Skip to main content

A pragmatic randomized controlled trial of a group self-management support program versus treatment-as-usual for anxiety disorders: study protocol



The integration of a personal recovery-oriented practice in mental health services is an emerging principle in policy planning. Self-management support (SMS) is an intervention promoting recovery that aims at educating patients on the nature of their mental disorder, improving their strategies to manage their day-to-day symptoms, fostering self-efficacy and empowerment, preventing relapse, and promoting well-being. While SMS is well established for chronic physical conditions, there is a lack of evidence to support the implementation of structured SMS programs for common mental disorders, and particularly for anxiety disorders. This study aims to examine the effectiveness of a group-based self-management support program for anxiety disorders as an add-on to treatment-as-usual in community-based care settings.


We will conduct a multicentre pragmatic randomized controlled trial with a pre-treatment, post-treatment (4-month post-randomization), and follow-ups at 8, 12 and 24-months.

Treatment and control groups

a) group self-management support (10 weekly 2.5-h group web-based sessions with 10–15 patients with two trained facilitators); b) treatment-as-usual. Participants will include adults meeting DSM-5 criteria for Panic Disorder, Agoraphobia, Social Anxiety Disorder, and/or Generalized Anxiety Disorder. The primary outcome measure will be the Beck Anxiety Inventory; secondary outcome measures will comprise self-reported instruments for anxiety and depressive symptoms, recovery, self-management, quality of life, and service utilisation.

Statistical analysis

Data will be analysed based on intention-to-treat with a mixed effects regression model accounting for between and within-subject variations in the effects of the intervention.


This study will contribute to the limited knowledge base regarding the effectiveness of structured group self-management support for anxiety disorders. It is expected that changes in patients’ self-management behaviour will lead to better anxiety management and, consequently, to improved patient outcomes.

Trial registration NCT05124639. Prospectively registered 18 November 2021.

Peer Review reports


Background and rationale

Anxiety disorders are prevalent and disabling mental disorders characterized by marked fear, anxiety and avoidance behavior [1,2,3]. More frequent in women than men, they often appear during childhood and adolescence, and 50–80% of cases are comorbid with other anxiety disorders, mood disorders, and substance use disorders [4,5,6,7]. They also frequently coexist with chronic physical illness [8]. Individuals with anxiety disorders demonstrate significant psychological distress, functional and social impairment, suicide risk, and service utilization [1, 9,10,11,12,13]. The Global Burden of Disease Study ranks anxiety disorders as the sixth leading cause of years of life lived with disability [14]. Pharmacological and psychological treatments are recommended in clinical practice guidelines for the management of anxiety disorders [1, 15]. However, anxiety disorders often present a relapsing or chronic course [16,17,18,19,20], and residual symptoms are frequent, even among patients in remission [21, 22]. Thus, individuals have an active role to play in their lifelong recovery, beyond the contribution of evidence-based treatments, to develop self-management skills and improve functioning, prevent relapse and live a fulfilling life despite the presence of residual symptoms [23, 24].

Self-management support (SMS) is an intervention promoting recovery that aims at educating patients on the nature of their mental disorder, improving their strategies to manage their day-to-day symptoms, fostering self-efficacy and empowerment, preventing relapse and promoting well-being [25,26,27]. SMS is consistent with patient-centered care [28] and has the potential to enhance the efficiency of the health care system for patients by improving health outcomes and reducing overall service utilization [29]. SMS is a promising avenue towards recovery by fostering social inclusion, self-determination, autonomy, hope, and personal responsibility. Recovery is defined by the Mental Health Commission of Canada [30] as “living a satisfying, hopeful and contributing life, even when there are ongoing limitations caused by mental health problems and illnesses”. Previous studies have found that patients in recovery from anxiety disorders use a large variety of self-management strategies in their day-to-day life to foster their recovery [24, 31]. No less than 60 different self-management strategies have been identified in a qualitative study among patients in recovery from mood or anxiety disorders [31]. It is expected that changes in patients’ self-management behaviour will lead to better anxiety management and, consequently, to improved patient outcomes, relapse prevention, lower utilization of health care services, and cost savings. SMS typically offers a wide variety of self-management strategies that each person can draw upon based on their needs and preferences to make informed health decisions in their everyday lives, with a predominant focus on self-efficacy, active engagement in the long term, relapse prevention, peer support and facilitation approach. SMS interventions are positioned as a complementary intervention to evidence-based pharmacological or psychological treatments for anxiety disorders and offer a specific contribution to interdisciplinary mental health practice. While some overlap (e.g., psychoeducation, problem solving, relapse prevention) with low-intensity cognitive behavioural therapy (CBT) is acknowledged, a primary difference is that structured SMS programs tend to implement a holistic recovery-oriented approach centered on optimizing wellness and living a fulfilling life even in the presence of ongoing symptoms, to empower people to develop their very own self-management toolbox in a supportive framework, and to be provided by people with a large diversity of backgrounds (e.g., health care providers, social and community workers, peer supporters) [25].

While the value of the integration of SMS programs to health care services for chronic physical conditions is well-established [27, 29, 32] and rapidly growing for depression [25, 33,34,35,36], few studies have examined the added value of structured SMS programs for anxiety disorders as a complement to usual care. In a review by Houle et al. [25], the efficacy of SMS for depression was examined in six studies and promising results were observed for symptom reduction, self-management behaviours and self-efficacy, and mixed results for relapse rates. A recent literature search identified two other studies, conducted in the United States, that evaluated the efficacy of SMS group interventions, that were both peer-led and administered to heterogeneous samples of patients with mental health problems [34, 37]. While promising, most studies did not examine patient outcomes for anxiety disorders. Only two trials were found specifically for self-management support in anxiety disorders. In Germany, a cluster-randomised controlled trial of a nurse-led collaborative care intervention to promote self-management support has shown a small effect on self-efficacy in primary care patients with anxiety, depressive or somatic symptoms [38]. In the Netherlands, a randomized controlled trial evaluated a group rehabilitation and self-management program among patients with chronic anxiety and/or depression in an outpatient mental health care setting and reported a moderate effect on empowerment, but did not observe any significant effects on quality of life or symptom severity [39]. Consequently, there is a knowledge gap about the added value of structured SMS programs to usual care for common mental disorders, and particularly for anxiety disorders.

A program of self-management workshops for mental health has gathered interest from policy makers, health care managers, clinicians, and patients alike over the past few years. The J’avance! program was developed by a well-established mental health community-based organisation in Quebec, Relief (, whose mission is to help individuals with anxiety disorders, depression, and bipolar disorder. The SMS program designed for anxiety disorders draws on personal recovery models as well as on low-intensity psychosocial and psychological interventions; it has been thoroughly developed in collaboration with researchers (JH; scientific lead) and reviewed by an interdisciplinary expert committee as well as participants from pilot groups. The SMS program covers a broad range of mental health intervention strategies (e.g., problem solving, emotion regulation, exposure, cognitive restructuring, mindfulness) and wellness-focused approaches (e.g., strengths, social support, lifestyle habits) in a non-directive “toolkit” aimed at building self-management skills. Great emphasis is placed on peer support, with participants sharing experiential knowledge, committing to trying self-management strategies and overcoming stigmatization. Since 2014, the SMS intervention was delivered over 445 times and over 1000 facilitators have been trained to date, and implementation is also beginning across Canada and internationally. Initially an on-site only workshop, Relief has implemented in 2020 a virtual delivery format on an eLearning platform and is now conducting group SMS workshops with both modalities. Given this wide-spread implementation, we sought to examine how the group SMS workshop translates into better mental health outcomes, health care system utilization and overall efficiency as a complement to usual care for patients with anxiety disorders.


The aim of the present study is to evaluate the effectiveness of a structured group virtual SMS program as an add-on to treatment-as-usual (TAU) in a sample of adults with anxiety disorders. Primary questions: When group SMS is added to TAU in community-based care for patients with anxiety disorders, is the SMS + TAU group more effective in reducing anxiety symptoms than TAU alone? Secondary questions: a) Considering a recovery-oriented approach for patients with anxiety disorders, is there a significant difference between group SMS + TAU and usual care in terms of self-management strategies and personal recovery assessment at the 12-month follow-up? b) Does group SMS + TAU present superior cost-effectiveness and cost-utility, in terms of quality of life and anxiety-free days, than TAU for patients with anxiety disorders at the 12-months follow-up? c) Is there a significant difference between group SMS + TAU and usual care for high-end functioning rates? d) Is there maintenance of gains at 12- and 24-months follow-up? e) Is there differential effectiveness based on moderators (i.e., sociodemographic characteristics, clinical characteristics, past treatment experience) and mediators (i.e., group cohesion, therapeutic alliance, adherence)?

Trial design

The trial is a two-arm parallel group multicentre pragmatic superiority randomized controlled trial (RCT), with a 1:1 allocation at the individual level. The group SMS intervention will be offered to participants in the TAU groups after the 12-month follow-up (delayed-intervention). The 24-month follow-up will therefore only provide a within-group dataset. The proposed protocol conforms to SPIRIT guidance [40].


Participants, interventions, and outcomes

Study setting

The study will be conducted in four health administrative regions in Quebec (Canada): Eastern townships, Mauricie-et-Centre-du-Québec, Abitibi-Témiscamingue and Laurentides. Administrative regions were purposefully selected based on the following criteria: a) the in-person group SMS intervention is not currently largely implemented in the region; b) the virtual SMS intervention is rarely accessed by participants from the region, even though the virtual SMS format is technically accessible throughout the province; c) diversity (e.g., population size, region, university teaching hospital).

Eligibility criteria

This pragmatic RCT focuses on broad inclusion criteria for mixed anxiety disorders groups and minimal exclusion criteria. Inclusion criteria: (1) aged 18 and over, (2) fluent in spoken and written French, (3) meeting DSM-5 diagnostic criteria for at least one of the following anxiety disorders: Panic Disorder, Agoraphobia, Generalized Anxiety Disorder, and Social Anxiety Disorder, (4) access to a computer or tablet connected to the internet with microphone and video camera. Exclusion criteria: (1) previous enrolment in the SMS intervention for anxiety disorders provided by Relief, (2) active suicidal intentions, (3) severe depressive symptoms (i.e., PHQ-9 score ≥ 20), (4) active substance-related and addictive disorder, and (5) cognitive impairment.


Recruitment strategies will include self-referral following advertisements (e.g., waiting rooms of clinics, bulletin boards, geo-located website, and social media) and referrals from community-based primary care (e.g., family physician, community organization, mental health care team, mental health provider). The recruitment of participants will be conducted through a two-stage process. Filter 1: Self-referred individuals will acquire information on the study by accessing the study’s website or through a telephone call or email to our research laboratory. Self-referred individuals will complete a web-based screening survey comprising the required online consent form, basic eligibility criteria as well as anxiety symptoms and comorbidity overview. The initial web-based consent form and procedure has been approved by the ethics committee. At the end of the survey, they will provide their name and contact information. In the presence of clear exclusion criteria, a list of mental health resources will be provided. Filter 2: In the second stage (within 2 weeks of the screening survey), the baseline assessment will be conducted on a secure web-based platform with a trained clinical evaluator. The interview will begin with the consent form. The evaluator will explain the study, review the consent form with the participants, answer their questions, and verbally ask for their consent. The consent form will be sent by email for the participants to read prior to the online assessment, and this verbal consent procedure has been approved by the ethics committee given the web-based data collection method. The assessment will comprise sociodemographic data, service utilization and MINI International Neuropsychiatric Interview [41] for DSM-5 assessment (T0; random pre-assignment), combined with an adapted baseline Relief interview procedure (e.g., current main difficulties, interest in the program, capacity to use eLearning technology, readiness to take part in a group intervention). Patients meeting eligibility criteria at T0 will be given instructions to complete the remaining web-based self-reported questionnaires within 48 h, and only then will we have all required information to proceed with randomization. Figure 1 shows the study flowchart.

Fig. 1
figure 1

Flow of participants


Group SMS for anxiety disorders + treatment-as-usual (TAU)

The SMS manualized program for anxiety disorders ( aims at improving self-management capabilities through weekly 2.5-h sessions with 10–15 patients over a 10-week period. The SMS program (see Table 1) covers the following themes: getting to know your anxiety; building self-awareness; reconsidering your lifestyle habits; adopting a problem-solving method; avoidance and exposure; acceptance and committed action; seeing things differently; managing your emotions; receiving support from others; and consolidating your toolkit. The trial will focus solely on the virtual format. As in the groups delivered by Relief, SMS will be either co-facilitated by health care professionals (e.g., social worker, psycho-educator, nurse), or by a health care professional and a peer supporter, namely a person recovered from an anxiety disorder who has experience and training offering peer support, building on mutual understanding and respect [42,43,44], to emphasize experiential knowledge sharing. Relief will provide the material for the training of the facilitators, the program documentation, the eLearning platform, and the material used by the participants. Consistent with standard implementation of this SMS program, facilitators will participate in a one-day Relief training program. Three case discussions for each group delivered (before onset, mid-group, and following last session) will be conducted by the research team. A random review of 30% of recordings of sessions will be conducted to monitor adherence with a treatment integrity scale. Integrity data will not be used to intervene to improve compliance, but only to examine process-outcome correlation and to guide improvements following the trial. Patient compliance will be supported through the extensive Relief experience delivering SMS (e.g., material, training, support), and the convenient eLearning platform (e.g., easy access, reduced stigma).

Table 1 Content of the 10-week SMS manualized group program for anxiety disorders


No limitations will be imposed concerning usual care, as we aim at examining the added value of SMS to TAU. To reflect heterogeneity of health seeking behaviour and mental health practices for anxiety disorders in the community, we do not require that participants have a family physician, be constrained to a prespecified usual care or have contacts with the healthcare system. To minimize behavioural change in healthcare providers, we will not inform any healthcare provider of participation in the study. As the intervention will be provided on an eLearning platform, and not embedded in clinics, contact between intervention and control patients is unlikely. All participants will receive information about the SMS intervention and the goal of the study, i.e., “of helping them manage their anxiety”. We will thoroughly assess participant-reported service utilization 12 months prior to enrolment and during the study to examine risk of study-induced behavioral change with regards to usual care.

Participant assessment

Table 2 shows the assessment timeline. The data collection will be based on instruments with good psychometric properties, previously used in clinical trials for anxiety disorders to ensure comparability, and with validated French versions (when available).

Table 2 Study schedule of patient assessment


Sociodemographic variables will be collected at baseline (T−1 et T0), and comprise sex and gender, age, marital status, racial identity, ethnicity, education level, income level, occupation, and insurance coverage. We will also collect data on previous experience with mental health services. The web-based screening survey will comprise the Generalised Anxiety Disorder-7 (GAD-7) [45], a 7-item self-report questionnaire measuring anxiety symptomatology. Diagnostic-specific measures will also be administered. The Social Phobia Inventory (SPIN) [46, 47] is a 17-item self-report questionnaire measuring the fear, avoidance, and physiological discomfort associated with social anxiety disorder. Studies have reported good internal reliability, test-retest reliability, and convergent validity [46]. The Panic Disorder Severity Scale Self Report (PDSS-SR) [48] is a questionnaire measuring the severity of seven dimensions of panic disorder. The PDSS-SR shows good internal reliability, test-retest reliability and sensitivity to change [48]. The clinical assessment will be based on the Mini International Neuropsychiatric Interview (MINI) [41], a brief structured diagnostic interview for DSM-5 administered by a trained lay interviewer. Inter-rater reliability will be assessed for 25% of audio-recorded interviews.

Primary outcome measure

The severity of anxiety symptoms will be assessed using the self-report, 21-item Beck Anxiety Inventory (BAI) [49, 50]. The BAI assesses emotional, physiological, and cognitive symptoms of anxiety and indicates minimal (0–7), mild (8–15), moderate (16–25) and severe anxiety (26–63). The scale shows significant reliable improvement and clinically significant change cut-points [49,50,51].

Secondary outcome measures

Participants will also complete diagnostic-specific measures, as well as other questionnaires related to quality of life, self-management, and recovery. The Patient Health Questionnaire (PHQ-9) [52] is a 9-item, self -report questionnaire measuring the frequency of depressive symptoms with good reliability and validity. The Assessment of Quality of Life – 6D (AQol-6D) [53] is a valid and reliable 20-item questionnaire assessing six psychosocial and physical dimensions related to the quality of life. The Disease Burden Morbidity Assessment [54, 55] is a self-report questionnaire measuring the presence of chronic conditions and interference on daily activities. The self-administered Recovery Assessment Scale – revised (RAS-r) [56,57,58,59] is a 24-item validated patient-oriented outcome measure of recovery in five domains: personal confidence and hope, willingness to ask for help, goal and success orientation, reliance on others, no domination by symptoms. The RAS is the most frequently used and tested recovery measure, has good psychometric properties, including sensitivity to change, and correlates with a range of other measures (e.g., activation, psychological well-being, positive illness outlook). The Mental Health Self-Management Questionnaire (MHSQ) [23] assesses the use of mental health self-management strategies. It comprises 18 items. The scale has satisfactory internal reliability and construct validity, adequate test–retest reliability and its convergent and concurrent validity are supported.

Service utilization

Data will be obtained from provincial administrative databases (i.e., Régie de l’assurance-maladie du Québec (RAMQ), Quebec emergency department database (BDCU) and public primary health care database (I-CLSC)) for medical and biopsychosocial services, hospitalization’s registry, and medication data at the end of the data collection. A brief questionnaire on other mental health consultations (e.g., type of professional, duration, costs) and psychotropic medication will be administered at each assessment period to offset the limitations of administrative data.

Questionnaires completed during SMS sessions

The appreciation of the alliance for both participants and facilitators will be assessed with the 12-item version of the Working Alliance Inventory (WAI) [60, 61]. The WAI shows good construct validity and high internal consistency [62]. The perceived cohesiveness and bond for participants will be examined with the 9-item Gross Cohesion Scale (GCS) [63], a scale with acceptable reliability and validity. These measures will be used at sessions 3 and 8.

A logbook will also be used by facilitators to record intervention adherence for each participant as well as to report experiences and perceptions related to SMS group facilitation. The logbook content will provide a better understanding of the actual implementation of the program. The facilitators will also complete a brief questionnaire comprising sociodemographic questions, items on academic and professional backgrounds, as well as experience with SMS, group interventions and anxiety disorders.

Embedded qualitative interview

A sequential embedded qualitative approach [64] will be used to explore participants’ views and experiences regarding the SMS intervention. The data collection will include a brief individual telephone contact with open-ended questions at the T3 and T4 follow-ups. A semi-structured interview guide [65] with open-ended questions will be used to elicit information on topics such as participants’ experience with the intervention, its perceived effectiveness, and most useful strategies or skills acquired. We will obtain verbatim transcripts of all the audio recordings. Data coding and analysis will be conducted based on the interactive cyclical process of data reduction, data display and conclusion drawing and verification [66]. For data reduction, we will use the QSR*NVIVO database software [67] to analyze the transcriptions with a coding strategy based on emerging clustering during the process.

Data collection, management, and analysis

Participant timeline

The assessments will be conducted at baseline (T−1, T0), posttreatment (T1; 4-month post-randomization) and follow up at 8-month (T2), 12-month (T3) and 24-month (T4) post-randomization. In-treatment assessments for participants and facilitators will also be conducted at sessions 3 and 8. Self-report questionnaires at each assessment period will be completed online through the REDCap application managed at the Centre de recherche du Centre Hospitalier Universitaire de Sherbrooke (CRCHUS) at University of Sherbrooke on a secure server with systematic backups. The clinical interviews (T0, T3, T4 only) will be conducted with the Zoom video conferencing service. Data collection with the REDCap application will be managed independently of the treatment assignment. The database will only include coded, depersonalised data, and participant’s identifying information will be stored in a separate secure location with restricted access to the linking code.

We conservatively planned for a 25% attrition at follow up, but we will devote considerable efforts toward a < 5% target with study retention strategies: (1) limiting burden and inconvenience (minimal data collection; web-based; secondary direct data capture through administrative databases); (2) minimal dataset for participants identified at high-risk of attrition (BAI, AQoL-6D); (3) monitoring data collection in real time; (4) education strategies on patient engagement and appreciation (e.g. reminders, website), (5) contact of dropouts; (6) information gathering for relocation; (7) financial compensation (20 $ for each follow up assessment); (8) treatment incentives with delayed-access to SMS for control arm to increase perceived health benefits. Follow up measures at 12- and 24-month are more susceptible to attrition (secondary analysis), and we will include a brief web-based interview that will foster patient engagement. Moreover, we will obtain a complete dataset from provincial administrative data on service utilization.

Assignment of interventions: Sequence generation, allocation concealment mechanism and implementation

Participants will be randomized based on stratification for study site, with random block sizes (2, 4, 6) to ensure a balance in the allocation for the strata. The randomization schema will be carried out using a code generated by the study statistician. Concealment will be maintained for the participants, research team, and staff. The REDCap computerized platform will only release the randomization code to the research coordinator based on the allocation sequence after verification of eligibility. The research coordinator will then enrol and assign participants to interventions.

The randomization sequence will be recorded with random codes (“A” and “B”) until the primary outcome analyses are concluded. Masking of trial participants and facilitators is not possible in this trial. Clinical evaluations at T3 and T4 will not be masked as we will address through qualitative interviews patient experience following the SMS intervention, or readiness to enroll intervention at T3 for the control group.

Sample size

Due to challenges in calculations for mixed regression models [68], we estimated sample size based on the baseline (T0) and post-treatment (T1) difference between groups for the primary outcome. The sample size was calculated using G*Power with the BAI based on an estimated effect size of the SMS + TAU intervention (Cohen’s d) of 0.32 (0.56 intra-group). This corresponds to a 7-point difference based on previous studies [51] that have established clinically significant change thresholds for the BAI [69]; such an effect size at post-treatment for symptom reduction is consistent with previous SMS studies for mental disorders [25, 35, 37, 38] as well as with pilot data of SMS (conservative estimates). The 3-point difference and SD for the TAU only group are conservative values based on our current data in a similar study with a TAU group [70]. A sample size of 155 individuals per group is therefore required to detect a 4-point (pooled SD: 12.5) pre-post treatment difference between SMS + TAU and TAU (i.e., a 7-point difference for SMS + TAU and 3-point for TAU) with an 80% power and α = 0.05. As there is a potential for intraclass correlations (ICC) in an individually randomized group treatment trial [71], we also estimated [72, 73] that based on a mixed model accounting for possible between-individual correlations within each intervention group (ICC of 0.02 for based on a similar study [70]), the power would be of at least 76%. With an adjustment for a conservative 25% attrition rate, the proposed sample size is 207 individuals for each treatment arm.

Statistical Analyses

Clinical outcomes

Statistical analysis will follow intent-to-treat principles. The primary outcome analysis will be performed at T1. The remaining analysis will be conducted considering all measures over time when all participants have completed the 12-month (T0 through T3) and 24-month follow up (T0 through T4). Primary question: A mixed model regression with the maximum-likelihood method will be performed to consider between- and within-subject variations in the analysis of the longitudinal effects of SMS + TAU compared to TAU on the primary outcome measure (BAI) at post-treatment (T1). To control for potential intra-group variability, random effects will be added on the participants nested in the SMS groups. Baseline clinical variables (e.g., anxiety disorders, comorbid depressive symptoms, psychotropic medication, psychotherapy) will be entered in the model as covariates. Analyses will be conducted with all available data without imputation, as estimation of parameters by maximum likelihood is considered adequate to address missing data as post-treatment in the multilevel model [74, 75].

For secondary questions, logistic regression models will be used to examine high-end functioning rates. The mixed model regression approach will be repeated on all data at the 12-month (T0 through T3) and 24-month (T0 through T4) follow-up, and will allow for the inclusion of patients with missing data at any of the follow-up assessments (T1,T2,T3,T4). Additionally, treatment effect sizes will be estimated with Cohen’s d. We will also conduct hypothesis-generating moderator and mediator analysis [76]. Moderation analyses will be performed for three sets of moderators, including clinical characteristics (e.g., anxiety disorders at baseline, anxiety severity, comorbid depression), previous treatments (psychotropic medication, psychotherapy) and sociodemographic characteristics (e.g., age group, sex, education level). Mediators will be examined for therapeutic alliance, group cohesion and adherence. Sensitivity analysis will be applied to examine the influence of missing data, and to document per protocol treatment effects (≥ 8 sessions completed).

Economic evaluation outcomes

The cost-effectiveness and cost-utility analysis will be carried out from health system and patient perspectives based on Canadian guidelines [77]. The 2-year costs considered will include all medical services and resources used during hospitalization, emergency department visits, outpatient visits, physician fees and outpatient medications. Patient out-of-pocket costs will include drug co-payments, payments to professionals not covered by the provincial public health insurance coverage, costs related to transportation and time spent by patients while seeking outpatient medical attention, as well as costs related to presenteeism and absenteeism [78]. Program costs associated with the training of facilitators and group meetings will include salaries, benefits, institutional overhead, and opportunity costs [79]. Generalized linear models (GLM) with log link and appropriate distribution (i.e., gamma) will be used to study the difference in costs (Beta estimates) as a function of the intervention (TAU vs SMS) while controlling for potential confounding study factors. Health outcomes will include symptom reduction (BAI) and health-related multi-attribute utility quality of life (AQoL-6D). The number of Anxiety-Free Days (AFD) will be calculated for each BAI scores with a value between 1 (‘anxiety free’) and 0 (‘fully symptomatic’) with linear interpolation to estimate the number of AFDs between baseline and follow up [80]. We will measure quality of life with the AQoL-6D to assess utility estimates [81]. For data analyses, repeated measures will be used to assess the difference (Beta estimates) in health outcomes as a function of the intervention and variables of interest. The incremental cost-effectiveness ratios (ICER) and incremental cost-utility ratios (ICUR) will be calculated based on beta estimates obtained. A discounting rate of 3.5% will be used for future values. We will carry out a sensitivity analysis for estimated values while considering a range of plausible values (95% CI). The ICUR will quantify the trade-off between costs and health-related quality of life.

Trial coordination

The trial coordinating center will be at Université de Sherbrooke. The executive committee will be composed of the principal investigators, the principal knowledge user (or representative), and research coordinator, with web meetings every two to three weeks throughout the four years of the project, an efficient management strategy for multi-centric trials. A Steering committee (i.e., co-investigators and co-knowledge users) will meet at strategic decision-making points throughout the trial.

Dissemination policy

We have adopted an integrated knowledge transfer (KT) strategy in which knowledge users are integral team members and participate in the complete research process. We have established a collaboration with the Relief community organization - involved in the design of the study, full members of the research team, and involved as knowledge users throughout all project phases. Other collaborators, including national, provincial, and regional decision makers, clinicians, and patient-partners for the advisory board, will also contribute specific expertise to integrated knowledge application. All knowledge users will be involved in making decisions concerning data collection, analyses, interpretation of results and knowledge transfer. The detailed KT plan for the study will include activities for the public, organizations/professionals, and scientific community. We will follow best practices recommended by scientific journals to determine authorship in publications.

Monitoring Steering committee

The study will be overseen by an independent data and safety monitoring committee (DSMC) consisting of three members with collective expertise in statistics, health services research, and anxiety disorders. No interim analyses will be conducted. The Data Safety and Monitoring Committee (DSMC) could request allocation data for a specific participant in case of an incident. The DSMC will monitor patient recruitment, retention and adverse events using a prespecified adverse event reporting protocol. The DSMC will also conduct a semi-annual audit.


To our knowledge, this is the first randomized controlled trial to examine the effectiveness of a structured group SMS program specifically developed for anxiety disorders as a complement to usual care. The SMS intervention developed by Relief for anxiety disorders could promote personal recovery through psychoeducation, strategies for day-to-day symptoms management, self-efficacy and empowerment. In response to the knowledge gap about the added value of structured group SMS for anxiety disorders in community-based care, we have established a strong collaboration between researchers and knowledge users to address this question. This partnership will help us provide relevant data to knowledge users to increase the uptake of trial results. In Québec, this group-based SMS program for anxiety disorders developed and implemented by Relief has demonstrated good uptake, even without evidence-based data regarding the benefits of SMS as a complementary intervention for individuals with anxiety disorders. Moderator and mediator analysis will also provide informative hypothesis generating data for future trials to examine sociodemographic and clinical characteristics associated with SMS effectiveness, but also with regards to previous treatment experience. As there is an overlap between SMS and low-intensity psychotherapy interventions, this may provide interesting health services research hypothesis to inform future studies. Therefore, we will conduct this pragmatic randomized controlled trial to document potential benefits of SMS for individuals experiencing anxiety disorders with extensive patient-reported outcome measures as well as with health system data to inform policy makers, health care managers, clinicians, and patients on the potential impact of the intervention. The Relief community organization is committed to submitting the added value of the group SMS program to a rigorous evaluation, to share results to partner organizations as well as to review the methodology and content of the SMS intervention in case of negative results. A rigorous evaluation of the effectiveness and cost-effectiveness of SMS as a complement to treatment-as-usual could have a significant impact on evidence-based decision-making of stakeholders considering the upward emphasis on a personal recovery-based approach in mental health.

Availability of data and materials

The datasets generated during the current study will not be publicly available due to ethics committee regulations, but will be available from the corresponding author on reasonable request.



Anxiety-free days


Assessment of Quality of Life – 6D


Beck Anxiety Inventory


Quebec emergency department database


Cognitive behavioural therapy


Centre de recherche du Centre Hospitalier Universitaire de Sherbrooke


Diagnostic and Statistical Manual of Mental Disorders, 5th edition


Data and safety monitoring committee


Generalised Anxiety Disorder Questionnaire


Gross Cohesion Scale


Generalized linear models


Incremental cost-effectiveness ratios


Incremental cost-utility ratios


Knowledge transfer


Mental Health Self-Management Questionnaire


Mini International Neuropsychiatric Interview


Panic Disorder Severity Scale Self Report


Patient Health Questionnaire


Régie de l’assurance-maladie du Québec


Recovery Assessment Scale – revised


Randomized controlled trial


Self-management support


Social Phobia Inventory




Working Alliance Inventory


  1. Katzman MA, Bleau P, Blier P, Chokka P, Kjernisted K, Van Ameringen M, et al. Canadian clinical practice guidelines for the management of anxiety, posttraumatic stress and obsessive-compulsive disorders. BMC Psychiatry. 2014;14(Suppl 1):S1–S83.

    Article  PubMed  PubMed Central  Google Scholar 

  2. American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 5th ed. Arlington: American Psychiatric Publishing; 2013.

    Book  Google Scholar 

  3. Barlow DH. Anxiety and its disorders. The nature and treatment of anxiety and panic. NY: The Guilford Press; 2002.

    Google Scholar 

  4. Kessler RC, Ruscio AM, Shear K, Wittchen HU. Epidemiology of anxiety disorders. Curr Top Behav Neurosci. 2010;2:21–35.

    Article  PubMed  Google Scholar 

  5. Brown TA, Campbell LA, Lehman CL, Grisham JR, Mancill RB. Current and lifetime comorbidity of the DSM-IV anxiety and mood disorders in a large clinical sample. J Abnorm Psychol. 2001;110(4):585–99.

    CAS  Article  PubMed  Google Scholar 

  6. Lamers F, van Oppen P, Comijs HC, Smit JH, Spinhoven P, van Balkom AJ, et al. Comorbidity patterns of anxiety and depressive disorders in a large cohort study: the Netherlands Study of Depression and Anxiety (NESDA). J Clin Psychiat. 2011;72(3):341–8.

    Article  Google Scholar 

  7. Conway KP, Compton W, Stinson FS, Grant BF. Lifetime comorbidity of DSM-IV mood and anxiety disorders and specific drug use disorders: results from the National Epidemiologic Survey on Alcohol and Related Conditions. J Clin Psychiat. 2006;67(2):247–57.

    CAS  Article  Google Scholar 

  8. Roy-Byrne PP, Davidson KW, Kessler RC, Asmundson GJ, Goodwin RD, Kubzansky L, et al. Anxiety disorders and comorbid medical illness. Gen Hosp Psychiatry. 2008;30(3):208–25.

    Article  PubMed  Google Scholar 

  9. Kroenke K, Spitzer RL, Williams JB, Monahan PO, Lowe B. Anxiety disorders in primary care: prevalence, impairment, comorbidity, and detection. Ann Intern Med. 2007;146(5):317–25.

    Article  PubMed  Google Scholar 

  10. Greenberg PE, Sisitsky T, Kessler RC, Finkelstein SN, Berndt ER, Davidson JR, et al. The economic burden of anxiety disorders in the 1990s. J Clin Psychiat. 1999;60(7):427–35.

    CAS  Article  Google Scholar 

  11. McLean CP, Asnaani A, Litz BT, Hofmann SG. Gender differences in anxiety disorders: prevalence, course of illness, comorbidity and burden of illness. J Psychiatr Res. 2011;45(8):1027–35.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Wiebenga JXM, Dickhoff J, Merelle SYM, Eikelenboom M, Heering HD, Gilissen R, et al. Prevalence, course, and determinants of suicide ideation and attempts in patients with a depressive and/or anxiety disorder: A review of NESDA findings. J Affect Disord. 2021;283:267–77.

    Article  PubMed  Google Scholar 

  13. Roberge P, Fournier L, Duhoux A, Nguyen CT, Smolders M. Mental health service use and treatment adequacy for anxiety disorders in Canada. Soc Psychiatry Psychiatr Epidemiol. 2011;46(4):321–30.

    Article  PubMed  Google Scholar 

  14. Baxter AJ, Vos T, Scott KM, Ferrari AJ, Whiteford HA. The global burden of anxiety disorders in 2010. Psychol Med. 2014;44(11):2363–74.

    CAS  Article  PubMed  Google Scholar 

  15. National Institute for Health and Care Excellence (NICE). Common mental health disorders. Identification and pathway to care. London: The British Psychological Society and The Royal College of Psychiatrists; 2011.

    Google Scholar 

  16. Durham RC, Higgins C, Chambers JA, Swan JS, Dow MG. Long-term outcome of eight clinical trials of CBT for anxiety disorders: symptom profile of sustained recovery and treatment-resistant groups. J Affect Disord. 2012;136(3):875–81.

    Article  PubMed  Google Scholar 

  17. Yonkers KA, Bruce SE, Dyck IR, Keller MB. Chronicity, relapse, and illness-course of panic disorder, social phobia, and generalized anxiety disorder: findings in men and women from 8 years of follow-up. Depress Anxiety. 2003;17(3):173–9.

    Article  PubMed  Google Scholar 

  18. van Dis EAM, van Veen SC, Hagenaars MA, Batelaan NM, Bockting CLH, van den Heuvel RM, et al. Long-term Outcomes of Cognitive Behavioral Therapy for Anxiety-Related Disorders: A Systematic Review and Meta-analysis. JAMA Psychiatry. 2020;77(3):265–73.

    Article  PubMed  Google Scholar 

  19. Batelaan NM, Bosman RC, Muntingh A, Scholten WD, Huijbregts KM, van Balkom AJLM. Risk of relapse after antidepressant discontinuation in anxiety disorders, obsessive-compulsive disorder, and post-traumatic stress disorder: systematic review and meta-analysis of relapse prevention trials. BMJ. 2017;358:j3927.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Levy HC, O'Bryan EM, Tolin DF. A meta-analysis of relapse rates in cognitive-behavioral therapy for anxiety disorders. J Anxiety Disord. 2021;81:102407.

    Article  PubMed  Google Scholar 

  21. Rodriguez BF, Weisberg RB, Pagano ME, Bruce SE, Spencer MA, Culpepper L, et al. Characteristics and predictors of full and partial recovery from generalized anxiety disorder in primary care patients. J Nerv Ment Dis. 2006;194(2):91–7.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Kelly KM, Mezuk B. Predictors of remission from generalized anxiety disorder and major depressive disorder. J Affect Disord. 2017;208:467–74.

    Article  PubMed  Google Scholar 

  23. Coulombe S, Radziszewski S, Trepanier SG, Provencher H, Roberge P, Hudon C, et al. Mental health self-management questionnaire: Development and psychometric properties. J Affect Disord. 2015;181:41–9.

    Article  PubMed  Google Scholar 

  24. Coulombe S, Radziszewski S, Meunier S, Provencher H, Hudon C, Roberge P, et al. Profiles of recovery from mood and anxiety disorders: A person-centered exploration of people's engagement in self-management. Front Psychol. 2016;7:584.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Houle J, Gascon-Depatie M, Belanger-Dumontier G, Cardinal C. Depression self-management support: a systematic review. Patient Educ Couns. 2013;91(3):271–9.

    Article  PubMed  Google Scholar 

  26. Anthony WA. Recovery from mental illness: The guiding vision of the mental health service system in the 1990s. Psychosoc Rehabil J. 1993;16(4):11–23.

    Google Scholar 

  27. Coleman K, Austin BT, Brach C, Wagner EH. Evidence on the Chronic Care Model in the new millennium. Health Aff. 2009;28(1):75–85.

    Article  Google Scholar 

  28. Corrigan PW. Person-centered care for mental illness: The evolution of adherence and self-determination. Washington, DC: American Psychological Association; 2015.

    Book  Google Scholar 

  29. Panagioti M, Richardson G, Small N, Murray E, Rogers A, Kennedy A, et al. Self-management support interventions to reduce health care utilisation without compromising outcomes: a systematic review and meta-analysis. BMC Health Serv Res. 2014;14:356.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Mental Health Commission of Canada. Guidelines for recovery-oriented practice. Ottawa: Mental Health Commission of Canada; 2015.

    Google Scholar 

  31. Villaggi B, Provencher H, Coulombe S, Meunier S, Radziszewski S, Hudon C, et al. Self-management strategies in recovery from mood and anxiety disorders. Glob Qual Nurs Res. 2015;2:1–13.

    Article  Google Scholar 

  32. Brady TJ, Murphy L, O’Colmain BJ, Beauchesne D, Daniels B, Greenberg M, et al. A Meta-Analysis of Health Status, Health Behaviors, and Health Care Utilization Outcomes of the Chronic Disease Self-Management Program. Prev Chronic Dis. 2013;10:120112.

    Article  PubMed  Google Scholar 

  33. Cook JA, Copeland ME, Hamilton MM, Jonikas JA, Razzano LA, Floyd CB, et al. Initial outcomes of a mental illness self-management program based on wellness recovery action planning. Psychiatr Serv. 2009;60(2):246–9.

    Article  PubMed  Google Scholar 

  34. Lorig KR, Ritter PL, Pifer C, Werner P. Effectiveness of the chronic disease self-management program for persons with a serious mental illness: a translation study. Community Ment Health J. 2014;50(1):96–103.

    Article  PubMed  Google Scholar 

  35. Houle J, Gauvin G, Collard B, Meunier S, Frasure-Smith N, Lespérance F, et al. Empowering Adults in Recovery from Depression: A Community- Based Self-Management Group Program. Can J Commun Ment Health. 2016;35(2):55–68.

    Article  Google Scholar 

  36. Lam RW, McIntosh D, Wang J, Enns MW, Kolivakis T, Michalak EE, et al. Canadian Network for Mood and Anxiety Treatments (CANMAT) 2016 Clinical Guidelines for the Management of Adults with Major Depressive Disorder: Section 1. Disease Burden and Principles of Care. Can J Psychiatr. 2016;61(9):510–23.

    Article  Google Scholar 

  37. Cook JA, Copeland ME, Floyd CB, Jonikas JA, Hamilton MM, Razzano L, et al. A randomized controlled trial of effects of Wellness Recovery Action Planning on depression, anxiety, and recovery. Psychiatr Serv. 2012;63(6):541–7.

    Article  PubMed  Google Scholar 

  38. Zimmermann T, Puschmann E, van den Bussche H, Wiese B, Ernst A, Porzelt S, et al. Collaborative nurse-led self-management support for primary care patients with anxiety, depressive or somatic symptoms: Cluster-randomised controlled trial (findings of the SMADS study). Int J Nurs Stud. 2016;63:101–11.

    Article  PubMed  Google Scholar 

  39. Zoun MHH, Koekkoek B, Sinnema H, van der Feltz-Cornelis CM, van Balkom AJLM, Schene AH, et al. Effectiveness of a self-management training for patients with chronic and treatment resistant anxiety or depressive disorders on quality of life, symptoms, and empowerment: results of a randomized controlled trial. BMC Psychiatry. 2019;19(1):46.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Chan AW, Tetzlaff JM, Altman DG, Laupacis A, Gotzsche PC, Krleza-Jeric K, et al. SPIRIT 2013 statement: defining standard protocol items for clinical trials. Ann Intern Med. 2013;158(3):200–7.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Sheehan DV, Lecrubier Y, Sheehan KH, Amorim P, Janavs J, Weiller E, et al. The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J Clin Psychiatry. 1998;59(Suppl 20):22–33 quiz 4–57.

    PubMed  Google Scholar 

  42. Cyr C, McKee H, O’Hagan M, Priest R, for the Mental Health Commission of Canada. Making the case for peer support: Report to the Peer Support Project Committee of the Mental Health Commission of Canada(2010 first edition / 2016 second edition). Available from: Retrieved from:

  43. Mead S, Hilton D, Curtis L. Peer support: a theoretical perspective. Psychiatr Rehabil J. 2001;25(2):134–41.

    CAS  Article  PubMed  Google Scholar 

  44. Solomon P. Peer support/peer provided services underlying processes, benefits, and critical ingredients. Psychiatr Rehabil J. 2004;27(4):392–401.

    Article  PubMed  Google Scholar 

  45. Spitzer RL, Kroenke K, Williams JB, Lowe B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med. 2006;166(10):1092–7.

    Article  PubMed  Google Scholar 

  46. Connor KM, Davidson JR, Churchill LE, Sherwood A, Foa E, Weisler RH. Psychometric properties of the Social Phobia Inventory (SPIN). New self-rating scale. Br J Psychiatry. 2000;176:379–86.

    CAS  Article  PubMed  Google Scholar 

  47. Radomsky AS, Ashbaugh AR, Saxe ML, Ouimet AJ, Golden ER, Lavoie SL, et al. Psychometric Properties of the French and English Versions of the Social Phobia Inventory. Can J Behav Sci. 2006;38(4):354–60.

    Article  Google Scholar 

  48. Houck PR, Spiegel DA, Shear MK, Rucci P. Reliability of the self-report version of the panic disorder severity scale. Depress Anxiety. 2002;15(4):183–5.

    Article  PubMed  Google Scholar 

  49. Beck AT, Epstein N, Brown G, Steer RA. An inventory for measuring clinical anxiety: psychometric properties. J Consult Clin Psychol. 1988;56(6):893–7.

    CAS  Article  PubMed  Google Scholar 

  50. Freeston MH, Ladouceur R, Thibodeau N, Gagnon F, Rheaume J. The Beck Anxiety Inventory. Psychometric properties of a French translation. Encephale. 1994;20(1):47–55.

    CAS  PubMed  Google Scholar 

  51. Oei TP, McAlinden NM. Changes in quality of life following group CBT for anxiety and depression in a psychiatric outpatient clinic. Psychiatry Res. 2014;220(3):1012–8.

    Article  PubMed  Google Scholar 

  52. Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001;16(9):606–13.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  53. Richardson JRJ, Peacock SJ, Hawthorne G, Iezzi A, Elsworth G, Day NA. Construction of the descriptive system for the assessment of quality of life AQoL-6D utility instrument. Health Qual Life Outcomes. 2012;10(1):38.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Bayliss EA, Ellis JL, Steiner JF. Subjective assessments of comorbidity correlate with quality of life health outcomes: initial validation of a comorbidity assessment instrument. Health Qual Life Outcomes. 2005;3:51.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Poitras M-E, Fortin M, Hudon C, Haggerty J, Almirall J. Validation of the disease burden morbidity assessment by self-report in a French-speaking population. BMC Health Serv Res. 2012;12:35.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Corrigan PW, Giffort D, Rashid F, Leary M, Okeke I. Recovery as a psychological construct. Community Ment Health J. 1999;35(3):231–9.

    CAS  Article  PubMed  Google Scholar 

  57. Giffort D, Schmook A, Woody C, Vollendorf C, Gervain M. Construction of a Scale to Measure Consumer Recovery. Springfield: Department of Health and Human Services, Office of Mental Health; 1995.

    Google Scholar 

  58. Salzer MS, Brusilovskiy E. Advancing recovery science: reliability and validity properties of the Recovery Assessment Scale. Psychiatr Serv. 2014;65(4):442–53.

    Article  PubMed  Google Scholar 

  59. Pelletier J-F, Corbière M, Lecomte T, Briand C, Corrigan P, Davidson L, et al. Citizenship and recovery: two intertwined concepts for civic-recovery. BMC Psychiatry. 2015;15(1):37.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Horvath AO, Greenberg LS. Development and validation of the Working Alliance Inventory. J Couns Psychol. 1989;36(2):223–33.

    Article  Google Scholar 

  61. Corbiere M, Bisson J, Lauzon S, Ricard N. Factorial validation of a French short-form of the Working Alliance Inventory. Int J Methods Psychiatr Res. 2006;15(1):36–45.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Tracey TJ, Kokotovic AM. Factor structure of the working alliance inventory. Psychol Assess. 1989;1(3):207–10.

    Article  Google Scholar 

  63. Stokes JP. Toward an understanding of cohesion in personal change groups. Int J Group Psychother. 1983;33:449–67.

    CAS  Article  PubMed  Google Scholar 

  64. Creswell J, Plano Clark VL. Designing and Conducting Mixed Methods Research. 3rd ed. Thousand Oaks: SAGE Publications; 2017.

    Google Scholar 

  65. Patton MQ. Qualitative Research & Evaluation Methods. 4th ed. Thousand Oaks: SAGE Publications; 2014.

    Google Scholar 

  66. Miles MB, Huberman AM, Saldana J. Qualitative Data Analysis: a Methods Sourcebook. 3rd ed. Thousand Oaks: SAGE Publications; 2014.

    Google Scholar 

  67. QSR International Pty Ltd. NVivo (Version 12).2018.

    Google Scholar 

  68. Tango T. On the repeated measures designs and sample sizes for randomized controlled trials. Biostatistics. 2016;17(2):334–49.

    Article  PubMed  Google Scholar 

  69. Jacobson NS, Truax P. Clinical significance: a statistical approach to defining meaningful change in psychotherapy research. J Consult Clin Psychol. 1991;59(1):12–9.

    CAS  Article  PubMed  Google Scholar 

  70. Roberge P, Provencher MD, Gaboury I, Gosselin P, Vasiliadis HM, Benoit A, et al. Group transdiagnostic cognitive-behavior therapy for anxiety disorders: a pragmatic randomized clinical trial. Psychol Med. 2020:1–11.

  71. Pals SL, Murray DM, Alfano CM, Shadish WR, Hannan PJ, Baker WL. Individually randomized group treatment trials: a critical appraisal of frequently used design and analytic approaches. Am J Public Health. 2008;98(8):1418–24.

    Article  PubMed  PubMed Central  Google Scholar 

  72. Hooper R, Teerenstra S, de Hoop E, Eldridge S. Sample size calculation for stepped wedge and other longitudinal cluster randomised trials. Stat Med. 2016;35(26):4718–28.

    Article  PubMed  Google Scholar 

  73. The Shiny CRT Calculator: power and sample size for cluster randomised trials. Accessed 27 Oct 2021.

  74. van Buuren S. In: Hall C, editor. Flexible Imputation of Missing Data. Boca Raton: Taylor & Francis Group; 2012. 297 p.

    Chapter  Google Scholar 

  75. Little RJ, Rubin DB. Statistical analysis with missing data. 3rd ed. Hoboken: John Wiley & Sons; 2019.

  76. Pincus T, Miles C, Froud R, Underwood M, Carnes D, Taylor SJC. Methodological criteria for the assessment of moderators in systematic reviews of randomised controlled trials: a consensus study. BMC Med Res Methodol. 2011;11(1):14.

    Article  PubMed  PubMed Central  Google Scholar 

  77. Canadian Agency for Drugs and Technologies in Health (CADTH). Canadian guidelines for the economic evaluation of health technologies. 3rd ed. Ottawa: The Canadian Agency for Drugs and Technologies in Health (CADTH); 2006.

  78. Vasiliadis H-M, Latimer E, Dionne PA, Préville M. The costs associated with antidepressant use in depression and anxiety in community-living older adults. Can J Psychiatr. 2013;58(4):201–9.

    Article  Google Scholar 

  79. Vasiliadis H-M, Briand C, Lesage A, Reinharz D, Stip E, Nicole L, et al. Health care resource use associated with integrated psychological treatment. J Ment Health Policy Econ. 2006;9(4):201–7.

    PubMed  Google Scholar 

  80. Lave JR, Frank RG, Schulberg HC, Kamlet MS. Cost-effectiveness of treatments for major depression in primary care practice. Arch Gen Psychiatry. 1998;55(7):645–51.

    CAS  Article  PubMed  Google Scholar 

  81. Richardson J, Khan MA, Iezzi A, Maxwell A. Comparing and explaining differences in the magnitude, content, and sensitivity of utilities predicted by the EQ-5D, SF-6D, HUI 3, 15D, QWB, and AQoL-8D multiattribute utility instruments. Med Decis Mak. 2015;35(3):276–91.

    Article  Google Scholar 

Download references


Thank you to Bruno Collard (2009-2019) and Danielle Germain, respectively past and current clinical director at Relief, for their contribution to the trial protocol. Thank you to Pierre Cardinal, patient partner, for sharing advice on trial development.


The Canadian Institutes of Health Research funded this study (CIHR grant #169163). The CIHR has no role in the design of this study and will not have any role during its execution, analyses, interpretation of the data, or decision to submit results. Relief will provide in-kind support to the trial and will participate in specific aspects of the execution of the trial, including training of facilitators and management of the SMS platform. Relief will not be involved in the decision to submit results for publication.

Author information

Authors and Affiliations



PR and JH had the initial idea for this study, and the SMS intervention was developed by JH and Relief. PR prepared the first draft of the paper; JH, JRP and SC revised the first version of the study protocol thoroughly. All authors, including PR, JH, JRP, SC, AB, PB, FCL, MD, MSD, CH, MDP and HMV, have contributed to the design of the clinical trial, and have also critically revised and approved the final manuscript.

Corresponding author

Correspondence to Pasquale Roberge.

Ethics declarations

Ethics approval and consent to participate

Study approval was given on September 27th, 2021, by the institutional Research Ethics Board (Centre intégré universitaire de santé et de services sociaux de l’Estrie – Centre hospitalier universitaire de Sherbrooke, reference number 2022–4191). The REB approved online and verbal consent procedures given the Internet-based data collection strategies; informed consent material is available on request from the corresponding author.

Consent for publication

Not applicable.

Competing interests

Relief is a non-profit organization whose mission is to support people living with anxiety, depression or bipolarity, and their loved ones, so they can keep moving forward. Relief has developed the group self-management support intervention for anxiety disorders.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Roberge, P., Houle, J., Provost, JR. et al. A pragmatic randomized controlled trial of a group self-management support program versus treatment-as-usual for anxiety disorders: study protocol. BMC Psychiatry 22, 135 (2022).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI:


  • Anxiety disorders
  • Self-management support
  • Pragmatic trial
  • Group intervention
  • Web-based intervention
  • Transdiagnostic