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Psychology and Psychotherapy: Theory, Research and Practice (2021)
©2021 The Authors. Psychology and Psychotherapy: Theory, Research and Practice
published by John Wiley &Sons Ltd
on behalf of British Psychological Society.
Review of the current empirical literature on using
videoconferencing to deliver individual
psychotherapies to adults with mental health
, Caity McDonald
, Kathleen deBoer
Rachel M. Brand
, Maja Nedeljkovic
and Liz Seabrook
National eTherapy Centre, Swinburne University of Technology, Melbourne,
Centre for Mental Health, Swinburne University of Technology, Melbourne, Victoria,
Alfred Hospital, Melbourne, Victoria, Australia
School of Health and Behavioural Sciences, University of the Sunshine Coast, Sippy
Downs, Qld, Australia
Abstract. Purpose. The COVID-19 pandemic has resulted in a widespread adoption of
videoconferencing as a communication medium in mental health service delivery. This
review considers the empirical literature to date on using videoconferencing to deliver
psychological therapy to adults presenting with mental health problems.
Method. Papers were identiﬁed via search of relevant databases. Quantitative and
qualitative data were extracted and synthesized on uptake, feasibility, outcomes, and
participant and therapist experiences.
Results. Videoconferencing has an established evidence base in the delivery of cognitive
behavioural therapies for post-traumatic stress disorder and depression, with prolonged
exposure, cognitive processing therapy, and behavioural activation non-inferior to in-
person delivery. There are large trials reporting efﬁcacy for health anxiety and bulimia
nervosa compared with treatment-as-usual. Initial studies show applicability of cognitive
behavioural therapies for other anxiety and eating disorders and obsessive–compulsive
spectrum disorders, but there has yet to be study of use in severe and complex mental
health problems. Therapists may ﬁnd it more difﬁcult to judge non-verbal behaviour, and
there may be initial discomfort while adapting to videoconferencing, but client ratings of
the therapeutic alliance are similar to in-person therapy, and videoconferencing may have
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and
reproduction in any medium, provided the original work is properly cited.
*Correspondence should be addressed to Neil Thomas, Centre for Mental Health, Swinburne University of Technology, PO
Box 218, Hawthorn, Vic. 3122, Australia, (e-mail: firstname.lastname@example.org).
advantages such as being less confronting. There may be useful opportunities for
videoconferencing in embedding therapy delivery within the client’s own environment.
Conclusions. Videoconferencing is an accessible and effective modality for therapy
delivery. Future research needs to extend beyond testing whether videoconferencing can
replicate in-person therapy delivery to consider unique therapeutic affordances of the
Videoconferencing is an efﬁcacious means of delivering behavioural and cognitive therapies to adults
with mental health problems.
Trial evidence has established it is no less efﬁcacious than in-person therapy for prolonged exposure,
cognitive processing therapy, and behavioural activation.
While therapists report nonverbal feedback being harder to judge, and clients can take time to adapt to
videoconferencing, clients rate the therapeutic alliance and satisfaction similarly to therapy in-person.
Videoconferencing provides opportunities to integrate therapeutic exercises within the person’s day-
One of the notable impacts of the COVID-19 pandemic on psychological therapy delivery
has been the use of videoconferencing becoming widespread. Telehealth—the use of
telecommunication technology to deliver services—includes a range of networked
communication modalities, also including telephone, email, and text chat messaging.
With improvements in online videoconferencing software and internet speeds, products
such as Skype, FaceTime, and Zoom had already entered mainstream personal and
business communication usage prior to the pandemic, and by incorporating video offer a
close approximation to being in-person. While in-person services had been slow to adopt
digital technologies prior to the pandemic, substantial potential was already seen in
making services more accessible, and the necessity to minimize in-person interaction has
catalysed the adoption of this technology in psychotherapy delivery (Chen et al., 2020;
Shore, Schneck, & Mishkind, 2020; Torous, Myrick, Rauseo-Ricupero, & Firth, 2020;
Wind, Rijkeboer, Andersson, & Riper, 2020).
Videoconferencing has been researched as a medium for therapy delivery over the past
three decades, adopting contemporaneous communication technologies such as televi-
sion-based telemedicine equipment, videophones, and Internet-based webcam systems
(Simpson, 2009). While therapists report concerns about technical difﬁculties and the
potential impact of videoconferencing on the therapeutic alliance (Connoly, Miller,
Lindsay, & Bauer, 2020; Simpson & Reid, 2014), they make adaptations such as
emphasizing their own non-verbal behaviour and clarifying the client’s own responses,
and overall are positive about the technology (Connoly et al., 2020). Backhaus et al. (2012)
conducted a systematic review of 65 papers across a range of populations, concluding that
videoconferencing was feasible, associated with good user satisfaction and similar clinical
outcomes to in-person therapy delivery. Recent systematic reviews by Berryhill, Culmer,
et al. (2019), and Berryhill, Halli-Tiemey, et al. (2019) have conﬁrmed that there are
signiﬁcant post-therapy effects on the most commonly used outcome measures of anxiety
and depressive symptoms aggregated across different clinical groups.
Findings of overall acceptability and efﬁcacy of videoconferencing have informed the
implementation of videoconferencing within services, particularly for programmes
delivered to geographically isolated or dispersed individuals (Morriss et al., 2019; Muir
et al., 2020; Varker, Brand, Ward, Terhaad, & Phelps, 2018). Now adoption is more
2Neil Thomas et al.
widespread, practitioners and clients may need to choose between video and in-person as
more equally available options. To inform clinical decision-making, it is now important to
consider when, and for whom, this mode of therapy delivery may be applicable. This is
particularly important when weighing up choices against pandemic-related health risks
associated with transit and in-person contact, which can be avoided by remote therapy
This review considers the literature to date on how videoconferencing can be utilized
for the delivery of psychological therapy to adults presenting with mental health
problems. Extending upon previous reviews, which have considered outcomes and
satisfaction with videoconferencing across studies as a whole, we consider the following
For which mental health populations and psychological interventions is there current
evidence for psychological therapy being acceptable and efﬁcacious when delivered
What are client and therapist experiences of psychological therapy delivered by
videoconferencing, including perceived beneﬁts, challenges and opportunities?
Primary research studies were identiﬁed via the databases PubMed, Medline, PsycINFO,
and EMBASE in July 2020. Search terms included combinations of the search terms
videoconferencing, telehealth telemedicine, telemental health, telepsychology, telepsy-
chiatry, telepsychotherapy, or telecounselling; psychological therapy, psychotherapy,
counselling, psychological intervention, or cognitive behaviour; and mental disorder,
mental health, mental illness, anorexia, anxiety, bipolar, bulimia, depression, eating
disorder, mood disorder, obsessive–compulsive, personality disorder, post-traumatic
stress, psychosis, and schizophrenia. Database searches were supplemented by review of
reference lists of included papers and previous review papers.
Studies were included which focused on adult populations experiencing adult mental
disorders or clinically signiﬁcant symptoms of mental disorder. Studies were excluded that
focused on children and/or adolescents; people with mental health problems secondary
due to physical illness, substance abuse and/or addictions, neurocognitive disorders,
learning difﬁculties, or intellectual disabilities; healthy populations at risk of developing
mental health difﬁculties; and families of people with mental health difﬁculties. Studies
were included that used one-to-one psychological interventions delivered via videoconfer-
encing. This excluded group-based, couple or family interventions; simulated therapy
sessions; self-help; general psychiatric care; asynchronous psychological therapy delivered
via recorded video. Studies were included that reported quantitative or qualitative data
relevant to understandingoutcomes or experiences of therapy. Case studies were excluded,
as were studies that did not disaggregate psychological therapy results from broader
ﬁndings, but multiple baseline case series were included.
Abstracts were screened by CM, and full papers were independently reviewed against
the inclusion criteria by CM and NT. Each author led extraction of data for a component of
the review, with all data extraction checked and veriﬁed by NT. Data on outcomes and
acceptability were extracted and considered within diagnostic groupings, with a main focus
on randomized controlled trial ﬁndings, and pre-to-post studies and case series ﬁndings
considered when they added to the trial literature. Client and practitioner experiences of
Using videoconferencing to deliver psychological therapy 3
videoconferencing were considered across the literature, prioritizing systematically
collected data reported by papers, but also including anecdotal participant comments. A
thematic synthesis (Lucas, Baird, Arai, Law, & Roberts, 2007) was conducted with a lens of
identifying the prominent beneﬁts, challenges, and considerations in delivery.
The literature search identiﬁed 1637 papers once duplicates were removed, with a total of
69 papers reporting on 54 discrete studies meeting inclusion criteria (see Table 1). These
included 21 randomized controlled trials (RCTs), 20 pre-to-post and non-randomized
comparison trials, 6 case series, 4 stand-alone qualitative studies, and 3 studies examining
rates of uptake. Of the RCTs, 7 examined efﬁcacy compared with a non-therapy control,
and 15 included a head-to-head comparison with in-person therapy, of which 9 conducted
formal non-inferiority or equivalence analyses (detailed in Table 2). No studies contrasted
videoconferencing with other remote communication modalities (e.g., telephone).
The most frequently studied diagnostic groups were post-traumatic stress disorder
(PTSD; 14 studies), and depression (10), for which there were a number of well-powered
RCTs, followed by anxiety disorders (6), obsessive–compulsive spectrum disorders (6)
and eating disorders (6). Twelve additional studies examined mixed diagnosis populations
including a large RCT. Across these studies, a number examined implementations to
speciﬁc populations, with a large number, particularly PTSD studies, conducted with
veterans or military personnel, and others focusing on populations with difﬁculties
attending clinic settings in person, including people with difﬁculties leaving the home,
people living in rural or remote areas, prison inmates, and geographically dispersed
members of migrant populations. Less than half of studies were conducted within the
person’s home/residence, with many especially older studies, involving visiting a local
clinic using telehealth equipment to connect with a therapist in a different location. The
types of technology used for videoconferencing included dedicated telemedicine
hardware, analogue videophones, and, increasingly, using Internet-based videoconfer-
encing software on computers or smartphones. Many studies provided participants with
equipment such as laptop or tablet computers, but more recent studies have used
participants’ own devices.
Across the full range of studies, therapy was found feasible to deliver via videocon-
ferencing, clients were satisﬁed with therapy, and expected improvements in targeted
symptoms occurred. We consider the ﬁndings for speciﬁc populations in detail
(summarized in Table 3), followed by broader ﬁndings about use of videoconferencing
across all studies.
Application of videoconferencing with different populations
Post-traumatic stress disorder
PTSD was the most researched mental health diagnosis. In addition to small pre–post
studies and pilot RCTs, the search identiﬁed 7 well-powered RCTs of videoconferencing
therapy for PTSD, covering a range of treatment protocols, including cognitive processing
therapy (CPT), prolonged exposure (PE), and behavioural activation.
Two trials examined the use of the eight-to-twelve session PE protocol to treat PTSD in
veterans (Acierno et al., 2017, also reported on in Gros, Allan, Lancaster, Szafranski, &
Acierno, 2018; Gros, Lancaster, L
opez, & Acierno, 2018; and Yuen et al., 2015), and one
4Neil Thomas et al.
Table 1. Included studies
Study Population Country Design Comparison NTherapy Location System
Acierno et al. (2016),
Strachan et al.
(2012), Gros et al.
USA RCT IP (NI) 232 BA-TE Home Own device +provided software,
or videophone (Viterion 500)
PCL-M, BDI CPOSS, SDPQ
Acierno et al. (2017),
Gros, Allan, et al.
Lancaster, et al.
USA RCT IP (NI) 150 PE Home Own device +AK Summit software
or provided tablet or videophone
Franklin et al. (2017) Veterans with
USA RCT TAU 27 PE Home or clinic Computer +provided software,
or iPhone +Tango
CAPS, PDS Preferred therapy
Germain et al. (2009),
Germain et al.
et al. (2011)
NRCT IP 68 CBT Clinic Tandberg 2500 VC units MPSS WAI, SEQ, DCCS,
Gros et al. (2011) Veterans with
USA NRCT IP 89 PE Clinic Tandberg 1000 MXP VC units PCL-M IIRS
Hassija and Gray
pre–post - 15 PE or CPT Clinic Polycom VSX3000 VC units PCL, CES-D Satisfaction
Liu et al. (2019) Veterans with
USA RCT IP (NI) 207 CPT Clinic Not stated CAPS, PCL-S,
Luxton et al. (2015) Active military
USA pre–post - 10 BA Home Laptop +Cisco Jabber CAPS, PCL-M,
Maieritsch et al.
USA RCT IP (E) 90 CPT Clinic Not stated CAPS, PCL WAI
Using videoconferencing to deliver psychological therapy 5
Table 1. (Continued)
Study Population Country Design Comparison NTherapy Location System
Morland et al. (2015) Women with
USA RCT IP (NI) 149 CPT Clinic Not stated CAPS WAI, CPOSS-VA,
Olden et al. (2017) PTSD in
USA pre–post - 11 PE Home or clinic Polycom VC units (clinic)
or own device (home)
CAPS, PCL WAI, CSQ, TSAS,
Tuerk et al. (2010) Veterans with
NRCT IP 47 PE Clinic Tandberg 1000 MXP VC units PCL-M, BDI -
Yuen et al. (2015) PTSD, combat
USA RCT IP (NI) 52 PE Home Own device/tablet +VC software or
CAPS, PCL-M -
Ziemba et al. (2014) PTSD USA RCT IP 18 CT Clinic Polycom VC units CAPS Satisfaction survey
Arnaert et al. (2007) Older adults
qualitative - 4 PST Home Videophone - Interviews
Jang et al. (2014) Korean
USA pre–post - 12 CBT ‘Place
Laptop +Vidyo PHQ-9 CSQ
Lazzari, Egan, and
Depression Australia pre–post - 3 BA Clinic Not stated GDS Satisfaction
Choi, Hegel, et al.
(2014), Choi, Marti,
et al. (2014), Choi
et al. (2013)
USA RCT IP, TAU 158 PST Home Laptop +Skype HRSD,
Deen et al. (2013) Primary care
USA uptake study - 179 CBT Home Not stated Uptake of
6Neil Thomas et al.
Table 1. (Continued)
Study Population Country Design Comparison NTherapy Location System
Egede et al. (2015) Veterans with
USA RCT IP (NI) 241 BA Home Videophone BDI, GDS,
Luxton et al. (2016),
Smolenski et al.
(2017), Pruitt et al.
USA RCT IP (NI) 121 BA Home Laptop +Cisco Jabber BDI, BHS IASMHS
Sayal et al. (2019) Young adults
UK RCT TAU 22 PST Not stated Mobile phone or video calling (WebeX) BDI Interviews
Lichstein et al. (z2013) Comorbid
USA pre–post - 5 CBT Clinic Laptop +Skype HRSD, CSD,
Scogin et al. (2018) Comorbid
USA (rural) RCT TAU 40 CBT Clinic Computer +Skype HRSD, CSD,
et al. (2015)
GAD Canada MBCS - 5 CBT Clinic Tandberg 2500 VC system PSWQ -
Watts et al. (2020) GAD Canada RCT IP (S) 115 CBT Clinic Computer +Tandberg MXP software Not yet
Bouchard et al. (2000) Panic disorder/
Canada pre–post - 8 CBT Clinic Tandberg 2000 VC system P&A WAI, session
Bouchard et al. (2004) Panic disorder/
NRCT IP 21 CBT Clinic Tandberg 2500 VC system
Using videoconferencing to deliver psychological therapy 7
Table 1. (Continued)
Study Population Country Design Comparison NTherapy Location System
Morriss et al. (2019) Health anxiety UK RCT TAU 156 CBT Clinic WebeX or telephone SHAI -
Yuen et al. (2013) Social anxiety USA pre–post - 24 ABBT Home Own device +Skype SPAI, LSAS,
Fitt and Rees (2012) OCD Australia MBCS - 4 MCT Clinic Computer +Polycom PVX v 8.0.2 Y-BOCS WAI
Himle et al. (2006) OCD USA MBCS - 3 CBT Not stated Polycom Viewstation VC units Y-BOCS WAI, VTS,
Goetter et al. (2014) OCD USA pre–post - 15 ERP Home Not stated Y-BOCS RTQ, WAI, CSS,
Vogel et al. (2014) OCD Norway RCT SH, TAU 30 ERP Clinic Computer/tablet +FaceTime ADIS-IV, Y-
Muroff and Steketee
Hoarding USA case series - 7 CBT Home Own device +VC software HRS-I, SI-R WAI
Lee et al. (2018) Trichotillomania USA RCT
TAU 22 ACT +HRT Home VSee software
MGH-HPS WAI, CSQ
Abrahamsson et al.
case series - 5 CBT Not stated Mobile device +VC software Meal
WAI, CSQ, SUS
Giel et al. (2015) Anorexia
Germany pre–post - 16 MM Not stated Laptop +Cisco VC software BMI, SCID
Hamatani et al. (2019) Japan pre–post - 7 CBT Home Cisco WebEx (device not stated) EDE WAI
8Neil Thomas et al.
Table 1. (Continued)
Study Population Country Design Comparison NTherapy Location System
Mitchell et al. (2008);
Ertelt et al. (2011);
Marrone et al.
USA RCT IP 128 CBT Clinic Telemedicine equipment (model not
EDE WAI, HPRS
Simpson et al. (2005,
UK (remote) case series - 6 CBT Clinic Sony 1600 VC units +VC software SEDS, BEI-II,
Yu et al. (2020) Binge eating
USA RCT IP 18 CBT Not stated Own device +Fruit Street EQE, EAT,
Brunnbauer et al.
Australia pre–post - 20 Individualized Not stated Not stated CORE-10,
Dunstan and Tooth
Australia pre–post - 8 Individualized Clinic Video monitor +VC software SUDS, DASS,
Grifﬁths et al. (2006) Mood or
pre–post - 15 CBT Clinic Computer +VC software MHI, HoNOS Satisfaction rating
USA (rural) pre–post - 52 Individualized Clinic Not stated CORE, PHQ-
Lindsay et al. (2015) USA (rural) qualitative - 93 Individualized Home Not stated -
Using videoconferencing to deliver psychological therapy 9
Table 1. (Continued)
Study Population Country Design Comparison NTherapy Location System
Matsumoto et al.
Japan pre–post - 30 CBT Home iPad Mini +Cisco WebEx Y-BOCS,
Morgan et al. (2008) People in
USA RCT IP 186 Individualized Prison/
Not stated - WAI, SEQ, CSQ
Simpson et al. (2001),
People living in
UK (remote) qualitative - 10 Individualized Clinic Computer +VC software Interview PHAS
Simpson et al. (2015) Psychology
Australia qualitative - 6 CBT Clinic Computer +Cisco C20 endpoint Interview,
Stubbings et al. (2013) Australia RCT IP 26 CBT Clinic Computer +iChat DASS, QLESQ WAI, CSQ, TSQ
10 Neil Thomas et al.
Table 1. (Continued)
Study Population Country Design Comparison NTherapy Location System
and Sexton (2020)
- 250 CBT Clinic/ home Not stated Uptake of VC -
Yang et al. (2019) Psychotherapy
Canada uptake (RCT
IP 38 CBT Home Own device +VC software Uptake of VC,
Note. VC videoconferencing. Populations: EDNOS =eating disorder not otherwise speciﬁed; GAD =generalized anxiety disorder; OCD =obsessive–compulsive disorder; PTSD =post-traumatic stress disorder. Design: MBCS =multiple
baseline case series; NRCT =non-randomized controlled trial; RCT =randomized controlled trial. Comparison: IP =in-person; IP (E) =in-person, including an equivalence analysis; IP (NI) =in-person, including a non-inferiority analysis.
TAU =treatment-as-usual or enhanced treatment-as-usual condition; SH =self-help. Therapies: ABBT =acceptance-based behaviour therapy; BA =behavioural activation; BA-TE =behavioural activation and therapeutic exposure;
CPT =cognitive processing therapy; CT =cognitive therapy; HRT =habit reversal therapy; MM =Maudsley model; PE =prolonged exposure; ERP =exposure and response prevention; MCT =metacognitive therapy; PST =problem-solving
therapy. Measures: ACQ =Agoraphobic Cognitions Questionnaire; ADIS-IV =Anxiety Disorders Interview for DSM-IV; BDI Beck =Depression Inventory; BHS =Beck Hopelessness Scale; BITE =Bulimic Investigatory Test; BMI =body mass
index; BSQ =Body Sensation Questionnaire; CAPS =Clinical Administered PTSD Scale; CES-D =Centre for Epidemiology Scale for Depression; CORE =Clinical Outcomes Routine Evaluation; CPOSS =Charleston Psychiatric Outpatient
Satisfaction Scale; CSD =Consensus Sleep Diary; CSQ =Client Satisfaction Questionnaire; CSS =Client Satisfaction Survey; DASS =Depression Anxiety Stress Scale; DCCS =Distance Communication Comfort Scale; EAT =Eating Attitude
Test; EDE =Eating Disorder Examination; EPDS =Edinburgh Postnatal Depression Scale; ETO =Expectancy of Therapeutic Outcome; GDS =Geriatric DepressionScale; HPRS =Hill Process Rating System; HRSD =Hamilton Rating Scale for
Depression; HRS-I =Hoarding Rating Scale-Interview; IASMHS =Inventoryof Attitudes Toward Seeking MentalHealth Service; ISI =Insomnia Severity Index; LSAS =Liebowitz Social Anxiety Scale; MGH-HPS =Massachusetts General Hospital
Hair Pulling Scale; MHI =Mental health Inventory; MI =Mobility Inventory for Agoraphobia; MPSS =Modiﬁed PTSD Symptom Scale; OQ45 =Outcome Questionnaire 45; P&A =Panic and Agoraphobia Scale, PCL PTSD Checklist (M Military
version) ; PDS =Posttraumatic Diagnostic Scale; PDSS =Panic Disorder Severity Scale; PEAS =Patient EX/RP AdherenceScale; PHAS =Penn Helping Alliance Scale; PHQ-9 =Patient Health Questionnaire for Depression; PSWQ =Penn State
Worry Questionnaire; QLESQ =Quality of Life Enjoyment and Satisfaction Questionnaire-18 item; RTQ =Reaction to Treatment Questionnaire; SCID =Structured Clinical Interview for DSM; SDPQ =Service Delivery Perception
Questionnaire; SEDS =Survey for Eating Disorders; SEQ =Session Evaluation Questionnaire; SHAI =Short Health Anxiety Inventory; SI-R =Saving Inventory Revised; SPAI =Social Phobia and Anxiety Inventory; SUDS =Subjective Units of
Distress Scale; TEI =Treatment Evaluation Inventory; TEQ =Treatment Expectancy Questionnaire; TFEQ =Three-Factor Eating Questionnaire; TSAS =Telemedicine Satisfaction and Acceptance Scale; TSC =Treatment Session Checklist;
TSQ =Telehealth Satisfaction Questionnaire; VOCI =Vancouver Obsessional Compulsive Inventory; VTF =Videoconference Therapy Questionnaire; VTS =Videoconferencing Telepresence Scale; WAI =Working Alliance Inventory;
WHODAS =World Health Organization Disability Scale; YAFS =Yale Food Addiction Scale; Y-BOCS =Yale-Brown Obsessive–Compulsive Scale.
Using videoconferencing to deliver psychological therapy 11
Table 2. Between group differences in working alliance, primary outcomes, dropout, and satisfaction in large randomized controlled trials involving direct
comparisons with in-person therapy
Study Population NTherapy Therapeutic alliance Primary outcome Dropout/satisfaction
Acierno et al. (2016) PTSD and depression,
232 BA-TE - PCL-M, BDI: VC non-inferior to IP at
post-therapy, and 3 and 12 months
Rate of completion of both therapy and
post-treatment assessment: no
difference (VC 82%, IP 77%)
Acierno et al. (2017),
Gros, Allan, et al. (2018)
PTSD and depression,
150 PE - PCL-M: VC non-inferior to IP at post-
therapy, 3 months and 6 months;
BDI: VC non-inferior to IP at 6 months,
inconclusive at post and 3 months
No difference in number of sessions
attended (VC 7.6, IP 8.6) or
completion of a minimum dose of 6
sessions, but discontinuation
occurred earlier in VC over sessions
Liu et al. (2019) PTSD, veterans 207 CPT - CAPS: VC non-inferior to IP at
6 months, but not at post-therapy;
PCL: VC non-inferior to IP at post and
6 months. PHQ-9: VC non-inferior to
IP at post and 6 months
No difference in study dropout (VC 23%,
Maieritsch et al. (2016) PTSD, veterans 90 CPT WAI client ratings show equivalence CAPS, PCL: inconclusive but trend for
equivalence between groups (p<.10)
High rates of treatment dropout (43%
overall) but no difference by group
Morland et al. (2015) PTSD, female,
civilians and veterans
149 CPT WAI client ratings: VC inferior to IP at
session 2, but difference small (d=
0.07), and no difference at session 6
or 12; therapist ratings: no difference
at any time point. Homework
completion: no difference (VC 77%, IP
CAPS: VC non-inferior to IP at post-
treatment, 3 and 6 months.
Therapy completion rate: no
difference (≥10 sessions: VC 76%, IP
79%). Treatment expectations: no
Satisfaction ratings: both groups rated
service highly on global ratings, with
no difference, but VC inferior to IP on
CPOSS ratings of broader service
Yuen et al. (2015) PTSD, combat-related 52 PE No difference on ratings of how
comfortable feel talking with therapist
or quality of communication
CAPS: VC non-inferior to IP; PCL:
neither group superior but non-
inferiority analysis inconclusive
SDPQ: 100% satisﬁed with treatment in
both VC and IP
Choi, Hegel, et al. (2014),
Choi, Marti, et al. (2014)
adults over 50
158 PST - HAMD: neither group superior at 12 or
24 weeks; VC superior to IP at
36 weeks; WHODAS: neither
superior at any time point
Treatment Evaluation Inventory: VC
superior to IP
Egede et al. (2015) Depression, veterans 241 BA - BDI, GDS, SCID: VC non-inferior at
4 weeks (mid), 8 weeks (post) and
No difference in full therapy completion
rate (VC 81%, IP 79%)
Luxton et al. (2016) Depression, military
121 BA - BDI: VC non-inferior to IP at mid-
therapy and 12 weeks, but not at post-
therapy; BHS: VC non-inferiority not
CSQ: high satisfaction, no difference
12 Neil Thomas et al.
Table 2. (Continued)
Study Population NTherapy Therapeutic alliance Primary outcome Dropout/satisfaction
established at any time point, and
found to be inferior to IP at post-
Attitudes to seeking mental health
treatment: no difference between
groups. No difference in full therapy
completion rate (VC 64%, IP 71%)
Watts et al. (2020) Generalized anxiety disorder 115 CBT WAI: Across 8 time points, VC superior
to IP in client ratings; neither group
superior on therapists’ ratings.
Mitchell et al. (2008),
Ertelt et al. (2011),
Marrone et al. (2009)
Bulimia nervosa or EDNOS 128 CBT WAI: no difference in client ratings, VC
inferior to IP in therapist ratings.
EDE: neither group superior for
abstinence from bingeing and/or
purging. VC inferior to IP for
reduction in binge eating frequency
across time points.
Client ratings of treatment suitability,
client expectation of success, and
number of sessions completed: no
Morgan et al. (2008) People in prison or secure
forensic psychiatric hospital
WAI: no difference in client ratings. - No differences on CSQ, or ratings of
session depth, smoothness, positivity
Note:. Only includes randomized controlled trials sufﬁciently powered to detect large between group effects (N≥52 at 80% power). If no primary outcome
speciﬁed, symptoms of target disorder listed. Superiority/inferiority refers to group differences observed versus a null hypothesis of no difference;non-inferiority (one
tailed test) and equivalence (two-tailed test) refer to whether or not the conﬁdence interval for the difference includes a null hypothesis of the groups differing by the
minimum clinically signiﬁcant difference. PTSD =post-traumatic stress disorder; EDNOS =Eating disorder not otherwise speciﬁed. Therapies: BA =behavioural
activation; BA-TE =behavioural activation and therapeutic exposure; CBT =cognitive behavioural therapy; CPT =cognitive processing therapy; PST =problem-
solving therapy. Groups: IP =in-person; VC =videoconferencing. Measures: BDI =Beck Depression Inventory; CAPS =Clinician Administered PTSD Scale;
CGI =Clinical Global Impression; CPOSS =Charleston Psychiatric Outpatient Satisfaction Scale; CSQ =Client Satisfaction Questionnaire; EDE =Eating
Disorders Examination; GDS =Geriatric Depression Scale; HAMD =Hamilton Rating Scale for Depression; SCID =Structured Clinical Interview for DSM
diagnosis; SCL-90R =Hopkins Symptom Checklist; SDPQ =Service Delivery Perceptions Questionnaire; SEQ =Session Evaluation Questionnaire;
WAI =Working Alliance Inventory.
Using videoconferencing to deliver psychological therapy 13
trial combined behavioural activation with exposure therapy to treat both PTSD and
depression (Acierno et al., 2016; Gros et al., 2012; Strachan, Gros, Ruggiero, Lejuez, &
Acierno, 2012). All compared videoconferencing to in-person delivery and had samples
that were over 90% male. Videoconferencing showed similar rates of therapy completion
(Acierno et al., 2016, 2017; Yuen et al., 2015) and satisfaction (Gros, Allan, et al., 2018;
Yuen et al., 2015) and was non-inferior to in-person for PTSD, depression, and anxiety
(Acierno et al., 2016, 2017; Yuen et al., 2015).
Four trials examined CPT delivered by videoconferencing in comparison with in-person
therapy (Glassman et al., 2019; Lui et al., 2019; Maieritsch et al., 2016;Morland et al., 2015).
Participants were again predominantly veterans, with one study also including civilians
(Morland et al., 2015), but females were better represented in CPT studies (Lui et al., 2019:
45% female, Morland et al., 2015: 100% female). Delivery by videoconferencing was found
to be non-inferior to in-person in reducing PTSD symptoms in all studies other than Lui et al.
(2019) who found that videoconferencing was inferior at post-treatment, but equivalent at
6-month follow-up. All studies found no signiﬁcant differences in dropout or satisfaction
between videoconferencing and in-person conditions.
Overall, the generally positive ﬁndings of acceptability and efﬁcacy of videoconfer-
encing for exposure-based therapies are noteworthy, suggesting this modality is able to
support this emotionally challenging, experientially focused, treatment. It has also been
observed that videoconferencing clients rate the therapeutic alliance as highly for
exposure-based sessions as other CBT-based sessions (Germain, Marchand, Bouchard,
Guay, & Drouin, 2010).
We identiﬁed 3 well-powered RCTs of videoconferencing therapy for depression, 3
smaller RCTs, and 4 studies using other designs. Two studies, including one of the RCTs
(Yang, Vigod, & Hensel, 2019), primarily reported on uptake of videoconferencing.
Intervention models included problem-solving therapy, behavioural activation and
combined CBT protocols for depression with insomnia, and for depression with self-
harm. Overall, results suggested participants were satisﬁed with therapy, and ratings of
acceptability and efﬁcacy appeared similar to in-person delivery.
Problem-solving therapy was examined in a three-arm RCT which compared
videoconferencing or in-person delivery with a supportive weekly care-call control
condition in 158 housebound adults over the age of 50 with depression (Choi, Hegel, et al.,
2014; Choi, Marti, et al., 2014). On the Hamilton Rating Scale for Depression (HRSD), both
videoconferencing and in-person problem-solving therapy were superior to the control
condition at 12 weeks, 24 weeks, without differing from each other, and videoconfer-
encing was superior to both conditions at 36 weeks (Choi, Marti, et al., 2014).
Videoconferencing-based behavioural activation has been examined in two RCTs,
both conducted with veterans. Luxton et al. (2016) conducted an RCT of an 8-session
behavioural activation intervention delivered by telehealth or in-person to 121 military
personnel and veterans with depression. Both conditions showed signiﬁcant post-
treatment improvements on the Beck Depression Inventory (BDI) as the primary
outcome, and non-inferiority analyses showed videoconferencing was non-inferior at mid-
treatment and 12-week follow-up, but not immediately post-therapy. Egede et al. (2015)
obtained more conclusive results in a larger non-inferiority trial with 241 older veterans
with major depression. Comparing videoconferencing delivery using a videophone
system with in-person delivery, non-inferiority was established with no signiﬁcant
14 Neil Thomas et al.
Table 3. Summary of evidence for feasibility, acceptability, and efﬁcacy by population
Therapy models found feasible to deliver using
videoconferencing Outcomes of videoconferencing delivery
PTSD BA-based exposure therapy, CPT, prolonged
6 of 7 RCTs found non-inferior to in-person
therapy, with the other ﬁnding
videoconferencing inferior at post-treatment and
non-inferior at follow-up
Depression BA, CBT, problem-solving therapy 1 RCT found superior to routine care. 3 RCTs
compared with in-person therapy, ﬁnding few
differences between modalities, and 1 trial
Anxiety disorders CBT, including focused therapies for GAD, panic
disorder, social anxiety and health anxiety
1 RCT, with health anxiety, found superior to
routine care. Pre–post studies show
improvements following therapy for other
anxiety disorders. No non-inferiority trials
conducted, but 1 small RCT (mixed diagnoses)
found similar outcomes to in-person delivery.
Obsessive–compulsive disorders CBT, ERP; CBT for hoarding; habit reversal
therapy for trichotillomania
No fully powered RCTs. Pre–post studies show
improvements following therapy.
Eating disorders CBT; Maudsley Model-based relapse prevention 1 RCT (bulimia nervosa) comparing to in-person
therapy, ﬁnding few differences. Pre–post
improvements observed for both bulimia
nervosa and anorexia nervosa
Psychotic disorders No studies identiﬁed -
Bipolar disorder No studies identiﬁed -
Personality disorders No studies identiﬁed -
Note:.BA=behavioural activation; CBT =cognitive behaviour therapy; CPT =cognitive processing therapy; ERP =exposure and response prevention;
RCT =randomized controlled trial.
Using videoconferencing to deliver psychological therapy 15
differences observed in trajectories of improvement on the BDI and Geriatric Depression
Scale, with rates of recovery similar between conditions.
Smaller studies have additionally demonstrated feasibility and acceptability of
delivering CBT-based therapies via videoconferencing to speciﬁc populations such as
women with post-partum depression or anxiety (Yang et al., 2019) and Korean migrants
with depression (Jang et al., 2014). Among other notable studies, Scogin et al. (2018)
conducted a small RCT of a 10-session CBT-based treatment for comorbid depression and
insomnia delivered via Skype, which found superiority over usual care on a measure of
insomnia, but not the HRSD. Finally, in treating self-harm, Sayal et al. (2019) commenced a
small RCT (N=22) of problem-solving therapy for young adults following presentation
for self-harm and mild depression. However, this was discontinued due to recruitment
difﬁculties (an analysis of which did not attribute these to the use of videoconferencing).
Anxiety disorders have been less fully studied than depression. Nonetheless, anxiety
disorders feature as a major group in a number of mixed diagnosis studies, which have
demonstrated that CBT-based therapies can be satisfactorily delivered (e.g., Brunnbauer
et al., 2016; Dunstan & Tooth, 2012; Grifﬁths, Blignault, & Yellowlees, 2006; Matsumoto
et al., 2018, 2020; Stubbings et al., 2013). Among these, an RCT design was used by
Stubbings, Rees, Roberts, and Kane (2013) in a study of 26 people with mainly anxiety
disorders. Reductions on all subscales of the Depression Anxiety Stress Scale (DASS) were
observed following videoconferencing CBT, and, while underpowered, no differences in
the magnitude of effect were observed between videoconferencing and an in-person
comparison group. The feasibility of applying videoconferencing to deliver therapies to
other speciﬁc populations is indicated by the following, mainly small, studies.
Generalized anxiety disorder (GAD)
A multiple baseline case series by Th
eberge-Lapointe, Marchand, Langlois, Gosselin, and
Watts (2015) showed evidence for successful cognitive behavioural treatment of GAD,
with ﬁve participants no longer meeting diagnostic criteria post-therapy and 3 months
later, and this outcome persisting to 12 months after treatment in all but one case. At the
time of writing, initial results from a large RCT of CBT for GAD (N=115), focusing on
working alliance, have been reported by Watts et al. (2020), with clients rating the
working alliance more highly for videoconferencing than in-person therapy across time
points, although therapists rated both modes of delivery similarly.
Panic disorder and agoraphobia have only been studied in small pre-to-post studies,
all of CBT. Bouchard et al. (2000) found signiﬁcant improvements across all measures,
reporting that ﬁve out of the eight participants no longer experienced panic attacks after
the 12-week treatment. Bouchard et al. (2004) delivered the same intervention to a further
10 videoconferencing cases, compared with a non-randomized in-person delivery group.
Nearly all participants achieved remission at the end of treatment, maintained six months
later, a similar to in-person delivery. Matsumoto et al. (2018) also found signiﬁcant
reductions in panic symptoms among 10 participants with panic disorder in their pre-to-
post study of CBT.
16 Neil Thomas et al.
Social anxiety. Modality of delivery is of particular interest for social anxiety, where
communication itself is a source of anxiety. Yuen et al. (2013) examined 12 sessions of
acceptance-based behaviour therapy for 24 individuals with SAD. Therapists rated the use
of videoconferencing as feasible, and there were post-therapy improvements on several
questionnaire measures of social anxiety, maintained and at the 3-month follow-up, as well
as changes on observer-rated social behaviour; participants indicated that they were
satisﬁed with the treatment. Likewise, Matsumoto et al. (2018) found reductions in social
anxiety following videoconferencing-based CBT in their small sample of 10 social anxiety
Health anxiety. The largest study for a speciﬁc anxiety disorder has been for health
anxiety: Morris et al. (2019) conducted an RCT comparing CBT delivered via videocon-
ferencing or telephone with routine care in 156 participants. Supporting the use of
videoconferencing, health anxiety was reduced in the therapy group relative to routine
care at 6-, 9-, and 12-month time points.
Obsessive–compulsive and related disorders
Research into videoconferencing-delivered psychological treatments in obsessive–
compulsive and related disorders was limited, with studies limited to case series and
small sample single-arm open trials and pilot RCTs. Nevertheless, there is an emerging
support for the acceptability and effectiveness of videoconferencing for a range of
intervention types across OCD, hoarding and trichotillomania.
Matsumoto et al. (2018) reported on a standard 16-week CBT treatment for their 10
OCD patients. Symptom reduction pre–post treatment, strong therapeutic alliance, high
rates of satisfaction with treatment, and 100% retention, supported the effectiveness and
feasibility of the intervention. Further, two studies (Goetter, Herbert, Forman, Yuen, &
Thomas, 2014; Vogel et al., 2014) successfully used exposure and response prevention
(ERP) to treat OCD via videoconferencing, with post-treatment symptom reductions.
Vogel et al. (2014) noted high engagement with treatment, an ability to observe exposure
exercises as they occur in participants’ natural environments, and an opportunity to
involve family members and carers, thus addressing family accommodation to rituals
Emerging investigations in hoarding and trichotillomania provide support for its
effectiveness, feasibility, and that it provides additional beneﬁts when compared to
existing treatments. Muroff and Steketee (2018) delivered a structured CBT treatment for
seven patients with hoarding. Six of the seven patients experienced improvements in
symptoms post-treatment, with ﬁve maintaining the gains at 3-month follow-up. The
ability to use portable devices to move around rooms was noted as an important facilitator
in the treatment. In relation to trichotillomania, Lee, Haeger, Levin, Ong, and Twohig
(2018) conducted an RCT comparing videoconferencing-based ACT-enhanced Habit
Reversal Therapy to waitlist control in 22 trichotillomania patients. The study had high
retention rates with only one dropout in each condition, and high levels of participant
satisfaction and therapeutic alliance. Statistically and clinically signiﬁcant improvements
in trichotillomania symptoms were noted among the treatment group.
Using videoconferencing to deliver psychological therapy 17
In the treatment of eating disorders, there has been a single large RCT, which examined
CBT for bulimia nervosa and related disorders (Ertelt et al., 2011; Marrone, Mitchell,
Crosby, Wonderlich, & Jollie-Trottier, 2009; Mitchell et al., 2008). Although bulimia
symptoms reduced for both videoconferencing and in-person delivery, and rates of
abstinence from bingeing and/or purging showed were similar, the reduction in binge
eating frequency was less for videoconferencing participants across multiple time points
(Mitchell et al., 2008). Working alliance was rated similarly by clients for each of the
conditions, but therapists rated the alliance less strongly in the videoconferencing
condition (Ertelt et al., 2011).
Most other studies identiﬁed by the search examined smaller single group samples for
bulimia and related disorders, reporting reductions in bulimic symptoms (Abrahamssom,
Ahlund, Ahrin, & Alfonsson, 2018; Hamatani et al., 2019; Simpson et al., 2006) and
satisfaction with the online modality (Abrahamssom et al., 2018; Simpson et al., 2005).
For anorexia nervosa, Giel et al. (2015) conducted a single group pilot study examining
a relapse prevention intervention based on the Maudsley model (Schmidt, Magill, &
Renwick, 2015) in 16 individuals. Eight sessions were delivered via videoconferencing,
bookended by two in-person sessions. Three-quarters of participants completed therapy,
rating high satisfaction, and at post-intervention body mass index had increased by an
average of 1.1 points, eating concerns were reduced, and two participants were in
No studies were identiﬁed providing data on videoconferencing therapy delivery to
persons with psychotic disorders, bipolar disorder, or personality disorder.
Client and practitioner experience
Every RCT comparing at-home videoconferencing with in-person delivery at a clinic
reported no group differences on questionnaire measures of satisfaction (see Table 2).
Differences in satisfaction or dropout were only seen in two studies overall, both
delivering interventions within the same environment: Morland et al. (2015) reported
lower satisfaction ratings primarily related to negative experiences of the clinic setting
that was attended for videoconferencing (also used in the in-person condition),
suggesting speciﬁcity to the potentially impersonal experience of attending a clinic for
a video-based appointment. Conversely, Choi, Hegel, et al. (2014) found that housebound
people with depression receiving in-home therapy via videoconferencing were more
satisﬁed than those being visited by a therapist. Overall, this demonstrates that satisfaction
with videoconferencing-based therapy is as high as traditional forms of delivery.
In terms of therapy dropout, nearly all comparisons with in-person therapy revealed no
group differences (see Table 2). An exception was a follow-up analysis of discontinuation
in the trial by Acierno et al. (2017) reported that early dropout tended to arise more often
with videoconferencing (Gros, Allan, et al., 2018), even though overall session attendance
rates were similar. While dropout seems to only arise in a small number of people, other
studies report discomfort with videoconferencing being cited by participants as a reason
for dropout, so this may be an issue with a small number of people, although at this stage
18 Neil Thomas et al.
there is a lack of information on what contributes to this (Germain, Marchand, Bouchard,
Drouin, & Guay, 2009; Lichstein et al., 2013; Simpson, Bell, Knox, Mitchell, & Eating,
It should be noted that individual comments expressing a preference for in-person
therapy were often noted from videoconferencing participants (Choi, Wilson, Sirrianni,
Marinucci, & Hegel, 2013; Lichstein et al., 2013; Simpson et al. 2005, 2006). Among
qualitative client reports, a period of early discomfort and adaptation to using
videoconferencing technology was also an experience reported by participants across
studies (Choi, Hegel, et al., 2014; Dunstan & Tooth, 2012; Fitt & Rees, 2012; Germain et al.,
2009; Lichstein et al., 2013; Simpson et al., 2005, 2006; Simpson et al., 2015; Yuen et al.,
2015). For some participants, attitudes towards videoconferencing (including scepticism,
anxiety, unfamiliarity) were linked to the experiences of discomfort in early sessions
(Arnaet, Klooster, & Chow, 2007; Choi, Hegel, et al., 2014; Fitt & Rees, 2012; Simpson
et al., 2005, 2006). For most, this early discomfort was reduced over time, as participants
got more comfortable with the technology (Choi, Hegel, et al., 2014; Dunstan & Tooth,
2012; Simpson et al., 2005, 2006; Simpson et al., 2015) or their interactions with their
therapist became more ‘natural’ (Yuen et al., 2015), although this did not always occur
(Choi, Hegel, et al., 2014; Choi et al., 2013; Lichstein et al., 2013; Simpson et al., 2005).
Therapists reported similar experiences of initial apprehension and discomfort, before
becoming more conﬁdent in using videoconferencing technology and adapting to the
modality (Dunstan & Tooth, 2012; Michell et al., 2008). This is balanced by other reports
of participants embracing the novelty and use of technology in therapy delivery (e.g.,
Aranaet et al., 2007; Choi, Hegel, et al., 2014; Choi et al., 2013; Dunstan & Tooth, 2012). It
should be noted that many of these studies were conducted before the widespread day-to-
day use of videoconferencing platforms, and less adaptation may be required in the 2020s.
One of the presumed beneﬁts of videoconferencing is that it facilitates access. As shown in
Table 1, many of the studies reviewed targeted participants in rural or geographically
remote areas, and some involved applications to potentially isolated groups (e.g.,
housebound older adults; victims of domestic violence, migrants). Participant reports
indicated that many people receiving videoconferencing therapy would otherwise have
been unable to access any therapy (Choi et al., 2013; Hassija & Gray, 2011), while others
included references to challenges of travel distance and its associated ﬁnancial impact
(Abrahamsson et al., 2018; Simpson et al., 2005; Simpson et al. 2015). Some studies also
referred to the opportunity to provide specialist services for a speciﬁc issue to people over
a broad area (Hassija & Gray, 2011; Lee et al., 2018).
Even when not an absolute barrier, the increased accessibility appeared valued. The
post-partum mental health study by Yang et al. (2019) examined uptake when the option
to use videoconferencing in place of in-person psychotherapy sessions was offered: 74%
used videoconferencing for at least one therapy session, with 21% doing all therapy via
video; Time and cost savings were identiﬁed, and participants reported being able to
attend more frequently. In other studies, participants spoke of convenience, such as
ﬁtting therapy into busy life schedules (Abrahamsson et al., 2018; Choi, Hegel, et al., 2014;
Choi et al., 2013; Lee et al., 2018; Yuen et al., 2015), and being able to access therapy from
home (Choi, Hegel, et al., 2014). Continuity of care independent of location was also
highlighted, both in relation to moving house (Simpson et al., 2005, 2006), and being
released from prison (Morgan, Patrick, & Magaletta, 2008).
Using videoconferencing to deliver psychological therapy 19
Symptoms of anxiety, concerns about stigma, and negative thought processes also
featured as potential barriers to accessing in-person services that videoconferencing was
able to circumvent (Abrahamsson et al., 2018; Bouchard et al., 2000; Simpson, Guerrini, &
Rochford, 2015). For example, in the trichotillomania study by Lee et al. (2018), 40% of
participants reported that they would not have entered treatment in an in-person setting
due to shame. Privacy for persons in small or rural communities was also referred to
(Simpson et al., 2005; Simpson et al., 2015). Nonetheless, privacy was not always assured
by videoconferencing with concerns about privacy from others within the person’s own
home being raised by some participants (Abrahamsson et al., 2018; Choi, Hegel, et al.,
2014; Franklin, Cuccurullo, Walton, Arseneau, & Petersen, 2017). Notably, concerns
about privacy from use of networked digital technology did not tend to be reported.
Client factors predicting uptake and satisfaction
Studies of client variables predicting uptake, engagement and completion of therapy have
identiﬁed relatively few predictors. In considering predictors of uptake among American
primary care attendees with a positive depression screen, Deen, Fortney, and Schroeder
(2013) found that uptake of videoconferencing-based CBT was predicted by perceiving
illness to be persisting, believing that treatment would be effective, and reporting
geographic barriers to attending; Time barriers, ﬁnancial barriers, perceived stigma, and
other beliefs about depression were unrelated to uptake. In a mixed diagnosis veteran
sample offered therapy, Valentine et al. (2020) found that videoconferencing therapy
uptake, and sessions completed, were each unrelated to age, race, gender, and marital
Several studies have examined predictors of differential satisfaction with, or dropout
from, videoconferencing therapy. In most studies, completion of therapy appears
unrelated to baseline demographic (age, gender, ethnicity, income) and clinical variables
(Choi, Hegel, et al., 2014; Germain et al. 2009; Luxton et al., 2016; Watts et al., 2020),
although unreplicated ﬁndings reported by single studies include greater completion
rates for mood rather than anxiety disorders (Valentine et al., 2018), lower baseline PTSD
and absence of disability status (Gros, Allan, et al., 2018), and, among veteran samples,
being an older, Vietnam-era veteran (Gros, Yoder, Tuerk, Lozano, & Acierno, 2011). Pruitt
et al. (2019) also found that satisfaction with therapy was higher for older military,
although, in their sample, this was confounded with serving vs veteran status, with active
military needing to travel off base to access videoconferencing facilities. Analyses of
predictors of outcome have been limited, but in a military sample, Smolenski, Pruitt,
Vuletic, Luxton, and Gahm (2017) found greater baseline anxiety and loneliness predicted
participants having a better outcome from in-person than from videoconferencing-based
Among their participants with depression, Choi, Hegel, et al. (2014) found no
relationship between ratings of treatment acceptability and computer/Internet owner-
ship, or network quality. Similarly, in an analysis of PTSD trial data, Price and Gros (2014)
observed that outcome of PTSD treatment via telehealth was unrelated to prior
experience with, or expressed comfort with, telehealth at the outset of treatment. This
suggests that prior experience is not a requirement to beneﬁt. However, prior experience
of therapy appears to predict completion. In their study of uptake, Deen et al. (2013)
found predictors of treatment completion were different from those for uptake, and
completion was most related to engagement with other treatments: receipt of prior
20 Neil Thomas et al.
counselling and being prescribed antidepressant medication. Watts et al. (2020) also
found prior therapy experience predicted completion.
Most studies referred to technical issues as an experience impacting on the delivery of
therapy. These included difﬁculties establishing connection, disconnection, suboptimal
audio and visual quality, and bandwidth and connection stability issues resulting in lag and
frozen images. Participants considered minor disruptions such as lag as a frustrating and
distracting disadvantage of videoconferencing, but, overall, this did not negatively impact
on participant engagement (Abrahamsson et al., 2018; Choi et al., 2013; Dunstan & Tooth,
2012; Lichstein et al., 2013). Studies resolved these issues through in-session trou-
bleshooting or reconnection. Severe technical issues (e.g., disconnection and inability to
re-establish connection) were managed by postponing or cancelling scheduled sessions,
or by utilizing a back-up communication method (e.g., telephone) (Abrahamsson et al.,
2018; Germain et al., 2010; Hassija and Gray, 2011; Lee et al., 2018; Luxton, Pruitt,
O’Brien, & Kramer, 2015; Olden et al., 2017; Yu et al., 2020; Vogel et al., 2014; Watts et al.,
To proactively manage technical issues, test calls or in-person training were often
provided to therapists to resolve potential technical issues at the outset (Acierno et al.,
2016, 2017; Choi, Hegel, et al., 2014; Choi, Marti, et al., 2014; Goetter et al., 2014; Gros,
Allan, et al., 2018; Gros, Lancaster, et al., 2018; Luxton et al., 2015, 2016; Yuen et al., 2013,
2015), and many studies arranged for technical support to be available as part of the study
design (Acierno et al., 2016, 2017; Germain et al., 2009, 2010; Liu et al., 2019; Olden et al.,
2017; Scogin et al., 2018; Watts et al., 2020; Yuen et al., 2013). Yuen et al. (2013, 2015)
observed that technical difﬁculties reduced over the course of the study, in part due to
participants becoming proﬁcient at troubleshooting. Overall, while technical issues were
encountered in most studies, participant feedback and reports from the study authors
indicate that disruptions were not sufﬁciently impactful to detract from therapy.
Therapy relationship and process
On both formal measures and in qualitative reports, studies consistently reported that the
videoconferencing clients were typically able to develop a positive connection with the
therapist (Simpson et al., 2005, 2006; Simpson et al., 2015; Choi et al., 2013; Dunstan &
Tooth, 2012; Fitt & Rees, 2012; Yuen et al., 2015), although some individual reports found
a reduced sense of the therapist’s presence (e.g., Arnaet et al., 2007; Choi, Marti, et al.,
2014). Furthermore, nearly all well-powered RCTs that directly compared client ratings of
the therapeutic relationship with in-person delivery found no signiﬁcant differences
(Table 2), consistent with observations in smaller studies (e.g., Morgan et al., 2008; Scogin
et al., 2018). Additionally, in an analysis of equivalence, Maieritsch et al. (2016) found
conﬁdence intervals for the working alliance fell within a priori bounds of equivalence in
their trial of CPT. An exception to these ﬁndings is the CPT trial by Morland et al., (2015),
which found statistically, but marginally, lower ratings for videoconferencing in the
second session, with no differences at later time points. It is notable that, mirroring the
adaptation to discomfort reported in some studies, some studies have also observed that
videoconferencing clients rate a stronger alliance as sessions progress (Ertelt et al., 2011;
Germain et al., 2010).
Using videoconferencing to deliver psychological therapy 21
The converse ﬁnding of a stronger alliance in the videoconferencing condition by
Watts et al. (2020) corresponds to qualitative comments in other studies to there being
potential advantages of videoconferencing for the therapeutic relationship. Participants
discussed ﬁnding therapy easier through having a greater sense of control (i.e., of
emotion, of context, of the ability to leave) and the creation of a less intense therapy
environment (Dunstan & Tooth, 2012; Fitt & Rees, 2012; Simpson, 2001; Simpson, Deans,
& Brebner, 2001, Simpson et al. 2005; Simpson et al. 2006; Simpson et al. 2015).
Participants discussed the ability to ‘talk more freely’, being less self-conscious, ﬁnding it
easier to communicate and feeling less pressured or intimidated in videoconferencing
than they might be in-person (Fitt & Rees, 2012; Simpson et al., 2005, 2015; Yuen et al.,
Two of the three well-powered studies that included both client and therapist ratings
(Ertelt et al., 2011; Morland et al., 2015; Watts et al., 2020) identiﬁed differences of
perspective: videoconferencing clients rated a stronger alliance than in-person clients,
while therapists rated the conditions the same (Watts et al., 2020), or clients rated the
conditions similarly when therapists rated videoconferencing as inferior (Ertelt et al.,
2011). These quantitative ﬁndings correspond to therapist reports of some difﬁculties in
detecting emotion and ability to read body language through videoconferencing (Dunstan
& Tooth, 2012; Simpson et al., 2005; Yu et al., 2020; Yuen et al., 2013). This highlights that
therapists and clients may have discrepant experiences of videoconferencing therapy and
that therapists can ﬁnd the process of therapy more challenging, without that necessarily
being reﬂected in client experience.
Adaptations of therapy
To deliver therapy via videoconferencing, several studies reported adaptations to therapy
protocols. Most commonly, the practical logistic changes to how components of therapy
were delivered involved using other technologies to share documents (e.g., mailing,
faxing, emailing, or screen sharing worksheets and homework) (Gros et al., 2011; Himle
et al., 2006; Lindsay et al., 2017; Luxton et al., 2015; Matsumoto et al., 2018; Turek, Yoder,
Ruggiero, Gros, & Acierno, 2010). Clinical variations included removing situation-speciﬁc
in vivo exposure exercises from videoconferencing sessions and asking participants to
complete exposure as homework only (Gros et al., 2011; Yuen et al., 2013), or creatively
adapting or restricting exposure exercises so that they would be suitable for delivery
within the virtual environment (e.g., talking on the phone to someone; Yuen et al., 2013).
While feasible, for some clients, exposure tasks via videoconferencing were perceived to
be less real and less engaging when compared with in-person (Yuen et al., 2013).
Conversely, where videoconferencing was delivered by smartphone, opportunities were
identiﬁed in using the portability of the device to observe and conduct exposure activities
within the person’s environment (Franklin et al., 2017; Turek et al., 2010; Vogel et al.,
2012, Vogel et al., 2014).
Clients also reported that some activities translated less well such as meditation
(Linsday et al., 2017) and use of imagery (Simpson et al., 2005) and that sensitive topics
may be easier to discuss in person than over videoconferencing (Lindsay et al., 2017). It is
notable that the studies surveyed used primarily behaviour al models of treatment, so more
reﬂective therapies are relatively less tested.
In addition to facilitating exposure tasks, the opportunity to see the person in their
home environment was mentioned by some practitio ners as helpful in contextualizing the
person’s experiences (Lindsay et al., 2017) and potentially altering the power balance by
22 Neil Thomas et al.
seeing the person in their own territory (Simpson et al., 2005). However, environmental
distractions arose more frequently within the home environment were also noted, and
some clients treated the session less formally (e.g., smoking, attending wearing pyjamas),
sometimes requiring boundary setting to maintain focus (Franklin et al., 2016; Lindsay
et al., 2017; Yu et al., 2020). When contrasting with therapy delivered in-person within the
home, even greater distractions were noted when the therapist is in the home
environment, and videoconferencing was noted to help to formalize the interaction
and help clients stay focused (Choi, Hegel, et al., 2014).
Discussion and conclusions
The literature to date shows consistent positive ﬁndings about the suitability of the
videoconferencing modality for delivery of psychological therapies, with consistent
ﬁndings that videoconferencing does not differ from in-person therapy on outcome,
satisfaction, therapy completion, and client experiences of the therapeutic alliance.
Advantages include accessibility, particularly to persons without local in-person services,
but also in terms of convenience, reducing time and ﬁnancial costs, and circumventing
stigma, self-consciousness and privacy concerns. Disadvantages include therapists ﬁnding
it harder to judge body language, both clients and therapists experiencing initial
discomfort with the modality while adapting to it, and interruptions arising from
inevitable technical issues. However, it appeared that these concerns became less as
clients and therapists adjusted: It may be that these issues become less of a concern as
familiarity with videoconferencing grows across the population.
In considering the clinical populations for whom videoconferencing-based therapy is
most evidenced, conclusions primarily reﬂect the availability of trial data, rather than
patterns of superior or inferior efﬁcacy being observed. That withstanding, the
videoconferencing modality has its most established evidence base in the delivery of
cognitive behavioural therapies for PTSD and depression, where multiple trials have
determined non-inferiority to in-person therapy. Across anxiety, obsessive–compulsive
spectrum and eating disorders, there is also emergent evidence supporting use. Notably,
there was a lack of study of videoconferencing therapy delivery to people with psychosis
(although see Santestaban-Echarri et al., 2020, for ﬁndings of broader service delivery,
such as psychiatry appointments, being acceptable to this population).
Among therapy modalities, CPT, PE, and behavioural activation all have evidence of
non-inferiority, so can be considered the best supported for delivery in this modality. It is
notable that trauma-focused therapies, as some of the most confronting therapeutic
approaches, are the best evidenced, which suggests that an in-room presence is not
required to deliver quite challenging therapies. Nonetheless, studies with available data
have primarily utilized behavioural therapies. This leaves it unknown how therapies that
use greater Socratic dialogue and reﬂection may operate within a videoconferencing
environment, where some of the technical issues such as lag may prove more interruptive
to the therapy process. Likewise, it is not known whether therapies for complex
presentations, such as personality disorder and psychosis, which require more careful
monitoring of in-session rapport, would be equally successful.
A further caveat is that most large-scale studies have been conducted in American
veteran/military populations, with predominantly male participants, raising questions of
generalizability. Of note, the clearest ﬁnding of videoconferencing having slightly poorer
outcomes than in-person therapy was in a trial for bulimia nervosa with a predominantly
Using videoconferencing to deliver psychological therapy 23
female group (although also using older telemedicine technology). On the other hand, the
female-only study by Morland et al. (2015) also found non-inferiority and broadly similar
results and observed that outcomes were in fact better among civilians compared with
veterans. Nonetheless, these limitations in the available data urge some caution in
assuming that videoconferencing therapies will function as well as in-person therapy with
all therapies and populations. It should also be noted that we did not aggregate and meta-
analyse mean scores for variables across studies, so there may be small between group
differences that individual trials were not powered to detect.
In considering areas for further research, it is notable that since the COVID-19
pandemic, new questions have emerged as in-person therapy has not always been the
most important reference point. We did not identify any studies that contrasted
videoconferencing with telephone as the other widely accessible communication
modality. While, in a non-clinical client group, Day and Schnier (2002) failed to ﬁnd any
advantages of video counselling over telephone on process or outcome measures,
considering the contrasting uses of these two widely accessible platforms, and
understanding whether visual non-verbal feedback facilitates maintaining rapport, is
needed in clinical populations. Further study also needs to be directed at examining the
opportunities that may be presented by using videoconferencing as a therapeutic
medium. Observations suggest there are particular affordances of video, allowing access
to the home environment and potentially for portability, which may have advantages in
better connecting with the person’s daily life, and developing more ecologically valid
therapeutic exercises. Rather than considering videoconferencing second to a presumed
gold standard of in-person therapy, attention to these affordances is needed to evolve
videoconferencing-based therapy practice in its own right.
This research received no speciﬁc funding.
Conﬂict of interest
All authors declare no conﬂict of interest.
Neil Thomas (Conceptualization; Data curation; Formal analysis; Investigation; Method-
ology; Supervision; Writing –original draft; Writing –review & editing) Caity McDonald
(Conceptualization; Data curation; Formal analysis; Investigation; Writing –review &
editing) Kathleen de Boer (Data curation; Formal analysis; Investigation; Writing –original
draft; Writing –review & editing) Rachel M. Brand (Investigation; Writing –original draft;
Writing –review & editing) Maja Nedeljkovic (Investigation; Writing –original draft;
Writing –review & editing) Liz Seabrook (Conceptualization; Data curation; Formal
analysis; Investigation; Writing –original draft; Writing –review & editing).
24 Neil Thomas et al.
Data availability statement
The data that support the ﬁndings of this study are available from the corresponding author
upon reasonable request.
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30 Neil Thomas et al.