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Depressive disorders (DDs) are a public health problem. Face-to-face psychotherapeutic interventions are a first-line option for their treatment in adults. There is a growing interest in eHealth interventions to maximize accessibility for effective treatments. Thus, the number of randomized controlled trials (RCTs) of eHealth psychotherapeutic interventions has increased, and these interventions are being offered to patients. However, it is unknown whether patients with DDs differ in internet-based and face-to-face intervention trials. This information is essential to gain knowledge about eHealth trials’ external validity.
We aimed to compare the baseline characteristics of patients with DDs included in the RCTs of eHealth and face-to-face psychotherapeutic interventions with a cognitive component.
In this meta-epidemiological study, we searched 5 databases between 1990 and November 2017 (MEDLINE, Embase, PsycINFO, Google Scholar, and the database of Cuijpers et al). We included RCTs of psychotherapeutic interventions with a cognitive component (eg, cognitive therapy, cognitive behavioral therapy [CBT], or interpersonal therapy) delivered face-to-face or via the internet to adults with DDs. Each included study had a matching study for predefined criteria to allow a valid comparison of characteristics and was classified as a face-to-face (CBT) or eHealth (internet CBT) intervention trial. Two authors selected the studies, extracted data, and resolved disagreements by discussion. We tested whether predefined baseline characteristics differed in face-to-face and internet-based trials using a mixed-effects model and testing for differences with
We included 58 RCTs (29 matching pairs) with 3846 participants (female: n=2803, 72.9%) and mean ages ranging from 20-74 years. White participants were the most frequent (from 63.6% to 100%). Other socioeconomic characteristics were poorly described. The participants presented DDs of different severity measured with heterogeneous instruments. Internet CBT trials had a longer depression duration at baseline (7.19 years higher, CI 95% 2.53-11.84; 10.0 vs 2.8 years;
The baseline characteristics of patients with DDs included in the RCTs of eHealth and face-to-face psychotherapeutic interventions are generally similar. However, patients in eHealth trials had a longer duration of depression, and a lower proportion had received previous depression treatment, which might indicate that eHealth trials attract patients who postpone earlier treatment attempts.
PROSPERO CRD42019085880; https://tinyurl.com/4xufwcyr
Depressive disorders (DDs) affect more than 300 million people worldwide and have prevailed as a leading nonfatal health issue for almost 3 decades [
Psychotherapeutic interventions aim to improve depressive symptoms by increasing self-efficacy, developing coping skills, and changing cognitions, emotions, and behaviors with exercises and sometimes homework between sessions. Examples include cognitive therapy, cognitive behavioral therapy (CBT), interpersonal therapy, and psychodynamic treatments. Face-to-face psychotherapeutic interventions are accepted as a first-line treatment for DDs [
Internet-based (also known as eHealth) psychotherapeutic interventions, such as internet CBT (iCBT), treat psychological problems via digital platforms [
Available meta-analyses suggest that internet-based psychotherapeutic interventions are effective for DDs compared to a waiting list or attention control condition. Internet-based interventions improved depression severity in adults with major depression (SMD –0.90, 95% CI –1.07 to –0.73) [
Although the previous data suggest that iCBT can be as effective as face-to-face CBT for treating DDs, the evidence is not conclusive. Other systematic reviews found that iCBT is more effective than face-to-face CBT at reducing symptom severity in depression (SMD –1.73, 95% CI –2.72 to –0.74) [
At present, using technology to maximize accessibility for depression treatments is an important next step [
The baseline characteristics of patients in the RCTs of eHealth interventions for DDs have received little consideration. Determining whether these characteristics differ among eHealth and face-to-face intervention trials is essential to gain knowledge about the external validity of eHealth trials. The aim of our study was to compare the baseline characteristics of patients with DDs included in the RCTs of eHealth and face-to-face psychotherapeutic interventions with a cognitive component.
This meta-epidemiological study was prospectively registered in PROSPERO (registration CRD42019085880).
We included RCTs published as an article in any language from 1990 to November 2017.
Participants included adults (aged ≥16 years) with a diagnosis of DD according to an established diagnostic procedure. Depression could be the only diagnosis or coexist with other conditions, but DD should be the leading psychological diagnosis. We excluded studies with patients who are hospitalized.
Psychotherapeutic interventions with at least 5 sessions and a cognitive component—that is, cognitive therapy, CBT, and interpersonal therapy—were eligible. We tried to reduce the heterogeneity among the included psychotherapeutic interventions by focusing on those with a cognitive component. From now on, we will label these interventions as CBT, since they share basic principles, such as that cognitions contribute to the maintenance of depression via their association with emotions and behaviors [
As a comparator, the studies should have another psychotherapeutic intervention, a sham intervention, or an inactive control (such as a waiting list). To reduce heterogeneity among the included studies, we excluded pharmacological treatment or bibliotherapy as comparators, since the motivation to participate in these trials may differ. However, we admitted antidepressants with stable dosage as cointervention, as the combination of antidepressants and psychotherapeutic interventions reflects routine practice in managing DDs. We created 2 subgroups of studies based on the following criteria.
eHealth CBT interventions (iCBT): This group included studies evaluating the effects of an eHealth CBT intervention (internet- or device-based self-help program delivered via computer or smartphone). The iCBT must be provided by a health professional with minimum or absent email support. We excluded studies with regular or direct web-based contact (eg, web-based session or chat) or using bibliotherapy on screen. We acknowledge that these can also be eHealth interventions, but we focused on interventions requiring patients working on their own.
Face-to-face CBT interventions (CBT): This group included studies evaluating the effects of a CBT intervention delivered face-to-face—that is, the sessions require the patient and therapist being in the same room with direct contact. We excluded interventions delivered without visual contact—for example, communication via chat or phone exclusively.
We compared the patients’ characteristics at baseline, as shown in
Age (years; mean, SD)
Gender (proportion of women)
Education (proportion of patients with higher education; ie, at least a high school degree)
Living area (proportion of patients living in a metropolitan area)
Depression score (mean, SD)
Depression duration (years; mean, SD)
History of depression (proportion of patients with at least one previous episode of depression)
Previous depression treatment (proportion of patients who had received any kind of treatment for depression; ie, psychotherapy, antidepressants, or both)
Actual antidepressant medication (proportion of patients receiving antidepressants at the start of [and during] the study)
Actual physical comorbidity (proportion of patients having at least one physical comorbidity; eg, diabetes mellitus)
Actual mental comorbidity (proportion of patients having at least one additional mental disorder; eg, Axis I diagnosis)
Study dropout (proportion of patients who dropped out or did not finish the study)
Quality of life (measured with a validated scale; mean, SD)
Proficiency with computers (measured with a validated scale; mean, SD)
Having children (proportion of patients having children)
Family status (proportion of patients living alone; ie, single, divorced, or widowed)
Employment (proportion of patients being employed)
First, we searched the following sources for face-to-face CBT intervention studies: (1) the database of Cuijpers et al [
Second, we searched the following electronic databases (from October 16 to December 31, 2017) for iCBT studies: (1) MEDLINE (via PubMed), (2) Embase, (3) PsycINFO, and (4) Google Scholar. The search strategies combined relevant search terms related to the main concepts of the search (depression, eHealth, and RCTs). We also screened the bibliographies of key publications (see
In the first stage, 1 author (VA) screened the records (titles and abstracts) in the database of Cuijpers et al [
To include a study in the analysis, it must have had a matching study (being either iCBT or face-to face CBT) for all the following factors (all of them predefined and implemented in this order): (1) the same depression measurement or scale (eg, Edinburgh Postnatal Depression Scale), (2) similar depression treatment (eg
Next, 2 researchers (Lena Kümmel and VA) independently used a Microsoft Excel form to extract data on participants, interventions, comparators, outcomes, and matching criteria. JLA cross-checked the extracted numerical data. Discrepancies were resolved by discussion. We did not assess the risk of bias or contact the study authors to clarify unclear information.
For each outcome, we extracted the total number of randomized participants, the number of participants with the characteristic (dichotomous data), and the mean and SD (continuous data). If different scales were used for the same construct, we standardized each study’s mean and SD to a 100-point scale. To standardize means, we applied the following formula:
For missing SDs, we first tried to calculate them from the report using the Review Manager calculator (version 5.4.1; The Cochrane Collaboration) [
We attempted to perform an “available-case analysis” of the randomized population: we took as denominators the randomized participants with a complete baseline measurement of the outcome. We considered the randomized population if the population measured at baseline was unclear. When authors presented the baseline information for those who completed the intervention and those lost to follow-up separately, we pooled the data with the Review Manager calculator (version 5.4.1; The Cochrane Collaboration) [
We used the Comprehensive Meta-Analysis software (version 3; Biostat) [
To test whether each baseline characteristic differed in CBT and iCBT trials, we used a mixed-effects model. This model pools the studies within each subgroup using the random-effects model and tests for differences between the subgroups using a fixed-effects model [
The search for iCBT studies generated 123 records, and the search for face-to-face studies found 351 records. Therefore, we screened 474 titles and abstracts and excluded 290. We examined 184 full-text reports, of which 68 were excluded. We further assessed 64 face-to-face and 52 internet-based full-text RCTs, from which we finally included 29 matching pairs (with a total of 58 included RCTs). More details are provided in
Flow chart. RCT: randomized controlled trial. Face-to-face studies screened from the database of Cuijpers et al [
The studies included a total of 3846 patients. The patients were adults (mean ages ranging from 20 to 74 years in the 57 studies reporting this information) and mostly female (n=2803, 72.9%). In the 29 studies reporting the patients’ race, White patients were the most frequently reported, representing from 63.6% to 100% of the samples. The participants’ socioeconomic status was poorly described in the 58 studies: 39 (67%) studies reported the participants’ education, ranging from college to doctoral degrees. There were 27 (47%) studies that reported the participants’ employment status: from 14% to 80% of the patients were employed (full- or part-time). There were 4 (7%) studies that reported the social class or income of the included participants: from 16% to 36% of the participants had a social class I/II or an income higher than US $30,000/year.
The included patients had different types of DDs: mild to moderate, major depression, postnatal depression, and others. Depression severity was measured with different tools, with the Beck Depression Index being the most common (n=20, 34%). The participants presented mental (eg, addictions) and physical (eg, diabetes mellitus or cardiac surgery) comorbidities that were matched in the study pairs.
All the included studies delivered psychotherapeutic interventions with a cognitive component. The duration of the interventions ranged from 6 to 20 weeks with daily, weekly, or fortnightly sessions that lasted from 10 to 90 minutes each. The cointerventions were poorly described.
The results are provided in
Comparison of eHealth and face-to-face psychotherapeutic studies according to baseline characteristics. No study provided data for the outcome “proficiency with computers.”
Characteristic | Meta-analyses (random-effects model) | |||||||||
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Estimate (95% CI) | Study, n | Participant, n | Subgroup analysesa | |||||
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Difference (95% CI)b | ||||
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–1.89 (–10.08 to 6.29) | .65 | ||||||||
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iCBTc | 39.98 (35.22-44.74) | 29 | 2574 | 99.7 |
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Face-to-face CBTd | 41.81 (35.21-48.54) | 28 | 1056 | 99.5 |
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—e | .16 | ||||||||
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iCBT | 72.9 (69.2-76.4) | 29 | 2575 | 66 |
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Face-to-face CBT | 68.2 (62.2-73.7) | 29 | 1271 | 71.1 |
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— | .38 | ||||||||
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iCBT | 84.1 (77.8-88.8) | 22 | 1801 | 86.4 |
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Face-to-face CBT | 79.2 (67.4-87.5) | 15 | 789 | 85.2 |
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— | .38 | ||||||||
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iCBT | 99.5 (96.2-99.9) | 2 | 345 | 36.9 |
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Face-to-face CBT | 98.1 (88-99.7) | 2 | 52 | <0.001 |
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1.10 (–3.43 to 5.61) | .64 | ||||||||
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iCBT | 41.34 (37.37-45.31) | 29 | 2581 | 98.6 |
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Face-to-face CBT | 42.25 (38.09-42.41) | 28 | 1020 | 96.5 |
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7.19 (2.53-11.84) | .002 | ||||||||
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iCBT | 10.0 (5.6-14.4) | 1 | 36 | 0 |
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Face-to-face CBT | 2.8 (1.2-4.4) | 5 | 155 | 89.2 |
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— | .42 | ||||||||
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iCBT | 56.6 (39-72.7) | 10 | 774 | 93.3 |
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Face-to-face CBT | 65.1 (53.1-75.5) | 10 | 342 | 73.3 |
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— | .04 | ||||||||
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iCBT | 24.8 (18-33.1) | 8 | 908 | 75.2 |
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Face-to-face CBT | 42 (28.3-57.1) | 7 | 303 | 80.9 |
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— | .11 | ||||||||
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iCBT | 33.1 (23.6-44.2) | 13 | 1419 | 91.3 |
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Face-to-face CBT | 14.8 (5-36.6) | 13 | 423 | 85.3 |
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— | .33 | ||||||||
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iCBT | 99.6 (97.3-99.9) | 2 | 254 | 0 |
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Face-to-face CBT | 98.5 (90-99.8) | 2 | 66 | 0 |
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— | .77 | ||||||||
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iCBT | 73.8 (39.2-92.5) | 5 | 132 | 84.6 |
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Face-to-face CBT | 66.9 (28.7-91.1) | 5 | 196 | 89.7 |
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— | .36 | ||||||||
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iCBT | 19.5 (14.1-26.4) | 24 | 1878 | 89.5 |
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Face-to-face CBT | 15.4 (10.1-22.7) | 24 | 987 | 83.4 |
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14.50 (–12.54 to 41.53) | .29 | ||||||||
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iCBT | 48.11 (36.5-59.62) | 9 | 904 | 99.3 |
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Face-to-face CBT | 33.61 (9.15-58.07) | 2 | 90 | 98.5 |
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— | .55 | ||||||||
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iCBT | 99 (95.3-99.8) | 3 | 221 | 0 |
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Face-to-face CBT | 98.1 (91-99.6) | 3 | 79 | 0 |
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— | .37 | ||||||||
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iCBT | 38.3 (30.8-46.5) | 20 | 1795 | 88.2 |
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Face-to-face CBT | 44.2 (34.5-54.4) | 20 | 768 | 83.3 |
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— | .45 | ||||||||
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iCBT | 59.4 (47.9-69.9) | 13 | 1413 | 90.6 |
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Face-to-face CBT | 53 (40.9-64.8) | 13 | 519 | 80.9 |
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aDegrees of freedom=1.
b95% CI for the difference in prevalence was not calculated, as there is no meaningful way to compute it.
ciCBT: internet cognitive behavioral therapy.
dCBT: cognitive behavioral therapy.
eNot available.
fSubgroup analyses for depression measured with individual scores: Beck Depression Inventory (
gProportion of patients (%) having received any kind of treatment for depression (ie, psychotherapy, antidepressants, or both).
The mean depression duration was 7.19 years higher (CI 95% 2.53-11.84) in iCBT trials than in face-to-face CBT trials (10.0 vs 2.8 years;
We found no evidence of differences between iCBT and face-to-face CBT studies for quality of life, having children, family status, and employment. Subgroup analysis for the proficiency with computers could not be performed due to insufficient studies.
To our knowledge, our study is the first to compare the baseline characteristics of patients with DDs included in the RCTs of eHealth and face-to-face CBT interventions. Overall, we found that the patients’ characteristics between eHealth and face-to-face RCTs were generally similar. This finding suggests that patients in both types of trials are comparable rather than different. However, patients in eHealth trials had a longer depression duration, and a lower proportion had received previous depression treatment.
eHealth psychological interventions have several advantages compared to face-to-face interventions. First, iCBT creates the opportunity to deliver psychological treatment to people without access to face-to-face therapy [
We assumed that the baseline characteristics of patients in eHealth and face-to-face psychotherapeutic intervention RCTs would differ. For example, we hypothesized that patients in eHealth RCTs would be younger due to their familiarity with computers and frequent use of social media [
Our study found that patients in eHealth RCTs presented a longer depression duration but had received previous depression treatment in a lower number. The longer depression duration in eHealth RCTs could be explained by the fact that patients in eHealth trials perceive barriers concerning face-to-face treatments, and therefore, eHealth treatment might be more attractive to them. Conversely, we expected that patients in eHealth RCTs would present more severe depression since a lower proportion had received treatment for depression. However, our analyses did not support this assumption. Finally, our findings might indicate that eHealth trials attract patients who postpone earlier treatment attempts, but future research should be conducted to confirm this finding.
Our searches identified a high number of RCTs, which confirms the recent expansion of research into digital interventions [
This incomplete reporting highlights the need to agree to a consensus-based minimum set of baseline characteristics that should be measured and reported in all RCTs of eHealth psychotherapeutic interventions. Once the list is defined, consensus should be achieved on how to measure these characteristics, such as which measurement instruments should be selected to measure proficiency with computers. Finally, the reporting of these characteristics should be encouraged in future RCTs to allow the assessment of the applicability of the study findings.
Our study had several limitations, but we tried to overcome them by following rigorous methods [
First, our searches may have missed eligible studies. Particularly, we limited the searches from 1990 onward as no eligible study would have been published before. The restriction until 2017 was because the searches were executed that year, and we did not have the resources to update them. However, we did not attempt to perform a systematic review and, thus, include all the studies in this field. We consider that the 58 included RCTs probably give an unbiased view of the situation in this research field.
Second, our matching process by relevant characteristics may have minimized differences between subgroups. Moreover, otherwise eligible studies were excluded because we could not find their matching pair. However, we consider that the matching process minimized confounding in the subgroup analyses (see below).
Third, subgroup analysis is a technique with considerable pitfalls. Nevertheless, we followed established guidelines to overcome the main limitations. (1) We prevented post hoc analyses and undue emphasis on particular findings by choosing the analyses in advance with clear rationale [
Fourth, there is an increasing risk of type 2 error concurrent with the number of analyses, which was 16 in our case [
This is the first study comparing the baseline characteristics of patients with DDs included in the RCTs of eHealth and face-to-face psychotherapeutic interventions. Overall, our study did not find differences in the patients’ characteristics between eHealth and face-to-face RCTs. However, patients in eHealth trials had a longer depression duration, and a lower proportion had received previous depression treatment. This finding might indicate that eHealth trials attract patients who postpone earlier treatment attempts. Our findings highlight a need to improve the reporting of the baseline characteristics of patients included in the RCTs of eHealth psychotherapeutic interventions.
Key publications.
Included studies.
Summary of the included studies.
Meta-analyses of baseline characteristics.
cognitive behavioral therapy
depressive disorder
internet cognitive behavioral therapy
randomized controlled trial
standardized mean difference
We thank Christopher James Rose (Norwegian Institute of Public Health) and Alfonso Muriel and Borja Manuel Felix (Hospital Universitario Ramón y Cajal) for their statistical support.
CMW, JB, and VA defined the research question. VA performed the searches. All authors discussed the inclusion and matching criteria. Lena Kümmel and VA selected the studies. VA matched the included studies. Lena Kümmel and VA independently extracted the outcome data. The data extraction was cross-checked by JLA. JLA and VA performed the analysis. JLA and VA wrote the manuscript under the supervision of JB. All authors approved the final manuscript.
CMW has active research grants to the University for digital health projects from the German health care Innovation Fund, and Newsense Lab GmbH. Board positions related to digital health for mind and body (nonpaid) are as follows: Co-Director of the Digital Society Initiative of the University of Zurich and President Fachverband Mind Body Medicine. All other authors do not have any conflict related to the content of the manuscript.