Internet-based self-help using automatic messages and support on demand for generalized anxiety disorder : an open pilot study

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Internet-based self-help using automatic

messages and support on demand for generalized

anxiety disorder: an open pilot study

Mats Dahlin , Per Carlbring , Andreas Håkansson & Gerhard Andersson

To cite this article: Mats Dahlin , Per Carlbring , Andreas Håkansson & Gerhard Andersson (2020): Internet-based self-help using automatic messages and support on demand for generalized anxiety disorder: an open pilot study, Digital Psychiatry, DOI: 10.1080/2575517X.2020.1822730 To link to this article:

© 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Published online: 12 Oct 2020.

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Internet-based self-help using automatic messages and support on

demand for generalized anxiety disorder: an open pilot study

Mats Dahlina,b, Per Carlbringc, Andreas Håkanssondand Gerhard Anderssona,e a

Department of Behavioural Sciences and Learning, Link€oping University, Link€oping, Sweden;bPsykologpartners, Private Practice, Link€oping, Sweden;cDepartment of Psychology, Stockholm University, Stockholm, Sweden;dDepartment of Psychology, Umeå University, Umeå, Sweden;eDepartment of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden


Generalized anxiety disorder (GAD) is a disabling and often chronic condition. Internet-based treatments for GAD have been shown to be effective, but many studies include weekly con-tact with a therapist with the aim to increase adherence and clinical outcomes. The current study evaluated a less therapist-intensive alternative: support on demand and automatic messages. Thirty-three participants with GAD went through a self-help program targeting excessive worry. Treatment lasted 9 weeks and consisted of seven modules. Participants received short messages with reminders and encouragement. Therapist support was given when asked for. The intervention led to significant and large within-group effects on the pri-mary outcome, Penn State Worry Questionnaire (PSWQ; Cohen’s d ¼ 1.17), as well as on sec-ondary outcomes such as Generalized Anxiety Disorder Questionnaire-IV (GAD-Q-IV; Cohen’s d ¼ 2.71) and Patient Health Questionaire-9 (PHQ-9; Cohen’s d ¼ 1.05). The exception was a small effect on quality of life (d ¼ 0.34). Twenty-four (74.9%) were satisfied with the treat-ment and one dropped out. Therapist support was used by 65.6%. Limitations include lack of control condition and a small sample. While preliminary, the findings suggest that self-guided internet interventions can work and be acceptable when automated messages and support on demand is provided.

ARTICLE HISTORY Received 9 March 2020 Accepted 9 September 2020 KEYWORDS Internet; treatment; generalized anxiety disorder; acceptance; mindfulness Introduction

The life-time prevalence of generalized anxiety dis-order (GAD) is estimated to be between 4.3% and 5.9% [1]. The disorder is one of the most prevalent anxiety disorders in medical care, with a point preva-lence of 8–10% in primary and ambulatory care [2]. Individuals with GAD experience excessive worry that they find hard to control and is present more days than not [3]. The worry and associated anxiety have negative effects on the individual’s functioning, well-being, and quality of life [2], and are associated with elevated mortality in medical conditions and suicide [4]. The economic burden on society is com-parable to that of major depressive disorder and chronic medical conditions, with an increase in the number of days on sick leave and high utilization of medical care [5]. The natural course of GAD is often lifelong, with periods of lesser symptoms that increase again because of elevated stress [6]. Spontaneous remission occurs, but a large number of the cases relapse within a few years [7]. Given the chronic nature of the condition and substantial negative effects for the individual and society, it is

important to establish effective and accessible treat-ment options that can be delivered in regular care.

Internet-based treatment, mainly in the form of Internet-based cognitive therapy (ICBT) [8], has been found to be an effective treatment for a number of psychiatric disorders such as depression, social anx-iety disorder, and panic disorder [9]. There is emerg-ing evidence from controlled trials that the effects of ICBT are comparable to traditional face-to-face cog-nitive behavioral therapy (CBT) [10], and that the effects can be long lasting [11]. Response and remis-sion rates appear to be similar to face-to-face CBT as well [12]. Internet-based treatment for GAD has not been as extensively evaluated as ICBT for some other anxiety disorders, but a meta-analysis [13] included 11 randomized control trials (RCTs) and indicated that both disorder-specific and transdiagnostic pro-grams showed moderate to large effects. Compared to waiting list controls, the treatment programs yielded significant effects with effect sizes of d ¼ 0.91 for GAD symptoms and d ¼ 0.74 for patho-logical worry. Large effects were also found for depressive symptoms, comorbid anxiety, distress,

CONTACT Mats Dahlin Department of Behavioural Sciences and Learning, Link€oping University, Link€oping, SE-581

83, Sweden

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disability, and quality of life compared to a waiting-list control.

There are versions of CBT that incorporate accept-ance, mindfulness, and values within specific therapy approaches, like acceptance and commitment ther-apy (ACT) and mindfulness-based cognitive therther-apy (MBCT). Most of the research on ACT has been in the form of face-to-face studies, but there are also ICBT programs that have incorporated ACT or ele-ments of ACT [14,15], and also applications for health problems such as chronic pain [16] and tin-nitus [17].

ICBT manuals usually incorporate guidance from a therapist who has weekly contact with the partici-pant [18]. The contact centers around the assign-ments in the program, through feedback and messages of encouragement. Incorporation of sup-port has been shown to improve adherence and clinical outcomes compared to pure self-help treat-ments [19]. However, less is known about how this support should be delivered. For example, frequency, content, and mode of delivery are still in need of fur-ther exploration [20,21]. In many studies the support has been delivered by a therapist writing feedback with no strict manual. It is possible that parts of the support could be more efficient without compromis-ing the effects [22].

Support on demand has been suggested as a way of delivering guidance without placing as much demand on the therapists. In this type of support, the contact is initiated by the client and focused on the specific needs the participant has at the moment. The research on support on demand is still in its early stages and has showed mixed results. One trial examining a self-help program for panic disorder with scheduled support via telephone ver-sus non-scheduled support found significant differ-ences in clinical outcomes, adherence, and dropout in favor of the scheduled support [23]. However, the support-on-demand condition was significantly bet-ter than the waiting-list control group. On the other hand, an early study by Berger et al., in which partic-ipants with social phobia were randomized to pure self-help, self-help with weekly support, or self-help with support on demand showed different results [24]. All groups made significant improvements with large effect sizes, and the dropout rate was low (7%). No significant differences were found regarding clinical outcomes, adherence, or dropouts between the three conditions. Similar effects were found in an RCT by Dear et al. in which pain patients were randomized to a pain program with regular contact, optional contact, no contact, or a waiting-list control condition [25]. All three treatment groups showed significant improvements compared to the control condition. No significant differences were found

between the treatment groups in effects, adherence, or satisfaction with the treatment. Results from more recent studies comparing weekly support with sup-port on demand when delivering ICBT strengthen the indications that support on demand can be as effective as weekly contacts [26,27] on clinical out-comes. But in Hadjistavropoulos et al. the comple-tion rates between the two groups differed significantly (57% versus 82% completers in favor of weekly support). To further explore the effects of dif-ferent types of support, Hadjistavropoulos et al. did a preference trial comparing weekly support with support on demand when delivering an 8-week internet treatment in routine care [28]. In this trial 22% selected support on demand and 78% weekly contact. Those selecting support on demand had lower baseline scores on measures of anxiety and panic. Both groups showed large improvements, and there were no differences in effects.

Another alternative to save therapist time is to include automated messages in the treatment. Automated messages are designed to enhance motivation and provide reminders during the treat-ment, and have been included in some programs [29]. A controlled trial comparing pure self-help with self-help plus automatic messages showed an ele-vated number of completers in the group who received automated messages (35% vs 58%), but no significant differences in depression and anxiety scores, except in a small subsample who reported significantly lower symptoms if they were in the group that received automated messages [22]. Another study examined the effects of human or automated support with an ICBT program for depression in a partial factorial design including 239 participants [30]. The automatic and human support were designed to be as equal as possible with the exception that in the human support the participant could ask questions. The automated support con-sisted of tailored automated feedback messages sent after completion of a lesson. In addition to the sup-port, both groups received three coaching text mes-sages per week, which had been written before the treatment started. There were no significant differen-ces between the groups in follow-up or adherence. However, the groups differed in their paths of improvement. The group that received human sup-port improved during treatment, but not between post-measures and follow-up. The group that received automated support, on the other hand, had a smaller improvement from pre- to post-measure but continued to improve until follow-up. The authors argue that this could be a result of different senses of agency when going through a treatment with human support or without. Other forms of automated support, for example using


conversational agents [31], have been tested but are still at an early stage of development [32].

In conclusion, research suggests that support on demand and automated messages can be a viable alternative to weekly support under some conditions. But to our knowledge this type of support has not yet been explored regarding ICBT for GAD. The pre-sent study builds on our previous research on inter-net-based treatment for GAD and a program called ‘Oroshj€alpen.’ Previous studies on a therapist-guided version of the program showed significant and last-ing improvements in measures of worry, anxiety, and depressive symptoms [33,34]. To further investigate the possibilities of delivering treatments for GAD, the aim of this open pilot study was to evaluate if Oroshj€alpen can be delivered with automated and minimal clinical support.

Methods Research design

The research protocol for a randomized controlled trial including a subsequent treatment of the control condition in the RCT was submitted and approved by the ethics committee at Umeå University in Sweden, registration number 2011-185-31 €O. The protocol was also registered at (NCT01570374). Before final inclusion in the RCT, written consent was collected from the participants. The RCT has been published, giving support for the treatment program used in the study when delivered with the support of weekly contact with a therapist [33]. In the RCT 103 participants were randomized to 9 weeks of internet-based treatment or waiting list control. Treatment consisted of the program Oroshj€alpen and weekly support. The participants were instructed to work with a module per week and send a report of the work to the support, who gave written feedback and encouragements. To fur-ther explore the possibilities of different ways of delivering ICBT, the present study included the same treatment program as in the RCT, but the support offered was support on demand and automated messages. Participants for the current study were thus recruited from the control group in the RCT. The same measures were used in the RCT and in the current trial, making it possible to use data from the RCT. The screening and post measures in the RCT were used as baseline and pretreatment measures in the current study and post measures were adminis-trated immediately after treatment in the current study. As in the controlled trial a secure platform with two-factor authentication was used for pre- and post-measures as well as for contact with the partici-pants [35].

Recruitment and inclusion criteria

Participants were initially recruited for the random-ized controlled trial. To be included, the participants registered at the study’s website, answered online screening measures, and went through a clinical interview. The main purpose of the screening was to ensure that the participants suffered from GAD and did not meet any exclusion criteria.

The measures used as screening and outcome measures were the Penn State Worry Questionnaire (PSWQ) [36], Generalized Anxiety Disorder Questionnaire-IV (GAD-Q-IV) [37], Generalized Anxiety Disorder Scale-7 (GAD-7) [38], Beck Anxiety Inventory (BAI) [39], Patient Health Questionnaire-9 (PHQ-9) [40], Montgomery Åsberg Depression Rating Scale Self-Assessment (MADRS-S) [41], and Quality of Life Inventory (QOLI) [42,43]. In addition to the self-report measures, demographical data and information about prior treatment were collected. Online admin-istration of self-report measures has been shown to have good psychometric properties in previous stud-ies [44]. The clinical interview was based on the Structural Clinical Interview for DSM-IV Axis I disor-ders (SCID-I) [45] and conducted over the telephone. The main purpose of the clinical interview was to determine that the participant suffered from GAD, was not too severely depressed or suicidal, and did not present with any other obstacles to being part of the study. Inclusion criteria in the RCT and the present study were the following: 18 years or older; living in Sweden; access to internet daily; 45 points or more on PSWQ; 30 points or fewer on MADRS-S; meeting criteria for generalized anxiety syndrome according to DSM-IV; no current suicidality; no ongoing alcohol or substance abuse; no ongoing psychological treatment; no adjustment of psychi-atric medications for the last 3 months; and if pre-senting with multiple psychiatric problems, suffering from GAD as a primary problem.

After inclusion in the RCT participants were randomized to treatment or waiting list control. After treatment and post-measures were collected in the RCT, we invited the participants on the waiting list condition to obtain treatment and offered the same treatment as in the RCT but with another type of support. Ten of the eligible 43 individuals declined. Reasons stated were lack of time, illness, fear of getting more anxiety, no internet access, hav-ing started another treatment. Of the 33 participants included, one failed to fill out the post-treatment measures and to answer our attempts to contact him or her. This participant was excluded from the analysis, resulting in a total of 32 participants in the current study. Before the treatment started the group had gone through the inclusion procedure, answered weekly measures (GAD-7 and PHQ-9)


during 9 weeks and completed post measures as a result of being part of the RCT. Demographic data on the 32 included participants are presented in

Table 1.

Outcome measures

Primary outcome was self-rated worry measured with the PSWQ. Secondary outcomes were GAD and anxiety symptoms as measured with Q-IV, GAD-7 and BAI; depressive symptoms measured with the PHQ-9 and MADRS-S, and life quality measured with the QOLI.


The treatment program used was an online self-help program consisting of seven modules targeting dif-ferent aspects of worry and anxiety [34]. The pro-gram is aimed at fostering a more accepting stance towards worry and anxiety as well as living a qualita-tively good life. The modules are presented in a pre-determined order and include exercises and writing assignments as a way to enhance the information given in the program. The content includes psycho-education, functional analysis of problematic behav-iors, acceptance, mindfulness, taking valued action, and relapse prevention. The presentation of the con-tent incorporates animations and films, as well as keeping the texts short to make the information easy to access. The program was originally designed to be used on a computer but can be used with a smartphone as well. A more detailed description of the program has been reported [34].

After inclusion the participants were given access to the treatment program and received a message

with instructions that they were expected to work with the program on their own and that they would have 9 weeks to complete the treatment and were encouraged to work with one module per week. Furthermore, they were informed that they could ask for support if they felt they needed it through the same secure website from which they received the instructions.

Automated messages and support on demand

During the treatment, short messages were sent to the participants. The messages were designed and written before the treatment as automated mes-sages. The messages were sent on a predetermined schedule with a fixed date and time (the same for all participants). The messages were managed by the same person giving the support on demand. A total of 17 messages were sent during the 9 weeks of treatment. A message was sent each Monday, and additional messages were sent on different days throughout the treatment period. The messages were short and included some of the following aspects: reminders to work with the program, encouragements, reminders of important information from the program, and the amount of time left in the treatment. The messages were signed with the name of the psychology student who served as sup-port for the study. The student was in his last year of a 5-year psychology program. If a participant needed support, he or she sent a message to the therapist trough the secure website. The therapist was instructed to keep the responses short and not introduce treatment components that were not pre-sent in the program. Replies were structured around the following guiding principles: validation of diffi-culties, messages of encouragement to keep work-ing, reference to the program when possible, and assistance to the participant in solving issues with understanding the program or using the platform. During the treatment, the therapist had weekly supervision of an experienced clinician.

Statistical analyses

Paired samples t-tests were used to analyze changes between pre- and post-scores on the primary and secondary measures. Within-group effect sizes (Cohen’s d) were calculated by dividing the average change score for each individual by the average standard deviation.

Table 1. Demographics and pre-treatment variables.

Participants (N ¼ 32) Gender

Female 28 (87.5%)

Male 4 (12.5%)

Age, mean and SD 37.9 (10.9) Marital status

Single 7 (21.9%)

Living apart 5 (15.6%)

Married/living with partner 20 (62.5%) Highest education High school 7 (21.9%) University 25 (78.1%) Occupation Working 25 (78.1%) Student 3 (9.4%)

Working & student 1 (3.1%) Student & unemployed 1 (3.1%)

Other 2 (6.3%) Psychiatric medication Never 16 (50%) Previous 10 (31.2%) Current 6 (18.8%) Previous Psychotherapy No 6 (18.8%) Yes 26 (81.2%) 4 M. DAHLIN ET AL.



Results are presented for the 32 participants included in the study who completed the post-treat-ment measures.

Baseline information

The mean age was 37.9 years (SD ¼ 10.9), 87.5% were women, 62.5% were married/living with part-ner, 78.1% had a university education, and 81.2% were currently employed. Regarding treatment experience 18.8% were currently using psychiatric medication, and 81.2% had been in psychotherapy before the study. A more detailed description of the demographic and baseline characteristics for the 32 participants is presented inTable 1.

Primary and secondary outcome measures Table 2 presents mean scores pre- and post-treat-ment and Cohen’s d effect sizes. The table also include the scores on the measures at inclusion to the RCT (called baseline in the table) where the group in this study was the control condition as a way to describe effects of being in a waiting-list con-trol group before receiving treatment. During the control condition the participants answered GAD-7

and PHQ-9 weekly. As can be seen in the table, the time as a waiting-list control resulted in significant effects, but the effects of treatment are still signifi-cant and of greater sizes, except for QOLI. A paired sample t-test showed significant differences in all measures between pre- and post-treatment: PSWQ: t [31]¼ 6.0, p¼ .001; GAD-Q-IV: t [31]¼ 9.4, p ¼ .001; GAD-7: t [31]¼ 5.7, p ¼ .001; BAI: t [31]¼ 4.7, p ¼ .001; MADRS-S: t [31]¼ 6.3, p ¼ .001; PHQ-9: t [31]¼ 6.0, p ¼ .001; QOLI: t [31] ¼ 2.2, p ¼ 0.034. The effect sizes on all measures were large (d ¼ 0.84–2.71), except for QOLI with a small effect size (d ¼ 0.34).


The participants were encouraged to work with one module per week but were able to access the next module as soon as they had gone through the cur-rent one, making it possible to access modules any-time. Table 3 shows the number of modules accessed during the treatment. As shown in the Table, 84.4% accessed at least five of the seven mod-ules, and 59.3% accessed all modules during the treatment. On average the participants logged in 9.68 times (range 2–27 times, SD ¼ 6.43) during the treatment.

When asked to report how much time the partici-pants had spent on the treatment, 7 (21.9%) reported less than 1 h per week, 13 (40.6%) 1–2 h per week, 9 (28.1%) 3–4 h per week, and 1 (6.3%) more than 5 h per week. When asked how much they had worked with the exercises in the program, 2 (6.3%) said ‘not at all,’ 13 (40.6%) answered ‘to some extent,’ and 17 (53.1%) answered ‘relatively much or much.’

Support on demand

Table 4 presents an overview of the use of support during the treatment. The participants were given the opportunity to ask for support during the 9 weeks of treatment. Nine participants (28.1%) con-tacted the therapist to ask questions regarding the treatment material, and 12 (37.5%) to ask technical questions (how to use the platform). Five of these participants (15.6%) asked questions of both types. Table 2. Observed means, (standard deviations), and effect

sizes on outcome measures at baseline (intake to RCT), pre-treatment and post-pre-treatment.

(N ¼ 32) M (SD)

Within group effects

Cohens d p Value PSWQ

Baseline 67.59 (6.50)

Pre-treatment 64.84 (5.96) Base– pre: d ¼ 0.44 p ¼ 0.013 Post-treatment 54.97 (10.87) Pre– post: d ¼ 1.17 p ¼ 0.001 GAD-Q-IV

Baseline 10.29 (0.83)

Pre-treatment 9.35 (1.60) Base– pre: d ¼ 0.77 p ¼ 0.001 Post-treatment 5.51 (1.23) Pre– post: d ¼ 2.71 p ¼ 0.001 GAD-7

Baseline 13.13 (4.03)

Pre-treatment 11.06 (3.65) Base– pre: d ¼ 0.53 p ¼ 0.006 Post-treatment 6.91 (3.64) Pre– post: d ¼ 1.13 p ¼ 0.001 BAI

Baseline 20.84 (8.14)

Pre-treatment 16.94 (6.14) Base– pre: d ¼ 0.54 p ¼ 0.004 Post-treatment 11.19 (7.51) Pre– post: d ¼ 0.84 p ¼ 0.001 MADRS-S

Baseline 20.13 (6.09)

Pre-treatment 17.34 (4.92) Base– pre: d ¼ 0.50 p ¼ 0.005 Post-treatment 10.00 (6.03) Pre– post: d ¼ 1.34 p ¼ 0.001 PHQ-9

Baseline 11.94 (4.78)

Pre-treatment 8.88 (4.10) Base– pre: d ¼ 0.68 p ¼ 0.002 Post treatment 4.56 (4.15) Pre– post: d ¼ 1.05 p ¼ 0.001 QOLI

Baseline 1.02 (1.67)

Pre-treatment 1.37 (1.41) Base– pre: d¼ 0.22# p ¼ 0.048 Post-treatment 1.90 (1.69) Pre– post: d¼-0.34# p ¼ 0.034


A negative score on QOLI indicates an improvement.

PSWQ: Penn State Worry Questionnaire; GAD-Q-IV: Generalized Anxiety Disorder Questionnaire-IV; GAD-7¼ Generalized Anxiety Disorder 7-item scale; BAI: Beck Anxiety Inventory; MADRS-S: Montgomery Åsberg Depression Rating Scale – Self rated; PHQ-9 ¼ Patient Health Questionnaire-9; QOLI: Quality of Life Inventory.

Table 3. Number and percentage of participants accessing treatment modules. (N ¼ 32).

n (percentage) Module 1: Psychoeducation 32 (100%) Module 2: Functional analysis 31 (96.8%) Module 3: Values & activities 29 (90.6%) Module 4: Mindfulness 27 (84.4%) Module 5: Alternatives to worry 27 (84.4%) Module 6: Acceptance 22 (68.7%) Module 7: Relapse prevention 19 (59.3%)


The participants asking for support had a minimum of one contact and at the most four contacts with the support. All contact was through the secure messages systems except for one occasion where a participant contacted support for a 21-minute tele-phone call to get technical support. These 21 min are almost one-third of the total time spent on tech-nical questions for the whole group. Table 4 shows an overview of the time spent by the support. Twenty-three of the participants (72%) rated the pos-sibility of getting support as good or very good, and one (3.1%) as not good. Twenty-five of the partici-pants (78.1%) rated the automated messages as positive or very positive, and three (9.4%) as not that positive or bad.

Treatment satisfaction

At posttreatment, participants answered questions about different aspects of the treatment received. Responses were reported on a scale with four options ranging from very much to not at all. A majority, 24 of the 32 participants (74.9%) reported that they were satisfied or very satisfied with the treatment, and two (6.3%) that they were not satis-fied. Twenty-eight participants (87.5%) rated the online program as good or very good, and three (9.4%) as not good. Furthermore, 30 participants (93.8%) rated the program as easy to use and educational.


The aim of this open pilot study was to investigate the effects of a program for GAD (Oroshj€alpen) when delivered with automated messages and min-imal clinical support. The results indicated that sup-port on demand and automated messages can be an alternative to weekly contact with a therapist dur-ing internet-based treatment. The treatment yielded significant effects on the primary and secondary out-come measures, with large effect sizes for all meas-ures except for the secondary measure quality of life (QOLI), which showed a small effect size. The effects were also significant when compared to 9 weeks of waiting for treatment in a control condition, even if significant changes was observed during that time as well. This strengthens previous studies indicating the possibility to treat GAD with acceptance, mind-fulness and valued action strategies delivered through internet-based treatment programs. Furthermore, 74.9% reported that they were satisfied

or very satisfied with the treatment, and 72% rated the possibility of getting support as good or very good. At the same time 65.6% used the support for clinical or technical questions indicating that the possibility to have support is important even if not used. The current study did not include a control condition, but when comparing the within-group effects with previous studies on the same program [33], the treatment effects are similar. A difference compared to the RCT is that in that study 76% accessed all modules compared to 59% in the cur-rent trial. These results are in line with previous tri-als, indicating that significant clinical effects can be achieved with internet-based treatments when par-ticipants are given support on demand, but possibly with lower rates of participants accessing the whole treatment [26]. More than half of the questions directed to the support on demand concerned tech-nical issues. These type of questions could be directed to a technical support team, enabling the psychologist to use valuable time and resources for more complex cases [35].

While the results of this open pilot trial are prom-ising, there are a number of limitations that should be taken into consideration. First, the study did not include a control condition and the sample was small which has consequences for statistical power. However, contrasting the effects of being in a con-trol condition for 9 weeks against the effects of the treatment give some indications of the effect of the treatment compared no treatment. Even if the effects are similar to the effects in previous trials on the treatment program, the results from this pilot trial should be interpreted with caution and further evaluated in larger trials with control conditions. Second, the participants were recruited from the control condition, a waiting-list control in a previous trial. As typical of many controlled trials on internet interventions, the actual waiting period was short, but as seen in Table 2, there were improvements between baseline and pretreatment for this group, and this study should be followed by controlled tri-als in which participants are directly randomly assigned to different levels of support. Third, and this is also relevant for the initial controlled trial, our sample were highly educated, and a large majority were female. While there are effectiveness trials on internet interventions [46], there is a need for further trials investigating whether automated and support-on-demand interventions work, as there might be differences in uptake, adherence, and effects when treatment is part of a regular service.

Table 4. Number of contacts with support and time spent by the support.

Total time used for support Number of contacts Average time spent per contact in minutes

Treatment support 59 min 18 3.3

Technical support 68 min 23 3.0


In conclusion, this study supports the use of auto-mated messages with support on demand as an alternative to weekly contact with a therapist during internet-based treatment for GAD. Further work, including studies on cost-effectiveness and con-trolled trials conducted in different countries and settings, is needed to validate our initial findings.


The authors would like to thank Tomas Johansson, Johan Sj€ogren and Magnus Pettersson for their valuable work with the RCT which made this study possible.

Disclosure statement

Mats Dahlin is employed Psykologpartners, the company that owns the program Oroshj€alpen that was used in this study. No other author has any conflicting interests. Data collection and calculations have been done in collabor-ation among the authors as a way to minimize risk of biased interpretations.


This study was supported in part by a professors’ grant to the last author from Link€oping University.

Notes on contributors

Mats Dahlinis a PhD student as well as a licensed psych-ologist and psychotherapist. His main research focus is on internet-based treatments for generalized anxiety disorder.

Professor Per Carlbringis a licensed psychologist and psy-chotherapist as well as a specialist in clinical psychology. He is the leader of the clinical psychology research group at Stockholm University. He is also an affiliated professor at Southern Denmark University, Odense, Denmark. His main research focus is effectiveness and efficacy of Internet interventions for depression, anxiety disorders and pathological gambling.

Andreas Håkansson is a clinical neuropsychologist and

researcher at the Department of Neurology at Førde Central Hospital, Norway. His clinical practice and research focuses on patients with various types of brain injury (mainly neurodegenerative dementias and stroke).

Gerhard Andersson is full professor of Clinical Psychology at Link€oping University, Sweden and affiliated researcher at Karolinska Institute, Stockholm, Sweden. In addition to degrees in psychology and medicine. His research mainly focus on clinical psychology. He has published several books in the area of clinical psychology and more than 700 articles and book chapters.


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