Efficacy of virtual interventions for reducing symptoms of depression in community-dwelling older adults: a systematic review

ABSTRACT Background: Older adults experience symptoms of depression, leading to suffering and increased morbidity and mortality. Although we have effective depression therapies, physical distancing and other public health measures have severely limited access to in-person interventions. Objective: To describe the efficacy of virtual interventions for reducing symptoms of depression in community-dwelling older adults. Design: Systematic review. Setting: We searched MEDLINE, EMBASE, Cochrane Libraries, PsycINFO, and gray literature from inception to July 5, 2021. Participants and interventions: We included randomized trials (RCTs) comparing the efficacy of virtual interventions to any other virtual intervention or usual care in community-dwelling adults ≥60 years old experiencing symptoms of depression or depression as an outcome. Measurements: The primary outcome was change in symptoms of depression measured by any depression scale. Results: We screened 12,290 abstracts and 830 full text papers. We included 15 RCTs (3100 participants). Five RCTs examined persons with depression symptoms at baseline and ten examined depression as an outcome only. Included studies demonstrated feasibility of interventions such as internet or telephone cognitive behavioral therapy with some papers showing statistically significant improvement in depressive symptoms. Conclusions: There is a paucity of studies examining virtual interventions in older adults with depression. Given difficulty in accessing in-person therapies in a pandemic and poor access for people living in rural and remote regions, there is an urgent need to explore efficacy, effectiveness, and implementation of virtual therapies.


Why does this paper matter?
The pandemic highlighted a need for improved virtual access to interventions that can reduce symptoms of depression in older adults. It is unclear which interventions are efficacious for reducing these symptoms. We identified virtual interventions that reduced symptoms of depression in older adults, including cognitive behavioral therapies.

Key points
1. Virtual (telephone or videoconference) selfdirected or supported cognitive behavioral therapy had statistically significant effects on reducing symptoms of depression in individual studies, but the clinical significance of these findings is unclear.
2. Older adults need access to efficacious psychotherapy interventions (e.g. cognitive behavioral therapy, chronic disease support) to reduce symptoms of depression; however, more studies are needed urgently to establish their efficacy via virtual modalities.

Introduction
Symptoms of depression are one of the most common mental health issues in older adults. Fifteen to 20% of community-dwelling older adults experience 'substantial symptoms of depression' (MacCourt and Tourigny-Rivard, 2011). Depressed older adults have poorer quality of life (Doraiswamy et al., 2002), difficulty with day-to-day tasks (Schillerstrom et al., 2008), and higher mortality (MacCourt and Tourigny-Rivard, 2011) compared to those without depression. Efficacious psychotherapies exist to reduce symptoms of depression for older adults with depression (MacQueen et al., 2016), but a lack of access to these interventions during the pandemic has precluded their use (Raue et al., 2017;Yang et al., 2020). Given minimal evidence of efficacy and the risk of adverse events with pharmacologic therapy, psychotherapy is a key initial component of treatment (MacQueen et al., 2016;Sobieraj et al., 2019).
Public health measures to minimize COVID-19 spread increased social isolation for older adults, which can worsen mood (Armitage and Nellums, 2020;Steinman et al., 2020). However, virtual options may facilitate use of interventions in settings where in person access is not feasible. There is increasing support for the use of virtual care in older adults, and rapid uptake during the COVID-19 pandemic has provided an understanding of usefulness Liu et al., 2021). A large retrospective cohort from the United States involving 313,516 telehealth visits in adults over 60 years from 2015 to 2019 (Bernstein et al., 2021) found that 84-87% of urgent and nonurgent primary care issues were resolved (Bernstein et al., 2021). For those patients who needed further visits, 95% of these were resolved in less than three visits (either in person or virtual) (Bernstein et al., 2021). The study also noted that certain conditions could be similarly addressed with either phone or videoconference visits (e.g. UTI) (Bernstein et al., 2021).
However, there are concerns around the barriers faced by older adults when trying to access virtual care. A cross-sectional study of 330 patients found that older adults who are frail or do not have a caregiver were less able to access videoconferencebased virtual care (Liu et al., 2021). When examining the accuracy of virtual cognitive testing in a systematic review, many barriers and facilitators to virtual care were identified, including sensory impairment, severe cognitive impairment, physical issues, and issues with technology .
To inform clinical practice during the COVID-19 pandemic, we conducted a systematic review of randomized controlled trials (RCTs) reporting the efficacy of virtual interventions for reducing symptoms of depression in older adults.

Methods
We registered our systematic review with PROS-PERO (CRD42020188465) and disseminated our protocol on Open Science Framework (https://osf .io/6tjcy/). We followed the Cochrane Handbook for Systematic Reviews of Interventions (Higgins and Green, 2011) and reported as per Preferred Reporting Items for Systematic Reviews and Meta-Analysis criteria (Moher et al., 2010;Page et al., 2021). All methods were reviewed by stakeholders, including persons with lived experience, and feedback was incorporated.

Study selection
We included RCTs comparing the efficacy of any virtual (e.g. telephone, videoconference, or internetbased) nonpharmacologic intervention to usual care or any other virtual nonpharmacologic intervention for reducing symptoms of depression in communitydwelling older adults (defined as ≥ 60 years old and average age ≥ 65 years old) with depressive symptoms or disorders at baseline or where depression was measured as an outcome (APA, 2013). We excluded interventions that incorporated both virtual and in-person components, as the focus was on interventions that were entirely administered virtually. We also excluded RCTs where the entire study population had a single specific medical comorbidity (e.g. heart failure), as these populations were too specific. We included studies where the population had multiple comorbidities, as this is representative of older populations. Two reviewers (ZG, JW) independently completed two study screening levels, after a calibration exercise to ensure agreement, conflicts were reviewed by a third party (i.e. title/ abstract and full-text papers).
Data extraction and risk of bias assessment After piloting, ZG and PW independently extracted data from included full-text papers and completed a risk of bias appraisal using the Cochrane Risk of Bias Tool for RCTs Green, 2011, Higgins et al., 2011). We extracted the following data: participant characteristics (e.g. age of study population, proportion of female study participants, proportion of participants with symptoms of depression or disorders at RCT baseline, presence of psychiatric comorbidities), study characteristics (e.g. year of publication, authorship, study setting [i.e. urban vs. rural], sample size, study duration, number of RCT intervention arms, inclusion criteria, exclusion criteria), details of intervention, how it was implemented and outcome data (e.g. mean depression scores pre and post intervention) from each intervention group. We extracted outcomes from all follow-up intervals. Where RCTs reported ≥ 2 scales for the same outcome, we extracted data from all reported scales. We reported outcomes from the commonly used Patient Health Questionnaire-9 (PHQ-9) (Spitzer et al., 1999), where available, in order to facilitate comparison between studies. The minimally clinical important difference (MCID) for community-dwelling older adults is 5 points for the PHQ-9 (on a scale from 0 to 27) (Lowe et al., 2004). If there were multiple tools used to measure outcomes, we reported tools specific to symptoms of depression or disorders over a subscale. We did not conduct a meta-analysis due to heterogeneity in study populations across studies, comparison groups (e.g. active vs. usual care), and virtual intervention delivery modalities.

Search results
The literature search identified 2633 citations after duplicates were removed ( Figure 1). Fifteen RCTs (n = 3100) were included in the systematic review, and one study was reported in two publications (Brenes et al., 2017;Brenes et al., 2015).

Study and patient characteristics
All RCTs were published since 2006 (Table 1). The mean age for all participants in included RCTs was 65.1-79.2 years. In included RCTs, the proportion of female participants ranged from 47% to 100%. Included studies were completed predominately in the United States (number [n] = 8) and Australia (n = 4). All RCTs excluded persons with suicidality or severe symptoms of depression or disorders (Supplementary Table 3). Nine studies had participants with co-diagnoses of anxiety and depression.
Included RCTs focused on two main groups: persons with symptoms of depression or disorders at baseline (n = 5) or those where symptoms of depression were measured as an outcome only (n = 10).

Risk of bias assessment
Allocation concealment (n = 10 unclear) and blinding procedures (n = 11 unclear; n = 4 high risk) were the most important sources of bias (Supplementary Table 4). Blinding of outcome assessment was variable, with only four studies being at low risk of bias. Most studies had low risk of bias for random sequence generation (n = 13), incomplete outcome reporting (n = 8), and selective reporting (n = 12).

RCTS W H E R E D E P R E S S I V E S Y M P T O M S O R D I S O R D E R S W E R E P R E S E N T A T B A S E L I N E ( P R I M A R Y O U T C O M E ).
In five RCTs, where participants had symptoms of depression or disorders at baseline (Table 2), the Virtual interventions for depressive symptoms 133 following therapies were compared to another intervention or usual care: telehealth management of chronic illness (Gellis et al., 2014), problemsolving therapy (Gellis et al., 2014), medication review (Mavandadi et al., 2015), mental health algorithms (Mavandadi et al., 2015), and cognitive behavioral therapy (CBT) (Silfvernagel et al., 2018;Titov et al., 2016;Titov et al., 2015). All interventions were delivered over the telephone or internet. The level of health care provider involvement in interventions varied from entirely selfdirected to being closely followed by healthcare providers. Health care providers involved were social workers, counsellors, nurses, or psychologists. The cognitive behavioral therapies used included mindfulness, problem-solving skills, behavioral activation, interpersonal skills, and psychoeducation. Self-guided CBT was done at the pace of the individual and sessions with clinicians ranged from 10 to 35 minutes.
The PHQ-9 was the most common tool used in four RCTs (Table 2 and Supplementary Table 5). All RCTs reported immediate post intervention outcomes at 8-12 weeks, and 4 RCTs reported outcomes at 24-or 52-weeks post intervention. Between study clinical and methodological differences precluded meta-analysis.
Of the four RCTs, two showed a statistically significant difference between groups at the initial follow-up (Titov et al., 2015;Gellis et al., 2012;Szczepanska-Gieracha et al., 2021). Internet CBT with online guidance compared to waitlist control demonstrated efficacy (Titov et al., 2015). In this study, authors explored an 8 week "Managing Your Mood Course", focused on five online lessons, with reminders, homework, case stories, and secure emailing with a clinical psychologist (Titov et al., 2015). This course involved didactic lessons including case learning with skills training (Titov et al., 2015). When comparing telehealth for chronic illness/depression to nursing check in and education, there was a statistically significant improvement at 3 months, but not at longer follow-up (Gellis et al., 2014). Neither met the between-groups MCID and only had small effect sizes.
Three studies demonstrated a statistically significant group by time interaction between interventions (Mavandadi et al., 2015;Silfvernagel et al., 2018;Shapira et al., 2021). One study examined mental health case management compared to monitoring alone (Mavandadi et al., 2015). Another examined internet CBT with online guidance by a clinician compared to weekly email support by clinicians (Silfvernagel et al., 2018).      Another showed significant change within groups but not between the three comparison groups of: i) internet CBT with orientation and clinician guidance, ii) internet CBT with orientation, and iii) internet CBT alone (Titov et al., 2016). One study examined a Zoom group intervention during COVID-19 (Shapira et al., 2021). In this intervention, participants did twice weekly online guided group sessions with social workers (Shapira et al., 2021). The goal was to provide social interaction and education on cognitive behavioral techniques (Shapira et al., 2021). There was a statistically different change between pre and post loneliness scores (Shapira et al., 2021). None of the studies reporting the PHQ-9 met the MCID.

RCTS W H E R E P A R T I C I P A N T S D O N O T H A V E B A S E L I N E S Y M P T O M S O R D I A G N O S I S O F D E P R E S S I O N , B U T W H E R E S Y M P T O M S O F D E P R E S S I O N W E R E M E A S U R E D A S A N O U T C O M E
Ten RCTs measured symptoms of depression solely as an outcome (Table 2 and Supplementary Table  5). Interventions focused on CBT investigated a range of support from an initial orientation to weekly clinician support and included various aspects of therapy such as relaxation (Supplementary Table 5 for details). Most studies (n = 5) looked at populations with anxiety (Brenes et al., 2017;Brenes et al., 2015;Dear et al., 2013;Gould et al., 2019;Jones et al ., 2016;Brenes et al., 2012). The following therapies were studied: telephone and internet delivery of CBT (Brenes et al., 2017;Brenes et al., 2015;Jones et al., 2016;Brenes et al., 2012;Dear et al., 2015;Read et al., 2020); nondirective supportive therapy (Brenes et al., 2017;Brenes et al., 2015); psychologist and breathing exercises (Gould et al., 2019); interactive website (Gustafson et al., 2021); online group intervention (Shapira et al., 2021); support groups (Hartke and King, 2003); and assessment and follow-up of physical symptoms/quality of life/ social support (Kornblith et al., 2006). Five studies reported outcomes with the PHQ-9, one with PHQ-8, one with Centre for Epidemiology Studies Depression Scale, two with the Beck depression inventory (BDI-I), and one with the Geriatric Depression Scale (GDS). Outcomes were reported between 4 and 60 weeks and three reporting at 24 months (Brenes et al., 2012;Read et al., 2020;Hartke and King, 2003). All studies showed improvement in depression scores and none reported harms. When examining internet CBT with clinician guidance compared to waitlist control, there was a statistically significant outcome at 8 weeks . Another study demonstrated a significant group and group by time interaction for guided internet CBT compared to usual care (Read et al., 2020).

Discussion
The need for virtual interventions that can reduce symptoms of depression and depressive disorders in older adults transcend the COVID-19 pandemic. Challenges with transportation, mobility, living rurally, lack of access to services locally, and cost all lead to poor access to psychotherapy for community-dwelling older adults (Wuthrich and Frei, 2015). Using virtual interventions helps to bridge some of the gaps to access for older adults (Gould and Hantke, 2020).
We identified 15 RCTs evaluating the efficacy of virtual interventions for reducing symptoms of depression in older adults. These studies demonstrate that virtual interventions are feasible, and in some studies demonstrated efficacy. Harm was not reported in any study. However, there was insufficient evidence to establish whether these interventions lead to clinically meaningful outcomes or durable results for patients. Virtual interventions were delivered via telephone or internet and had varied degrees of involvement from clinicians.
CBT is a well established and effective intervention for depression in person (Olthuis et al., 2016;Gotzsche and Gotzsche, 2017;Wuthrich and Rapee, 2013;Jayasekara et al., 2015;Huibers, 2011;Hall et al., 2016) and appears to adapt and be feasible in the virtual setting. However, the virtual setting does not completely eliminate issues of access to CBT associated with cost and the need for clinician involvement (Wuthrich and Frei, 2015).
There are factors to consider regarding feasibility of different virtual care modalities. A qualitative interview study looked at virtual care in a urban geriatric medicine clinic (not specific to interventions for depression) (Watt et al., 2022). Eight major barriers were identified in this study including the challenges associated with rapid uptake of virtual care due to COVID-19, providing virtual care to a medically complex population, the importance of ensuring caregivers are involved, difficulty with understanding the accuracy of virtual assessments compared to in person, issues with inequitable access, difficulties with changing clinic processes, technology issues, and the importance of technology uptake by older adults (Watt et al., 2022). These barriers, although focused on geriatric medicine clinic and not depression interventions, are likely transferable to other virtual interventions. Especially given the overlap with the barriers identified in a systematic review of the accuracy virtual cognitive tools .
There are additional social and health factors that impact accessibility of virtual care. Older adults without an available caregiver, or who are more frail, are less able to access videoconferencing options (Liu et al., 2021). Video-conferencing provides more information to the health care provider and more direct contact for patients, and while we don't have evidence to suggest that this is necessarily better than telephone-based virtual care; it does have advantages (Liu et al., 2021). Virtual care does enable a larger reach for programming, but there is a need to consider issues like individual access or capability with technology for any client (Watt et al., 2022). But providers must further consider the issues facing rural persons specifically such as internet bandwidth (Watt et al., 2022). Along with these there is very little literature speaking to the potential applicability of virtual care across different languages or ethnicities and how this may impact patient outcomes (Liu et al., 2021;Watt et al., 2022). These issues can, however, be further examined and services optimized to ensure intersectional factors are considered when delivering virtual care.
Our study has several strengths. We completed a rigorous search of indexed databases and grey literature. Despite this, we were unable to complete a meta-analysis due to important clinical heterogeneity. There were several limitations to included studies such as unclear or high risk of bias from participant and assessor blinding. All trials excluded persons with severe depression and persons experiencing suicidality; thus, it is unclear if these interventions are suitable or effective in these patient groups. No studies included persons with cognitive impairment or substance use disorders. Studies did not report diversity in race and ethnicity hence we cannot extrapolate to these populations.

Conclusion
Even prior to the COVID-19 pandemic, there was a need for improved accessibility to psychotherapy and interventions such as CBT for depression management in older adults. However, there is a need for further studies examining the efficacy and cost of virtual care for treating symptoms of depression and disorders in older adults. Future work should examine other barriers to virtual care, ensure inclusive participant recruitment, and establish efficacy for virtual psychotherapy for depression. A deeper understanding regarding the patient experience and perceptions of virtual care for mental illness is needed.