Online Counseling and Therapy for Mental Health Problems: A Systematic Review of Individual Synchronous Interventions Using Chat

Abstract

Online interventions are increasingly seen as having the potential to meet the growing demand for mental health services. However, with the burgeoning of services provided online by psychologists, counselors, and social workers, it is becoming critical to ensure that the interventions provided are supported by research evidence. This article reviews evidence for the effectiveness of individual synchronous online chat counseling and therapy (referred to as “online chat”). Despite using inclusive review criteria, only six relevant studies were found. They showed that although there is emerging evidence supporting the use of online chat, the overall quality of the studies is poor, including few randomized control trials (RCTs). There is an urgent need for further research to support the widespread implementation of this form of mental health service delivery.

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Online Counseling and Therapy for
Mental Health Problems: A Systematic
Review of Individual Synchronous
Interventions Using Chat
Mitchell Dowling a & Debra Rickwood a
a University of Canberra, ACT, Australia
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To cite this article: Mitchell Dowling & Debra Rickwood (2013): Online Counseling and Therapy for
Mental Health Problems: A Systematic Review of Individual Synchronous Interventions Using Chat,
Journal of Technology in Human Services, 31:1, 1-21
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1
Online Counseling and Therapy for
Mental Health Problems: A Systematic
Review of Individual Synchronous
Interventions Using Chat
MITCHELL DOWLING and DEBRA RICKWOOD
University of Canberra, ACT, Australia
Online interventions are increasingly seen as having the potential
to meet the growing demand for mental health services. However,
with the burgeoning of services provided online by psychologists,
counselors, and social workers, it is becoming critical to ensure
that the interventions provided are supported by research evidence.
This article reviews evidence for the effectiveness of individual syn-
chronous online chat counseling and therapy (referred to as
“online chat”). Despite using inclusive review criteria, only six rel-
evant studies were found. They showed that although there is
emerging evidence supporting the use of online chat, the overall
quality of the studies is poor, including few randomized control
trials (RCTs). There is an urgent need for further research to sup-
port the widespread implementation of this form of mental health
service delivery.
KEYWORDS effectiveness, mental health, online counseling and
therapy, outcome.
BACKGROUND
Mental distress is a significant burden on individuals and society. Almost half
the population will experience a mental disorder within their lifetime (Kessler,
Berglund et al., 2005; Merikangas et al., 2010; Slade, Johnston, Oakley-
Browne, Andrews, & Whiteford, 2009). Furthermore, between a fifth (Slade
Received June 13, 2012; revised August 20, 2012; accepted September 6, 2012.
Address correspondence to Mitchell Dowling, Centre for Applied Psychology, Faculty of
Health, University of Canberra, ACT, 2601, Australia. E-mail: Mitch.Dowling@canberra.edu.au
Journal of Technology in Human Services, 31:1–21, 2013
Copyright © Taylor & Francis Group, LLC
ISSN: 1522-8835 print/1522-8991 online
DOI: 10.1080/15228835.2012.728508
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2 M. Dowling and D. Rickwood
etal., 2009) and a quarter (Kessler, Chiu, Demler, Merikangas, & Walters,
2005) of the population will meet the criteria for a mental disorder during
any 12-month period. Mental health problems are common, although the
most cases (78%) are mild or moderate, with serious conditions (causing
significant impairment to general functioning) confined to a smaller, but still
substantial, proportion of the population (22%; Kessler, Chiu etal., 2005).
Mental disorders are most prevalent amongst young adults, and three quar-
ters of all lifetime disorders start by age 24 (Kessler, Berglund etal., 2005;
Merikangas etal., 2010; Slade etal., 2009). Consequently, there is a strong
argument that interventions designed to prevent or provide early treatment
should be aimed at young people (Kessler, Berglund etal., 2005).
The high prevalence of mental distress has considerable impact on national
economies, from both direct costs (e.g., counseling, medication, and hospital-
ization) and indirect costs, such as loss of worker productivity, reduced labor
supply, disability support payments, and unpaid care (World Health Organization,
2006). For example, during the 2004–2005 financial year, Australia spent AUD$4.1
billion (USD$4.27 billion) on mental health services (e.g., inpatient and outpa-
tient services, prescription medication, community mental health services, and
research), or 8% of all total health expenditure (Australian Institute of Health
and Welfare, 2010). Psychological distress in employees costs the Australian
economy AUD$5.9 billion (USD$6.14 billion) in lost productivity every year
(Hilton, Scuffham, Vecchio, & Whiteford, 2010). Current service provision does
not meet the societal and economic costs of mental health problems.
Despite the widespread prevalence of mental distress and its impact on
national economies, the availability and use of mental health services remains
disturbingly low. Only 35%–40% of people who meet the criteria for a mental
disorder seek professional treatment (Bebbington etal., 2000; Burgess etal.,
2009; Wang etal., 2005). Moreover, young people are the age group least
likely to seek professional help (Burgess etal., 2009; Tanielian etal., 2009).
Commonly cited barriers to help-seeking include: living in a rural area
(Emmelkamp, 2005), self- and perceived-stigmatization to seeking help for
mental health problems (Barney, Griffiths, Jorm, & Christensen, 2006), and
holding negative attitudes towards seeking help or having negative past
experiences with mental health professionals (Rickwood, Deane, & Wilson,
2007). While providing a service to every person with a mental health prob-
lem is neither feasible nor necessarily appropriate, there is still a significant
need to overcome the barriers for people who would like to seek profes-
sional help and are currently being underserved (Burgess etal., 2009).
Distance communication technology to deliver non-face-to-face therapy
may help to address this problem of service provision. Letters, phone calls and
closed-circuit television links, have been in use since the 1950s (Perle, Langsam,
& Nierenberg, 2011). However, with the increasingly widespread use of the
Internet over the last decade, online psychological services have grown tremen-
dously (Barak, Hen, Boniel-Nissim, & Shapira, 2008). There is now a plethora
of psychoeducational websites, online support groups, interactive self-help
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Online Counseling and Therapy for Mental Health Problems 3
programs, and psychologists giving online group and individual counseling via
e-mail exchanges, text chat room conversations, webcams, and voice-only
exchanges (Abbott, Klein, & Ciechomski, 2008; Ybarra & Eaton, 2005). The
presence of these online psychological services is expected to not only increase,
but branch out and utilize short message services (SMS), smart phone applica-
tions (apps), computer games, and virtual worlds (Barak & Grohol, 2011).
Rickwood (2012) has argued that we are entering an era where there is an
“e-spectrum” of interventions for youth mental health that can meet needs
across the entire spectrum of interventions to support mental well-being.
Mounting evidence suggests that online psychological services are as
good as similar services provided face-to-face (Barak etal., 2008; Gainsbury
& Blaszczynski, 2011; Griffiths & Christensen, 2006; Kaltenthaler, Parry, &
Beverley, 2004; Newman, Szkodny, Llera, & Przeworski, 2011). In their com-
prehensive meta-analysis of Internet-based interventions, Barak etal. (2008)
report the overall effect size to be 0.53, a medium effect size, which is com-
parable to that of traditional face-to-face interventions.
Types of Online Interventions
There is currently no agreed nomenclature to describe different psychologi-
cal services provided over the Internet. Common terms include: online coun-
seling (or therapy), Internet counseling (or therapy), cybertherapy, e-therapy
(or e-counseling), computer-mediated therapy, and web-based interventions.
Some researchers have used broad definitions of psychological interventions
provided on the Internet, such as “any type of professional therapeutic inter-
action that makes use of the Internet to connect qualified mental health
professionals and their clients” (Rochlen, Zack, & Speyer, 2004, p. 270), or
any delivery of mental or behavioural health services, including but not
limited to therapy, consultation, and psychoeducation, by a licensed
practitioner to a client in a non-face-to-face setting through distance
communication technologies such as telephone, asynchronous email,
synchronous chat, and videoconference. (Mallen & Vogel, 2005, p. 764 )
These definitions are ambiguous, however, and do not help differentiate
between types of interventions.
Several researchers have attempted to provide a unifying terminology
to label, define, and categorize different psychological services provided
online (Abbott etal., 2008; Barak, Klein, & Proudfoot, 2009; Rochlen etal.,
2004); however, these efforts are yet to be widely accepted within the psy-
chological community. The most comprehensive taxonomy is that of Barak,
Klein, and Proudfoot (2009), who divide online interventions into four cat-
egories: (a) online counseling and therapy; (b) web-based interventions; (c)
Internet-operated therapeutic software; and (d) personal publications, online
support groups, and online assessments. Table 1 uses this taxonomy to
describe different online service subtypes that are currently available.
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4
TABLE 1 Types of Psychological Services Provided Online
Psychological service provided online Subtypes Examples
Online Counseling: The provision of
psychological interventions delivered
over the Internet, either synchro-
nously or asynchronously, and in
either an individual or group setting.
Synchronous communication: Communications are
relayed between a therapist and client in real time
(e.g., chat, audio, and webcam).
Kids Helpline: http://www.kidshelp.com.au/
teens/get-help/web-counseling/
eheadspace: https://www.eheadspace.org.au/
Asynchronous communication: There is a time lag
between communications relayed between a therapist
and client (e.g., e-mail, forum, and SMS).
Living Well: https://livingwell.org.au/
Counselingandsupport/
LivingWellservicesonline/Onlinecounseling/
Emailcounseling.aspx
Web-based interventions: An online
intervention program to create
positive change and/or improve/
enhance knowledge, awareness, and
understanding for specific disorders.
Web-based education interventions: Programs providing
information regarding the associated features of a
mental disorder.
Better Health Channel: http://www.better-
health.vic.gov.au/
National Institute of Mental Health: http://
www.nimh.nih.gov/index.shtml
Web-based self-help therapeutic interventions: Self-
guided online programs to treat or prevent mental
disorders.
MoodGYM: http://moodgym.anu.edu.au/
moodgym
Human-supported web-based therapeutic interventions:
An online program with the additions of a mental
health professional to provide support, guidance, and
feedback.
Cool Teens: http://accessmq.com.au/
node/136
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5
Internet operated therapeutic software:
Uses advanced computer program-
ming to create positive change and/
or improve/enhance knowledge,
awareness, and understanding of
mental health problems.
Robotic simulation: Computer simulations of therapeutic
conversations.
ELIZA: http://www.cyberpsych.org/eliza
MYLO: http://manageyourlifeonline.org
Rule-based expert systems: Systems for assessment,
treatment selection, and progress monitoring.
Drinker’s Check-up: http://www.drinkers-
checkup.com/
Virtual environments: Games and virtual worlds to treat
or prevent mental disorders.
Reach Out Central: http://roc.reachout.
com.au/
SPARX: http://sparx.org.nz/
Other online activities: Services used
together with interventions by a
professional. Generally, they are not
stand alone services.
Online support groups: To bring people with mental
health issues together to offer relief, empathy, and
emotional support.
Daily Strength: http://www.dailystrength.org/
support-groups
Blue Board: http://blueboard.anu.edu.au/index.
php
Online mental health assessment allows people to fill in
questionnaires in order to obtain an indication of
their physical or mental health status.
Screening for Mental Health: http://www.
mentalhealthscreening.org/
Smart phone applications can be used to gather
information (e.g., negative and irrational thoughts)
and communicate with therapists.
CBTReferee: http://www.cbtreferee.com
CBT Applications: http://www.cbtapps.com
Note. CBT = Cognitive Behavioral Therapy. Summary from Barak, Klein, and Proudfoot, 2009.
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6 M. Dowling and D. Rickwood
Online counseling and therapy is defined as “a mental health interven-
tion between a patient (or a group of patients) and a therapist, using tech-
nology as the modality of communication” (Barak & Grohol, 2011, p. 157).
Modalities of communication include e-mail exchanges, forums, chat (instant
messaging), audio (voice only exchanges), and webcams (e.g., cameras that
transmit video over the internet). Some websites, such as LivePerson, provide
online counseling and therapy using a variety of communication modalities,
including online chat, e-mail, and audio (Finn & Bruce, 2008). Communication
exchanges can be asynchronous, meaning they have a lag in time between
contacts, or synchronous, meaning they occur in real time—that is, no sig-
nificant time delays between interactions are perceived by the user (Perle
etal., 2011). Methods of communication that do not regularly provide instan-
taneous responses, such as e-mails and forums, are asynchronous, while
programs that allow for real time communication, such as chat, audio, and
webcams, are synchronous.
Web-based interventions are
a primarily self-guided intervention program that is executed by means
of a prescriptive online program operated through a website and used by
consumers seeking health- and mental-health related assistance. The
intervention program itself attempts to create positive change and or
improve/enhance knowledge, awareness, and understanding via the pro-
vision of sound health-related material and use of interactive web-based
components. (Barak etal., 2009, p. 5)
Web-based programs can include education interventions (e.g., programs
about the associated features of a mental disorder, explanation of symptoms,
causes, effects, and treatment options), self-help therapies (e.g., treatment or
prevention self-guided online programs to promote positive cognitive,
behavioral, and emotional change), and therapist supported interventions
(e.g., similar to self-help interventions, but with a mental health professional
to provide support, guidance, and feedback).
Internet-operated therapeutic software is differentiated from web-based
interventions by the use of advanced computer programming, such as artifi-
cial intelligence and language recognition software (Barak etal., 2009). This
category includes computer simulations of therapeutic conversations. These
analyze the client’s input of text for key terms and themes, and then, using
algorithms based on scripts of therapeutic conversations, provide a suitable
reply. ELIZA comprised an early computer program designed to simulate a
nondirective therapy conversation based on Rogerian psychotherapy prin-
ciples (Weizenbaum, 1966). Manage Your Life Online (MYLO) is another
automated computer-based self-help program that simulates a conversation
between a client and therapist, but is based upon the principles of Method
of Levels therapy (Carey, 2006).
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Online Counseling and Therapy for Mental Health Problems 7
The fourth, and somewhat amorphous, Other category includes online
support groups, online mental health assessments, and smart phone applica-
tions (Barak & Grohol, 2011; Barak et al., 2009). Online support groups
allow people with mental health issues to communicate with each other
synchronously or asynchronously (e.g., by e-mail, forums, or chat rooms),
and can occur with or without moderation by a mental health professional
(Castelnuovo, Gaggioli, Mantovani, & Riva, 2003). Websites may offer mental
health screening and assessment tools—people fill in questionnaires to
obtain an indication of their physical or mental health status (Ybarra & Eaton,
2005). There are also cognitive behavioral smart phone applications that
now allow people to track and respond to negative and irrational thoughts
at anytime, anywhere they are (Barak & Grohol, 2011).
Effectiveness of Online Interventions
The previously described taxonomy allows comparision of various types of
online interventions through systematic reviews and meta-analyses. Several
researchers have already done so, particularly with regard to web-based
interventions (Andrews, Cuijpers, Craske, McEvoy, & Titov, 2010; Barak etal.,
2008; Gainsbury & Blaszczynski, 2011; Griffiths & Christensen, 2006; Hanley
& Reynolds, 2009; Kaltenthaler etal., 2004; Manzoni, Pagnini, Corti, Molinari,
& Castelnuovo, 2011; Newman etal., 2011; Postel, de Haan, & De Jong,
2008). Griffiths and Christensen (2006) reviewed self-help web-based
interventions and found consistent evidence that online programs were
efficacious. Newman etal. (2011) went a step further, comparing self-help
web-based therapies with therapist-supported web-based therapies to treat
anxiety and mood disorders. While self-help web-based therapies treated
anxiety and mood disorders effectively, therapist-supported interventions
offered the best outcomes, particularly for clinical depression.
Within their comprehensive meta-analysis, Barak etal. (2008) investi-
gated the effectiveness of online counseling modalities. They compared chat,
forum, e-mail, audio, and webcam modalities; chat and e-mail were more
effective than forum and webcam modalities. However, the authors note this
analysis was limited by the small number of studies in each modality. Of
particular concern are the articles related to online chat as a format. Of the
nine articles reviewed, seven were therapist-led group interventions using
chat rooms (Gollings & Paxton, 2006; Harvey-Berino etal., 2002; Harvey-
Berino, Pintauro, Buzzell, & Gold, 2004; Hopps, Pépin, & Boisvert, 2003;
Lieberman etal., 2005; Woodruff, Edwards, Conway, & Elliott, 2001; Zabinski,
Wilfley, Calfas, Winzelberg, & Taylor, 2004). Of the remaining two studies,
one was a combination of chat support, rather than counseling, accompa-
nied by a self-help website (Hasson, Anderberg, Theorell, & Arnetz, 2005).
Thus, of nine studies, only one investigated the effectiveness of individual
synchronous online chat counseling (Cohen & Kerr, 1998). This reveals a
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8 M. Dowling and D. Rickwood
significant gap in the evidence for individual synchronous online chat coun-
seling—a highly available form of online therapy.
Review of Evidence for Individual Synchronous
Online Chat Counseling
Online counseling is widely available: A Google search of “online counsel-
ing” retrieved about 4,060,000 results, and of the first 10 websites, nine were
virtual clinics offering online chat counseling. Furthermore, several textbooks
and courses now aim to teach the skills necessary to give online chat coun-
seling (Jones & Stokes, 2009; Kraus, Zack, & Stricker, 2004; Murphy,
MacFadden, & Mitchell, 2008). There is also a growing body of literature
analyzing the processes of online chat counseling (Mallen, Jenkins, Vogel, &
Day, 2011; Williams, Bambling, King, & Abbott, 2009), including the working
alliance (Hanley & Reynolds, 2009), session impact (King, Bambling, Reid, &
Thomas, 2006), and client attitudes to online chat counseling (Skinner &
Latchford, 2006; Young, 2005).
Mallen etal. (2011) and Williams etal. (2009) have both studied pro-
cesses within an online chat session. Mallen etal. reported that online chat
counselors-in-training most frequently gave approval and reassurance, and
asked open and confronting questions. However, counselors-in-training were
less likely than face-to-face counselors to use interpretation or provide direct
guidance. Williams etal. reported that Kids Helpline counselors most often
used paraphrasing, asking confronting and information-seeking questions, but
were less likely to use empathy, encouragement, and ask feeling-oriented
questions. Both studies suggested that online chat counselors used rapport-
building and information-gathering techniques to compensate for the lack of
nonverbal cues. Furthermore, it has been suggested that the slow pace of the
online chat sessions may limit the range of techniques being used (Williams
etal., 2009). Nevertheless, both studies concluded that most counseling inter-
ventions used during counseling can be successfully transferred to online chat.
A frequently cited criticism of online chat counseling is the perceived
difficulty of forming a working alliance (Fenichel etal., 2002). This appears
to be a legitimate concern, as it is harder to establish a working alliance
online, although the alliances established appear sufficient to facilitate psy-
chological change (Hanley, 2009; King, Bambling, Reid etal., 2006). Specific
factors affecting establishing a therapeutic alliance online include the ratio-
nale behind each client’s decision to seek help from an online chat service,
the counselor’s own computer-mediated communication skills (e.g., use of
emoticons), technical hurdles, and perceived session “control” (e.g., type of
intervention and the regularity of meetings; Hanley, 2011). Furthermore, this
difficulty in establishing a therapeutic relationship appears to be offset by
online clients’ greater willingness to self-disclose, also known as the disinhi-
bition effect (Suler, 2004).
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Online Counseling and Therapy for Mental Health Problems 9
Research into the session impact of synchronous online chat has been
positive (Barak & Bloch, 2006; Reynolds, Stiles, & Grohol, 2006). This sug-
gests that online chat can induce process characteristics (i.e., depth and
smoothness) and client moods (i.e., positivity and arousal) that are related to
feelings of session helpfulness (Barak & Bloch, 2006). However, King, Bambling,
Reid etal. (2006) reported that clients addressed their problems more effec-
tively by phone than online. The authors proposed that this may have been
related to time, as typing is a slower process than talking over the phone.
Online clients also appear to have generally positive attitudes towards
online chat counseling. Client ratings of online chat counselors at LivePerson
demonstrate a high level of service satisfaction (Finn & Bruce, 2008).
Typically, online clients reported the anonymity, convenience, and emo-
tional safety of the online environment as being important motivators for
choosing online chat counseling (King, Bambling, Lloyd etal., 2006; Skinner
& Latchford, 2006; Young, 2005). However, clients also reported being con-
cerned about confidentiality (e.g., who had access to their information) and
technical difficulties (e.g., time lag, or being unable to access a counselor).
Online chat counseling and therapy is a fast-growing field and has been
the subject of many studies. Many questions remain, however, regarding the
effectiveness of online chat counseling and therapy, particularly for individ-
ual counseling or therapy conducted via synchronous online chat. With
increasing demand for evidence-based psychological treatments, service
providers must be confident that their treatments will improve outcomes for
their clients (Carey, Rickwood, & Baker, 2009). The current study undertakes
a systematic review of the evidence related to the outcomes of individual
synchronous online chat counseling and therapy—a form of online mental
health service delivery that closely matches face-to-face therapy and an area
where the research has not been reviewed.
METHOD
A literature search for the systematic review initially identified all peer-
reviewed references related to online therapy, published between 1995 and
2012. A systematic search was conducted using the following EBSCO data-
bases: Academic Search Complete, CINAHL Plus, Psychology and Behavioral
Sciences Collection, PsychArticles, and Psych INFO. The following terms
formed the basis of the search strategy: “online therapy” OR “online counsel(l)
ing” OR “Internet therapy” OR “Internet counsel(l)ing” OR “Internet psycho-
therapy” OR “cybertherapy” OR “e-therapy” OR “chat support.” The expander
“Apply related words” was selected, as was the limiter “Scholarly (peer
reviewed) journals.” This search yielded 1,872 results. A further 29 studies
were identified through hand searching the references in relevant studies
and reviews. A total of 480 duplicates were then removed. After this database
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10 M. Dowling and D. Rickwood
search, abstracts and titles were scanned and irrelevant studies removed. The
inclusion and exclusion criteria are in Table 2. Two reviewers (the authors)
independently applied the inclusion and exclusion criteria once the irrele-
vant studies were removed. A consensus method was used to solve any
disagreements regarding the inclusion of studies.
RESULTS
Studies Included
A total of six studies met the inclusion criteria and a summary of each is
provided in Table 3. The studies included two randomized control trials
(RCTs) and four naturalistic comparisons. Two studies compared online chat
with face-to-face counseling, three compared online chat with telephone
counseling, while one study compared online chat with a waitlist control
group. The studies were from America (1), Australia (1), Canada (1), England
(1), and the Netherlands (2).
COMPUTER-MEDIATED COUNSELING
Cohen and Kerr’s (1998) study recruited 24 American undergraduates who
self-identified as wanting help for anxiety. They were randomly assigned to
one online chat counseling session or one face-to-face counseling session
led by counseling psychology graduate students. The study reported signifi-
cant reductions in anxiety as rated by the State-Trait Anxiety Inventory (STAI)
for both the online and face-to-face conditions. However, no effect size was
reported. No significant differences were found between the online and
face-to-face conditions.
TABLE 2 Inclusion and Exclusion Criteria
Inclusion criteria Exclusion criteria
Participants engaged with a therapist online
in real time via instant messaging or
online chat.
The participants engaged with a therapist
using audio or video-chat.
No web-based program was used in
conjunction with counseling sessions.
Counseling was assisted by a web-based
program.
There were more than five participants There were fewer than five participants
The intervention was one-on-one The intervention was group based.
The effectiveness of treatment was based
on outcome measures of psychological
symptoms, interpersonal, and social
functioning, and/or quality of life.
Dissertations and published poster abstracts.
RCT, quasi-experimental trials, and
naturalistic comparisons included.
Articles not written in English.
Note. RCT = Randomized control trials.
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11
TABLE 3 Study Characteristics
Study Sample Intervention Design Attrition Main findings
Cohen & Kerr
(1998)
– 24 American under-
graduate students
– Self identified as
wanting help dealing
with anxiety
– Single session.
– Counselors were
counseling psychology
graduate students.
– Counseling included issue
identification, exploration,
and problem solving.
– RCT
– Treatment group
(online chat)
– Treatment as
usual
(face-to-face)
– Significant reductions in
anxiety as rated by STAI
for both face-to-face and
chat groups.
– Differences between
groups nonsignificant.
Fukkink &
Hermanns
(2009a)
– 902 Dutch children
– Ages 8–18 years
(Online chat M = 13.8,
SD = 2.0; Telephone
M = 12, SD = 2.3)
– 339 Online chat (39
males, 272 female)
– 563 Telephone (120
male, 401 female)
– Single session.
– Counseling included
establishing contact, issue
clarification, goal setting,
problem solving, and
closure.
– Naturalistic
comparison
– Treatment group
(Online chat)
– Treatment as
usual
(telephone)
– After 1 month
only 223
participants
(119 chatters
and 94 callers)
were available
at follow-up.
– Well-being increased for
online chat (ES = .62,
medium) and
telephone (ES = .34,
small).
– Perceived burden
decreased for online chat
(ES = .44, medium) and
telephone (ES = .12,
small).
– After one month, the
changes in well-being
and perceived burden
remained stable for
both online and
telephone conditions.
– Online chat was slightly
more effective in
improving well-being,
and decreasing perceived
burden.
(Continued)
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12
Study Sample Intervention Design Attrition Main findings
Fukkink &
Hermanns
(2009b)
– 95 Dutch children
– Ages 9–17 years
– 53 online chat
(84% female)
– 42 telephone
(77% female)
– Single session.
– Counseling.
– Random
selection from
database
– Treatment group
(Online chat)
– Treatment as
usual
(telephone)
– 15 of the cases
were excluded
due to missing
data.
– Well-being increased for
online chat (ES = .45,
medium) and telephone
(ES = .40, medium)
– Perceived burden
decreased for online chat
(ES = .36, small) and
telephone (ES = .20,
small)
– No significant difference
between online chat and
telephone.
Kessler etal.
(2009)
– 297 English Adults
– Age range 18–75
(Intervention M 35.6,
SD = 11.9; Control
M = 34.3, SD = 11.3)
– 149 online chat (46
males, 103 females).
BDI M = 32.8, SD = 8.3.
– 148 waitlist control
(49 males, 99
females). BDI
M = 33.5, SD = 9.3
– Diagnosis of depres-
sion (Scored > 13 on
BDI)
– BDI scores: Mild
(14–19), Moderate
(20-28), Severe (>28)
– CBT with a therapist
online in real time.
– 5–10 sessions over
16-week period.
– 55 min per session.
– RCT
– Treatment group
(Online chat)
– Waitlist control
– At 4 months,
92 (62%) had
completed
therapy as
intended. Data
was collected
for 113 (76%)
of the
intervention
group
– At 8 months,
99 (66%) had
had therapy as
intended. Data
was collected
for 109 (73%)
of the
intervention
group
– At 4 months: Intervention
BDI M = 14.5, SD = 11.2
(ES = 0.81, large), and
38% (n = 43) reported a
BDI of < 10; Control BDI
M = 22.0, SD = 13.5, and
24% (n = 23) reported a
BDI of < 10.
– At 8 months: Intervention
BDI M = 14.7, SD = 11.6
(ES = 0.70, large), and
42% (n = 46) reported a
BDI of < 10; Control BDI
M = 22.2, SD = 15.2, and
26% (n = 26) reported a
BDI of <10.
TABLE 3 Continued
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13
King, Bambling,
Reid, & Thomas
(2006)
– 186 Australian
children
– Age range unspecified
(Online chat M = 15.4,
SD = 1.9; Telephone
M = 13.1, SD = 2.4)
– 86 Online chat (4
males, 82 female)
– 100 Telephone (33
male, 67 female)
– Single session.
– Counseling included
information gathering and
problem solving.
– Online chat 50–80 min.
– Telephone 45–60 min.
– Naturalistic
comparison
– Treatment group
(Online chat)
– Treatment as
usual
(telephone)
– Distress as rated by the
GHQ-12 was significantly
reduced in both condi-
tions (partial eta
squared = .50, large main
effect).
– Telephone had a greater
session impact, as rated
by the SIS, than online
chat (partial eta
squared = .15).
Murphy et al.
(2009)
– 127 Canadians adults
– Age range unspecified
(Online chat M = 42,
face-to-face M = 44)
– 26 online chat (73%
female)
– 101 face-to-face clients
(76% female)
– Therapy Online counselors
gave online counseling.
– Interlock counselors gave
face-to-face counseling.
– Specific intervention
unspecified. Counselors a
mixture of Masters degree
counselors and accredited
social workers.
– Naturalistic
comparison
– Treatment group
(Online chat)
– Treatment as
usual
(face-to-face)
– 44 online
clients
completed that
satisfaction
survey, but
only 26 were
given a GAF
score before
and after
treatment
– GAF increased signifi-
cantly in both conditions.
No effect size was
provided.
– There was no significant
interaction between time
and treatment method.
Note. RCT = Randomized control trials; STAI = State-Trait Anxiety Inventory; BDI = Beck Depression Inventory; CBT = Cognitive Behavioral Therapy; GHQ = General
Health Questionnaire; SIS = Session Impact Scale; GAF = Global Assessment of Functioning.
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14 M. Dowling and D. Rickwood
CHILDREN’S EXPERIENCES WITH CHAT SUPPORT AND TELEPHONE SUPPORT
Fukkink and Hermanns’ (2009a) study was a naturalistic comparison of
online and telephone counseling services at Dutch Kindertelefoon. Initially,
902 Dutch children were recruited, with a mean age of 14. About three quar-
ters were female. There were 339 participants online and 563 participants on
the telephone. The presenting problems were varied, including relationships,
home situations, violence/coercion, and emotional problems (e.g., loneli-
ness, self-harm, depression). The interventions were single sessions of coun-
seling led by trained volunteer counselors. Immediately after the counseling
session, client well-being increased for both online chat (ES = 0.62, medium)
and telephone (ES = 0.34, small) supported participants. The perceived
burden of the presenting problem fell for both online (ES = 0.44, medium)
and telephone (ES = 0.12, small). Twenty five percent (n = 223) of the partici-
pants were available for the follow-up. After one month the changes in well-
being and perceived burden were maintained and remained stable for both
online and telephone conditions.
COUNSELING CHILDREN AT A HELPLINE-TELEPHONE
SUPPORT AND CHAT SUPPORT
Fukkink and Hermanns’ (2009b) study randomly selected 110 records from
the Dutch Kindertelefoon database of online and telephone records.
However, 15 of the cases had to be excluded due to missing data. Included
in the study were the records of 53 online clients (84% female) and 42 tele-
phone clients (77% female). The participants’ ages ranged from 9 to 17 years;
no mean age was noted. Participants had one counseling session. Immediately
afterwards, clients reported an increase in well-being for online (ES = 0.45,
medium) and telephone (ES = 0.40, medium) conditions. Furthermore, per-
ceived burden fell for online (ES = 0.36, small) and telephone (ES = 0.26,
small) clients. No significant differences between the groups were reported.
THERAPIST-DELIVERED INTERNET PSYCHOTHERAPY VIA
CHAT FOR DEPRESSION IN PRIMARY CARE
Kessler etal.’s (2009) study recruited 297 English adults with depression who
scored over 13 on the Beck Depression Inventory (BDI), which indicates
mild, moderate, or severe depression; more than two-thirds were severe.
Mean age of the participants was 36 years and 68% were female. They were
randomly assigned to either online chat treatment or the waitlist control. The
treatment was 5–10 Cognitive Behavioral Therapy (CBT) sessions conducted
via online chat over 16 weeks. Each session took about 55 min. At 4 months,
62% of the online chat group had completed treatment as intended and data
were collected from 76% of the group. By 4 months, the online chat group’s
mean BDI score had decreased from 32.8 (SD = 8.3) to 14.5 (SD = 11.2),
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Online Counseling and Therapy for Mental Health Problems 15
which was a large effect (ES = 0.81). The control group’s mean fell from 33.5
(SD = 9.3) to 22 (SD = 13.5), but no effect size was reported. At 8 months the
online chat group’s mean BDI score was steady at 14.7 (SD = 11.6), which
was a large effect (ES = 0.70). The control group’s mean also remained steady
at 22.2 (SD = 15.2).
TELEPHONE AND ONLINE CHAT COUNSELING FOR YOUNG PEOPLE
King, Bambling, Reid etal.’s (2006) study was a naturalistic comparison of
online and telephone counseling services at Kids Helpline in Australia. There
were 86 online chat participants (95% female, M = 15.4 years) and 100 tele-
phone participants (67% female, M = 13.1 years). The presenting problems
were not reported. Participants had a single session of counseling from either
an online or telephone counselor. Immediately after the intervention, partici-
pant distress, as measured by the General Health Questionnaire (GHQ-12),
was significantly reduced for both online and telephone treatment groups
(partial eta squared = 0.50). A significant interaction effect was reported,
indicating that telephone counseling had a more substantial effect than
online chat counseling (partial eta squared = 0.15).
CLIENT SATISFACTION AND OUTCOME COMPARISONS OF ONLINE CHAT
AND FACE-TO-FACE COUNSELING
Murphy etal.’s (2009) study was a naturalistic comparison of online chat and
face-to-face counseling at Therapy Online and Interlock in Canada. Of the 44
online participants, 26 had a Global Assessment of Functioning (GAF) score.
For comparison, 101 face-to-face GAF scores were retrieved from the Interlock
database. Participants’ mean age was 42 years, and about three quarters were
female. Presenting problems included work stress, separation and divorce,
anxiety and depression, and parenting. The specific counseling intervention
and number of sessions were not specified. Counseling was given by a mix-
ture of trained counselors and social workers. The online intervention group’s
mean GAF score significantly increased from 70.3 (SE = 1.5) to 77.8 (SE = 1.6).
However, no effect size was given. The face-to-face comparison group’s GAF
scores also rose from 67.6 (SE = 0.8) to 73.7 (SE = 0.8). No significant interac-
tion between time and treatment method was reported.
DISCUSSION
Despite the proliferation of online chat counseling, there is a dearth of
studies related to the effectiveness of individual therapy and counseling
conducted online via synchronous chat. This systematic review of the lit-
erature identified six studies that assessed the outcome of individual online
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16 M. Dowling and D. Rickwood
synchronous chat interventions. Although the number of studies is small,
their results are promising. All six studies revealed a significant positive
effect of online chat counseling, of which two found that individual online
synchronous chat was equivalent to face-to-face help (Cohen and Kerr,
1998; Murphy etal., 2009); one found that it was better than a telephone-
delivered care (Fukkink & Hermanns, 2009a); one that it was equivalent to
a phone delivered service (Fukkink & Hermanns, 2009b); one that it was
better than a wait-list control (Kessler etal., 2009); and one that it was
effective but less so than a phone delivered service (King, Bambling, Reid
etal., 2006).
Online chat appears to be effective despite the relatively slow pace of
the sessions and the absence of face-to-face cues (e.g., verbal tone, facial
expressions, and body language). This may be due to the anonymity and
invisibility that can be gained through textual conversation (Suler, 2010).
During online chat it is entirely possible for clients to remain anonymous
and thus unidentifiable; this may help people feel less vulnerable about shar-
ing, as what they say cannot be linked back to the rest of their lives. Online
chat clients may also benefit from being invisible, that is to say, the client
cannot see, or be seen by, the counselor. This may reduce the stigma or
embarrassment of physically being seen to seek help and allow clients to be
more comfortable and expressive during counseling sessions.
Although these results are encouraging, there were several limitations.
The sample sizes were generally small, attrition rates were high where there
was follow-up, and little to no control was taken to prevent participants
seeking outside treatment including medication. Furthermore, the studies
were not congruent regarding age, presenting problem, type of intervention,
or number of sessions. Currently, services providing online chat counseling
and therapy rely, by and large, on evidence from related fields, such as tele-
phone and face-to-face care rather than demonstrated efficacy for this par-
ticular modality. This is especially significant at this time in Australia as the
Australian Government is implementing its first e-mental health strategy, pro-
viding $48 million in funding over the next 5 years for online support ser-
vices to aid in mental health prevention and early intervention (Department
of Health and Ageing, 2011). A great deal of further research is needed to
support the implementation of services, such as Kids Helpline’s Web
Counseling or e-headspace, and strong evaluation designs need to be built
into these initiatives to contribute to the evidence base.
FUTURE RESEARCH
Future research should focus on the effectiveness of online chat in relation
to different modalities such as e-mail, audio, and video. Other research
should investigate different methods of online chat interventions (e.g.,
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Online Counseling and Therapy for Mental Health Problems 17
nondirective supportive counseling) and more structured therapies (e.g.,
CBT). Furthermore, these interventions should be considered in terms of
their effectiveness in treating different presenting problems, such as anxiety
and mood disorders. The studies outlined in this systematic review pose
significant questions regarding the number of sessions required for treat-
ment. Four of the studies reported the use of single sessions, which yielded
positive outcomes for participants. However, there is not enough evidence to
draw conclusions regarding what type of problems single sessions treat
effectively, or whether single sessions of supportive counseling or structured
therapy are more effective. Furthermore, future studies would benefit from
having 3- and 6-month follow-ups, in order to identify any decline in effec-
tiveness. Finally, research needs to focus on children and younger adoles-
cents, as many of the services being implemented are aimed at supporting
these age groups. Appropriate and effective treatment as early as possible for
mental health problems is essential to improving the well-being of young
people as they grow into adulthood, and this requires a solid evidence base
to support the choice of interventions.
CONCLUSION
This review provides tentative support for the efficacy of individual synchro-
nous online chat counseling and therapy. The current evidence is, however,
based on a few effectiveness studies in naturalistic settings, and is not suffi-
cient to draw definitive conclusions. More research is needed and RCTs
would be a welcome addition. There is an urgent need for rigorous investi-
gation of the effectiveness of different types of therapeutic interventions
delivered through online modalities due to the rapid implementation of
these approaches.
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ABOUT THE AUTHORS
Mitchell Dowling is a Doctoral Candidate, BPsych & BA, Hons (Psych),
University of Canberra. Debra Rickwood, PhD, is a Fellow of the Australian
Psychological Society (FAPS), Professor of Psychology, University of Canberra
and Head of Clinical Leadership and Research at headspace National Youth
Mental Health Foundation.
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