Common mental health problems, particularly depression, are on track to be the leading cause of global disease burden by 2030 (WHO, 2012). The global prevalence of these disorders has been growing steadily, but there has been a significant hike in numbers since the onset of the pandemic. There are estimates of a rise of 52.2 million cases of depression, and 76.2 million cases of anxiety in 2020 alone (Santomauro et al., 2021).
Cognitive Behavioural Therapy (CBT) is effective in treating depression and anxiety, as seen across multiple meta-analyses and systematic reviews (Cape et al., 2010; Watts et al., 2014; Fordham et al., 2021). However, traditional CBT remains unlikely to increase accessibility to mental health services (Lovell & Richards, 2000). Exciting research developments have highlighted a potential remedy to this problem via Internet/computerised CBT (iCBT). However, the generalisability of this research area seems questionable. For example, effect sizes can rely on recruitment method (i.e., clinical vs. community recruitment) (Reomjin et al., 2019). Randomised controlled trials (RCTs) may overestimate the effectiveness of iCBT due to their settings being highly controlled by researchers; often reflecting a perfect version of the tested treatment (Wells, 1999). Therefore, we should not assume that the results of RCT research could be replicated under real-life clinical conditions.
In a systematic review and meta-analysis, Etzelmueller et al. (2020) attempt to investigate the effects of therapeutically guided iCBT for anxiety and depression under routine care conditions.
The authors searched three databases for articles examining the effectiveness of guided/blended iCBT, including participants with anxiety/depressive symptoms. All took place in routine care conditions with outcomes measured before and after treatment. Potential articles were checked by two independent reviewers, and a third in the case of disagreement.
Data on the variables in question were extracted independently by two reviewers, then the datasets were synthesised. Uncertainties were resolved through collaborative discussion, re-reading of the articles, and sometimes by conversing with the authors of the articles.
Bias risk was examined by adapting two quality assessment tools to the study’s needs and purposes. Various statistical analysis methods were then used to identify differences (e.g., Hedges g for symptom differences, i2 statistics for heterogeneity, etc.). Publication bias was investigated using Egger tests and funnel plots.
The initial literature search identified a total of 25,447 articles, which was then reduced to 17 articles after screening and refinement. There were 12,096 participants across the final studies, with 64.4% being female and an average age of 38 years old.
iCBT service characteristics
- 31.6% of services used clinical referrals, 26.3% included patients through the community, and 42.1% took referrals using both previously mentioned methods.
- The average number of sessions across all services was 8.
- Only 16.7% provided feedback to clients in response to client actions.
- 23.3% of services used untrained guides to assist clients, 63% supervised their guides, and 26.7% of guides had intervention manuals.
- 47.4% of services reported using risk assessments/safety measures to identify high-risk clients.
- The average pre-post effect size across treatments was 1.18, which the authors considered to be large, adding that they expect the effect size across 95% of populations to be within 0.74 to 1.62.
- The effect size depended on whether coaches were trained (no training produces a lower effect size), as well as on whether coaches were supervised (supervision appears to heighten effect sizes).
- The duration of treatment also impacted the effect size, with treatment lasting between 9-13 weeks having a smaller effect size.
- The average pre-post effect size of all treatments, including those for comorbid depression and anxiety, was 0.94 – a large effect. Confidence intervals predicted that in 95% of populations, an effect size of 0.44 to 1.44 will be found.
- The effect size was related to whether coaches were trained or not and coaches possessing a training manual (with this producing an effect size of 1.07), but supervision of coaches had no effect, along with the duration of treatment.
- 41% of the research reported deterioration, with an average rate of 2.9. No study reported other negative effects, with one saying there were no adverse outcomes at all. No study reported any predictors of negative effects.
- 48% of people screened by services started a course of treatment. The average percentage of sessions completed was 61.2%, with 61.3% of participants completing the whole course.
- Of the included studies, 10 (58.8%) reported patient satisfaction, with 9/10 reporting high or very high satisfaction. However, satisfaction outcomes were inconsistent as studies had different outcome measures – meaning the data could not be pooled.
The authors concluded positively, stating that their research:
provides further evidence supporting the acceptability and effectiveness of guided iCBT for the treatment of depression and anxiety when implemented in routine care.
Strengths and limitations
The authors addressed an important gap in research: is iCBT as effective in practice as in theory? The exclusion of studies using randomised control trials enabled the authors to gather a synthesised understanding of what iCBT would look like in more widespread practice. This suggests that ecological validity – defined as “when experimental findings reflect the real world outside of the laboratory” (Kihlstrom, 2021) – was achieved. This is very important when studying potential new mental health interventions, as we need to know that interventions really work before we trust them to assist large amounts of people in need of help.
However, this research used quantitative articles only. Including qualitative research allows for the inclusion of service-user voices. For example, a qualitative systematic review found that perceptions of iCBT amongst young people are mostly positive, just like the study in question, but delved deeper to discover why this is, finding themes of hopefulness, flexibility, and helpfulness from fun experiences (McCashin, Coyle & O’Reilley, 2019). Service-user voices can provide a deeper understanding of quantitative findings and authors should strive to include them in future research.
Under half of the services included in this research used risk assessments to identify high-risk clients, and over half excluded patients with severe depression/anxiety. The research then concludes by highlighting the importance of monitoring upcoming crises, and that iCBT can have positive effects on suicidality. It appears that this is a subtopic of mental health that the current research lacks clarity on. The statement about the positive effects of iCBT on suicidality was not found in this research, which addresses the generalisability problem in most online intervention research. Therefore, it is not clear whether the findings of this research can be generalised to suicidal service-users.
Implications for practice
An important barrier to breaking into mental healthcare is that of accessibility. A pandemic-related mental health crisis is looming, through restrictions and lockdowns, grief, and anxiety and depression related to virus exposure (Wind, Rijkeboer, Andersson & Riper, 2020), making this barrier even more fundamental to break. Aside from this, there have always been populations who have struggled with accessing traditional face-to-face therapy, such as family carers (Scott et al., 2016). As someone who struggles with mental health and has also provided full-time live-in care for a relative who had a neurodegenerative condition, this point rings true. I often found myself feeling isolated and anxious but felt I could not access help for this as I was not able to leave the house – because of my caring responsibilities and because of my mental health. This is an area where online interventions could be extremely positively impactful.
The NHS appears to be developing online/technological psychological interventions already through IAPT services, which offer low-intensity guided self-help programmes as the first line of treatment (Wakefield et al., 2021). Research into the efficacy and effects of online treatment is vital, as it could be that online interventions are becoming the future of mental healthcare.
However, it is questionable whether these implications are this impactful without investigating how online therapy could be unhelpful to clients. Several papers investigating online therapies found negative perceptions, such as clients feeling unsupported by clinicians, generalised materials and exercises being irrelevant to service-user issues, difficulty staying motivated, and misunderstanding of computerised feedback (Pedersen et al., 2020; Gericke et al., 2021). The current research does not provide insight into this, which would be an important issue when iCBT is applied to routine care.
Statement of interests
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