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CMAJ : Canadian Medical Association Journal logoLink to CMAJ : Canadian Medical Association Journal
. 2024 Mar 18;196(10):E327–E340. doi: 10.1503/cmaj.230274

Therapist-guided remote versus in-person cognitive behavioural therapy: a systematic review and meta-analysis of randomized controlled trials

Sara Zandieh 1, Seyedeh Maryam Abdollahzadeh 1, Behnam Sadeghirad 1, Li Wang 1, Randi E McCabe 1, Liam Yao 1, Briar E Inness 1, Ananya Pathak 1, Rachel J Couban 1, Holly Crandon 1, Kian Torabiardakani 1, Peter Bieling 1, Jason W Busse 1,
PMCID: PMC10948182  PMID: 38499303

Abstract

Background:

Cognitive behavioural therapy (CBT) has been shown to be effective for several psychiatric and somatic conditions; however, most randomized controlled trials (RCTs) have administered treatment in person and whether remote delivery is similarly effective remains uncertain. We sought to compare the effectiveness of therapist-guided remote CBT and in-person CBT.

Methods:

We systematically searched MEDLINE, Embase, PsycINFO, CINAHL, and the Cochrane Central Register of Controlled Trials from inception to July 4, 2023, for RCTs that enrolled adults (aged ≥ 18 yr) presenting with any clinical condition and that randomized participants to either therapist-guided remote CBT (e.g., teleconference, videoconference) or in-person CBT. Paired reviewers assessed risk of bias and extracted data independently and in duplicate. We performed random-effects model meta-analyses to pool patient-important primary outcomes across eligible RCTs as standardized mean differences (SMDs). We used Grading of Recommendations Assessment, Development and Evaluation (GRADE) guidance to assess the certainty of evidence and used the Instrument to Assess the Credibility of Effect Modification Analyses (ICEMAN) to rate the credibility of subgroup effects.

Results:

We included 54 RCTs that enrolled a total of 5463 patients. Seventeen studies focused on treatment of anxiety and related disorders, 14 on depressive symptoms, 7 on insomnia, 6 on chronic pain or fatigue syndromes, 5 on body image or eating disorders, 3 on tinnitus, 1 on alcohol use disorder, and 1 on mood and anxiety disorders. Moderate-certainty evidence showed little to no difference in the effectiveness of therapist-guided remote and in-person CBT on primary outcomes (SMD −0.02, 95% confidence interval −0.12 to 0.07).

Interpretation:

Moderate-certainty evidence showed little to no difference in the effectiveness of in-person and therapist-guided remote CBT across a range of mental health and somatic disorders, suggesting potential for the use of therapist-guided remote CBT to facilitate greater access to evidence-based care. Systematic review registration: Open Science Framework (https://osf.io/7asrc)


Cognitive behavioural therapy (CBT) is a form of psychotherapy that focuses on the identification and modification of unhelpful thoughts and behaviour patterns and has been shown to be effective for a wide range of mental health and somatic disorders. 15 For example, a 2022 systematic review found moderate-certainty evidence that CBT delivered with physiotherapy probably resulted in large improvements in pain relief and physical functioning for patients with chronic low back pain, compared with physiotherapy alone.6 In 2022, more than 5 million Canadians (18.3%) met diagnostic criteria for a mood, anxiety, or substance use disorder,7 and 1 in 5 adults live with chronic pain.8 In 2019, the World Health Organization advised that access to CBT was essential for evidence-based health care;9 however, treatment access is an important barrier to care for people with mental health disorders10 and those with somatic disorders such as chronic pain.11 Access is particularly an issue in a country as geographically large and sparsely populated as Canada.

In Canada, CBT may be provided within existing government-funded health care services (e.g., hospital settings) and by private providers such as registered psychotherapists, social workers, and psychologists, in which case people without private insurance must pay out of pocket. In an effort to increase access, the government of Saskatchewan began providing funding for Internet-based CBT in 2015,12 as did the Ontario Ministry of Health through the Ontario Structured Psychotherapy Program, starting in 2020;13 however, the relative effectiveness of in-person and remote CBT is uncertain.

A previous systematic review addressed this question, searching the literature up to February 2017, and found that Internet-based CBT may be similarly effective to in-person CBT, but suggested that effectiveness could differ by the clinical condition being targeted.14 A 2019 health technology assessment by Health Quality Ontario found that Internet-delivered CBT was more effective than waitlist control for mild to moderate depression and social anxiety disorder, and may be effective for anxiety and panic disorder, but concluded the relative effectiveness of Internet-delivered CBT and in-person delivery was uncertain.10 Given that these 2 reviews restricted their searches to English-language trials, several relevant trials have been published since their literature searches were conducted, and neither review conducted analyses to explore subgroup effects, we sought to compare the effectiveness of therapist-guided remote CBT and in-person CBT by conducting a systematic review and meta-analysis.

Methods

We registered the protocol for our systematic review on the Open Science Framework (https://osf.io/7asrc), adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting checklist,15 and followed Grading of Recommendations Assessment, Development and Evaluation (GRADE) guidance.16

We made 4 changes to our registered protocol. We increased the sensitivity of our literature search strategy by introducing terms to capture randomized controlled trials (RCTs) that administered CBT via telephone and telehealth. We included the Cochrane Central Register of Controlled Trials (CENTRAL) among the databases that we searched and conducted a subgroup analysis of RCTs that administered CBT on an individual basis versus group therapy. Finally, we conducted a sensitivity analysis by pooling the effect of remote versus in-person CBT for depression in natural units (i.e., original, unaltered units) of the most commonly reported outcome measure among eligible trials.

In our systematic review, we explored the comparative effectiveness of therapist-guided remote and in-person CBT on primary patient-important outcomes among adults presenting with any clinical condition.

Data sources

A medical librarian (R.J.C.) initially developed database-specific search strategies without language restrictions and searched MEDLINE, Embase, PsychInfo, and CINAHL from inception to May 11, 2022. We subsequently expanded our search strategy terms to increase sensitivity, included an additional database (CENTRAL), and re-ran our search of all 5 databases from inception to July 4, 2023 (Appendix 1, available at www.cmaj.ca/lookup/doi/10.1503/cmaj.230274/tab-related-content). One of the reviewers (S.Z.) searched the reference lists of all eligible articles and relevant systematic reviews to identify additional studies.

Eligibility criteria and study selection

We included RCTs that enrolled adult patients (aged ≥ 18 yr) who were seeking treatment for any clinical condition, randomized to receive either therapist-guided remote CBT (e.g., teleconference, videoconference) or in-person CBT. We excluded studies that administered CBT without therapist guidance or studies that administered virtual reality treatments in which a therapist accompanied the patient, in person, during treatment. We also excluded RCTs that administered modalities of psychotherapy other than standard CBT (e.g., acceptance and commitment therapy, mindfulness-based CBT, dialectical CBT) or that administered CBT in addition to another psychological intervention (e.g., motivational interviewing).17

Pairs of reviewers independently screened titles and abstracts of identified citations and full texts of all potentially eligible studies. One author with graduate training in psychology (S.Z.) reviewed all citations and potentially eligible full-text articles, with an independent review by a second reviewer (M.A., B.E.I., L.Y., A.P., K.T., H.C.). The pairs of reviewers resolved discrepancies through discussion to achieve consensus or with involvement of a third reviewer (J.W.B.), if necessary. We used online systematic review software (DistillerSR, Evidence Partners) to facilitate literature screening.

For all full-text articles deemed by a reviewer to be potentially eligible for inclusion, a clinical expert (P.B.), blinded to trial results, assessed the intervention details to confirm eligibility. A second clinical expert (R.E.M.), also blinded to trial results, independently reviewed a subset of full-text articles (43%) where reviewers were uncertain as to eligibility. Agreement between clinical experts on the RCTs they both reviewed for eligibility was perfect.

Data extraction

Each eligible RCT underwent duplicate data abstraction by pairs of trained reviewers (S.Z., M.A., B.E.I., L.Y., A.P., K.T.) working independently and using standardized, pilot-tested forms. Reviewers resolved disagreements through discussion or with the help of a third reviewer (J.W.B.).

We collected information on study characteristics, patient characteristics (as per study report), and treatment details (e.g., number of sessions, compliance rate, therapist background, level of therapist involvement, safety).

We extracted the effect on a patient-important primary outcome for each RCT, which we selected using the following hierarchy. 18 We first looked for the outcome declared as the primary outcome by the trial authors; otherwise, we chose the outcome measure used for sample size calculation or, lastly, we chose the first patient-important outcome reported in the results section of the publication. We defined a patient-important outcome as one for which, if the patient knew that this outcome was the only thing to change with treatment, they would likely elect to receive treatment.19 We included outcomes reported by patients, but not surrogate outcomes (e.g., changes in blood pressure). When outcome data were available at several time points, we used data from the longest follow-up.

Risk of bias

Six reviewers (S.Z., M.A., B.E.I., L.Y., A.P., K.T.) used the Cochrane risk-of-bias tool for RCTs (RoB 2)20 to assess 5 domains, independently and in triplicate, namely bias arising from the randomization process, deviations from the intended intervention, missing outcome data, bias in measurement of the outcome, and bias in the selection of the reported results.

Pairs of reviewers (S.Z., M.A., B.E.I., L.Y., A.P., K.T.) explored selective outcome reporting by comparing the reported results with those proposed in the study protocol (if published or publicly available through a clinical trials registry, otherwise by comparing the reported results with those proposed in the study methods). Each trial was designed as having low risk of bias, high risk of bias or some concerns regarding bias.

Statistical analysis

We measured inter-rater agreement of the decision to include an RCT after reviewing the full-text paper using an adjusted κ statistic. 21 All patient-important primary outcomes across eligible trials were continuous but measured diverse domains with a range of instruments. For each study, we acquired the change from baseline for their primary outcome in each treatment arm. When a change score was not provided, we used mean values at baseline and end of follow-up to calculate the change score. When the standard deviation (SD) for change from baseline was not reported, we used methods described by Weir and colleagues22 and the Cochrane handbook to impute this value.23

We used the change score and associated SD for therapist-guided remote and in-person CBT to calculate the between-group standardized mean difference (SMD) using the metan package in Stata.24 We pooled effect estimates using a random-effects model and the DerSimonian–Laird method25 to derive the pooled SMD and associated 95% confidence interval (95% CI).23 We used Cohen’s d thresholds for classifying the magnitude of the SMD as small (0.20), medium (0.50), or large (0.80).26

We pooled the difference in compliance between in-person and remote therapist-guided CBT as the relative risk (RR) and 95% CI using a random-effects model. We rated the compliance thresholds used in RCTs as high (i.e., requiring patient to complete 100% of modules to be considered compliant), moderate (50%–80% of modules completed), or low (< 30% of modules completed).

We performed all statistical analyses using Stata version 17.0 (StataCorp LP). Comparisons were 2-tailed, and we set our level of statistical significance at p of 0.05 or less.

Subgroup analyses and meta-regression

We used visual inspection of forest plots and the I2 statistic to determine statistical heterogeneity for our pooled effect estimate. 27 Following Cochrane guidance, heterogeneity of 0%–40% was considered as perhaps unimportant, 30%–60% as moderate, 50%–90% as substantial, and 75%–100% as considerable.23 We used meta-regression to establish if a priori factors explained between-study variability for the primary outcome, as long as 2 or more studies were in each subgroup, including clinical condition, whether CBT was provided individually or in group therapy, length of follow-up, and risk of bias.28 Our clinical experts (R.E.M., P.B.) did not anticipate that the delivery format of CBT would show systematic differences in effectiveness based on specific clinical conditions. We also used meta-regression to evaluate the association between number of treatment sessions and compliance rate by in-person or remote CBT.

We presented all subgroup analyses as forest plots to visualize differences. We assessed the credibility of statistically significant subgroup effects in regression analyses (test of interaction p ≤ 0.05) with the Instrument for Assessing the Credibility of Effect Modification Analyses (ICEMAN).29

Certainty of evidence

Two reviewers (J.W.B., S.Z.) used the GRADE approach to summarize the certainty of evidence for our meta-analysis of primary outcome measures. With GRADE, evidence from RCTs begins as high certainty but may be rated down based on risk of bias, indirectness, imprecision, inconsistency, or small study effects.30 We considered the pooled effect estimate to be precise if the associated 95% CI included only 1 magnitude of effect based on Cohen’s d thresholds (i.e., large [0.8], medium [0.5], small [0.2], or less than small).26

If we found a credible subgroup effect among RCTs at low, some concern, and high risk of bias, we presented the pooled effect for studies at low risk of bias. If no significant subgroup effect was found, we pooled across all RCTs and did not rate down for risk of bias.23 We evaluated small-study effects with contour-enhanced funnel plots and the Egger test for continuous outcomes or the Harbord test for dichotomous outcomes.31

Sensitivity analysis

We conducted a sensitivity analysis by pooling end-of-study scores for primary outcomes instead of change scores. Post hoc, we pooled treatment effects in natural units among eligible RCTS that enrolled patients with depression to illustrate the comparative effectiveness of in-person versus therapist-guided remote CBT. We selected depression among presenting clinical conditions as this was the most common condition reported among eligible RCTs in which the same outcome measure, the Beck Depression Inventory-II (BDI-II; minimally important difference = 5 points),32 was often reported. We converted other measures of depression to the BDI-II using a validated approach,33 and pooled between-group change scores across RCTs as the weighted mean difference and 95% CI, and used the DerSimonian–Laird method and a random-effects model.25

Ethics approval

We did not seek ethics approval for this systematic review and meta-analysis of published data.

Results

Of 19 115 unique citations, 54 studies were3487 eligible for review, including 52 English-language RCTs3479,8287 and single RCTs published in Mandarin80 and Persian,81 with a total of 5463 participants (Figure 1). Our original search yielded 32 eligible studies, with an additional 22 studies included with the expanded and updated search strategy (Appendix 1). At the full-text review stage, reviewers had almost perfect agreement (κ = 0.81). One RCT assigned participants to 3 arms (12 sessions of in-person CBT, 6 sessions of in-person CBT, and 6 sessions of remote CBT);63 we included data from the 2 arms with the same number of sessions. Another RCT randomized patients to 3 arms (CBT delivered in-person at the patient’s home, in-person CBT at a therapist’s office, or remote CBT);44 we combined data from both in-person CBT arms for our analysis.

Figure 1:

Figure 1:

Flow diagram of study inclusion. Note: CBT = cognitive behavioural therapy.

Eligible studies enrolled a median of 80 (interquartile range [IQR] 52–125) patients, 3354 (61.4%) of 5463 participants were female, and among the 52 RCTs that reported age, the median of the average age was 43 (IQR 35–51) years. Trials enrolled patients presenting with anxiety-related disorders (n = 17), depression and mood disorders (n = 14), insomnia (n = 7), chronic pain or fatigue syndromes (n = 6), body image or eating disorders (n = 5), tinnitus (n = 3), mood and anxiety disorders (n = 1), and alcohol use disorder (n = 1) (Table 1).

Table 1:

Study characteristics

Study Country of residence No. of participants Mean age, yr Sex, female, % Clinical condition Primary outcome measure No. of sessions Length follow-up, d
Alegría, 201479 USA Puerto Rico 257 45 82 Depression Severity of depression measured by Patient Health Questionnaire-9 8 120
Andersson, 201335 Sweden 69 42 78 Depression Depression severity measured by Montgomery Åsberg Depression Rating Scale 7 for remote, 8 for in-person 1095
Andrews, 201136 Australia 37 32 41 Social phobia Social phobia measured by Social Interaction Anxiety Scale 6 56
Axelsson, 202037 Sweden 204 39 70 Health anxiety Health anxiety measured by Health Anxiety Inventory 12 365
Azimi, 201981 Iran 30 NR 67 Insomnia and comorbid depression Gross memory impairment measured by Rivermead Behavioural Memory Test 6 30
Bergström, 201038 Sweden 104 34 61 Panic disorder Panic disorder severity measured by Panic Disorder Severity Scale 10 180
Bessell, 201239 England 56 46 61 Appearance concern Appearance concern measured by Derriford Appearance Scale-24 8 180
Blom, 201540 Sweden 48 54 48 Insomnia Insomnia severity measured by Insomnia Severity Index 8 180
Burgess, 201278 UK 80 37 79 CFS Fatigue measured by Chalder Fatigue Scale 12 for remote 11 for in-person 365
Carlbring, 200546 Sweden 49 35 71 Panic disorder Anxiety associated with physiologic sensations measured by Body Sensations Questionnaire 7 for remote 9 for in-person 365
Choi, 201477 USA 158 65 79 Depression Depression measured by HAM-D 6 252
Conrad, 201547 Germany 84 51 42 Chronic tinnitus Tinnitus distress measured by Tinnitus Handicap Inventory 18 for remote 10 for in-person 365
de Boer, 201448 Netherland 72 52 64 Nonspecific chronic pain Pain catastrophizing measured by Pain Catastrophizing Scale 8 60
Egede, 201576 USA 241 64 2 Depression Depression measured by BDI 8 360
Frueh, 200775 USA 38 56 0 PTSD PTSD symptom severity measured by PTSD Checklist-M 14 90
Glueckauf, 201274 USA 14 67 90 Depression Depression measured by CES-D 12 91
Gollings, 200649 Australia 40 22 100 Body dissatisfaction and disordered eating Body shape concern measured by Body Shape Questionnaire 8 60
Granberg, 202273 USA 41 33 63 Insomnia Qualitative measurement examining provider- and patient-level perspectives, attitudes, and preferences regarding CBT-I delivered via telemedicine versus in-person delivery, as well as barriers and facilitators to delivery or receipt of care in each approach 6 90
Hall, 201772 USA 100 49 90 CFS CFS symptoms measured by Chalder Fatigue Scale 10 for remote 12 for in-person 70 for remote 84 for in-person
Heapy, 201734 USA 125 58 21 Chronic back pain Pain intensity measured by Numeric Rating Scale 10 270
Hedman, 201150 Sweden 126 35 36 Social anxiety disorder Social phobia measured by Liebowitz Social Anxiety Scale 15 180
Himelhoch, 201371 USA 34 45 74 Depression Depression symptom severity measured by HAM-D 11 98
Jarnefelt, 202051 Finland 53 43 74 Insomnia Severity of insomnia measured by Insomnia Severity Index 10 for remote 6 for in-person 180
Jasper, 201452 Sweden 84 51 42 Chronic tinnitus Tinnitus distress measured by Tinnitus Handicap Inventory 18 180
Johansson, 202153 Sweden 301 50 38 Alcohol use disorder Number of standard drinks consumed measured by timeline follow-back method 8 180
Kaldo, 200843 Sweden 51 46 43 Distress associated with tinnitus Tinnitus distress measured by Tinnitus Reaction Questionnaire 7 365
Kenardy, 200363 Australia 95 37 76 Panic disorder Panic–anxiety composite score 6 180
Kheirkhah, 202370 Iran 60 33 100 Depression Depression measured by BDI 9 56
Kiropoulos, 200854 Australia 86 39 72 Panic disorder Panic severity measured by Panic Disorder Severity Scale 12 84
Lancee, 201656 Netherland 60 40 80 Insomnia Insomnia severity measured by Insomnia Severity Index 6 180
Laurel Franklin, 201869 USA 18 54 0 Trauma-related insomnia Sleep problems measured by Pittsburgh Sleep Quality Index 6 90
Leterme, 202055 France 80 37 65 Adjustment disorder with anxiety Trait anxiety measured by State–Trait Anxiety Inventory 5 180
Liu, 202068 USA 207 48 23 PTSD PTSD severity measured by CAPS 12 180
Lovell, 200667 UK 72 31 60 OCD OCD measured by the Yale Brown Obsessive–Compulsive Scale 10 180
Lundström, 202245 Sweden 80 33 65 OCD OCD severity measured by Yale-Brown Obsessive–Compulsive Scale 10 for remote 16 for in-person 365
Luxton, 201664 USA 121 NR 18 Depression Depression measured by BDI-II 8 90
Maieritsch, 201666 USA 90 31 7 PTSD PTSD severity measured by CAPS 10 84
McAndrew, 201882 USA 128 57 6 Chronic multi-symptom Illness Role physical measured by Role Physical Subscale VR-36 10 360
Meng, 201965 USA 109 59 92 Depressive symptoms Health services use and total health care expenditures 12 84
Milgrom, 202141 Australia 78 32 100 Postnatal depression Severity of depression measured by BDI-II 10 for remote 6 for in-person 147
Mitchell, 200885 USA 128 29 98 Bulimia nervosa Binge eating frequency measured by Eating Disorder Examination 20 365
Mohr, 201284 USA 325 48 78 Depression Depression measured by HAM-D 18 126
Morland, 201487 USA 125 55 0 PTSD PTSD severity measured by CAPS 12 180
Paxton, 200760 Australia 79 26 100 Body image and eating disorder Body dissatisfaction measured by Body Shape Questionnaire 8 180
Peterson, 202244 USA 120 41 12 PTSD PTSD symptom severity measured by PTSD Checklist for DSM-5 12 180
Sadeghijoola, 202283 Iran 40 54 100 Vasomotor symptoms Frequency of hot flashes measured by Kupperman Hot Flash Index 6 98
Stubbings, 201357 Australia 26 30 58 Mood and anxiety disorders Depression, anxiety, and stress measured by Depression Anxiety and Stress Scale 12 42
Thase, 201858 USA 154 46 66 Depression Depression severity measured by HAM-D 21 180
Vallejo, 201561 Spain 40 52 100 Fibromyalgia Global impact of fibromyalgia measured by Fibromyalgia Impact Questionnaire 10 365
Wagner, 201459 Switzerland 62 38 65 Depression Depression severity measured by BDI-II 7 90
Watts, 202086 Canada 115 41 83 Generalized anxiety disorder Working alliance scores measured by Working Alliance Inventory 15 105
Ye, 201680 China 53 46 81 Insomnia Sleep onset latency 8 56
Ying, 202242 China 220 42 53 Depression Depressive symptoms measured by CES-D 5 180
Zerwas, 201762 USA 196 28 98 Bulimia nervosa Abstinence from binge eating and purging measured by Eating Disorders Examination Interview 16 365

Note: BDI = Beck Depression Inventory, CAPS = Clinician-Administered PTSD Scale, CBT-I = cognitive behavioural therapy for insomnia, CES-D = Center for Epidemiological Studies Depression Scale, CFS = chronic fatigue syndrome, DSM-5 = Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, HAM-D = Hamilton Rating Scale for Depression, NR = not reported, OCD = obsessive–compulsive disorder, PTSD = posttraumatic stress disorder, VR-36 = Veterans RAND 36-Item Health Survey.

For delivery of CBT, 19 studies (35%) randomized patients to group therapy, whereas 32 (59%) provided individual therapy; 2 studies (4%) did not specify how CBT was provided and 1 RCT (2%) administered both group and individual therapy. Types of remote CBT included interactive voice response technology,34 computerized CBT,39,51,55,58,63 telehealth and telephone-based CBT,44,64,65,67,69,71,72,74,7679,8285 videoconference,57,66,68,73,75,86,87 and Internet-delivered CBT.3538,4043,4554,56,5962,70,80,81

Involvement of therapists in CBT interventions delivered remotely was variable. For 25 RCTs, remote CBT was delivered in real time by a therapist, requiring a time commitment equivalent to in-person CBT. For the remaining 29 RCTs, therapists supported remote CBT modules that patients completed on their own; when details on time spent by therapists was reported, the time commitment typically involved 10–30 minutes per module for responding to patient queries and evaluating submitted homework (Appendix 1, eTable 1).

Treatment duration ranged from 5 to 21 (median 10, IQR 7–12) sessions, and the median length of follow-up was 180 (IQR 90–252) days (Table 1). Among the 44 RCTs that reported patient compliance (Appendix 1, eTable 2), subgroup analysis found no significant difference between in-person or therapist-guided remote CBT; however, effects for moderate-and high-compliance thresholds showed substantial heterogeneity (Figure 2). Meta-regression also found no significant difference in compliance based on the number of treatment sessions for RCTs with high (p = 0.80), moderate (p = 0.07), or low (p = 0.75) compliance. We found no evidence of small study effects among RCTs reporting patient compliance (Appendix 1, eFigure 1 and eFigure 2).

Figure 2:

Figure 2:

Effect of patient compliance with remote versus in-person cognitive behavioural therapy (CBT). Weights are from random-effects model; continuity correction applied to studies with 0 cells. Note: CI = confidence interval, DL = DerSimonian–Laird, RR = risk ratio.

Safety data were reported by 16 of 54 RCTs (30%) and, of these, 9 (56%) reported no adverse events. Among the 7 RCTs that reported the occurrence of adverse events, 8 serious events were reported, namely suicidal ideation (2 patients, 1 in-person and 1 in remote CBT), hospitalization for a panic attack (1 patient, in-person CBT), victim of domestic violence (1 patient, remote CBT), death after emergency heart surgery (1 patient, in-person CBT), and overdose with acetaminophen (1 patient, remote CBT). One trial reported 2 serious adverse events unrelated to study participation without further details. No differences in serious or non-serious adverse events (e.g., increased anxiety) between in-person and therapist-guided remote CBT were observed (Appendix 1, eTable 1).

Risk of bias

Patients and health care providers were unblinded in all RCTs and no study was at high risk of bias for deviation from the intended intervention; however, 5 studies (9%) were at high risk of bias for their randomization process, 10 studies (19%) for missing outcome data, and 9 studies (17%) for measurement of the outcome (e.g., study personnel were aware of intervention received by participants, the participant may have been influenced by knowledge of the intervention for patient-reported incomes) (Appendix 1, eTable 4). We found study protocols for 29 (54%) RCTs, (Appendix 1, eTable 5); 5 of 29 were at high risk of bias for selection of their reported results (Appendix 1, eTable 4).

Effect of in-person versus remote CBT on primary outcomes

Moderate-certainty evidence from 51 RCTs (5384 patients) showed little to no difference in effectiveness between in-person and therapist-guided remote CBT on primary outcomes (SMD −0.02, 95% CI −0.11 to 0.07) (Figure 3, Table 2; Appendix 1, eTable 6). We did not find evidence of small-study effects (Appendix 1, eFigure 3). Analysis using end scores also showed little to no difference in effectiveness between in-person and remote CBT (SMD −0.01, 95% CI −0.11 to 0.08) (Appendix 1, eFigure 4).

Figure 3:

Figure 3:

Effect of remote versus in-person cognitive behavioural therapy (CBT) on patient compliance. Weights are from random-effects model; continuity correction applied to studies with 0 cells. Note: CI = confidence interval, DL = DerSimonian–Laird, SD = standard deviation, SMD = standardized mean difference.

Table 2:

Grading of Recommendations, Assessment, Development and Evaluation (GRADE) evidence profile of in-person versus therapist-guided remote cognitive behavioural therapy (CBT) on primary outcomes reported in randomized controlled trials (RCTs) involving patients with psychological and somatic complaints

Outcome No. of RCTs No. of participants Length of follow-up, d median (IQR) Risk of bias Inconsistency (I2) Indirectness Imprecision Small-study effects SMD (95% CI) Certainty of evidence
Primary 51 5384 180 (90–252) Serious* No serious inconsistency (52%) No serious indirectness No serious imprecision Undetected Egger p = 0.37 −0.02 (−0.11 to 0.07) Moderate

Note: CI = confidence interval, IQR = interquartile range, SMD = standardized mean difference.

*

All RCTs administered the same intervention in both treatment arms (CBT); however, patients and health care providers were unblinded to the method of delivery (remote or in-person CBT).

Although the I2 value showed moderate heterogeneity, we did not rate down the certainty of evidence because the magnitude and direction of effects were largely consistent across trials, and a substantial proportion of between-study variability was contributed by 1 trial56 that contributed less than 2% of the weight to our pooled estimate.

A contoured-enhanced funnel plot showed no evidence of small study effects (Appendix 1, eFigure 3), and Egger’s test was nonsignificant.

We found no credible subgroup effects based on clinical condition, (Appendix 1, eFigure 5 and eTable 3) individual or group therapy (Appendix 1, eFigure 6 and eTable 3), or risk of bias (Appendix 1, eFigures 7–11 and eTable 3). Meta-regression showed no significant association between length of follow-up and the difference in treatment effect between in-person and therapist-guided remote CBT (Appendix 1, eFigures 12–13 and eTable 3).

Three RCTs did not contribute to our meta-analysis because they did not report a patient-important outcome or reported data that were not possible to pool. One evaluated patient and provider perceptions of different forms of CBT for insomnia and found similar satisfaction with telemedicine and in-person delivery. 73 The second reported health services use and associated expenditures among caregivers with depressive symptoms who provided care for patients with dementia, and found no difference between in-person and telephone-based CBT.65 The third enrolled patients with panic disorder and reported a 3-way repeated-measures analysis of variance that found no difference in outcomes between in-person or therapist-supported, computer-delivered CBT.63

Sensitivity analysis

When restricted to RCTs exploring the effectiveness of in-person and therapist-guided remote CBT for depression, the meta-analysis showed no difference in effect on the 63-point BDI-II (weighted mean difference 0.00, 95% CI −1.75 to 1.75) (Appendix 1, eFigure 14).

Interpretation

Our systematic review found moderate-certainty evidence of little to no difference in effectiveness in CBT delivered either in person or remotely with therapist support. This finding was unaffected by type of clinical condition, length of follow-up, or whether CBT was provided individually or through group sessions.

Our findings update previous meta-analyses that compared in-person and remote CBT and concluded the need for additional research.10,14,8892 The most recent review included 20 RCTs that compared Internet-delivered CBT with face-to-face CBT and concluded that both appeared similarly effective; however, the authors did not assess the overall certainty of evidence or the credibility of their subgroup analysis based on risk of bias.14 They suggested that effectiveness may differ based on clinical condition, length of follow-up, and whether CBT was provided individually or in groups.14 This review restricted the search to English-language RCTs and to a single electronic database, and included 6 RCTs that our experts concluded were not eligible for our review because the remote CBT was not guided by a therapist, 93,94 the intervention was not conventional CBT,95 the in-person and remote CBT were not similar in content,96,97 or the couple therapy intervention that was described as traditional sexual counselling was not comparable to standard individual- or group-delivered CBT.98 We addressed the methodologic limitations of this review and identified 40 additional RCTs that had not been included.

To address previous limitations in the evidence, we conducted a comprehensive search for eligible RCTs in any language and engaged clinical experts, blinded to treatment results, to assess the descriptions of all interventions to confirm eligibility. We used the GRADE approach to appraise the certainty of evidence, used predefined subgroup analyses to explore sources of heterogeneity, and assessed the credibility of all potential subgroup effects. Further, although RCTs eligible for our review provided the same intervention administered in person or remotely, we rated down our certainty of evidence for unblinding. This is a conservative approach as several studies have found that most patients are willing to receive psychotherapy in either format,99101 and we found no evidence for differential compliance depending on whether CBT was provided in person or remotely, which we would anticipate if patients held strong preferences.

Cognitive behavioural therapy is effective for the treatment of several mental health disorders and somatic complaints;14 however, resource requirements are a barrier to in-person therapy. Our review provides moderate-certainty evidence that remote delivery of CBT with therapist guidance is probably similarly effective to in-person delivery. Remote CBT imposes fewer demands on patients’ time as travel for face-to-face sessions is unnecessary.102 Remote CBT may also be more cost-effective than in-person delivery, particularly when the intervention is supported by therapists, rather than being delivered remotely in real time.103105

Our finding that remote CBT is an effective alternative to in-person delivery has potential policy implications. Only 2 Canadian provinces (Saskatchewan and Ontario) currently provide funding for remote CBT.12,13 Access to psychotherapy is an important barrier for many people in Canada, particularly those living in remote or rural areas, including military veterans and Indigenous populations, both of which are at high risk for chronic pain and mental health disorders.106108

An August 2023 poll of 3189 adults in Canada, commissioned by Mental Health Research Canada, found that the proportion of participants who reported an inability to pay as a reason for not accessing mental health care had increased from 18% to 29% over the previous year.109 Canada’s provinces and territories should consider funding access to therapist-guided remote CBT to facilitate greater access to evidence-based care.

Several options for providing remote psychotherapy are available and use of this delivery method for CBT is likely to evolve rapidly. Recent advances in artificial intelligence tools may open further avenues for providing CBT with reduced involvement of human therapists. 110 Future studies should explore whether certain patients have strong preferences for in-person or therapist-guided remote CBT, the comparative effectiveness of different types of remote CBT (e.g., high or low involvement of therapist delivering CBT remotely v. in person), and the effectiveness of remote CBT compared with stepped care, whereby remote CBT is provided first, and then non-responders are offered in-person CBT.

Limitations

Although studies eligible for our review involved patients presenting with a wide range of clinical conditions, many conditions that are candidates for CBT were not represented in any studies or in only a single RCT (e.g., alcohol use disorder). Patients enrolled in RCTs eligible for review consented to be randomized to either in-person or remote CBT and likely were not people with strong preferences for 1 method of delivery over the other. Eligible RCTs were conducted in high-income countries, largely enrolled middle-aged participants, and followed patients for a median of 180 days. The generalizability of our findings to lower-income countries, older patients (who may be less comfortable with technology), and longer follow-up periods is uncertain.

Although we found no important difference in patient compliance between in-person and remote CBT, substantial unexplained heterogeneity was associated with the overall pooled estimate. We did not find evidence for differences in treatment effect based on clinical condition, but the small number of RCTs contributing to some subgroups may have obscured important subgroup effects. Finally, we pooled studies across a variety of outcome measures as the SMD, which limits interpretability and may be affected by baseline heterogeneity of participants.111 However, we did pool effects on RCTs of depression to demonstrate results in natural units for this condition and found no difference.

Conclusion

In this systematic review and meta-analysis of RCTs, moderate-certainty evidence found little to no difference in effectiveness between in-person and therapist-guided, remotely delivered CBT for a variety of mental health disorders and somatic conditions. Our findings suggest that therapist-guided remote CBT can be used to facilitate greater access to evidence-based care.

Footnotes

Competing interests: Behnam Sadeghirad reports funding from the Canadian Institutes of Health Research, the Michael G. DeGroote Institute for Pain Research and Care, and the Chronic Pain Centre of Excellence for Canadian Veterans. No other competing interests were declared.

This article has been peer reviewed.

Contributors: Jason Busse conceived and designed the study. Sara Zandieh, Maryam Abdollahzadeh, Liam Yao, Briar Inness, Annaya Pathak, Rachel Couban, Holly Crandon, and Kian Torabiardakani acquired the data. Sara Zandieh and Behnam Sadeghirad carried out the statistical analysis. Sara Zandieh, Behnam Sadeghirad, Li Wang, Randi McCabe, Peter Beiling, and Jason Busse interpreted the data. Sara Zandieh and Jason Busse drafted the manuscript. All of the authors revised the manuscript and contributed important intellectual content, gave final approval of the version to be published, and agreed to be accountable for all aspects of the work.

Funding: Jason Busse is supported, in part, by a Canadian Institutes of Health Research Canada Research Chair in the prevention and management of chronic pain.

Data sharing: The relevant data in this study are available from Sara Zandieh (zandiehs@mcmaster.ca)

References

  • 1.Katzman MA, Bleau P, Blier P, et al. Canadian clinical practice guidelines for the management of anxiety, posttraumatic stress and obsessive-compulsive disorders. BMC Psychiatry 2014;14 Suppl 1(Suppl 1):S1. doi: 10.1186/1471-244X-14-S1-S1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Liu J, Gill NS, Teodorczuk A, et al. The efficacy of cognitive behavioural therapy in somatoform disorders and medically unexplained physical symptoms: a meta-analysis of randomized controlled trials. J Affect Disord 2019;245:98–112. [DOI] [PubMed] [Google Scholar]
  • 3.Williams AC, Eccleston C, Morley S. Psychological therapies for the management of chronic pain (excluding headache) in adults. Cochrane Database Syst Rev 2012;(11):CD007407. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Busse JW, Montori VM, Krasnik C, et al. Psychological intervention for premenstrual syndrome: a meta-analysis of randomized controlled trials. Psychother Psychosom 2009;78:6–15. [DOI] [PubMed] [Google Scholar]
  • 5.Busse JW, Bhandari M, Guyatt GH, et al. Development and validation of an instrument to predict functional recovery in tibial fracture patients: the Somatic Pre-Occupation and Coping (SPOC). J Orthop Trauma 2012;26:370–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Ho EK-Y, Chen L, Simic M, et al. Psychological interventions for chronic, nonspecific low back pain: systematic review with network meta-analysis. BMJ 2022;376:e067718. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Statistics Canada. Insights on Canadian society: mental disorders and access to mental health care. Cat. no. 75-006-x. 2023. Available: https://www150.statcan.gc.ca/n1/pub/75-006-x/2023001/article/00011-eng.htm (accessed 2024 Feb. 13).
  • 8.Schopflocher D, Taenzer P, Jovey R. The prevalence of chronic pain in Canada. Pain Res Manag 2011;16:445–50. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.WHO highlights urgent need to transform mental health and mental health care. Geneva: World Health Organization; updated 2022 June 17. Available: https://www.who.int/news/item/17-06-2022-who-highlights-urgent-need-to-transform-mental-health-and-mental-health-care (accessed 2023 Dec. 24). [Google Scholar]
  • 10.Health Quality Ontario. Internet-delivered cognitive behavioural therapy for major depression and anxiety disorders: a health technology assessment. Ont Health Technol Assess Ser 2019;19:1–199. [PMC free article] [PubMed] [Google Scholar]
  • 11.Goldsmith ES, Miller WA, Koffel E, et al. Barriers and facilitators of evidence-based psychotherapies for chronic pain in adults: a systematic review. J Pain 2023;24:742–69. [DOI] [PubMed] [Google Scholar]
  • 12.Saskatchewan mental health innovation highlighted in national podcast [media release]. Regina: Government of Saskatchewan; 2021. Mar. 21. Available: https://www.saskatchewan.ca/government/news-and-media/2021/march/24/saskatchewan-mental-health-innovation-highlighted-in-national-podcast#:~:text=Since%20its%20inception%20in%202015,million%20into%20the%20ICBT%20program (accessed 2023 Dec. 24). [Google Scholar]
  • 13.Mental health and addictions programs and resources. Toronto: Ontario Health; 2022. Available: https://www.ontariohealth.ca/about-us/our-programs/clinical-quality-programs/mental-health-addictions/programs-resources (accessed 2023 Dec. 24). [Google Scholar]
  • 14.Carlbring P, Andersson G, Cuijpers P, et al. Internet-based vs. face-to-face cognitive behavior therapy for psychiatric and somatic disorders: an updated systematic review and meta-analysis. Cogn Behav Ther 2018;47:1–18. [DOI] [PubMed] [Google Scholar]
  • 15.Moher D, Liberati A, Tetzlaff J, et al. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med 2009; 6:e1000097. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Santesso N, Glenton C, Dahm P, et al. GRADE guidelines 26: informative statements to communicate the findings of systematic reviews of interventions. J Clin Epidemiol 2020;119:126–35. [DOI] [PubMed] [Google Scholar]
  • 17.Hayes SC, Hofmann SG. The third wave of cognitive behavioral therapy and the rise of process-based care. World Psychiatry 2017;16:245–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Sun X, Briel M, Busse JW, et al. Subgroup analysis of trials Is rarely easy (SATIRE): a study protocol for a systematic review to characterize the analysis, reporting, and claim of subgroup effects in randomized trials. Trials 2009;10:101. doi: 10.1186/1745-6215-10-101. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Kersting C, Kneer M, Barzel A. Patient-relevant outcomes: What are we talking about? A scoping review to improve conceptual clarity. BMC Health Serv Res 2020;20:596. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Sterne JAC, Savovic J, Page MJ, et al. RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ 2019;366:l4898. [DOI] [PubMed] [Google Scholar]
  • 21.Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics 1977;33:159–74. [PubMed] [Google Scholar]
  • 22.Weir CJ, Butcher I, Assi V, et al. Dealing with missing standard deviation and mean values in meta-analysis of continuous outcomes: a systematic review. BMC Med Res Methodol 2018;18:25. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Higgins JP, Thomas J, Chandler J, et al., editors. Cochrane handbook for systematic reviews of interventions. Hoboken (NJ): Wiley-Blackwell/Cochrane Collaboration; 2019. [Google Scholar]
  • 24.Harris RJ, Deeks JJ, Altman DG, et al. Metan: fixed-and random-effects meta-analysis. Stata J 2008;8:3–28. [Google Scholar]
  • 25.Murad MH, Montori VM, Ioannidis JPA, et al. Fixed-effects and random-effects models. In: Guyatt G, Rennie D, Meade MO, et al., editors. Users’ guides to the medical literature: a manual for evidence-based clinical practice, 3rd ed. New York: McGraw-Hill Education; 2015. [Google Scholar]
  • 26.Cohen J. Statistical power analysis for the behavioral sciences (revised ed.). Hillsdale (NJ): Lawrence Earlbaum Associates; 1988. [Google Scholar]
  • 27.Anzures-Cabrera J, Higgins JPT. Graphical displays for meta-analysis: an overview with suggestions for practice. Res Synth Methods 2010;1:66–80. [DOI] [PubMed] [Google Scholar]
  • 28.Baker WL, Michael White C, Cappelleri JC, et al. Understanding heterogeneity in meta-analysis: the role of meta-regression. Int J Clin Pract 2009; 63:1426–34. [DOI] [PubMed] [Google Scholar]
  • 29.Schandelmaier S, Briel M, Varadhan R, et al. Development of the Instrument to assess the Credibility of Effect Modification Analyses (ICEMAN) in randomized controlled trials and meta-analyses. CMAJ 2020;192:E901–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Guyatt GH, Oxman AD, Vist GE, et al. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ 2008;336:924–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Sterne JAC, Sutton AJ, Ioannidis JPA, et al. Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials. BMJ 2011;343:d4002. [DOI] [PubMed] [Google Scholar]
  • 32.Hiroe T, Kojima M, Yamamoto I, et al. Gradations of clinical severity and sensitivity to change assessed with the Beck Depression Inventory-II in Japanese patients with depression. Psychiatry Res 2005;135:229–35. [DOI] [PubMed] [Google Scholar]
  • 33.Thorlund K, Walter SD, Johnston BC, et al. Pooling health-related quality of life outcomes in meta-analysis-a tutorial and review of methods for enhancing interpretability. Res Synth Methods 2011;2:188–203. [DOI] [PubMed] [Google Scholar]
  • 34.Heapy AA, Higgins DM, Goulet JL, et al. Interactive voice response-based self-management for chronic back pain: the COPES noninferiority randomized trial. JAMA Intern Med 2017;177:765–73. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Andersson G, Hesser H, Veilord A, et al. Randomised controlled non-inferiority trial with 3-year follow-up of internet-delivered versus face-to-face group cognitive behavioural therapy for depression. J Affect Disord 2013;151:986–94. [DOI] [PubMed] [Google Scholar]
  • 36.Andrews G, Davies M, Titov N. Effectiveness randomized controlled trial of face to face versus Internet cognitive behaviour therapy for social phobia. Aust N Z J Psychiatry 2011;45:337–40. [DOI] [PubMed] [Google Scholar]
  • 37.Axelsson E, Andersson E, Ljotsson B, et al. Effect of internet vs face-to-face cognitive behavior therapy for health anxiety: a randomized noninferiority clinical trial. JAMA Psychiatry 2020;77:915–24. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Bergström J, Andersson G, Ljotsson B, et al. Internet-versus group-administered cognitive behaviour therapy for panic disorder in a psychiatric setting: a randomised trial. BMC Psychiatry 2010;10:54. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Bessell A, Brough V, Clarke A, et al. Evaluation of the effectiveness of Face IT, a computer-based psychosocial intervention for disfigurement-related distress. Psychol Health Med 2012;17:565–77. [DOI] [PubMed] [Google Scholar]
  • 40.Blom K, Tarkian Tillgren H, Wiklund T, et al. Internet-vs. group-delivered cognitive behavior therapy for insomnia: a randomized controlled non-inferiority trial. Behav Res Ther 2015;70:47–55. [DOI] [PubMed] [Google Scholar]
  • 41.Milgrom J, Danaher BG, Seeley JR, et al. Internet and face-to-face cognitive behavioral therapy for postnatal depression compared with treatment as usual: randomized controlled trial of MumMoodBooster. J Med Internet Res 2021;23:e17185. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Ying Y, Ji Y, Kong F, et al. Efficacy of an internet-based cognitive behavioral therapy for subthreshold depression among Chinese adults: a randomized controlled trial. Psychol Med 2023;53:3932–42. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Kaldo V, Levin S, Widarsson J, et al. Internet versus group cognitive-behavioral treatment of distress associated with tinnitus: a randomized controlled trial. Behav Ther 2008;39:348–59. [DOI] [PubMed] [Google Scholar]
  • 44.Peterson AL, Mintz J, Moring JC, et al. In-office, in-home, and telehealth cognitive processing therapy for posttraumatic stress disorder in veterans: a randomized clinical trial. BMC Psychiatry 2022;41:22. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Lundström L, Flygare O, Andersson E, et al. Effect of internet-based vs face-to-face cognitive behavioral therapy for adults with obsessive-compulsive disorder: a randomized clinical trial. JAMA Network Open 2022;5:e221967-e. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Carlbring P, Nilsson-Ihrfelt E, Waara J, et al. Treatment of panic disorder: live therapy vs. self-help via the Internet. Behav Res Ther 2005;43:1321–33. [DOI] [PubMed] [Google Scholar]
  • 47.Conrad I, Kleinstauber M, Jasper K, et al. The changeability and predictive value of dysfunctional cognitions in cognitive behavior therapy for chronic tinnitus. Int J Behav Med 2015;22:239–50. [DOI] [PubMed] [Google Scholar]
  • 48.de Boer MJ, Versteegen G, Vermeulen K, et al. A randomized controlled trial of an internet-based cognitive-behavioural intervention for non-specific chronic pain: an effectiveness and cost-effectiveness study. Eur J Pain 2014;18:1440–51. [DOI] [PubMed] [Google Scholar]
  • 49.Gollings EK, Paxton S. Comparison of Internet and face-to-face delivery of a group body image and disordered eating intervention for women: a pilot study. Eat Disord 2006;14:1–15. [DOI] [PubMed] [Google Scholar]
  • 50.Hedman E, Andersson G, Ljotsson B, et al. Internet-based cognitive behavior therapy vs. cognitive behavioral group therapy for social anxiety disorder: a randomized controlled non-inferiority trial. PLoS One 2011;6:e18001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.Jarnefelt H, Harma M, Sallinen M, et al. Cognitive behavioural therapy for insomnia among shift workers: analyses of an RCT study up to 24 months post-treatment. Int Arch Occup Environ Health 2020;93:535–50. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52.Jasper K, Weise C, Conrad I, et al. Internet-based guided self-help versus group cognitive behavioral therapy for chronic tinnitus: a randomized controlled trial. Psychother Psychosom 2014;83:234–46. [DOI] [PubMed] [Google Scholar]
  • 53.Johansson M, Sinadinovic K, Gajecki M, et al. Internet-based therapy versus face-to-face therapy for alcohol use disorder, a randomized controlled noninferiority trial. Addiction 2021;116:1088–100. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54.Kiropoulos LA, Klein B, Austin DW, et al. Is Internet-based CBT for panic disorder and agoraphobia as effective as face-to-face CBT? J Anxiety Disord 2008; 22:1273–84. [DOI] [PubMed] [Google Scholar]
  • 55.Leterme AC, Behal H, Demarty AL, et al. A blended cognitive behavioral intervention for patients with adjustment disorder with anxiety: a randomized controlled trial. Internet Interv 2020;21:100329. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56.Lancee J, van Straten A, Morina N, et al. Guided online or face-to-face cognitive behavioral treatment for insomnia: a randomized wait-list controlled trial. Sleep 2016;39:183–91. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57.Stubbings DR, Rees CS, Roberts LD, et al. Comparing in-person to videoconference-based cognitive behavioral therapy for mood and anxiety disorders: randomized controlled trial. J Med Internet Res 2013;15:e258. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 58.Thase ME, Wright JH, Eells TD, et al. Improving the efficiency of psychotherapy for depression: computer-assisted versus standard CBT. Am J Psychiatry 2018;175:242–50. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 59.Wagner B, Horn AB, Maercker A. Internet-based versus face-to-face cognitive-behavioral intervention for depression: a randomized controlled non-inferiority trial. J Affect Disord 2014;152–154: 113–21. [DOI] [PubMed] [Google Scholar]
  • 60.Paxton SJ, McLean SA, Gollings EK, et al. Comparison of face-to-face and internet interventions for body image and eating problems in adult women: an RCT. Int J Eat Disord 2007;40:692–704. [DOI] [PubMed] [Google Scholar]
  • 61.Vallejo MA, Ortega J, Rivera J, et al. Internet versus face-to-face group cognitive-behavioral therapy for fibromyalgia: a randomized control trial. J Psychiatr Res 2015;68:106–13. [DOI] [PubMed] [Google Scholar]
  • 62.Zerwas SC, Watson HJ, Hofmeier SM, et al. CBT4BN: a randomized controlled trial of online chat and face-to-face group therapy for bulimia nervosa. Psychother Psychosom 2017;86:47–53. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 63.Kenardy JA, Dow MG, Johnston DW, et al. A comparison of delivery methods of cognitive-behavioral therapy for panic disorder: an international multicenter trial. J Consult Clin Psychol 2003;71:1068–75. [DOI] [PubMed] [Google Scholar]
  • 64.Luxton DD, Pruitt LD, Wagner A, et al. Home-based telebehavioral health for U.S. military personnel and veterans with depression: a randomized controlled trial. J Consult Clin Psychol 2016;84:923–34. [DOI] [PubMed] [Google Scholar]
  • 65.Meng H, Marino VR, Conner KO, et al. Effects of in-person and telephone-based cognitive behavioral therapies on health services use and expenditures among African-American dementia caregivers with depressive symptoms. Ethn Health 2021;26:879–92. [DOI] [PubMed] [Google Scholar]
  • 66.Maieritsch KP, Smith TL, Hessinger JD, et al. Randomized controlled equivalence trial comparing videoconference and in person delivery of cognitive processing therapy for PTSD. J Telemed Telecare 2016;22:238–43. [DOI] [PubMed] [Google Scholar]
  • 67.Lovell K, Cox D, Haddock G, et al. Telephone administered cognitive behaviour therapy for treatment of obsessive-compulsive disorder: randomised controlled non-inferiority trial. BMJ 2006;333:883. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 68.Liu L, Thorp SR, Moreno L, et al. Videoconferencing psychotherapy for veterans with PTSD: results from a randomized controlled non-inferiority trial. J Telemed Telecare 2020;26:507–19. [DOI] [PubMed] [Google Scholar]
  • 69.Laurel Franklin C, Walton JL, Raines AM, et al. Pilot study comparing telephone to in-person delivery of cognitive-behavioural therapy for trauma-related insomnia for rural veterans. J Telemed Telecare 2018;24:629–35. [DOI] [PubMed] [Google Scholar]
  • 70.Kheirkhah F, Faramarzi M, Shafierizi S, et al. Preliminary examination of acceptability, feasibility, and effectiveness of internet-based cognitive behavioral therapy for treatment of depression and anxiety in infertile women. Heliyon 2023;9:e15760. doi: 10.1016/j.heliyon.2023.e15760. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 71.Himelhoch S, Medoff D, Maxfield J, et al. Telephone-based cognitive behavioral therapy targeting major depression among urban dwelling, low-income people living with HIV/AIDS: results of a randomized controlled trial. AIDS Behav 2013;17:2756–64. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 72.Hall DL, Lattie EG, Milrad SF, et al. Telephone-administered versus live group cognitive behavioral stress management for adults with CFS. J Psychosom Res 2017;93:41–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 73.Granberg RE, Heyer A, Gehrman PR, et al. Patient and provider experiences with CBT-I administered in-person or via telemedicine: a randomized non-inferiority trial. Cogent Psychol 2022;9:2038936. [Google Scholar]
  • 74.Glueckauf RL, Davis WS, Willis F, et al. Telephone-based, cognitive-behavioral therapy for African American dementia caregivers with depression: initial findings. Rehabil Psychol 2012;57:124–39. [DOI] [PubMed] [Google Scholar]
  • 75.Frueh BC, Monnier J, Yim E, et al. A randomized trial of telepsychiatry for posttraumatic stress disorder. J Telemed Telecare 2007;13:142–7. [DOI] [PubMed] [Google Scholar]
  • 76.Egede LE, Acierno R, Knapp RG, et al. Psychotherapy for depression in older veterans via telemedicine: a randomised, open-label, non-inferiority trial. Lancet Psychiatry 2015;2:693–701. [DOI] [PubMed] [Google Scholar]
  • 77.Choi NG, Marti CN, Bruce ML, et al. Six-month postintervention depression and disability outcomes of in-home telehealth problem-solving therapy for depressed, low-income homebound older adults. Depress Anxiety 2014;31:653–61. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 78.Burgess M, Andiappan M, Chalder T. Cognitive behaviour therapy for chronic fatigue syndrome in adults: face to face versus telephone treatment — a randomized controlled trial. Behav Cogn Psychother 2012;40:175–91. [DOI] [PubMed] [Google Scholar]
  • 79.Alegría M, Ludman E, Kafali EN, et al. Effectiveness of the Engagement and Counseling for Latinos (ECLA) intervention in low-income latinos. Med Care 2014;52:989–97. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 80.Ye YY, Liu J, Li XJ, et al. The efficacy of Internet-based cognitive behavioral therapy for insomnia [article in Chinese]. Med J Chinese People Liberation Army 2016;41:307–11. [Google Scholar]
  • 81.Azimi M, Moradi A, Hasani J. Effectiveness of cognitive behavioral therapy for insomnia (traditional and Internet-based) on everyday memory of people with insomnia and comorbid depression. Advance Cognitive Sci 2019;20:20–34. [Google Scholar]
  • 82.McAndrew LM, Greenberg LM, Ciccone DS, et al. Telephone-based versus in-person delivery of cognitive behavioral treatment for veterans with chronic multisymptom illness: a controlled, randomized trial. Mil Behav Health 2018;6:56–65. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 83.Sadeghijoola N, Afshari P, Jofreh M, et al. Comparing the effects of face-to-face versus phone counseling based on cognitive-behavioral therapy for vasomotor symptoms in postmenopausal women: a randomized controlled trial. Postep Psychiatr Neurol 2022;31:114–20. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 84.Mohr DC, Ho J, Duffecy J, et al. Effect of telephone-administered vs face-toface cognitive behavioral therapy on adherence to therapy and depression outcomes among primary care patients: a randomized trial. JAMA 2012;307: 2278–85. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 85.Mitchell JE, Crosby RD, Wonderlich SA, et al. A randomized trial comparing the efficacy of cognitive–behavioral therapy for bulimia nervosa delivered via telemedicine versus face-to-face. Behav Res Ther 2008;46:581–92. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 86.Watts S, Marchand A, Bouchard S, et al. Telepsychotherapy for generalized anxiety disorder: impact on the working alliance. J Psychother Integration 2020;30:208–25. [Google Scholar]
  • 87.Morland LA, Mackintosh MA, Greene CJ, et al. Cognitive processing therapy for posttraumatic stress disorder delivered to rural veterans via telemental health: a randomized noninferiority clinical trial. J Clin Psychiatry 2014;75:470–6. [DOI] [PubMed] [Google Scholar]
  • 88.Dedert E, McDuffie JR, Swinkels C, et al. Computerized cognitive behavioral therapy for adults with depressive or anxiety disorders. Washington (D.C.): US Department of Veterans Affairs; 2013. Oct. 13. [Google Scholar]
  • 89.Andersson G, Cuijpers P, Carlbring P, et al. Guided Internet-based vs. face-toface cognitive behavior therapy for psychiatric and somatic disorders: a systematic review and meta-analysis. World Psychiatry 2014;13:288–95. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 90.Adelman CB, Panza KE, Bartley CA, et al. A meta-analysis of computerized cognitive-behavioral therapy for the treatment of DSM-5 anxiety disorders. J Clin Psychiatry 2014;75:e695–704. [DOI] [PubMed] [Google Scholar]
  • 91.Mehta S, Peynenburg VA, Hadjistavropoulos HD. Internet-delivered cognitive behaviour therapy for chronic health conditions: a systematic review and meta-analysis. J Behav Med 2019;42:169–87. [DOI] [PubMed] [Google Scholar]
  • 92.Luo C, Sanger N, Singhal N, et al. A comparison of electronically delivered and face to face cognitive behavioural therapies in depressive disorders: a systematic review and meta-analysis. EClinicalMedicine 2020;24:100442. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 93.Botella C, Gallego M, Garcia-Palacios A, et al. An Internet-based self-help treatment for fear of public speaking: a controlled trial. Cyberpsychol Behav Soc Netw 2010;13:407–21. [DOI] [PubMed] [Google Scholar]
  • 94.Spek V, Nyklícek I, Smits N, et al. Internet-based cognitive behavioural therapy for subthreshold depression in people over 50 years old: a randomized controlled clinical trial. Psychol Med 2007;37:1797–806. [DOI] [PubMed] [Google Scholar]
  • 95.Lappalainen P, Granlund A, Siltanen S, et al. ACT Internet-based vs face-toface? A randomized controlled trial of two ways to deliver Acceptance and Commitment Therapy for depressive symptoms: an 18-month follow-up. Behav Res Ther 2014;61:43–54. [DOI] [PubMed] [Google Scholar]
  • 96.Andersson G, Waara J, Jonsson U, et al. Internet-based self-help versus one-session exposure in the treatment of spider phobia: a randomized controlled trial. Cogn Behav Ther 2009;38:114–20. [DOI] [PubMed] [Google Scholar]
  • 97.Andersson G, Waara J, Jonsson U, et al. Internet-based exposure treatment versus one-session exposure treatment of snake phobia: a randomized controlled trial. Cogn Behav Ther 2013;42:284–91. [DOI] [PubMed] [Google Scholar]
  • 98.Schover LR, Canada AL, Yuan Y, et al. A randomized trial of Internet-based versus traditional sexual counseling for couples after localized prostate cancer treatment. Cancer 2012;118:500–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 99.Renn BN, Hoeft TJ, Lee HS, et al. Preference for in-person psychotherapy versus digital psychotherapy options for depression: survey of adults in the U.S. DNPJ Digit Med 2019;2:6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 100.Kozlov E, McDarby M, Prescott M, et al. Assessing the care modality preferences and predictors for digital mental health treatment seekers in a technology-enabled stepped care delivery system: cross-sectional study. JMIR Form Res 2021;5:e30162. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 101.Alavi N, Moghimi E, Stephenson C, et al. Comparison of online and in-person cognitive behavioral therapy in individuals diagnosed with major depressive disorder: a non-randomized controlled trial. Front Psychiatry 2023;14:1113956. doi: 10.3389/fpsyt.2023.1113956. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 102.Andersson G, Titov N, Dear BF, et al. Internet-delivered psychological treatments: from innovation to implementation. World Psychiatry 2019;18:20–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 103.Hedman E, El Alaoui S, Lindefors N, et al. Clinical effectiveness and cost-effectiveness of Internet-vs. group-based cognitive behavior therapy for social anxiety disorder: 4-year follow-up of a randomized trial. Behav Res Ther 2014;59:20–9. [DOI] [PubMed] [Google Scholar]
  • 104.Nordgren LB, Hedman E, Etienne J, et al. Effectiveness and cost-effectiveness of individually tailored Internet-delivered cognitive behavior therapy for anxiety disorders in a primary care population: a randomized controlled trial. Behav Res Ther 2014;59:1–11. [DOI] [PubMed] [Google Scholar]
  • 105.Clinically appropriate use of virtual care for depression and anxiety-related conditions: Guidance Reference Document. Toronto: Ontario Health; 2023. Available: https://www.ontariohealth.ca/sites/ontariohealth/files/DepressionAnxietyRelatedConditionsVirtualCareGuidance.pdf (accessed 2023 Dec. 24). [Google Scholar]
  • 106.Reyes Velez J, Thompson JM, Sweet J, et al. Cluster analysis of Canadian Armed Forces veterans living with chronic pain: Life After Service Studies 2016. Can J Pain 2021;5:81–95. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 107.Jimenez N, Garroutte E, Kundu A, et al. A review of the experience, epidemiology, and management of pain among American Indian, Alaska Native, and Aboriginal Canadian peoples. J Pain 2011;12:511–22. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 108.Qureshi AR, Patel M, Neumark S, et al. Prevalence of chronic non-cancer pain among military veterans: a systematic review and meta-analysis of observational studies. BMJ Mil Health 2023. Dec. 12:e002554. doi: 10.1136/military-2023-002554. [Epub ahead of print]. [DOI] [PubMed] [Google Scholar]
  • 109.Understanding the mental health of Canadians through COVID-19 and beyond: Poll 17. Toronto: Mental Health Research Canada; 2023. Available: https://www.mhrc.ca/national-polling (accessed 2023 Dec. 24). [Google Scholar]
  • 110.Eliot L. People are eagerly consulting generative AI ChatGPT for mental health advice, stressing out AI ethics and AI law. Forbes 2023. Jan. 1. Available: https://www.forbes.com/sites/lanceeliot/2023/01/01/people-are-eagerly-consulting-generative-ai-chatgpt-for-mental-health-advice-stressing-out-ai-ethics-and-ai-law/?sh=75b788592643 (accessed 2023 Dec. 24).
  • 111.Cuijpers P. Has the time come to stop using the “standardised mean difference”? Clin Psychol Eur 2021;3:e6835. [DOI] [PMC free article] [PubMed] [Google Scholar]

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