Objective Determine the effectiveness of digital mental health interventions for individuals with a concomitant chronic disease.
Design We conducted a rapid review of systematic reviews. Two reviewers independently conducted study selection and risk of bias evaluation. A standardised extraction form was used. Data are reported narratively.
Interventions We included systematic reviews of digital health interventions aiming to prevent, detect or manage mental health problems in individuals with a pre-existing chronic disease, including chronic mental health illnesses, published in 2010 or after.
Main outcome measure Reports on mental health outcomes (eg, anxiety symptoms and depression symptoms).
Results We included 35 reviews, totalling 702 primary studies with a total sample of 50 692 participants. We structured the results in four population clusters: (1) chronic diseases, (2) cancer, (3) mental health and (4) children and youth. For populations presenting a chronic disease or cancer, health provider directed digital interventions (eg, web-based consultation, internet cognitive–behavioural therapy) are effective and safe. Further analyses are required in order to provide stronger recommendations regarding relevance for specific population (such as children and youth). Web-based interventions and email were the modes of administration that had the most reports of improvement. Virtual reality, smartphone applications and patient portal had limited reports of improvement.
Conclusions Digital technologies could be used to prevent and manage mental health problems in people living with chronic conditions, with consideration for the age group and type of technology used.
- mental health
- health informatics
- general medicine (see internal medicine)
Data availability statement
Data are available on reasonable request with the first (MS) or last (MPG) authors.
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
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Strengths and limitations of this study
We conducted a rapid review of systematic reviews published in the last 10 years, including a large body of evidence in four clusters of population.
A panel of knowledge users were involved in each step of the review, from conceptualisation to publication to ensure relevance in clinical context and policy making.
Study selection and bias evaluation were completed by two independent reviewers and data extraction used a standardised form.
We limited the search to the most relevant databases and the last 10 years.
The overlapping of primary studies was not evaluated.
Chronic diseases are the main burden on healthcare systems in developed countries and account for almost 70% of deaths worldwide.1 An individual with a chronic condition is two to three times more likely to present a concomitant mental health problem than the general population.2 As the number of physical chronic conditions increase in a population, so do the mental health ones. The co-occurrence of chronic and mental health conditions leads to an increase in total healthcare costs and services utilisation, as well as poorer quality of life and health outcomes for these individuals.3 4
The psychosocial consequences of the current COVID-19 pandemic are alarming and will persist long after the pandemic is over.5 In the current COVID-19 pandemic context, efforts have been invested to rapidly produce scientific evidence in mental health for adapting the clinical setting and supporting policy making (eg, confinement measures). Adapting to telehealth, when in-person consultation is not recommended, requires efficient and relevant digital mental health interventions for the population with concomitant chronic diseases and mental health issues. While a large number of interventions using digital technologies have been evaluated for the management of depression or anxiety,6 7 the relevance of these interventions for people living with chronic diseases remains to be defined.
This rapid review of systematic reviews aimed to determine effectiveness of digital mental health interventions aiming to prevent, detect or manage mental health problems in individuals with a pre-existing chronic condition.
We conducted a rapid review following the guidance from the Cochrane Rapid Reviews Methods Group.8 We report our results based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Statement.9 The protocol for this rapid review was registered in the National Collaborating Centre for Methods and Tools COVID-19 Rapid Evidence Service (ID 75).
Knowledge users engagement
We engaged a panel of knowledge users (patients, clinicians and decision makers), content experts, review methodologists and researchers throughout the review process, from question development, literature search, data extraction and analysis, interpretation and writing of results, and dissemination of findings.
We followed the PICO Framework in establishing eligibility criteria10 (table 1). We considered any review that included digital health interventions aiming to prevent, detect or manage mental health problems in individuals with a pre-existing chronic disease, including chronic mental health diseases, published in 2010 or after. There was no language restriction.
An experienced medical information specialist developed and tested the search strategies through an iterative process in consultation with the review team and knowledge users. Using the OVID platform, we searched Ovid MEDLINE, including Epub Ahead of Print and In-Process & Other Non-Indexed Citations, Embase Classic+Embase, Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects and the Health Technology Assessment Database. We also searched CINAHL (EBSCO) and Web of Science. All searches were performed on 11 June 2020. We used a combination of controlled vocabulary (eg, “Chronic Disease”, “Mood Disorders” and “Internet”) and keywords (eg, “cancer”, “anxiety” and “telehealth”) and adjusted vocabulary and syntax across the databases. We applied a systematic review filter to all searches except for the Cochrane databases, where it is not required. Specific details regarding the strategies appear in online supplemental file 1).
Study selection, data extraction and synthesis
Six reviewers individually performed screening for titles, abstracts and then full text using a standardised form pilot-tested by all reviewers on 25 citations. All citations were reviewed by two reviewers independently at the first level of screening. We developed a standardised extraction form that included study characteristics (eg, authors, country and design), intervention characteristics (eg, type of digital intervention) and outcomes reported. A senior reviewer reviewed all full-text citations for inclusion. Single reviewers extracted data, which were then confirmed by a senior reviewer. We resolved discrepancies through discussion. We report data using a narrative approach that includes tables of study characteristics, intervention characteristics and mental health outcomes.
We used the AMSTAR 2 tool to critically appraise each included review.11 This revised version of the AMSTAR tool was developed for the evaluation of systematic reviews that include randomised or non-randomised studies of healthcare interventions. This tool has good inter-rater reliability, is widely used for healthcare research and uses a four-level rating of overall confidence. A single reviewer rated the critical appraisal tool and all judgements were verified by a second author.11
Patient and public involvement
A panel of knowledge users (patients and clinicians) was involved throughout the research process, from funding acquisition to publication. The panel will also be involved in subsequent dissemination activities.
Characteristics of included reviews
Our search strategy identified 2320 individual citation. Following screening of titles and abstracts, we excluded 2153 records. We excluded an additional 132 citations during full-text screening, resulting in a total of 35 citations included in our review (figure 1).12–46Of these reviews, there were 17 systematic reviews, 17 systematic reviews with meta-analysis and one integrative review, totalising 702 primary studies with a total sample of 50 692 participants.
Most reviews described digital interventions performed in a specialised care setting (42%) and targeted an adult population (83%). They were looking at interventions to manage and treat a mental health problem (60%), testing web-based and internet interventions (32%) by comparing them with usual care (48%), for people affected with cancer or various chronic diseases (77%). We present the complete description of included reviews in table 2. A presentation of the reviews by technology used in available in additional table 1.
The overall confidence ratings of the AMSTAR 2 tool were mostly high or moderate (31/35) with a limited number of low ratings (4/35) and no critically low rating (table 3). A small percentage of the AMSTAR 2 items were not reported in the included reviews with the exception of the source of funding of primary studies in the included reviews (0%) (figure 2).
We structured our synthesis according to four population clusters: (1) chronic diseases; (2) cancer; (3) mental health; and (4) children and youth. The mental health outcomes found in the included reviews were mainly depression and anxiety symptoms, assessed through heterogeneous outcomes measures. The results are further presented by type of reporting (quantitative or narrative).
Chronic diseases cluster
We identified 13 reviews referring to people with various chronic diseases (table 2). Six of the 13 reviews reported their results using pooled difference of score mean.16 19 23 36 42 43 The majority of the reviews presenting quantitative results reported improvement of depressive symptoms (5/6), but only one identified improvement in anxiety symptoms (1/3). One review reported improvement of general distress.42 The synthesis with the largest effect size included 108 primary studies with only web-based and internet cognitive–behavioural therapy (CBT) interventions.23 Most of the reviews that yielded narrative results reported improvement of depressive symptoms (6/7), improvement in anxiety symptoms (6/7) and psychosocial outcomes (1/1). Only one report of inferior effectiveness was identified for both depression and anxiety symptoms.18 Narrative reports described a small to moderate effect size within group in depression and anxiety symptoms. One integrative review report based on qualitative data described that digital health interventions for people with chronic diseases promoted active acceptance of their disease, improved the awareness of physical manifestations of the disease, helped identify signs and symptoms of worsening and improved management of acute events.18 The types of digital technology that had the most reports of improvements were web-based interventions, followed by email. Virtual reality and patient portal had no reports of improvements on outcomes when used (table 4).
We identified 14 reviews referring to people with cancer (table 2). Quantitative reporting was present in six reviews.17 24 25 30 44 46 Four (4/6) of those reported improvements of depressive symptoms, and half showed improvements in anxiety symptoms (3/6). Other quantitative reports of improvements in mental health outcomes included distress and quality of life. The quantitative report with the largest effect size included 20 primary studies, a total sample of 2190 participants, and looked at web-based and teleconsultations CBT interventions.17 Reviews that yielded narrative results reported improvements of depression symptoms (6/7), anxiety symptoms (5/5), distress (3/3), quality of life (1/1) and mood regulation (1/1). Pooling of the results was impossible in one review due to heterogeneity.12 The narrative outcome reports described a small effect size within group for depression and anxiety symptoms.21 The types of digital intervention that had the most reports of improvements were web-based interventions and email. Virtual reality had no reports of improvements (table 4)
Children and youth cluster
We identified four reviews related to digital health interventions targeting children and youth (table 2). Two reviews reported a quantitative synthesis presenting mixed effects: one showing within group improvements in depression and anxiety and both showing no between group difference on these outcomes.20 39 As for narrative syntheses, both reported improvements on depression and anxiety, with one of the reviews reporting on post-traumatic stress disorder (PTSD) symptoms improvement.28 32 The limited reports on improvement for this population was associated with the used of web-based interventions (3/4), smartphone applications (2/4) and virtual reality (1/4) (table 4).
Mental health cluster
We identified four reviews related to population with mental health conditions (table 2). The quantitative reports showed improvements in anxiety symptoms for generalised anxiety disorder and disease-specific anxiety (3/3), improvements of depression symptoms (1/1) and PTSD symptoms (1/1). The only narrative report for that cluster showed no improvement on PTSD symptoms between groups.45 The types of digital technology that had the most reports of improvement were web-based interventions (3/4) and email (2/4) with unique reports for smart phone applications, text messages and online chat (table 4).
We conducted a rapid review of systematic reviews to identify digital health interventions effective to prevent, detect or manage mental health problems in individuals with a pre-existing chronic disease. In total, 35 reviews were included.
Our findings are in line with the extensive evidence that internet CBT interventions are effective and comparable to face-to-face interventions.47 Our analysis adds to the body of evidence on effectiveness regarding concomitant chronic diseases in four clusters of population. For people with various chronic diseases, most of the included reviews showed that digital health interventions have a positive effect on depression, anxiety, distress and psychosocial outcomes. The data showed that interventions have a moderate effect size within the intervention group and a small effect size when compared with usual care. For the cluster of population affected by cancer (including survival), evidence already exists regarding the effectiveness of digital mental health interventions with positive to mixed effect.48 Our data also showed that digital health interventions are effective in improving depression, anxiety, distress, quality of life and mood regulation. Also, teleconsultation and web-based interventions were the most effective modes of delivery for this population. Regarding the paediatric population, a meta-review targeting digital mental health interventions for children and youth reported a positive effect for the use of web-based CBT but only in children and youth with anxiety and depression with no other concomitant conditions.49 Quantitative data were inconclusive regarding effectiveness and effect size within group but showed a non-inferiority when compared with usual care. All included reviews in this population combined smartphone applications and web-based interventions, making it difficult to draw any conclusion about the most effective mode of delivery for the intervention at this level of analysis. For the mental health population, the included reviews emphasised that digital health interventions are effective for individuals with a combination of physical and mental conditions, as well as for people with multiple mental health problems.
Available evidence suggests that digital health interventions such as web-based CBT, email messaging and teleconsultation could be effective and provide an alternative to face-to-face psychological interventions to prevent and manage mental health problems in people affected by cancer or other chronic diseases. In line with our findings, Torous et al50 described that offering health provider-directed synchronous digital health solutions such as teleconsultation is the first step to increase access to quality mental healthcare in the midst of the COVID-19 pandemic. Many of these innovations support the care of people in need of special attention, including those with chronic illnesses. Due to smaller effect size, we were not able to draw any conclusion related to the other forms of digital health interventions such as online chat, text message and smartphone applications. These types of digital health interventions are asynchronous; they may improve access and promote low-threshold alternatives to mental health consultations within the healthcare system. However, more evidence regarding implementation and evaluation to be safe for patients would be required.50 Included reviews that looked at other intervention delivery methods reported smaller to no effect, but it could be related to heterogeneity of the data. Even with reports of effectiveness, there is still a lack of evidence of economic data to perform a proper cost analysis of digital health interventions.51 52
This review was rapidly performed to inform knowledge users in a timely matter. In line with recommendations for rapid reviews,53 methods that would lead to a systematic review were not followed as strictly to allow for a faster methodology. We limited the scope of the search to the aim of the study by looking at limited databases and imposing a period of publication. These methodological choices resulted in the ability to perform an appropriate and structured study selection, data extraction and critical appraisal.
This rapid review of reviews has limitations. In order to respect the requirements of this urgent strategic call in response to the COVID-19 pandemic and provide stakeholders and decision makers with up-to-date evidence, we limited the search to the most relevant databases and the last 10 years. Despite our best efforts, we may have missed some publications. Moreover, we did not assess the overlapping of primary studies in the included reviews. While we rigorously followed guidance for the conduct of rapid reviews, results from this study should be interpreted with caution. Further analyses will be required for stronger recommendations, notably by considering the potential publication bias, as well as other factors that could decrease the level of confidence in the reported effects.
Future research on digital mental health interventions should provide economic data to give a broader insight for possible implementation. Research on digital mental health interventions could also further assess the safety and limitations of asynchronous and self-administered technologies. Finally, efforts should be put on developing a structured method to report what kind of technology (eg, internet based and smartphone app) and function (eg, communication, intervention and evaluation) were used in the intervention. A structured method of reporting would improve the evidence precision and knowledge implementation.
This rapid review outlines the current evidence regarding the use of digital health interventions for people with a concomitant chronic disease. For individuals with a chronic disease or cancer, health provider directed digital interventions (eg, teleconsultation) are effective and safe. However, further analyses of this large body of evidence are required in order to provide precise recommendations regarding relevance for specific populations (such as children and youth), modes of delivery and type of intervention. In response to the current crisis, but also to better prepare for the postcrisis and future crises, digital technologies could be used to prevent and manage mental health problems in people living with chronic conditions, with consideration for the age group and type of technology used.
Data availability statement
Data are available on reasonable request with the first (MS) or last (MPG) authors.
The authors would like to thank the knowledge users for their support throughout this review and the SPOR Evidence Alliance for their support.
Contributors MS, AL, M-PG, M-CC, MBe, NB, PC, CA, AL and GC identified the need for this study and contributed to its conception and design. BS developed and conducted the search strategy. MS, M-PG, MBo, MD, MG and JT conducted the data collection and analysis. MS developed the first draft of the report. All authors contributed to writing and editing and gave the final approval of the version submitted.
Funding This review was funded by the Canadian Institute for Health Research in the Operating Grant: Knowledge Synthesis: COVID-19 in Mental Health & Substance Use. Grant number: 202005CMS-442711-CMV-CFBA-111141.
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.
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