacy, remission status at the end of inpatient treatment, reliable change in psychopathological symptom severity during inpatient treatment, and Internet literacy. However, given that these analyses were exploratory and the study was not powered to find small interaction effects, these null findings should be interpreted with caution.
The finding that participants with low education benefited more from using TIMT than participants with high education contrasts with findings from a study investigating moderators in face-to-face continuation phase psychotherapy in which education did not interact with treatment outcome [
On the basis of our data, we can only speculate on possible explanations as to why participants with anxiety disorder profited to a greater extent (in the short term) than participants with depression. These results are consistent with findings showing that effect sizes are typically larger for Internet interventions targeting anxiety than interventions targeting depression. In a review of 26 RCTs, Griffiths and colleagues [
The significant finding for positive outcome expectancies regarding change differences from discharge to 3-month follow-up is consistent with the idea that high expectancies for change are associated with better treatment outcome [
To validly interpret the results of this study, several limitations should be considered. First, as in most moderator studies, the analyses in this study were exploratory with participants not being randomized based on potential moderators of interest. Despite the limitations of this procedure, a growing recognition among methodologists has developed about its importance for fostering empirically founded hypotheses to be tested in future studies before clinical application [
Strengths of the study include (1) its large sample size compared to other studies, (2) a TAU control condition, which allowed us to specify which participants might and might not benefit from TIMT compared to treatment provided by routine health care services, (3) inclusion and exclusion criteria were kept to a minimum to maximize the ecological validity, and (4) generalizability of findings was assessed by comparing the moderator sample with a large sample of participants representing basically all patients treated in the study site.
Transdiagnostic Internet-based guided self-help interventions may represent a cost-effective, far-reaching method for implementing maintenance phase treatments. Findings from the current study suggest that TIMT following inpatient psychotherapy helps patients differing in various characteristics to maintain treatment outcome. It is especially effective for participants with low education levels. Although some subgroups were identified as having profited less from the intervention than others, all subgroups benefited significantly. Future studies should replicate our results before clinical application.
CONSORT-EHEALTH checklist V1.6.2 [
cognitive behavior therapy
full information maximum likelihood
intention-to-treat
randomized controlled trial
treatment as usual
transdiagnostic Internet-based maintenance treatment
David Ebert and Matthias Berking contributed to the design of the study. David Ebert and Mario Gollwitzer contributed to the analysis of data. All authors contributed to the interpretation of data, to the final draft of the paper, and approved the final version for publication. This study was funded by the Dr Ebel Fachkliniken–Vogelsbergklinik, Grebenhain, Germany and the European Union (EFRE: CCI 2007DE161PR001).
The first author (DE) developed the intervention under study.