Effectiveness of Guided Self-Help Versus Internet-Delivered or Face-to-Face Cognitive Behavioral Therapy for Depression and Anxiety: Four Parallel Randomized Controlled Non-Inferiority Trials of the Finnish First-Line Therapies – Initiative (FLT-Step)

Effectiveness of Guided Self-Help Versus Internet-Delivered or Face-to-Face Cognitive Behavioral Therapy for Depression and Anxiety: Four Parallel Randomized Controlled Non-Inferiority Trials of the Finnish First-Line Therapies – Initiative (FLT-Step) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Study protocol Effectiveness of Guided Self-Help Versus Internet-Delivered or Face-to-Face Cognitive Behavioral Therapy for Depression and Anxiety: Four Parallel Randomized Controlled Non-Inferiority Trials of the Finnish First-Line Therapies – Initiative (FLT-Step) Eeva-Eerika Helminen, Suoma E. Saarni, Kasperi Mikkonen, M. Katariina Mattila, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7039628/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 11 Mar, 2026 Read the published version in BMC Psychiatry → Version 1 posted 13 You are reading this latest preprint version Abstract Background Low-intensity cognitive behavioral therapy (CBT) based guided self-help (GSH) and therapist-guided internet-delivered CBT (iCBT) have demonstrated equivalent effectiveness and superior cost-efficiency compared to traditional face-to-face CBT (fCBT) for treating depression and anxiety. This study aims to address critical gaps in the current understanding of the effectiveness and cost-effectiveness of various CBT interventions for depression and anxiety within a stepped care model. Methods This paper outlines FLT-step, a multi-center randomized controlled trial (RCT) study with four parallel study protocols for examining widely used CBT interventions in public healthcare using a stepped care approach. The objective is to compare the effectiveness and cost-effectiveness of three treatment approaches for depression (protocol 1) and anxiety (protocol 2) in a non-inferiority setting within the Finnish public healthcare: A) a stepped care model (GSH followed by fCBT for non-responders), B) fCBT, and C) therapist-guided iCBT. The non-inferiority margin was based on patient-detectable improvement and is set at 1.7 points on the Patient Health Questionnaire (PHQ-9, protocol 1) and 1.5 points on the Generalized Anxiety Disorder 7-item scale (GAD-7, protocol 2). We plan to recruit 948 adults (≥ 16 years old) with depression (PHQ-9 ≥ 10 p) and 948 adults with anxiety (GAD-7 ≥ 10 p). A randomized sub study will examine the effect of waiting time (≤4 or ≥ 5 weeks) for the treatment outcomes of depression (n = 115, protocol 3) or anxiety (n = 115, protocol 4), comparing the stepped care model (A) and fCBT (B). In all four RCTs, the primary outcome measures are the within-individual change in depression (PHQ-9) or anxiety (GAD-7) symptoms at six months. Secondary outcomes include wellbeing, work and social ability, costs associated with illness, and quality of life. The follow-up is planned to span up to 20 years. Finnish national registry data will be used to supplement participant data and create population-matched controls to evaluate whether the interventions can prevent clinical episodes, reduce long-term societal costs, and decrease somatic morbidity. Discussion This extensive RCT aims to deliver new insights into comparative effectiveness and cost-effectiveness of widely utilized low-intensity CBT treatments for depression and anxiety, and the impact of waiting times on outcomes. Trial Registrations (Registration date): ISRCTN14296278 (18 Sep 2024), ISRCTN63914711 (8 Oct 2024), ISRCTN10064801 (20 Sep 2024), ISRCTN14990924 (8 Oct 2024) Issue date: 3 Jul 2025 Eeva-Eerika Helminen and Suoma E. Saarni are equal first author contributions Depression Anxiety Randomized controlled trial Cognitive behavioral therapy Guided self-help Internet-delivered CBT Stepped care Cost-effectiveness Waiting-time Figures Figure 1 Figure 2 Figure 3 Background Mental disorders are at the core of the public health care crisis. Given that depression and anxiety are the most common mental disorders in western countries (1), it is crucial to effectively organize the management of these disorders within primary care settings. An increasing amount of research supports the cost-effectiveness of psychotherapeutic interventions for depression and anxiety disorders (2–5). Cognitive-behavioral therapy (CBT) has been found effective in the treatment of depression (6,7), subclinical depression (8), and anxiety disorders (9), but access to evidence-based treatments in primary care settings is often inadequate, also in Finland. Furthermore, along with conventional face-to-face CBT (fCBT), low-intensity CBT-based guided self-help (GSH) (6,10,11) and guided internet delivered CBT (iCBT) (12,13) have been reported to be as effective as and more affordable than the traditional forms of psychotherapeutic treatment for depression and anxiety. The use of GSH, fCBT and iCBT as a part of a stepped care model could provide an applicable solution to make evidence-based treatment accessible in public healthcare. In stepped care, patients are treated at the lowest appropriate service level and stepped up only when clinically needed. In recent years, attention has been directed toward identifying the most effective strategies for establishing an optimally cost-effective sequence and equilibrium among various steps (14–17). However, these optimization efforts tend to focus on immediate gains, often assuming that similar short-term average efficacies will result in analogous long-term outcomes. Thus, thoroughly evaluating the non-inferiority, cost-effectiveness, and long-term health economic impacts of three presumably equally effective treatments (GSH, fCBT, iCBT), each with varying costs, within a stepped-care model, can potentially provide valuable information for policymakers to optimize resource allocation and improve accessibility. In publicly funded healthcare systems, the goal is to optimize the cost-effectiveness on system level while ensuring access to necessary services to all. This calls for a modified stepped-care model that integrates a stratified approach, allowing patients to skip steps based on professional assessments of their individual needs. Modified stepped care has been implemented since 2008 in the British NHS Talking Therapies program, previously known as IAPT (Improving Access to Psychological Treatments) (18). Subsequently, similar programs have been piloted and implemented in other countries including Norway (19), Ireland (20), France (21), Spain (22), and Australia (23) in various clinical settings including communities, schools as well as private and public healthcare services. In Finland, a stepped-care model has been launched through the First-line Therapies initiative (FLT), a comprehensive nationwide program aimed at providing early, evidence-based treatment for common mental health problems. This initiative also focuses on systematizing pre-treatment assessments within the national public health care system. In the British NHS Talking Therapies program, longer waiting times to treatment have been linked to lower recovery rates within service-providing units (24). Consequently, addressing delays in these low-cost, easily accessible treatments is crucial for enhancing the cost-effectiveness of stepped-care systems at a societal level. This study protocol details the FLT-Step trial (Effectiveness of Psychosocial Interventions for Depression and Anxiety in the Stepped Care Model of the Finnish First-Line Therapies), which comprises four parallel multicenter randomized controlled trials (RCTs). The protocol is described in adherence to the SPIRIT statement (25). Methods/Design This study consists of four parallel study protocols for four multicenter, randomized controlled trials (RCTs) aimed at treating depression or anxiety symptoms with CBT interventions in public healthcare using a stepped care approach. Primary Hypothesis The primary hypotheses of protocols 1 (main study, depression) and 2 (main study, anxiety): A stepped care model, which involves sequential GSH followed by fCBT for non-responders, and guided iCBT are both non-inferior to fCBT for treating clinical depression and anxiety symptoms. Protocols 3 (substudy, depression) and 4 (substudy, anxiety): Longer waiting time for the treatment is associated with poorer treatment response in depression (protocol 3) or anxiety (protocol 4) symptoms in both study interventions: A) a stepped care model (sequential GSH followed by fCBT for non-responders) and B) direct admission to fCBT. In addition to hypothesis testing, we strived to estimate the quantitative causal effect of waiting time on treatment efficacy, as only observational estimates exist thus far to our knowledge (see power calculations - section). The primary hypothesis in all four protocols will be tested at the primary outcome measurement point, which is six months after enrollment, for patients with a baseline score of ≥10 p on either the Patient Health Questionnaire (26) (PHQ-9, protocols 1 and 3) or Generalized Anxiety Disorder 7-item Scale (27) (GAD-7, protocols 2 and 4). The treatment response is assessed with the within-individual change in depression/anxiety symptoms measured by the PHQ-9/GAD-7, depending on the primary symptom being studied. Secondary hypotheses protocols 1, 2, 3 and 4 If non-inferiority is demonstrated, effectiveness of the stepped care model (sequential GSH followed by fCBT for non-responders) is superior compared to directly admitting patients to fCBT when treating 1) clinical depression symptoms (baseline score of ≥10 p on PHQ-9) or 2) anxiety symptoms (baseline score of ≥10 p on GAD-7), assessed at six months after enrollment. Stepped care is more cost-effective than directing all patients with depression symptoms (baseline score ≥10 p on PHQ-9) or anxiety symptoms (baseline score ≥10 p on GAD-7) directly to fCBT assessed six months after enrollment. iCBT is more cost-effective than directing all patients with depression symptoms (baseline score ≥10 p on PHQ-9) or anxiety symptoms (baseline score ≥10 p on GAD-7) directly to fCBT (protocols 1 and 2 only) assessed six months after enrollment. Data collected by the Finnish Therapy Navigator (28) (FTN), a digital tool to help assess individual needs and symptom profile for psychotherapy, can be used to predict responses to treatment by using a multivariate model (an ability that would allow for treatment personalization) (29). All treatment approaches studied are cost-saving in the long term compared to matched population controls, when direct and indirect health care, social care, employment, and societal costs are considered (see section “health economic evaluation”). Patients seeking treatment with subclinical depressive symptoms (baseline score of 5–9 on the PHQ-9) benefit from the studied treatment approaches, in terms of reduced risk of developing clinical episodes, reduced total long-term societal costs, and decreased somatic morbidity. Longer waiting times for the study treatments are associated with poorer overall long-term outcomes when direct and indirect health care, social care, employment, and societal costs are considered (protocols 3 and 4 only, see section “health economic evaluation”). Design Protocols 1 (depression) and 2 (anxiety) each include three treatment arms of equal sample size. The following treatment approaches are included in research arms: A) GSH + fCBT (sequential GSH followed by fCBT for non-responders, planned n=316), B) fCBT (planned n=316), and C) guided iCBT (planned n=316). Non-responder is a participant who still scores above the clinical cut-off on the respective symptom measure i.e. PHQ-9 ≥10 p (30) or GAD-7 ≥10 p (31). The treatment sites participating in this trial are in public primary mental health care services in Southern and Western Finland across six wellbeing service counties (population approx. 3,4 million), covering 60% of the total population of Finland. Alongside the RCTs of protocols 1 and 2, we will collect a convenience sample of patients with subclinical symptoms of depression (PHQ-9 5–9 p) or anxiety (GAD-7 5–9 p) to receive treatment in all three treatment arms (A, B or C). Protocols 3 (depression, planned n=115) and 4 (anxiety, planned n=115) concentrate on a substudy examining the impact of waiting time, featuring two equally sized treatment arms: A) GSH followed by fCBT for non-responders, and B) fCBT. Participants in both arms are randomly assigned (1:1) to two groups: I) those commencing treatment within 4 weeks, and II) those starting treatment after 5 weeks or more. These sub studies are being carried out in the Pirkanmaa wellbeing service county, which has a population of approximately 540,000, located in Central Finland. For all study participants, including those involving patients seeking help for subclinical symptoms, the study data will be combined with data from Finnish national registries. Matched population controls will be identified to conduct a comprehensive registry study among these patients. The flow of patients through the protocols 1-4 is presented in Figure 1. Recruitment and patients To achieve maximal external validity in the study, all patients evaluated by a professional in primary care as suitable for the studied treatments for depression or anxiety (e.g., GSH, iCBT, and fCBT) are invited to participate. The FTN is used to assess treatment needs as part of routine practice by the trained health care professional responsible for clinical signposting. If the patient is interested in participating in this trial, the clinician will schedule an appointment with a research nurse. During this appointment, the research nurse will provide information about the study, review the inclusion and exclusion criteria, and give the patient a written study information sheet. The inclusion and exclusion criteria used in the study are described in Table 1. Patients deemed eligible for the study will be asked to provide informed consent to participate. If the patient does not wish to participate, permission to use the information gathered in the FTN during the prescreening process of the study is requested. This approach ensures a more comprehensive understanding of the representativeness of the sample of primary care patients, thereby enhancing the overall quality and applicability of the study findings. Table 1. Inclusion and exclusion criteria in the FLT-Step trial (protocols 1–4). Inclusion Criteria Exclusion Criteria ≥16 years of age Suitable for studied treatments (GSH, iCBT or fCBT intervention) for depression/anxiety (cf. exclusions) Depression: PHQ ≥10 p Anxiety: GAD-7 ≥10 p General exclusion criteria for studied treatments (i.e. recommended more intensive or other treatment forms) Serious suicidal thoughts, plans or any self-harming act or suicidal attempt within the past 2 months. Ongoing other psychological treatment for depression and/or anxiety Cognitive impairment Inability to speak, read and write Finnish Currently symptomatic psychotic illness or bipolar disorder Drug or alcohol dependence In a sub-clinical cconvenience sample adjacent to protocols 1 and 2: Depression: PHQ-9 5–9 p Anxiety: GAD-7 5–9 p GSH guided self-help; iCBT Internet-based cognitive-behavioral therapy; fCBT face-to-face cognitive-behavioral therapy; PHQ-9 Patient Health Questionnaire; GAD-7 Generalized Anxiety Disorder 7-item scale Power calculations Protocols 1 and 2 Three types of power calculations were essential to these protocols. First, we tested the hypothesis that difference between PHQ-9 score change in the stepped care model (GSH + fCBT) and fCBT groups is no greater than a margin of 1.7 points, which amounts to the estimated threshold at which patients with moderate-severity symptoms can detect the difference between “feeling the same” and “feeling better” after a treatment (32). Second, the analogous margin for GAD-7 was 1.5 points. This threshold is slightly more stringent (leads to larger sample-size requirements) than a previously used statistically motivated margin (33), but more clinically meaningful in our opinion. We computed statistical power to detect non-inferiority (34) assuming no efficacy difference exists between the treatment arms and assuming the relevant clinical population standard deviation of PHQ-9 is 6 points and that of GAD-7 is 3.6 points, as previously observed in Finnish context (35,36). Third, we computed statistical power to detect superiority between treatment groups when their standardized mean difference is d = 0.3 (i.e., small but larger than the standardized subjective-difference detection threshold of PHQ-9 from above 1.7/6 ≈ 0.28). We used significance level α = 0.025 for one-sided non-inferiority test, which corresponds to 95% two-sided confidence interval being wholly on the better side of the margin. We used level α = 0.05 in the two-sided tests of superiority. Figure 2 shows the results from the first three statistical power calculations. We observed that a treatment group size 263 leads to at least 90% statistical power for all the three types of study questions. We inflated this estimate by 20% to allow for some participant follow-up attrition, resulting in a target of 316 patients per intervention group. The detailed scripts for the study's power calculations are available from the authors upon request. Additionally, similar matching and cross-validation will be conducted on the registry data linked to the study as described in Rosenström et al. (13). Permission will be requested from those excluded from the study (not eligible or decliners) for the use of collected background information (FTN). The impact of non-adherence will be investigated using multiple imputation (37). Protocols 3 and 4 Fourth, and finally, we estimated statistical power to detect the (previous) observational effect of waiting time of treatment on the subsequent treatment effect (assuming that the observational effect of Clark et al. (24) is also a causal effect; i.e., this effect is what our RCT tests). We digitized the Figure A of Clark et al. (24) (with minor loss in accuracy) using the “digitize” R package (38) and fitted a standard local regression smoother on the resulting data points (Figure 3A; result looks much like Clark et al., 2018, r was computed from the digitized data). We simulated treatment success per waiting time by taking the mean-prediction of this local regression plus a random draw from a normal distribution with standard deviation corresponding to the model residuals (i.e., 4.14). We can also investigate what happens in more noisy data, having double the residual standard deviation, as Clark et al. (24) modeled averages over clinical commissioning groups rather than individual patients’ scores (Figure 3B; r computed from 10 thousand simulated observations, of which first 195 are plotted). For research-logistic reasons, we were requested to use two waiting-time groups instead of a continuous-valued allocation, for simplicity. We created two waiting-time groups by simulating uniformly distributed waiting times on 6 to τ days and on τ + g to 100 days. By varying the parameters τ (threshold between short and long wait) and g (gap between the groups) in the simulations, we ensured that random allocation of 48 patients to a group who waits 1 to 4 weeks (but no longer than 4 weeks) and 48 patients to a group who waits over 5 weeks resulted in > 90% power even in the above-modeled high-noise case when using a standard t-test. With the 20% sample inflation to guard against attrition, we strived to collect 115 patients per studied diagnoses (115 with depression for protocol 3 and 115 with anxiety symptoms for protocol 4). This is the power calculation for our primary waiting-time hypothesis test. Besides verifying the existence of a causal effect of waiting time on treatment outcome in the simplest possible way, we also want a quantitative estimate on the causal effect of waiting days on symptom change (to support various later service-optimization efforts). For this, we will use instrumental variable analysis, with the random waiting-time group allocation being the instrument. We studied this setting by simulating the above-defined 96 patients (2 × 48) using the high-noise case of Figure 3B, to verify the procedure and sufficient statistical power. Across 10 000 repeated simulations, ordinary least squares regression of outcome on waiting time was –0.12 (95% CI = –0.15 to –0.09). Two-stage least squares estimate using waiting-time group allocation as the instrumental variable was –0.13 (CI = –0.17 to –0.10), indicating good agreement. We then investigated a scenario where a normally distributed confounding variable is added to waiting times and outcome after allocation, such that it cancels their correlation. This procedure fully diluted the ordinary least squares estimate, to –0.00 (CI = –0.07 to 0.06), but not the two-stage least squares estimate, which was still –0.14 (CI = –0.24 to –0.05). Statistical power to detect the causal effect was still 83%. Thus, we can be relatively certain that our procedure provides a valid causal estimate, even in the presence of quite catastrophic failures of experimental control. We used R package “ivmodel”, version 1.9.1, in these analyses. Register trial sample size and statistical analysis It is not ethical and feasible to (a) monitor patients with heavy questionnaires over multiple years and (b) include a group of untreated patients. Therefore, we collect register-based data on the participating patients and population controls. (a) Because of the passive register sampling, we do not expect additional attrition for the long-term follow up of patients and, thus, above power calculations pertain here too. (b) It is possible to create balanced control groups representing untreated patients without risking over-fitting to data (cf. (13,39)). In this approach, more data, including data on familial risks (cf. Rosenström et al., 2025)), allows for learning more comprehensive balancing models and the ‘true’ balancing model is always unknown. Therefore, we strive to sample as much from the general population as feasible with the pertinent future funding, at the minimum, as large a population sample as the clinical sample. Randomization Randomization will be performed using the random permuted block method with SAS software, Version 9.4 of the SAS System for Windows (SAS Institute Inc., Cary, NC, USA). Stratification (disorder, severity of disorder, and area of study site) will be used. A biostatistician (EL) outside the study team has prepared the randomisation lists, which have been entered into the REDCap software. Patient randomization will be conducted in REDCap by the research nurse at the press of a button, after they have been deemed eligible and have read the study information sheet and signed the informed consent. A biostatistician outside the study team (EL) will keep the randomization key confidential until the analyses for the primary follow-up time point (6 months after enrollment) have been completed. The treatment arms differ in both format and duration (e.g., guided self-help vs. face-to-face CBT) making blinding of participants and intervention providers not feasible. Given the lack of blinding, risk of bias will be mitigated by pre-specifying statistical analyses and using validated, standardized outcome measures. Protocols 1, 2 and the subclinical sample: In the initial phase of the study, participants in Southern Finland and Western Finland collaborative areas will be randomized (1:1:1) into the following three (A-C) treatment arms separately for depression (protocol 1) and anxiety (protocol 2): A) stepped care model: GSH, followed by fCBT for non-responders; B) fCBT; C) therapist-guided iCBT. To minimize potential randomly occurring biases in the treatment-group compositions, we employ stratified randomization. The stratification will be based on two criteria: 1) symptom severity (protocols 1 and 2 ≥10 points on the PHQ-9/GAD-7; subclinical sample 5–9 points on the PHQ-9/GAD-7;) and 2) research location (wellbeing service county). Protocols 3 and 4: In Pirkanmaa wellbeing service county, where we are investigating the effect of waiting time on treatment efficacy among patients with clinical symptoms of depression or anxiety (PHQ-9/GAD-7 ≥10 points), participants will be randomized into two treatment arms (1:1) separately for depression and anxiety: I) those with a waiting time of less than 4 weeks and II) those with a waiting time of more than 5 weeks. Before waiting-time randomization, the patients are randomized to two treatment arms A) stepped care model: GSH, followed by fCBT non-responders or B) fCBT. Assessments Finnish Therapy Navigator (FTN) Patients seeking help for mental health concerns in primary care services are asked to complete the FTN (28), a digital tool designed to help assess individual needs and preferences for psychosocial treatments. The FTN, in brief, collects information on current symptoms, as well as previous treatment, current social and working ability and treatment preferences. The FTN also covers possible traumatic events, recent crises and significant life events. The FTN is freely available on the internet (https://www.terapianavigaattori.fi/). The FTN comprises several well established and validated screening questions and accordingly applied self-reported symptom-specific measures: PHQ-9, GAD-7, Social Phobia Inventory (SPIN) (40), Panic Disorder Severity Scale-Self Report (PDSS-SR) (41), Alcohol Use Disorders Identification Test-Concise (AUDIT-C) (42), Alcohol Use Disorders Identification Test (AUDIT) (43) for those scoring ≥6/5 p (men/women) in AUDIT-C, Drug Use Disorders Identification Test (DUDIT) (44), Obsessive-Compulsive Inventory –Revised (OCI-R) (45), Burnout Assessment Tool (BAT-12) (46), and Trauma Screening Questionnaire (TSQ) (47). In January 2025, the Emotional and Psychological Single-Item Outcome (EPO-1) (48) was also added to the FTN. All patients suitable for the studied treatment approaches for depression or anxiety are offered the possibility to participate in the study. The suitability is assessed by a trained health care professional utilizing the information gathered by FTN. The FTN creates a case summary, which the clinician complements with a manualized semi-structured interview. The FTN interview manual supports treatment selection in line with clinical practice guidelines, but treatment decision is always left for the assessing clinician to negotiate with the patient. Interventions Guided self-help (GSH) Separate web-based self-help programs for depression and anxiety, both based on evidence-based CBT models, are used in the study. The programs are focused on the core elements of CBT: identifying and restructuring dysfunctional cognitions and emotional responses, and their interaction on patients’ current behavior through psychoeducation and exercises. The online materials contain: 1) psychoeducation and illustrations about the symptoms, severity, treatment, and causes of mental health problems and the cognitive model of the described problem, 2) multimedia exercise instructions and materials which target the change in thought and behavior patterns, and 3) information of several lifestyles and habits which generate and maintain the problems or symptoms. In the self-help material for depression, the patient is tasked to monitor their mood and recognize their thoughts, emotions and behaviors and their inter-related connections, which maintain depressive symptoms. With increased attentive skills and knowledge of one’s own beliefs, the patient is tasked to challenge and modify these beliefs and to form plans to increase pleasant and value-based activities in their life. The self-help material for anxiety focuses on modifying the catastrophic thinking patterns and dysfunctional beliefs that worrying is serving a useful function. The behavioral techniques include relaxation training, scheduling specific ‘worry time’ as well as planning pleasurable activities, and controlled exposure to thoughts and situations that are being avoided. GSH is administered utilizing symptom-specific (depression/anxiety) self-help materials, accessible at Mentalhub.fi website (https://www.mielenterveystalo.fi/en), in conjunction with 1–5 (an average of 3) face-to-face, video conference, or telephone sessions with a trained healthcare professional (49). These professionals assist patients in a collaborative manner by establishing goals, reviewing the self-help materials, and practicing the included exercises. Progress, outcomes, and possible side effects are routinely monitored. Guided Internet-delivered cognitive behavioral therapy (iCBT) The HUS guided iCBT programs are therapist supported and diagnosis-specific, each designed by an expert group including leading national level experts, selected separately for each disorder. The programs are divided into three phases: 1) introduction including psychoeducation, 2) actual treatment phase, and 3) summarizing phase including a plan for relapsing prevention and maintenance of the treatment results. Treatments consist of altogether 7–12 weekly sessions, which the patient can proceed at her own pace. The therapists are trained mental health professionals specialized in certain treatment programs and disorders. The patient is supported by the therapist throughout the treatment by asynchronous written messaging. iCBT for depression: The program for Depressive Disorder consists of seven treatment sessions and one follow-up session. Sessions include different topics each and build a proceeding treatment program. The topics and exercises are for example goal setting, behavioral activation, cognitive restructuring, advice on balanced life and relapse prevention. Throughout the program the outcomes and possible side effects are assessed with validated symptom measures (50). iCBT for generalized anxiety: The program for Generalized Anxiety Disorder (GAD) consists of 12 consecutive sessions and a follow-up session 3 months after treatment completion. The program is theoretically based on several models of GAD and anxiety, including aspects of the cognitive avoidance model, model of intolerance of uncertainty, metacognitive therapy, and acceptance and commitment therapy, as well as social aspects, such as assertiveness training. The sessions include text and videos, as well as educational illustrations, example stories, therapeutic exercises, and homework (35). Throughout the program the outcomes and possible side effects are assessed with validated symptom measures. Face to face cognitive behavioral therapy (fCBT) The fCBT intervention consists of 5–10 (avg. 7 sessions) weekly sessions with a therapist trained to deliver symptom-specific structured fCBT. The intervention protocol is grounded in evidence-based CBT practices for depression or anxiety and encompasses the same core elements as the GSH and guided iCBT models, including goal setting, psychoeducation, exercises, and homework assignments (51). Therapists providing face-to-face CBT (fCBT) are mental health professionals employed in public sector primary care units, including nurses (over 80%), clinical psychologists, and social workers. All therapists have received specialized training in administering CBT-based interventions. The one-year (15 ECTS) training program includes asynchronous learning activities on a digital learning platform, as well as supervised interventions: 30 hours of supervision and a minimum of 70 hours of clinical casework (51). The therapists participating in this study have either completed or are currently undergoing their supervised therapy training according to this curriculum, and this information about the intervention provider's training status will be collected during the study. Adherence to the intervention is not systematically audited due to the project's scope and naturalistic nature. However, adherence to guided GSH and iCBT is partially ensured through the extensive use of written materials. Professionals conducting all three treatment approaches receive clinical supervision to reinforce adherence to treatment protocols. The trial does not interfere with standard care practices, such as pharmacotherapy. The discontinuation of studied interventions and reasons for discontinuation are monitored, and all study participants will be analyzed within the groups to which they were randomized, following the intention-to-treat principle. Evaluation Pretreatment information is gathered in the clinical assessment together with FTN or clinical assessment during the recruitment process described above. Baseline information (as well as all data except registries used in the study) is gathered at the beginning of the treatment via the secure REDCap (52) software. Baseline self-reported measures include the PHQ-9, GAD-7, AUDIT-C, and EPO-1 measure applicable to all participants. Additional measures are administered only to those who screen positive for the corresponding symptoms, which include the PDSS-SR, SPIN, TSQ, OCI-R, BBGS, BAT-12, AUDIT, and DUDIT. Background information collected at baseline and measurements used throughout the study are described in Table 2. Primary outcome measure The primary outcome measure for protocols 1 and 3 is the within-individual change in depression symptoms, as assessed by the PHQ-9, and for protocols 2 and 4, the within-individual change in anxiety symptoms, as assessed by the GAD-7, from baseline to six months after enrollment. The PHQ-9 (protocols 1 & 3) or GAD-7 (protocols 2 & 4) is administered weekly for the first 16 weeks of the intervention and at follow-up time points (e.g., 4, 6, 8, and 12 months, as well as 2, 5, 10, 15, and 20 years) to facilitate intention-to-treat (ITT) analysis and to model symptom changes over time. Secondary outcome measures The secondary outcome measure is the proportion of patients in remission (30,31), defined as scoring below the clinical cut-off (<10 p in PHQ-9 or GAD-7 respectively), and those experiencing a clinically significant change in depression symptoms, indicated by a change of ≥5 (53) points on the PHQ-9 or ≥4 points on the GAD-7 (54). For protocols 1 and 3, the assessment is conducted using the PHQ-9 and for protocols 2 and 4, the assessment is conducted using the GAD-7. Table 2: Overview clinical data to be collected. T0= baseline; T1=treatment initiation T2=post-treatment after the initial intervention (after GSH/fCBT/iCBT); T3=4 months after enrolment: T4= 6- and 8-months follow-up; T5=planned years 1, 2, 5, 10, 15 and 20. T0 T1 T2 T3 T4 T5 Background information History of depression X Somatic comorbidities X Exercise, sleep, smoking, weight X X X X Height X Marital status and basic socioeconomic information X X X Previous psychotherapeutic interventions, yes/no, duration X Psychotropic medication: use of antidepressants and tranquilizers X X X X Employment status, inc. sick leaves + pensions X X X X Baseline diagnosis-specific measures (only for screen positives in FTN) PDSS-SR (Panic Disorder Severity Scale) X SPIN (Social Phobia Inventory) X TSQ (Trauma Screening Questionnaire) X OCI-R (Obsessive Compulsive Inventory -Revised) X BBGS (Brief Biosocial Gambling Screen) X BAT-12 (Burnout Assessment Tool) X AUDIT-C and AUDIT (if AUDIT-C ≥6/5 p men/women) X DUDIT (Drug Use Disorders Identification Test) X Primary outcomes (6-months) NOTE: 16 times weekly after treatment initiation PHQ-9 / GAD-7 according to the target symptom X X X X X X Secondary outcomes/covariate information PHQ-9 / GAD-7 other than the target symptom X X X X X X AUDIT-C and T4-5 AUDIT (if AUDIT-C ≥6/5 p men/women) X X X X PSSS-R (Perceived Social Support Scale-Revised) X X X X WSAS (Work and Social Adjustment Scale) X X X X EQ-5D-5L (Health Related Quality of Life) X X X X Euro-HIS (Quality of Life) X X X X EPO-1 (Wellbeing) X X X X X Number of sessions attended X Patient experience X Subjective work ability X X X X X Healthcare visits in the previous 12 months X X Income in the previous year X X Register data collection Registered data is collected for all patients, matched population controls and family members in order to a) conduct detailed analyses of consequences and societal costs of investigated interventions and b) modelling of alternative courses of treatments on population level. Register data is collected from the following registries: Digital and Population Data Services Agency (DVV), Finnish Centre for Pensions (ETK), The Social Insurance Institution of Finland (KELA), Finnish Institute for Health and Welfare (THL) and Statistics Finland’s Register. The main groups of variables are presented in Table 3. Table 3. Main groups of register data from patients, matched population and family controls. Main groups of register data to be collected Health care service use (e.g. date, procedure, diagnosis, provider’s professional group, psychotherapeutic treatments such as rehabilitative psychotherapy, online therapy, other) Diagnoses (any ICD diagnosis) Medications (prescriptions and purchases) Rehabilitation (rehabilitation services and benefits) Physiological measurements and lifestyle factors (depending on availability: eg. height, weight, smoking, laboratory tests) Cause and date of death Employment (e.g. education, work classification, income, sick leaves, labor market status, employment) Pension benefits (incl. disability and old-age pensions) Other social benefits (e.g. economic benefits like housing support and reimbursed travel expenses) Income information (incl. work and pension income) Health-economic evaluation The study includes a wide range of data collection that allows for comprehensive evaluation of both costs and consequences of treatments. This study adopts a societal perspective to estimate the economic impact of investigated treatments and waiting time for treatment of depression and anxiety. The analysis includes direct healthcare costs, indirect costs from lost productivity, and broader societal costs such as social services and illness-related changes in income. Health-utility analyses are conducted using EQ-5D-5L based health utility and register-based mortality data during follow-up. Incremental cost-effectiveness ratios (ICERs) will compare the costs and effectiveness of different interventions. Additionally, a budget impact analysis will estimate the potential savings of implementing the optimal treatments at a national level. Cost-related data is collected with questionnaires from patients at baseline and follow-up visits by asking about their use of different health services, medications, employment status, sickness absence days and household income by using standard questionnaires employed in current national health surveys (55). Healthcare visits will be converted to money using standard Finnish healthcare unit cost tables (56) or more recent official estimates. All costs are reported in Euros (€). Costs from previous years will be adjusted for inflation based on the Finnish Consumer Price Index (CPI). Future costs and benefits will be discounted at a rate based on national recommendations (currently 3%) with sensitivity analyses for different rates. For long-term follow-up and wide societal perspective of costs and consequences, register data will be used. Detailed modelling of total societal costs and their constituent factors from register data will be planned, tested and reported before the health economic analyses are conducted. This can be done in detail when registered data is obtained, as it is not fully transparent what kind of register data will be available for long-term follow-up. In brief, the study estimates societal costs as widely as possible using Finnish registry data. We categorize costs into direct healthcare costs, productivity losses, and other societal costs. Some costs are directly available from registries, whereas others will be converted using unit costs recommended for national health economics evaluations. Direct health care costs are available in detail from registries. The costs included will include at least hospitalizations, outpatient visits to different healthcare professionals, medications, and procedures. Cost-conversions will be done based on national unit costs for different interventions. Indirect costs from productivity loss arise from sickness absences, disability pensions, unemployment and loss of income due to other factors. The economic impact of sickness benefits and disability pensions is assessed using the duration of absence and average monthly earnings, but direct payments from registers are used where applicable. Individual income data is used to model changes in income. Other societal costs available from registries including rehabilitation, social service and patient travel costs. Travel costs are estimated by multiplying the number of reimbursed trips by standard trip costs or using direct payment data where applicable. Rehabilitation and social service costs are derived from unit costs of long-term care and rehabilitation programs. Housing benefits and social assistance payments are accounted for using direct register data. Monitoring Data collection and storage The data will be collected by digital surveys and research nurses working for the wellbeing counties and/or for Helsinki University Hospital (HUS). The data will be collected using REDCap software (52) for HUS and stored on a secure server of HUS. Research nurses will register a new patient in REDCap only after the patient's identity has been verified in accordance with the protocol of the respective wellbeing county. Study participants will provide the research nurse with a personal code from the FTN, which allows access to their results for a limited time. The research nurse will manually transfer the information from the Therapy Navigator to REDCap as part of the study's baseline data collection. Patients will complete the questionnaires directly in REDCap via a link sent to the email address they have provided. Automated reminders and weekly symptom questionnaires will also be sent through REDCap starting from the date of the first intervention session and continuing for 16 weeks. The research group of FLT-Step will supervise and support the research nurses from various wellbeing counties to ensure the proper conduct of the trial. To maintain compliance with the study protocol—such as inclusion and exclusion criteria, informing participants, and obtaining consent—the research nurses meet biweekly with members of the clinical and research team to address any questions or concerns that may arise. Additionally, continuous consultation is available. In the event of a protocol modification, the trial registries will be updated, and the research nurses as well as the participating wellbeing counties will be informed by the research group. Since this trial takes place in a naturalistic setting within public healthcare, we do not interfere with the treatment practices, which are aligned with national treatment guidelines. Patient recruitment for the study began in October 2024 and is planned to continue at least until June 2026. The main results of the study will be published in scientific journals. The research team is responsible for preparing the articles that present the study findings. Authorship will be determined in accordance with the criteria set by the International Committee of Medical Journal Editors (ICMJE). Safety All participants will receive comprehensive information about the study protocol to ensure they can provide truly informed consent. Guardians of participants aged 16–17 will receive a written notification of their ward's participation. All patients in the study will receive at least one evidence-based treatment (GSH, iCBT or fCBT). Patients who do not respond to the initial GSH will be offered fCBT. The level of care provided to study patients will be at least equivalent to what they would receive in current clinical practice. Participants are only randomized to a waitlist arm in clinical contexts (Pirkanmaa) where waiting is expected regardless of the research project. Since HUS iCBT treatment does not entail any waiting times, it is not included in the protocols 3–4. We do not anticipate increased risks for patients participating in this study, based on existing research literature on low-threshold CBT-based interventions (see background). To minimize the risk of adverse effects, we have excluded individuals with severe acute suicidality or a recent suicide attempt from the study. If a participant reports suicidal thoughts at any point on the PHQ-9 questionnaire, REDCap will automatically provide instructions on where to seek help and additional support. These procedures align with the operating principles of the FTN. During the treatment, providers will clinically and through questionnaires monitor patients' well-being and suicidality. All patients participate voluntarily in accordance with the Helsinki Declaration, and any adverse events will be closely monitored and reported. In the event of adverse events or symptom deterioration, therapists are trained to refer patients for appropriate evaluation and treatment. If serious suicidal thoughts, plans, or any self-harming acts are reported at follow-up points, patients will be instructed to contact healthcare emergency phone services for further evaluation and instructions. Participation, non-participation, or opting out of the study after initial consent will have no impact on the patient's ongoing treatment or access to other treatment modalities. The possible risks associated with these forms of treatment are minimal and fully comparable to current standard treatments. Compensation for any potential patient injuries can be sought from the Patient Insurance Centre in accordance with standard Finnish healthcare procedures. The study has received approval from the ethics committee of HUS Helsinki University Hospital (HUS/6234/2023). The necessary research permits have been obtained from HUS Helsinki University Hospital and all participating wellbeing service counties. Discussion The FLT-Step study aims to address critical gaps in the current understanding of the effectiveness and cost-effectiveness of various CBT interventions for depression and anxiety within a stepped care model. The primary hypothesis posits that a stepped care model (sequential GSH followed by fCBT for non-responders) and iCBT are non-inferior to fCBT for treating clinical depression and anxiety symptoms. This hypothesis is grounded in existing literature that supports the efficacy of CBT-based interventions of different delivery formats ( 5 – 8 , 11 , 12 , 57 , 58 ). The study's design (protocols 1 and 2), which includes three treatment arms, allows for a comprehensive comparison of these interventions within a naturalistic stepped-care approach. One secondary hypothesis suggests that the effectiveness and cost-effectiveness of stepped care (sequential GSH followed by fCBT for non-responders) may be superior to directly admitting patients to fCBT when treating clinical depression or anxiety symptoms ( 17 ). This aspect of the study is crucial for public healthcare systems that aim to optimize resource allocation while maintaining high-quality care. The study also hypothesizes that longer waiting times for the study interventions will be associated with poorer treatment responses in depression or anxiety symptoms (protocols 3 and 4). This, in turn, offers valuable information to policymakers about the effects of service system organization and delays in accessing care ( 24 ). Furthermore, this hypothesis highlights the importance of timely access to mental health services and the need for efficient triage systems and resource allocation to optimize treatment timing. Across all 4 RCTs (protocols 1–4), we plan to evaluate the predictive validity of the FTN in assessing individual needs and symptom profiles for therapeutic interventions. The data collected by FTN could potentially be used to predict treatment responses, facilitate personalized care and improve outcomes. This digital tool's integration into routine practice could enhance the precision of treatment allocation in addition to streamlining the assessment process. Long-term follow-up data collection is planned to evaluate the cost-saving potential of the studied stepped care model compared to matched population controls. By considering direct and indirect healthcare, social care, employment, and societal costs the study aims to provide a comprehensive assessment of the economic viability of implementing stepped care models in public health systems. Finally, the study will assess whether patients with subclinical depressive or anxiety symptoms benefit from psychotherapeutic interventions in terms of reduced risk of developing clinical episodes, decreased somatic morbidity, and reduced total long-term societal costs. This aspect of the study underscores the importance of knowledge in planning early intervention and preventive measures in the management of mental health conditions. In conclusion, the FLT-Step trial (protocols 1–4) outlines a rigorous approach to evaluating the effectiveness and cost-benefit of integrating GSH, iCBT, and fCBT into a stepped care model within the public healthcare system. The study's findings are expected to provide valuable evidence that could inform the broader implementation of stepped care models, enhancing accessibility, cost-effectiveness, and long-term societal benefits. Abbreviations CBT = cognitive-behavioral therapy GSH = guided self-help iCBT= internet-delivered cognitive-behavioral therapy fCBT = face-to-face cognitive-behavioral therapy PHQ-9 = Patient Health Questionnaire GAD-7 = Generalized Anxiety Disorder 7-item scale FLT = First-Line Therapies FTN = Finnish Therapy Navigator FU = Follow-up SPIN = Social Phobia Inventory PDSS-SR = Panic Disorder Severity Scale-Self Report AUDIT-C = Alcohol Use Disorders Identification Test-Concise AUDIT = Alcohol Use Disorders Identification Test DUDIT = Drug Use Disorders Identification Test OCI-R = Obsessive-Compulsive Inventory –Revised BAT-12 = Burnout Assessment Tool TSQ = Trauma Screening Questionnaire EPO-1 = Emotional and Psychological Outcome Declarations Ethics approval and consent to participate The study has been approved by the Helsinki University Hospital Regional Committee on Medical Research Ethics (HUS/6234/2023). Written informed consent will be obtained from all participants, fully informing them of the aims and procedures of the study. Participants will also be asked for permission for the further use of their data, which will be anonymized to ensure confidentiality and privacy. Consent for publication Not applicable. Availability of data and materials Public access to trial protocols is available through the trial registrations. Access to the study data is restricted to members of the research team only. According to Finnish legislations and institutional research permissions access to pseudonymised research data is granted only to members of the research team and do not allow sharing of data with third parties directly. All data will be pseudonymized prior to statistical analyses and reported at an aggregate level to ensure that individual patients cannot be identified. The statistical code will be reported alongside the publication of study results, in accordance with standard principles of good scientific writing. Members of research group will have access to the final trial dataset. No contractual agreements exist that would limit investigator access. Competing interests The authors declare that they have no competing interests. Study sponsor This is a researcher-initiated study, with Helsinki University Hospital (HUS) acting as an organizational sponsor. Contact information for HUS Jesper Ekelund, email: [email protected] , HUS Psychiatry, Välskärinkatu 12, 00059 HUS, Finland. Funding The study is funded by the European Union – NextGenerationEU. Roles and responsibilities—sponsor and funder Funders or organizational sponsors had no role in the design of this study and will not have any role in the data management, analyses and interpretation of the data, nor in the decision to submit the reports for publication. 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Cite Share Download PDF Status: Published Journal Publication published 11 Mar, 2026 Read the published version in BMC Psychiatry → Version 1 posted Editorial decision: Revision requested 07 Oct, 2025 Reviews received at journal 05 Oct, 2025 Reviews received at journal 17 Sep, 2025 Reviewers agreed at journal 14 Sep, 2025 Reviewers agreed at journal 11 Sep, 2025 Reviews received at journal 22 Aug, 2025 Reviewers agreed at journal 12 Aug, 2025 Reviewers agreed at journal 31 Jul, 2025 Reviewers invited by journal 24 Jul, 2025 Editor invited by journal 11 Jul, 2025 Editor assigned by journal 10 Jul, 2025 Submission checks completed at journal 10 Jul, 2025 First submitted to journal 03 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7039628","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Study protocol","associatedPublications":[],"authors":[{"id":490214868,"identity":"1367c45e-f6fb-4911-b216-5ce8c70828f0","order_by":0,"name":"Eeva-Eerika Helminen","email":"data:image/png;base64,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","orcid":"","institution":"Helsinki University Hospital","correspondingAuthor":true,"prefix":"","firstName":"Eeva-Eerika","middleName":"","lastName":"Helminen","suffix":""},{"id":490214869,"identity":"51742e05-5181-4b9a-a43a-7912fde085d7","order_by":1,"name":"Suoma E. Saarni","email":"","orcid":"","institution":"Helsinki University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Suoma","middleName":"E.","lastName":"Saarni","suffix":""},{"id":490214870,"identity":"8fde3ee1-64cc-48b1-b2cd-8bc5436ac640","order_by":2,"name":"Kasperi Mikkonen","email":"","orcid":"","institution":"Helsinki University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Kasperi","middleName":"","lastName":"Mikkonen","suffix":""},{"id":490214871,"identity":"8b1c7f02-0a23-474c-8930-173a15c71c21","order_by":3,"name":"M. Katariina Mattila","email":"","orcid":"","institution":"Helsinki University Hospital","correspondingAuthor":false,"prefix":"","firstName":"M.","middleName":"Katariina","lastName":"Mattila","suffix":""},{"id":490214872,"identity":"eaf812ce-5304-4a70-a128-073cac2a379b","order_by":4,"name":"Tom H. Rosenström","email":"","orcid":"","institution":"University of Helsinki","correspondingAuthor":false,"prefix":"","firstName":"Tom","middleName":"H.","lastName":"Rosenström","suffix":""},{"id":490214873,"identity":"d0f3b2b2-de0a-4768-abb2-e9a1775cb608","order_by":5,"name":"Max Karukivi","email":"","orcid":"","institution":"University of Turku","correspondingAuthor":false,"prefix":"","firstName":"Max","middleName":"","lastName":"Karukivi","suffix":""},{"id":490214874,"identity":"d8276b08-e7f8-413f-b088-cd03f5245e7e","order_by":6,"name":"Erkki Isometsä","email":"","orcid":"","institution":"University of Helsinki","correspondingAuthor":false,"prefix":"","firstName":"Erkki","middleName":"","lastName":"Isometsä","suffix":""},{"id":490214875,"identity":"eacc1ed5-2598-45df-a9bc-2b055b773a14","order_by":7,"name":"Jan-Henry Stenberg","email":"","orcid":"","institution":"Helsinki University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jan-Henry","middleName":"","lastName":"Stenberg","suffix":""},{"id":490214876,"identity":"26ca560c-0a73-4917-8176-0b488888f9f7","order_by":8,"name":"Jesper Ekelund","email":"","orcid":"","institution":"Helsinki University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jesper","middleName":"","lastName":"Ekelund","suffix":""},{"id":490214877,"identity":"1670a333-639d-4eeb-951d-41364da4d183","order_by":9,"name":"Samuli I. Saarni","email":"","orcid":"","institution":"Tampere University","correspondingAuthor":false,"prefix":"","firstName":"Samuli","middleName":"I.","lastName":"Saarni","suffix":""}],"badges":[],"createdAt":"2025-07-03 15:23:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7039628/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7039628/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12888-026-07962-w","type":"published","date":"2026-03-11T15:58:21+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":87797485,"identity":"9237fa5b-ccd9-47e7-901e-45f968735870","added_by":"auto","created_at":"2025-07-29 07:15:48","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":118861,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003ePanel A\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e) The main study protocol 1 (depression) and protocol 2 (anxiety).\u003c/em\u003e\u003cem\u003e\u003cstrong\u003e Panel B\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e) the substudy protocol 3 (depression) and protocol 4 (anxiety).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7039628/v1/475a1001fb26e1696a0bef1f.jpg"},{"id":87796612,"identity":"ab2edbb8-3ad2-47f9-a88b-197d6bb1035f","added_by":"auto","created_at":"2025-07-29 07:07:47","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":45591,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eStatistical power as a function of the treatment-arm size. Power for the PHQ-9-based non-inferiority test is shown with the thick solid line, the same for GAD-7 with the dashed line, and the power of the superiority test with the dotted line.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7039628/v1/82fc78121c20952208d7771b.jpg"},{"id":87796614,"identity":"ec9b95f0-7de1-4e31-8bb9-4a950421a84a","added_by":"auto","created_at":"2025-07-29 07:07:48","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":76248,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e)\u003cem\u003e Data (circles) digitized from Clark et al. \u003c/em\u003e(24; their Figure A)\u003cem\u003e using the R software package “digitize”, and a local regression fit (solid line) with default parameters of R (loess function). \u003c/em\u003e\u003cstrong\u003eB\u003c/strong\u003e) \u003cem\u003eData simulated from the local regression model (of panel A) with twice the residual standard deviation compared to original. Wait times were simulated from a truncated exponential distribution (see text for details).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7039628/v1/03afd736b863f46704b332f6.jpg"},{"id":104739398,"identity":"b7f25f9d-594d-40c1-856a-d82fc68d9a79","added_by":"auto","created_at":"2026-03-16 16:05:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1110401,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7039628/v1/f2e274be-fad9-4058-aa6b-85d61f355239.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Effectiveness of Guided Self-Help Versus Internet-Delivered or Face-to-Face Cognitive Behavioral Therapy for Depression and Anxiety: Four Parallel Randomized Controlled Non-Inferiority Trials of the Finnish First-Line Therapies – Initiative (FLT-Step)","fulltext":[{"header":"Background","content":"\u003cp\u003eMental\u0026nbsp;disorders\u0026nbsp;are at the core of the public health care crisis. Given that depression and anxiety are the most common mental disorders in western countries\u0026nbsp;(1), it is crucial to effectively organize the management of these disorders within primary care settings.\u0026nbsp;An increasing amount of research supports the cost-effectiveness of psychotherapeutic interventions for depression and anxiety disorders\u0026nbsp;(2\u0026ndash;5).\u003c/p\u003e\n\u003cp\u003eCognitive-behavioral therapy (CBT)\u0026nbsp;has been\u0026nbsp;found effective in the treatment of\u0026nbsp;depression\u0026nbsp;(6,7), subclinical depression\u0026nbsp;(8), and anxiety\u0026nbsp;disorders (9),\u0026nbsp;but access to evidence-based treatments in primary care settings is\u0026nbsp;often\u0026nbsp;inadequate, also in Finland. Furthermore,\u0026nbsp;along with conventional face-to-face CBT (fCBT), low-intensity CBT-based\u0026nbsp;guided self-help (GSH)\u0026nbsp;(6,10,11)\u0026nbsp;and guided internet delivered CBT (iCBT)\u0026nbsp;(12,13)\u0026nbsp;have been reported to be as effective as and more affordable than the\u0026nbsp;traditional forms of psychotherapeutic treatment for depression and anxiety.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe use of GSH, fCBT and iCBT as a part of a stepped care model could provide an applicable solution to make evidence-based treatment\u0026nbsp;accessible in public healthcare.\u0026nbsp;In\u0026nbsp;stepped care,\u0026nbsp;patients\u0026nbsp;are\u0026nbsp;treated at the lowest appropriate service level and stepped up only when clinically needed. In recent years, attention has been directed toward identifying the most effective strategies for establishing an optimally cost-effective sequence and equilibrium among various steps\u0026nbsp;(14\u0026ndash;17).\u0026nbsp;However, these optimization efforts tend to focus on immediate gains, often assuming that similar short-term average efficacies will result in analogous long-term outcomes. Thus, thoroughly evaluating the non-inferiority, cost-effectiveness, and long-term health economic impacts of three presumably equally effective treatments (GSH, fCBT, iCBT), each with varying costs, within a stepped-care model, can potentially provide valuable information for policymakers to optimize resource allocation and improve accessibility.\u003c/p\u003e\n\u003cp\u003eIn publicly funded healthcare systems, the goal is to optimize the cost-effectiveness on system level while ensuring access to necessary services to all. This calls for a modified stepped-care model that integrates a stratified approach, allowing patients to skip steps based on professional assessments of their individual needs. Modified\u0026nbsp;stepped care has been implemented since 2008 in the British NHS Talking Therapies program, previously known as IAPT (Improving Access to Psychological Treatments)\u0026nbsp;(18). Subsequently, similar programs have been piloted and implemented in other countries including Norway\u0026nbsp;(19),\u0026nbsp;Ireland (20), France\u0026nbsp;(21), Spain\u0026nbsp;(22), and Australia\u0026nbsp;(23)\u0026nbsp;in various clinical settings including communities, schools as well as private and public healthcare services. In Finland, a stepped-care model has been launched through the First-line Therapies initiative (FLT), a comprehensive nationwide program aimed at providing early, evidence-based treatment for common mental health problems. This initiative also focuses on systematizing pre-treatment assessments within the national public health care system.\u003c/p\u003e\n\u003cp\u003eIn the British NHS Talking Therapies program, longer waiting times to treatment have been linked to lower recovery rates within service-providing units\u0026nbsp;(24). Consequently, addressing delays in these low-cost, easily accessible treatments is crucial for enhancing the cost-effectiveness of stepped-care systems at a societal level.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study protocol details the FLT-Step trial (Effectiveness of Psychosocial Interventions for Depression and Anxiety in the Stepped Care Model of the Finnish First-Line Therapies), which comprises four parallel multicenter randomized controlled trials (RCTs). The protocol is described in adherence to the SPIRIT statement (25).\u0026nbsp;\u003c/p\u003e"},{"header":"Methods/Design","content":"\u003cp\u003eThis study consists of four parallel study protocols for four multicenter, randomized controlled trials (RCTs) aimed at treating depression or anxiety symptoms with CBT interventions in public healthcare using a stepped care approach.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePrimary Hypothesis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eThe primary hypotheses of protocols 1 (main study, depression) and 2 (main study, anxiety):\u003c/u\u003e A stepped care model, which involves sequential GSH followed by fCBT for non-responders, and guided iCBT are both non-inferior to fCBT for treating clinical depression and anxiety symptoms.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eProtocols 3 (substudy, depression) and 4 (substudy, anxiety):\u003c/u\u003e Longer waiting time for the treatment is associated with poorer treatment response in depression (protocol 3) or anxiety (protocol 4) symptoms in both study interventions: A) a stepped care model (sequential GSH followed by fCBT for non-responders) and B) direct admission to fCBT.\u003c/p\u003e\n\u003cp\u003eIn addition to hypothesis testing, we strived to estimate the quantitative causal effect of waiting time on treatment efficacy, as only observational estimates exist thus far to our knowledge (see power calculations - section).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe primary hypothesis in all four protocols will be tested at the primary outcome measurement point, which is six months after enrollment, for patients with a baseline score of \u0026ge;10 p on either the Patient Health Questionnaire (26) (PHQ-9, protocols 1 and 3) or Generalized Anxiety Disorder 7-item Scale (27) (GAD-7, protocols 2 and 4).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe treatment response is assessed with the within-individual change in depression/anxiety symptoms measured by the PHQ-9/GAD-7, depending on the primary symptom being studied.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSecondary hypotheses protocols 1, 2, 3 and 4\u003c/em\u003e\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eIf non-inferiority is demonstrated, effectiveness of the stepped care model (sequential GSH followed by fCBT for non-responders) is superior compared to directly admitting patients to fCBT when treating 1) clinical depression symptoms (baseline score of \u0026ge;10 p on PHQ-9) or 2) anxiety symptoms (baseline score of \u0026ge;10 p on GAD-7), assessed at six months after enrollment.\u003c/li\u003e\n \u003cli\u003eStepped care is more cost-effective than directing all patients with depression symptoms (baseline score \u0026ge;10 p on PHQ-9) or anxiety symptoms (baseline score \u0026ge;10 p on GAD-7) directly to fCBT assessed six months after enrollment.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eiCBT is more cost-effective than directing all patients with depression symptoms (baseline score \u0026ge;10 p on PHQ-9) or anxiety symptoms (baseline score \u0026ge;10 p on GAD-7) directly to fCBT (protocols 1 and 2 only) assessed six months after enrollment.\u003c/li\u003e\n \u003cli\u003eData collected by the Finnish Therapy Navigator (28) (FTN), a digital tool to help assess individual needs and symptom profile for psychotherapy, can be used to predict responses to treatment by using a multivariate model (an ability that would allow for treatment personalization) (29).\u003c/li\u003e\n \u003cli\u003eAll treatment approaches studied are cost-saving in the long term compared to matched population controls, when direct and indirect health care, social care, employment, and societal costs are considered (see section \u0026ldquo;health economic evaluation\u0026rdquo;).\u003c/li\u003e\n \u003cli\u003ePatients seeking treatment with subclinical depressive symptoms (baseline score of 5\u0026ndash;9 on the PHQ-9) benefit from the studied treatment approaches, in terms of reduced risk of developing clinical episodes, reduced total long-term societal costs, and decreased somatic morbidity.\u003c/li\u003e\n \u003cli\u003eLonger waiting times for the study treatments are associated with poorer overall long-term outcomes when direct and indirect health care, social care, employment, and societal costs are considered (protocols 3 and 4 only, see section \u0026ldquo;health economic evaluation\u0026rdquo;).\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u003cem\u003eDesign\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProtocols 1\u003c/strong\u003e (depression) \u003cstrong\u003eand 2\u003c/strong\u003e (anxiety) each include three treatment arms of equal sample size. The following treatment approaches are included in research arms: \u003cstrong\u003eA)\u0026nbsp;\u003c/strong\u003eGSH + fCBT (sequential GSH followed by fCBT for non-responders, planned n=316),\u003cstrong\u003e\u0026nbsp;B)\u003c/strong\u003e fCBT (planned n=316), and \u003cstrong\u003eC)\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eguided iCBT (planned n=316). Non-responder is a participant who still scores above the clinical cut-off on the respective symptom measure i.e.\u0026nbsp;PHQ-9\u0026nbsp;\u0026ge;10 p\u0026nbsp;(30)\u0026nbsp;or GAD-7\u0026nbsp;\u0026ge;10 p\u0026nbsp;(31). The treatment sites participating in this trial are in public primary mental health care services in Southern and Western Finland across six wellbeing service counties (population approx. 3,4 million), covering 60% of the total population of Finland. Alongside the RCTs of protocols 1 and 2, we will collect a convenience sample of patients with subclinical symptoms of depression (PHQ-9\u0026nbsp;5\u0026ndash;9 p)\u0026nbsp;or anxiety (GAD-7\u0026nbsp;5\u0026ndash;9 p)\u0026nbsp;to receive treatment in all three treatment arms (A, B or C).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProtocols 3\u0026nbsp;\u003c/strong\u003e(depression, planned n=115) \u003cstrong\u003eand 4\u003c/strong\u003e (anxiety, planned n=115) concentrate on a substudy examining the impact of waiting time, featuring two equally sized treatment arms: \u003cstrong\u003eA)\u003c/strong\u003e GSH followed by fCBT for non-responders, and \u003cstrong\u003eB)\u003c/strong\u003e fCBT. Participants in both arms are randomly assigned (1:1) to two groups: \u003cstrong\u003eI)\u003c/strong\u003e those commencing treatment within 4 weeks, and \u003cstrong\u003eII)\u003c/strong\u003e those starting treatment after 5 weeks or more. These sub studies are being carried out in the Pirkanmaa wellbeing service county, which has a population of approximately 540,000, located in Central Finland.\u003c/p\u003e\n\u003cp\u003eFor all study participants, including those involving patients seeking help for subclinical symptoms, the study data will be combined with data from Finnish national registries. Matched population controls will be identified to conduct a comprehensive registry study among these patients.\u003c/p\u003e\n\u003cp\u003eThe flow of patients through the protocols 1-4 is presented in Figure 1.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eRecruitment and patients \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTo achieve maximal external validity in the study, all patients evaluated by a professional in primary care as suitable for the studied treatments for depression or anxiety (e.g., GSH, iCBT, and fCBT) are invited to participate. The FTN is used to assess treatment needs as part of routine practice by the trained health care professional responsible for clinical signposting. If the patient is interested in participating in this trial, the clinician will schedule an appointment with a research nurse.\u0026nbsp;During this appointment, the research nurse will provide information about the study, review the inclusion and exclusion criteria, and give the patient a written study information sheet. The inclusion and exclusion criteria used in the study are described in Table 1.\u003c/p\u003e\n\u003cp\u003ePatients deemed eligible for the study will be asked to provide informed consent to participate. If the patient does not wish to participate, permission to use the information gathered in the FTN during the prescreening process of the study is requested. This approach ensures a more comprehensive understanding of the representativeness of the sample of primary care patients, thereby enhancing the overall quality and applicability of the study findings.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTable 1. Inclusion and exclusion criteria in the FLT-Step trial (protocols 1\u0026ndash;4).\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInclusion Criteria\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExclusion Criteria\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cul\u003e\n \u003cli\u003e\u0026ge;16 years\u0026nbsp;of\u0026nbsp;age\u003c/li\u003e\n \u003cli\u003eSuitable for studied treatments\u0026nbsp;(GSH,\u0026nbsp;iCBT\u0026nbsp;or\u0026nbsp;fCBT\u0026nbsp;intervention)\u0026nbsp;for depression/anxiety (cf.\u0026nbsp;exclusions)\u003c/li\u003e\n \u003cli\u003eDepression: PHQ \u0026ge;10 p\u003c/li\u003e\n \u003cli\u003eAnxiety: GAD-7 \u0026ge;10 p\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cul\u003e\n \u003cli\u003eGeneral exclusion criteria for studied treatments (i.e. recommended more intensive or other treatment forms)\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eSerious suicidal thoughts, plans or any\u0026nbsp;self-harming act or suicidal attempt\u0026nbsp;within the past 2 months.\u003c/li\u003e\n \u003cli\u003eOngoing other psychological treatment\u0026nbsp;for depression and/or anxiety\u003c/li\u003e\n \u003cli\u003eCognitive\u0026nbsp;impairment\u003c/li\u003e\n \u003cli\u003eInability to speak, read and write\u0026nbsp;Finnish\u003c/li\u003e\n \u003cli\u003eCurrently symptomatic psychotic\u0026nbsp;illness or bipolar disorder\u003c/li\u003e\n \u003cli\u003eDrug\u0026nbsp;or\u0026nbsp;alcohol\u0026nbsp;dependence\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 321px;\"\u003e\n \u003cp\u003eIn a sub-clinical cconvenience sample adjacent to protocols 1 and 2:\u0026nbsp;\u003c/p\u003e\n \u003cul\u003e\n \u003cli\u003eDepression: PHQ-9 5\u0026ndash;9 p\u003c/li\u003e\n \u003cli\u003eAnxiety: GAD-7 5\u0026ndash;9 p\u0026nbsp;\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eGSH guided self-help; iCBT Internet-based cognitive-behavioral therapy; fCBT face-to-face cognitive-behavioral therapy; PHQ-9 Patient Health Questionnaire; GAD-7 Generalized Anxiety Disorder 7-item scale\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003ePower calculations\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eProtocols 1 and 2\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThree types of power calculations were essential to these protocols. First, we tested the hypothesis that difference between PHQ-9 score change in the stepped care model (GSH + fCBT) and fCBT groups is no greater than a margin of 1.7 points, which amounts to the estimated threshold at which patients with moderate-severity symptoms can detect the difference between \u0026ldquo;feeling the same\u0026rdquo; and \u0026ldquo;feeling better\u0026rdquo; after a treatment (32). Second, the analogous margin for GAD-7 was 1.5 points. This threshold is slightly more stringent (leads to larger sample-size requirements) than a previously used statistically motivated margin (33), but more clinically meaningful in our opinion. We computed statistical power to detect non-inferiority\u0026nbsp;(34)\u0026nbsp;assuming no efficacy difference exists between the treatment arms and assuming the relevant clinical population standard deviation of PHQ-9 is 6 points\u0026nbsp;and that of GAD-7 is 3.6 points, as previously observed in Finnish context (35,36). Third, we computed statistical power to detect superiority between treatment groups when their standardized mean difference is d = 0.3 (i.e., small but larger than the standardized subjective-difference detection threshold of PHQ-9 from above 1.7/6 \u0026asymp; 0.28). We used significance level \u0026alpha; = 0.025 for one-sided non-inferiority test, which corresponds to 95% two-sided confidence interval being wholly on the better side of the margin. We used level \u0026alpha; = 0.05 in the two-sided tests of superiority.\u003c/p\u003e\n\u003cp\u003eFigure 2 shows the results from the first three statistical power calculations. We observed that a treatment group size 263 leads to at least 90% statistical power for all the three types of study questions. We inflated this estimate by 20% to allow for some participant follow-up attrition, resulting in a target of 316 patients per intervention group.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe detailed scripts for the study\u0026apos;s power calculations are available from the authors upon request. Additionally, similar matching and cross-validation will be conducted on the registry data linked to the study as described in Rosenstr\u0026ouml;m et al. (13). Permission will be requested from those excluded from the study (not eligible or decliners) for the use of collected background information (FTN). The impact of non-adherence will be investigated using multiple imputation (37).\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eProtocols 3 and 4\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eFourth, and finally, we estimated statistical power to detect the (previous) observational effect of waiting time of treatment on the subsequent treatment effect (assuming that the observational effect of Clark et al. (24) is also a causal effect; i.e., this effect is what our RCT tests). We digitized the Figure A of Clark et al. (24) (with minor loss in accuracy) using the \u0026ldquo;digitize\u0026rdquo; R package (38) and fitted a standard local regression smoother on the resulting data points (Figure 3A; result looks much like Clark et al., 2018, \u003cem\u003er\u003c/em\u003e was computed from the digitized data). We simulated treatment success per waiting time by taking the mean-prediction of this local regression plus a random draw from a normal distribution with standard deviation corresponding to the model residuals (i.e., 4.14). We can also investigate what happens in more noisy data, having double the residual standard deviation, as Clark et al. (24) modeled averages over clinical commissioning groups rather than individual patients\u0026rsquo; scores (Figure 3B; \u003cem\u003er\u003c/em\u003e computed from 10 thousand simulated observations, of which first 195 are plotted). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor research-logistic reasons, we were requested to use two waiting-time groups instead of a continuous-valued allocation, for simplicity. We created two waiting-time groups by simulating uniformly distributed waiting times on 6 to \u003cem\u003e\u0026tau;\u003c/em\u003e days and on \u003cem\u003e\u0026tau; + g\u003c/em\u003e to 100 days. By varying the parameters\u003cem\u003e\u0026nbsp;\u0026tau;\u0026nbsp;\u003c/em\u003e(threshold between short and long wait) and \u003cem\u003eg\u0026nbsp;\u003c/em\u003e(gap between the groups) in the simulations, we ensured that random allocation of 48 patients to a group who waits 1 to 4 weeks (but no longer than 4 weeks) and 48 patients to a group who waits over 5 weeks resulted in \u0026gt; 90% power even in the above-modeled high-noise case when using a standard t-test. With the 20% sample inflation to guard against attrition, we strived to collect 115 patients per studied diagnoses (115 with depression for protocol 3 and 115 with anxiety symptoms for protocol 4). This is the power calculation for our primary waiting-time hypothesis test.\u003c/p\u003e\n\u003cp\u003eBesides verifying the existence of a causal effect of waiting time on treatment outcome in the simplest possible way, we also want a quantitative estimate on the causal effect of waiting days on symptom change (to support various later service-optimization efforts). For this, we will use instrumental variable analysis, with the random waiting-time group allocation being the instrument. We studied this setting by simulating the above-defined 96 patients (2 \u0026times; 48) using the high-noise case of Figure 3B, to verify the procedure and sufficient statistical power. Across 10 000 repeated simulations, ordinary least squares regression of outcome on waiting time was \u0026ndash;0.12 (95% CI = \u0026ndash;0.15 to \u0026ndash;0.09). Two-stage least squares estimate using waiting-time group allocation as the instrumental variable was \u0026ndash;0.13 (CI = \u0026ndash;0.17 to \u0026ndash;0.10), indicating good agreement. We then investigated a scenario where a normally distributed confounding variable is added to waiting times and outcome after allocation, such that it cancels their correlation. This procedure fully diluted the ordinary least squares estimate, to \u0026ndash;0.00 (CI = \u0026ndash;0.07 to 0.06), but not the two-stage least squares estimate, which was still \u0026ndash;0.14 (CI = \u0026ndash;0.24 to \u0026ndash;0.05). Statistical power to detect the causal effect was still 83%. Thus, we can be relatively certain that our procedure provides a valid causal estimate, even in the presence of quite catastrophic failures of experimental control. We used R package \u0026ldquo;ivmodel\u0026rdquo;, version 1.9.1, in these analyses.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eRegister trial sample size and statistical analysis\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eIt is not ethical and feasible to (a) monitor patients with heavy questionnaires over multiple years and (b) include a group of untreated patients. Therefore, we collect register-based data on the participating patients and population controls. (a) Because of the passive register sampling, we do not expect additional attrition for the long-term follow up of patients and, thus, above power calculations pertain here too. (b) It is possible to create balanced control groups representing untreated patients without risking over-fitting to data (cf. (13,39)). In this approach, more data, including data on familial risks (cf. Rosenstr\u0026ouml;m et al., 2025)), allows for learning more comprehensive balancing models and the \u0026lsquo;true\u0026rsquo; balancing model is always unknown. Therefore, we strive to sample as much from the general population as feasible with the pertinent future funding, at the minimum, as large a population sample as the clinical sample.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eRandomization\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eRandomization will be performed using the random permuted block method with SAS software, Version 9.4 of the SAS System for Windows (SAS Institute Inc., Cary, NC, USA). Stratification (disorder, severity of disorder, and area of study site) will be used. A biostatistician (EL) outside the study team has prepared the randomisation lists, which have been entered into the REDCap software. Patient randomization will be conducted in REDCap by the research nurse at the press of a button, after they have been deemed eligible and have read the study information sheet and signed the informed consent.\u0026nbsp;A biostatistician outside the study team (EL) will keep the randomization key confidential until the analyses for the primary follow-up time point (6 months after enrollment) have been completed. The treatment arms differ in both format and duration (e.g., guided self-help vs. face-to-face CBT) making blinding of participants and intervention providers not feasible. Given the lack of blinding, risk of bias will be mitigated by pre-specifying statistical analyses and using validated, standardized outcome measures.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eProtocols 1, 2 and the subclinical sample:\u003c/u\u003e In the initial phase of the study, participants in Southern Finland and Western Finland collaborative areas will be randomized (1:1:1) into the following three (A-C) treatment arms separately for depression (protocol 1) and anxiety (protocol 2): A) stepped care model: GSH, followed by fCBT for non-responders; B) fCBT; C) therapist-guided iCBT. To minimize potential randomly occurring biases in the treatment-group compositions, we employ stratified randomization. The stratification will be based on two criteria: 1) symptom severity (protocols 1 and 2 \u0026ge;10 points on the PHQ-9/GAD-7; subclinical sample 5\u0026ndash;9 points on the PHQ-9/GAD-7;) and 2) research location (wellbeing service county).\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eProtocols 3 and 4:\u003c/u\u003e In Pirkanmaa wellbeing service county, where we are investigating the effect of waiting time on treatment efficacy among patients with clinical symptoms of depression or anxiety (PHQ-9/GAD-7 \u0026ge;10 points), participants will be randomized into two treatment arms (1:1) separately for depression and anxiety: I) those with a waiting time of less than 4 weeks and II) those with a waiting time of more than 5 weeks. Before waiting-time randomization, the patients are randomized to two treatment arms A) stepped care model: GSH, followed by fCBT non-responders or B) fCBT. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAssessments\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eFinnish Therapy Navigator (FTN)\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003ePatients seeking help for mental health concerns in primary care services are asked to complete the FTN\u0026nbsp;(28), a digital tool designed to help assess individual needs and preferences for psychosocial treatments. The FTN, in brief, collects information on current symptoms, as well as previous treatment, current social and working ability and treatment preferences. The FTN also covers possible traumatic events, recent crises and significant life events. The FTN is freely available on the internet (https://www.terapianavigaattori.fi/).\u003c/p\u003e\n\u003cp\u003eThe FTN comprises several well established and validated screening questions and accordingly applied self-reported symptom-specific measures: PHQ-9, GAD-7, Social Phobia Inventory (SPIN)\u0026nbsp;(40), Panic Disorder Severity Scale-Self Report (PDSS-SR)\u0026nbsp;(41), Alcohol Use Disorders Identification Test-Concise (AUDIT-C)\u0026nbsp;(42), Alcohol Use Disorders Identification Test (AUDIT)\u0026nbsp;(43)\u0026nbsp;for those\u0026nbsp;scoring\u0026nbsp;\u0026ge;6/5 p (men/women) in AUDIT-C,\u0026nbsp;Drug Use Disorders Identification Test (DUDIT)\u0026nbsp;(44), Obsessive-Compulsive Inventory \u0026ndash;Revised (OCI-R) (45), Burnout Assessment Tool (BAT-12)\u0026nbsp;(46), and Trauma Screening Questionnaire (TSQ)\u0026nbsp;(47). In January 2025, the Emotional and Psychological Single-Item Outcome (EPO-1)\u0026nbsp;(48)\u0026nbsp;was also added to the FTN.\u003c/p\u003e\n\u003cp\u003eAll patients suitable for the studied treatment approaches for depression or anxiety are offered the possibility to participate in the study. The suitability is assessed by a trained health care professional utilizing the information gathered by FTN. The FTN creates a case summary, which the clinician complements with a manualized semi-structured interview. The FTN interview manual supports treatment selection in line with clinical practice guidelines, but treatment decision is always left for the assessing clinician to negotiate with the patient.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eInterventions\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eGuided self-help (GSH)\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eSeparate web-based self-help programs for depression and anxiety, both based on evidence-based CBT models, are used in the study. The programs are focused on the core elements of CBT: identifying and restructuring dysfunctional cognitions and emotional responses, and their interaction on patients\u0026rsquo; current behavior through psychoeducation and exercises. The online materials contain: 1) psychoeducation and illustrations about the symptoms, severity, treatment, and causes of mental health problems and the cognitive model of the described problem, 2) multimedia exercise instructions and materials which target the change in thought and behavior patterns, and 3) information of several lifestyles and habits which generate and maintain the problems or symptoms.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the self-help material for depression, the patient is tasked to monitor their mood and recognize their thoughts, emotions and behaviors and their inter-related connections, which maintain depressive symptoms. With increased attentive skills and knowledge of one\u0026rsquo;s own beliefs, the patient is tasked to challenge and modify these beliefs and to form plans to increase pleasant and value-based activities in their life. The self-help material for anxiety\u0026nbsp;focuses on modifying the catastrophic thinking patterns and dysfunctional beliefs that worrying is serving a useful function. The behavioral techniques include relaxation training, scheduling specific \u0026lsquo;worry time\u0026rsquo; as well as planning pleasurable activities, and controlled exposure to thoughts and situations that are being avoided.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGSH is administered utilizing symptom-specific (depression/anxiety) self-help materials, accessible at Mentalhub.fi website (https://www.mielenterveystalo.fi/en), in conjunction with 1\u0026ndash;5 (an average of 3) face-to-face, video conference, or telephone sessions with a trained healthcare professional\u0026nbsp;(49). These professionals assist patients in a collaborative manner by establishing goals, reviewing the self-help materials, and practicing the included exercises. Progress, outcomes, and possible side effects are routinely monitored.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eGuided Internet-delivered cognitive behavioral therapy (iCBT)\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe HUS guided iCBT programs are therapist supported and diagnosis-specific, each designed by an expert group including leading national level experts, selected separately for each disorder. The programs are divided into three phases: 1) introduction including psychoeducation, 2) actual treatment phase, and 3) summarizing phase including a plan for relapsing prevention and maintenance of the treatment results. Treatments consist of altogether 7\u0026ndash;12 weekly sessions, which the patient can proceed at her own pace. The therapists are trained mental health professionals specialized in certain treatment programs and disorders. The patient is supported by the therapist throughout the treatment by asynchronous written messaging.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eiCBT for depression:\u003c/u\u003e The program for Depressive Disorder consists of seven treatment sessions and one follow-up session. Sessions include different topics each and build a proceeding treatment program. The topics and exercises are for example goal setting, behavioral activation, cognitive restructuring, advice on balanced life and relapse prevention. Throughout the program the outcomes and possible side effects are assessed with validated symptom measures\u0026nbsp;(50).\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eiCBT for generalized anxiety:\u003c/u\u003e The program for Generalized Anxiety Disorder (GAD) consists of 12 consecutive sessions and a follow-up session 3 months after treatment completion. The program is theoretically based on several models of GAD and anxiety, including aspects of the cognitive avoidance model, model of intolerance of uncertainty, metacognitive therapy, and acceptance and commitment therapy, as well as social aspects, such as assertiveness training. The sessions include text and videos, as well as educational illustrations, example stories, therapeutic exercises, and homework (35). Throughout the program the outcomes and possible side effects are assessed with validated symptom measures.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eFace to face cognitive behavioral therapy (fCBT)\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe fCBT intervention consists of 5\u0026ndash;10 (avg. 7 sessions) weekly sessions with a therapist trained to deliver symptom-specific structured fCBT. The intervention protocol is grounded in evidence-based CBT practices for depression or anxiety and encompasses the same core elements as the GSH and guided iCBT models, including goal setting, psychoeducation, exercises, and homework assignments\u0026nbsp;(51).\u003c/p\u003e\n\u003cp\u003eTherapists providing face-to-face CBT (fCBT) are mental health professionals employed in public sector primary care units, including nurses (over 80%), clinical psychologists, and social workers. All therapists have received specialized training in administering CBT-based interventions. The one-year (15 ECTS) training program includes asynchronous learning activities on a digital learning platform, as well as supervised interventions: 30 hours of supervision and a minimum of 70 hours of clinical casework\u0026nbsp;(51). The therapists participating in this study have either completed or are currently undergoing their supervised therapy training according to this curriculum, and this information about the intervention provider\u0026apos;s training status will be collected during the study.\u003c/p\u003e\n\u003cp\u003eAdherence to the intervention is not systematically audited due to the project\u0026apos;s scope and naturalistic nature. However, adherence to guided GSH and iCBT is partially ensured through the extensive use of written materials. Professionals conducting all three treatment approaches receive clinical supervision to reinforce adherence to treatment protocols. The trial does not interfere with standard care practices, such as pharmacotherapy. The discontinuation of studied interventions and reasons for discontinuation are monitored, and all study participants will be analyzed within the groups to which they were randomized, following the intention-to-treat principle.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eEvaluation\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePretreatment information is gathered in the clinical assessment together with FTN or clinical assessment during the recruitment process described above. Baseline information (as well as all data except registries used in the study) is gathered at the beginning of the treatment via the secure REDCap\u0026nbsp;(52)\u0026nbsp;software.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBaseline self-reported measures include the PHQ-9, GAD-7, AUDIT-C, and EPO-1 measure applicable to all participants. Additional measures are administered only to those who screen positive for the corresponding symptoms, which include the PDSS-SR, SPIN, TSQ, OCI-R, BBGS, BAT-12, AUDIT, and DUDIT.\u003c/p\u003e\n\u003cp\u003eBackground information collected at baseline and measurements used throughout the study are described in Table 2.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePrimary outcome measure\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe primary outcome measure for protocols 1 and 3 is the within-individual change in depression symptoms, as assessed by the PHQ-9, and for protocols 2 and 4, the within-individual change in anxiety symptoms, as assessed by the GAD-7, from baseline to six months after enrollment.\u0026nbsp;The PHQ-9 (protocols 1 \u0026amp; 3) or GAD-7 (protocols 2 \u0026amp; 4) is administered weekly for the first 16 weeks of the intervention and at follow-up time points (e.g., 4, 6, 8, and 12 months, as well as 2, 5, 10, 15, and 20 years) to facilitate intention-to-treat (ITT) analysis and to model symptom changes over time.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSecondary outcome measures\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe secondary outcome measure is the proportion of patients in remission\u0026nbsp;(30,31), defined as scoring below the clinical cut-off (\u0026lt;10 p in PHQ-9 or GAD-7 respectively), and those experiencing a clinically significant change in depression symptoms, indicated by a change of \u0026ge;5\u0026nbsp;(53)\u0026nbsp;points on the PHQ-9 or \u0026ge;4 points on the GAD-7\u0026nbsp;(54). For protocols 1 and 3, the assessment is conducted using the PHQ-9 and for protocols 2 and 4, the assessment is conducted using the GAD-7.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTable 2: Overview clinical data to be collected. T0= baseline; T1=treatment initiation T2=post-treatment after the initial intervention (after GSH/fCBT/iCBT); T3=4 months after enrolment: T4= 6- and 8-months follow-up; T5=planned years 1, 2, 5, 10, 15 and 20.\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"604\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eT0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eT1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eT2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eT3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eT4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eT5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 604px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBackground information\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003eHistory of depression\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003eSomatic comorbidities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003eExercise, sleep, smoking, weight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003eHeight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003eMarital status and basic socioeconomic information\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003ePrevious psychotherapeutic interventions, yes/no, duration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003ePsychotropic medication: use of antidepressants and tranquilizers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003eEmployment status, inc. sick leaves + pensions\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 604px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBaseline diagnosis-specific measures (only for screen positives in FTN)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003ePDSS-SR (Panic Disorder Severity Scale)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003eSPIN (Social Phobia Inventory)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003eTSQ (Trauma Screening Questionnaire)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003eOCI-R (Obsessive Compulsive Inventory -Revised)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003eBBGS (Brief Biosocial Gambling Screen)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003eBAT-12 (Burnout Assessment Tool)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003eAUDIT-C and AUDIT (if AUDIT-C \u0026ge;6/5 p men/women)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003eDUDIT (Drug Use Disorders Identification Test)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 604px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrimary outcomes (6-months) NOTE: 16 times weekly after treatment initiation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003ePHQ-9 / GAD-7 according to the target symptom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 604px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSecondary outcomes/covariate information\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003ePHQ-9 / GAD-7 other than the target symptom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003eAUDIT-C and T4-5 AUDIT (if AUDIT-C \u0026ge;6/5 p men/women)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003ePSSS-R (Perceived Social Support Scale-Revised)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003eWSAS (Work and Social Adjustment Scale)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003eEQ-5D-5L (Health Related Quality of Life)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003eEuro-HIS (Quality of Life)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003eEPO-1 (Wellbeing)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003eNumber of sessions attended\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003ePatient experience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003eSubjective work ability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003eHealthcare visits in the previous 12 months\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003eIncome in the previous year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eRegister data collection\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eRegistered data is collected for all patients, matched population controls and family members in order to a) conduct detailed analyses of consequences and societal costs of investigated interventions and b) modelling of alternative courses of treatments on population level. Register data is collected from the following registries: Digital and Population Data Services Agency (DVV), Finnish Centre for Pensions (ETK), The Social Insurance Institution of Finland (KELA), Finnish Institute for Health and Welfare (THL) and Statistics Finland\u0026rsquo;s Register. The main groups of variables are presented in Table 3.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTable 3. Main groups of register data from patients, matched population and family controls.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"595\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 595px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMain groups of register data to be collected\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 595px;\"\u003e\n \u003cp\u003eHealth care service use (e.g. date, procedure, diagnosis, provider\u0026rsquo;s professional group, psychotherapeutic treatments such as rehabilitative psychotherapy, online therapy, other)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 595px;\"\u003e\n \u003cp\u003eDiagnoses (any ICD diagnosis)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 595px;\"\u003e\n \u003cp\u003eMedications (prescriptions and purchases)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 595px;\"\u003e\n \u003cp\u003eRehabilitation (rehabilitation services and benefits)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 595px;\"\u003e\n \u003cp\u003ePhysiological measurements and lifestyle factors (depending on availability: eg. height, weight, smoking, laboratory tests)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 595px;\"\u003e\n \u003cp\u003eCause and date of death\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 595px;\"\u003e\n \u003cp\u003eEmployment (e.g. education, work classification, income, sick leaves, labor market status, employment)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 595px;\"\u003e\n \u003cp\u003ePension benefits (incl. disability and old-age pensions)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 595px;\"\u003e\n \u003cp\u003eOther social benefits (e.g. economic benefits like housing support and reimbursed travel expenses)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 595px;\"\u003e\n \u003cp\u003eIncome information (incl. work and pension income)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eHealth-economic evaluation\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe study includes a wide range of data collection that allows for comprehensive evaluation of both costs and consequences of treatments. This study adopts a societal perspective to estimate the economic impact of investigated treatments and waiting time for treatment of depression and anxiety. The analysis includes direct healthcare costs, indirect costs from lost productivity, and broader societal costs such as social services and illness-related changes in income.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHealth-utility analyses are conducted using EQ-5D-5L based health utility and register-based mortality data during follow-up.\u0026nbsp;Incremental cost-effectiveness ratios (ICERs) will compare the costs and effectiveness of different interventions. Additionally, a budget impact analysis will estimate the potential savings of implementing the optimal treatments at a national level.\u003c/p\u003e\n\u003cp\u003eCost-related data is collected with questionnaires from patients at baseline and follow-up visits by asking about their use of different health services, medications, employment status, sickness absence days and household income by using standard questionnaires employed in current national health surveys\u0026nbsp;(55).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHealthcare visits will be converted to money using standard Finnish healthcare unit cost tables\u0026nbsp;(56)\u0026nbsp;or more recent official estimates. \u0026nbsp;All costs are reported in Euros (\u0026euro;). Costs from previous years will be adjusted for inflation based on the Finnish Consumer Price Index (CPI). Future costs and benefits will be discounted at a rate based on national recommendations (currently 3%) with sensitivity analyses for different rates. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor long-term follow-up and wide societal perspective of costs and consequences, register data will be used. \u0026nbsp;Detailed modelling of total societal costs and their constituent factors from register data will be planned, tested and reported before the health economic analyses are conducted. This can be done in detail when registered data is obtained, as it is not fully transparent what kind of register data will be available for long-term follow-up. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn brief, the study estimates societal costs as widely as possible using Finnish registry data. We categorize costs into direct healthcare costs, productivity losses, and other societal costs. Some costs are directly available from registries, whereas others will be converted using unit costs recommended for national health economics evaluations.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDirect health care costs are available in detail from registries. The costs included will include at least hospitalizations, outpatient visits to different healthcare professionals, medications, and procedures. Cost-conversions will be done based on national unit costs for different interventions.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIndirect costs from productivity loss arise from sickness absences, disability pensions, unemployment and loss of income due to other factors. The economic impact of sickness benefits and disability pensions is assessed using the duration of absence and average monthly earnings, but direct payments from registers are used where applicable. Individual income data is used to model changes in income.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOther societal costs available from registries including rehabilitation, social service and patient travel costs. Travel costs are estimated by multiplying the number of reimbursed trips by standard trip costs or using direct payment data where applicable. Rehabilitation and social service costs are derived from unit costs of long-term care and rehabilitation programs. Housing benefits and social assistance payments are accounted for using direct register data.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMonitoring\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eData collection and storage\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe data will be collected by digital surveys and research nurses working for the wellbeing counties and/or for Helsinki University Hospital (HUS). The data will be collected using REDCap software (52) for HUS and stored on a secure server of HUS. Research nurses will register a new patient in REDCap only after the patient\u0026apos;s identity has been verified in accordance with the protocol of the respective wellbeing county.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eStudy participants will provide the research nurse with a personal code from the FTN, which allows access to their results for a limited time. The research nurse will manually transfer the information from the Therapy Navigator to REDCap as part of the study\u0026apos;s baseline data collection.\u003c/p\u003e\n\u003cp\u003ePatients will complete the questionnaires directly in REDCap via a link sent to the email address they have provided. Automated reminders and weekly symptom questionnaires will also be sent through REDCap starting from the date of the first intervention session and continuing for 16 weeks.\u003c/p\u003e\n\u003cp\u003eThe research group of FLT-Step will supervise and support the research nurses from various wellbeing counties to ensure the proper conduct of the trial. To maintain compliance with the study protocol\u0026mdash;such as inclusion and exclusion criteria, informing participants, and obtaining consent\u0026mdash;the research nurses meet biweekly with members of the clinical and research team to address any questions or concerns that may arise. Additionally, continuous consultation is available. In the event of a protocol modification, the trial registries will be updated, and the research nurses as well as the participating wellbeing counties will be informed by the research group. Since this trial takes place in a naturalistic setting within public healthcare, we do not interfere with the treatment practices, which are aligned with national treatment guidelines.\u003c/p\u003e\n\u003cp\u003ePatient recruitment for the study began in October 2024 and is planned to continue at least until June 2026. The main results of the study will be published in scientific journals. The research team is responsible for preparing the articles that present the study findings. Authorship will be determined in accordance with the criteria set by the International Committee of Medical Journal Editors (ICMJE).\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eSafety\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eAll participants will receive comprehensive information about the study protocol to ensure they can provide truly informed consent. Guardians of participants aged 16\u0026ndash;17 will receive a written notification of their ward\u0026apos;s participation. All patients in the study will receive at least one evidence-based treatment (GSH, iCBT or fCBT).\u0026nbsp;Patients who do not respond to the initial GSH will be offered fCBT.\u0026nbsp;The level of care provided to study patients will be at least equivalent to what they would receive in current clinical practice. Participants are only randomized to a waitlist arm in clinical contexts (Pirkanmaa) where waiting is expected regardless of the research project. Since HUS iCBT treatment does not entail any waiting times, it is not included in the protocols 3\u0026ndash;4.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe do not anticipate increased risks for patients participating in this study, based on existing research literature on low-threshold CBT-based interventions (see background). To minimize the risk of adverse effects, we have excluded individuals with severe acute suicidality or a recent suicide attempt from the study. If a participant reports suicidal thoughts at any point on the PHQ-9 questionnaire, REDCap will automatically provide instructions on where to seek help and additional support. These procedures align with the operating principles of the FTN. During the treatment, providers will clinically and through questionnaires monitor patients\u0026apos; well-being and suicidality.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll patients participate voluntarily in accordance with the Helsinki Declaration, and any adverse events will be closely monitored and reported. In the event of adverse events or symptom deterioration, therapists are trained to refer patients for appropriate evaluation and treatment. If serious suicidal thoughts, plans, or any self-harming acts are reported at follow-up points, patients will be instructed to contact healthcare emergency phone services for further evaluation and instructions. Participation, non-participation, or opting out of the study after initial consent will have no impact on the patient\u0026apos;s ongoing treatment or access to other treatment modalities. The possible risks associated with these forms of treatment are minimal and fully comparable to current standard treatments. Compensation for any potential patient injuries can be sought from the Patient Insurance Centre in accordance with standard Finnish healthcare procedures.\u003c/p\u003e\n\u003cp\u003eThe study has received approval from the ethics committee of HUS Helsinki University Hospital (HUS/6234/2023). The necessary research permits have been obtained from HUS Helsinki University Hospital and all participating wellbeing service counties.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe FLT-Step study aims to address critical gaps in the current understanding of the effectiveness and cost-effectiveness of various CBT interventions for depression and anxiety within a stepped care model. The primary hypothesis posits that a stepped care model (sequential GSH followed by fCBT for non-responders) and iCBT are non-inferior to fCBT for treating clinical depression and anxiety symptoms. This hypothesis is grounded in existing literature that supports the efficacy of CBT-based interventions of different delivery formats (\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e). The study's design (protocols 1 and 2), which includes three treatment arms, allows for a comprehensive comparison of these interventions within a naturalistic stepped-care approach.\u003c/p\u003e\u003cp\u003eOne secondary hypothesis suggests that the effectiveness and cost-effectiveness of stepped care (sequential GSH followed by fCBT for non-responders) may be superior to directly admitting patients to fCBT when treating clinical depression or anxiety symptoms (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). This aspect of the study is crucial for public healthcare systems that aim to optimize resource allocation while maintaining high-quality care.\u003c/p\u003e\u003cp\u003eThe study also hypothesizes that longer waiting times for the study interventions will be associated with poorer treatment responses in depression or anxiety symptoms (protocols 3 and 4). This, in turn, offers valuable information to policymakers about the effects of service system organization and delays in accessing care (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Furthermore, this hypothesis highlights the importance of timely access to mental health services and the need for efficient triage systems and resource allocation to optimize treatment timing.\u003c/p\u003e\u003cp\u003eAcross all 4 RCTs (protocols 1\u0026ndash;4), we plan to evaluate the predictive validity of the FTN in assessing individual needs and symptom profiles for therapeutic interventions. The data collected by FTN could potentially be used to predict treatment responses, facilitate personalized care and improve outcomes. This digital tool's integration into routine practice could enhance the precision of treatment allocation in addition to streamlining the assessment process.\u003c/p\u003e\u003cp\u003eLong-term follow-up data collection is planned to evaluate the cost-saving potential of the studied stepped care model compared to matched population controls. By considering direct and indirect healthcare, social care, employment, and societal costs the study aims to provide a comprehensive assessment of the economic viability of implementing stepped care models in public health systems.\u003c/p\u003e\u003cp\u003eFinally, the study will assess whether patients with subclinical depressive or anxiety symptoms benefit from psychotherapeutic interventions in terms of reduced risk of developing clinical episodes, decreased somatic morbidity, and reduced total long-term societal costs. This aspect of the study underscores the importance of knowledge in planning early intervention and preventive measures in the management of mental health conditions.\u003c/p\u003e\u003cp\u003eIn conclusion, the FLT-Step trial (protocols 1\u0026ndash;4) outlines a rigorous approach to evaluating the effectiveness and cost-benefit of integrating GSH, iCBT, and fCBT into a stepped care model within the public healthcare system. The study's findings are expected to provide valuable evidence that could inform the broader implementation of stepped care models, enhancing accessibility, cost-effectiveness, and long-term societal benefits.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cem\u003eCBT = cognitive-behavioral therapy\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eGSH = guided self-help\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eiCBT= internet-delivered cognitive-behavioral therapy\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003efCBT = face-to-face cognitive-behavioral therapy\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePHQ-9 = Patient Health Questionnaire\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eGAD-7 = Generalized Anxiety Disorder 7-item scale\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFLT = First-Line Therapies\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFTN = Finnish Therapy Navigator\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFU = Follow-up\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSPIN = Social Phobia Inventory\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePDSS-SR = Panic Disorder Severity Scale-Self Report\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAUDIT-C = Alcohol Use Disorders Identification Test-Concise\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAUDIT = Alcohol Use Disorders Identification Test\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDUDIT = Drug Use Disorders Identification Test\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eOCI-R =\u0026nbsp;Obsessive-Compulsive Inventory \u0026ndash;Revised\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eBAT-12 = Burnout Assessment Tool\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTSQ = Trauma Screening Questionnaire\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eEPO-1 = Emotional and Psychological Outcome\u0026nbsp;\u003c/em\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe study has been approved by the Helsinki University Hospital Regional Committee on Medical Research Ethics (HUS/6234/2023). Written informed consent will be obtained from all participants, fully informing them of the aims and procedures of the study. Participants will also be asked for permission for the further use of their data, which will be anonymized to ensure confidentiality and privacy.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePublic access to trial protocols is available through the trial registrations. Access to the study data is restricted to members of the research team only. According to Finnish legislations and institutional research permissions access to pseudonymised research data is granted only to members of the research team and do not allow sharing of data with third parties directly.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll data will be pseudonymized prior to statistical analyses and reported at an aggregate level to ensure that individual patients cannot be identified. The statistical code will be reported alongside the publication of study results, in accordance with standard principles of good scientific writing. Members of research group will have access to the final trial dataset. No contractual agreements exist that would limit investigator access.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStudy sponsor\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis is a researcher-initiated study, with Helsinki University Hospital (HUS) acting as an organizational sponsor. Contact information for HUS Jesper Ekelund, email: [email protected], HUS Psychiatry, Välskärinkatu 12, 00059 HUS, Finland.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe study is funded by the European Union\u0026nbsp;–\u0026nbsp;NextGenerationEU.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eRoles and responsibilities—sponsor and funder\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFunders or organizational sponsors had no role in the design of this study and will not have any role in the data management, analyses and interpretation of the data, nor in the decision to submit the reports for publication.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe study is coordination is led by PI, supported by the research team. No additional formal steering committee is established as this is a pragmatic, researcher-initiated trial conducted within routine public health care services and poses minimal risk. Data management is overseen by the research team, with institutional support from the respective wellbeing services counties and HUS. Outcomes are collected using validated self-report instruments or registry data, minimizing the need for external adjudication.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eData monitoring\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eA data monitoring committee (DMC) will not be established, as this is a low-risk, researcher-initiated trial involving non-invasive psychosocial interventions, with no planned interim analyses.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGBD 2019 Mental Disorders Collaborators. Global, regional, and national burden of 12 mental disorders in 204 countries and territories, 1990\u0026ndash;2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet Psychiatry. 2022 Feb;9(2):137\u0026ndash;50. \u003c/li\u003e\n\u003cli\u003eSmith ORF, Clark DM, Hensing G, Layard R, Knapstad M. Cost\u0026ndash;benefit of IAPT Norway and effects on work-related outcomes and health care utilization: results from a randomized controlled trial using registry-based data. Psychol Med. 2025;55:e86. \u003c/li\u003e\n\u003cli\u003eCastelnuovo G, Pietrabissa G, Cattivelli R, Manzoni GM, Molinari E. Not Only Clinical Efficacy in Psychological Treatments: Clinical Psychology Must Promote Cost-Benefit, Cost-Effectiveness, and Cost-Utility Analysis. Front Psychol. 2016;7:563. \u003c/li\u003e\n\u003cli\u003eLayard R, Clark DM. Why More Psychological Therapy Would Cost Nothing. Front Psychol. 2015;6:1713. \u003c/li\u003e\n\u003cli\u003eChisholm D, Sweeny K, Sheehan P, Rasmussen B, Smit F, Cuijpers P, et al. Scaling-up treatment of depression and anxiety: a global return on investment analysis. Lancet Psychiatry. 2016 May;3(5):415\u0026ndash;24. \u003c/li\u003e\n\u003cli\u003eCuijpers P, Noma H, Karyotaki E, Cipriani A, Furukawa TA. Effectiveness and Acceptability of Cognitive Behavior Therapy Delivery Formats in Adults With Depression: A Network Meta-analysis. JAMA Psychiatry. 2019 Jul 1;76(7):700. \u003c/li\u003e\n\u003cli\u003eCuijpers P, Miguel C, Harrer M, Plessen CY, Ciharova M, Ebert D, et al. Cognitive behavior therapy vs. control conditions, other psychotherapies, pharmacotherapies and combined treatment for depression: a comprehensive meta-analysis including 409 trials with 52,702 patients. World Psychiatry. 2023 Feb;22(1):105\u0026ndash;15. \u003c/li\u003e\n\u003cli\u003eCuijpers P, Koole SL, van Dijke A, Roca M, Li J, Reynolds CF. Psychotherapy for subclinical depression: meta-analysis. Br J Psychiatry. 2014 Oct;205(4):268\u0026ndash;74. \u003c/li\u003e\n\u003cli\u003eSzuhany KL, Simon NM. Anxiety Disorders: A Review. JAMA. 2022 Dec 27;328(24):2431. \u003c/li\u003e\n\u003cli\u003ePowell CLYM, Chiu CY, Sun X, So SH wai. A meta-analysis on the efficacy of low-intensity cognitive behavioural therapy for generalised anxiety disorder. BMC Psychiatry. 2024 Jan 2;24(1):10. \u003c/li\u003e\n\u003cli\u003eCuijpers P, Donker T, van Straten A, Li J, Andersson G. Is guided self-help as effective as face-to-face psychotherapy for depression and anxiety disorders? A systematic review and meta-analysis of comparative outcome studies. Psychol Med. 2010 Dec;40(12):1943\u0026ndash;57. \u003c/li\u003e\n\u003cli\u003eHedman-Lagerl\u0026ouml;f E, Carlbring P, Sv\u0026auml;rdman F, Riper H, Cuijpers P, Andersson G. Therapist-supported Internet-based cognitive behaviour therapy yields similar effects as face-to-face therapy for psychiatric and somatic disorders: an updated systematic review and meta-analysis. World Psychiatry. 2023 Jun;22(2):305\u0026ndash;14. \u003c/li\u003e\n\u003cli\u003eRosenstr\u0026ouml;m TH, Saarni SE, Saarni SI, Tammilehto J, Stenberg JH. Efficacy and effectiveness of therapist-guided internet versus face-to-face cognitive behavioural therapy for depression via counterfactual inference using naturalistic registers and machine learning in Finland: a retrospective cohort study. Lancet Psychiatry. 2025 Mar;12(3):189\u0026ndash;97. \u003c/li\u003e\n\u003cli\u003eJeitani A, Fahey PP, Gascoigne M, Darnal A, Lim D. Effectiveness of stepped care for mental health disorders: An umbrella review of meta-analyses. Pers Med Psychiatry. 2024 Nov;47\u0026ndash;48:100140. \u003c/li\u003e\n\u003cli\u003eDelgadillo J, Ali S, Fleck K, Agnew C, Southgate A, Parkhouse L, et al. Stratified Care vs Stepped Care for Depression: A Cluster Randomized Clinical Trial. JAMA Psychiatry. 2022 Feb 1;79(2):101\u0026ndash;8. \u003c/li\u003e\n\u003cli\u003eRivero-Santana A, Perestelo-Perez L, Alvarez-Perez Y, Ramos-Garcia V, Duarte-Diaz A, Linertova R, et al. Stepped care for the treatment of depression: a systematic review and meta-analysis. J Affect Disord. 2021 Nov;294:391\u0026ndash;409. \u003c/li\u003e\n\u003cli\u003eSalomonsson S, Santoft F, Linds\u0026auml;ter E, Ejeby K, Lj\u0026oacute;tsson B, \u0026Ouml;st LG, et al. Stepped care in primary care - guided self-help and face-to-face cognitive behavioural therapy for common mental disorders: a randomized controlled trial. Psychol Med. 2018 Jul;48(10):1644\u0026ndash;54. \u003c/li\u003e\n\u003cli\u003eClark DM. Implementing NICE guidelines for the psychological treatment of depression and anxiety disorders: The IAPT experience. Int Rev Psychiatry. 2011 Aug;23(4):318\u0026ndash;27. \u003c/li\u003e\n\u003cli\u003eKnapstad M, Nordgreen T, Smith ORF. Prompt mental health care, the Norwegian version of IAPT: clinical outcomes and predictors of change in a multicenter cohort study. BMC Psychiatry. 2018 Aug 16;18(1):260. \u003c/li\u003e\n\u003cli\u003eMcHugh P, Martin N, Hennessy M, Collins P, Byrne M. An evaluation of Access to Psychological Services Ireland: year one outcomes. Ir J Psychol Med. 2016 Dec;33(4):225\u0026ndash;33. \u003c/li\u003e\n\u003cli\u003eGandr\u0026eacute; C, Rosenberg S, Coldefy M, Or Z. Experimenting locally with a stepped-care approach for the treatment of mild to moderate mental disorders in France: Challenges and opportunities. Health Policy. 2019 Nov;123(11):1021\u0026ndash;7. \u003c/li\u003e\n\u003cli\u003eCano-Vindel A, Ruiz-Rodr\u0026iacute;guez P, Moriana J, Medrano L, Gonz\u0026aacute;lez-Blanch C, Aguirre E, et al. Improving Access to Psychological Therapies in Spain: From IAPT to PsicAP. Psicothema. 2022 Feb 1;1(34):18\u0026ndash;24. \u003c/li\u003e\n\u003cli\u003eAustralian Government Department of Health and Ageing. Primary Health Networks (PHN) primary mental health care guidance \u0026ndash; stepped care [Internet]. Australian Government Department of Health and Aged Care; 2021 [cited 2025 Jun 11]. Available from: https://www.health.gov.au/resources/publications/primary-health-networks-phn-primary-mental-health-care-guidance-stepped-care?language=en\u003c/li\u003e\n\u003cli\u003eClark DM, Canvin L, Green J, Layard R, Pilling S, Janecka M. Transparency about the outcomes of mental health services (IAPT approach): an analysis of public data. The Lancet. 2018 Feb 17;391(10121):679\u0026ndash;86. \u003c/li\u003e\n\u003cli\u003eChan AW, Tetzlaff JM, Altman DG, Laupacis A, G\u0026oslash;tzsche PC, Krleža-Jerić K, et al. SPIRIT 2013 Statement: Defining Standard Protocol Items for Clinical Trials. Ann Intern Med. 2013 Feb 5;158(3):200\u0026ndash;7. \u003c/li\u003e\n\u003cli\u003eKroenke K. Enhancing the clinical utility of depression screening. Can Med Assoc J. 2012 Feb 21;184(3):281\u0026ndash;2. \u003c/li\u003e\n\u003cli\u003eSpitzer RL, Kroenke K, Williams JBW, L\u0026ouml;we B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med. 2006 May 22;166(10):1092\u0026ndash;7. \u003c/li\u003e\n\u003cli\u003eSaarni SI, Nurminen S, Mikkonen K, Service H, Karolaakso T, Stenberg JH, et al. The Finnish therapy navigator \u0026ndash; digital support system for introducing stepped care in Finland. Psychiatr Fenn. 2022(53):120\u0026ndash;37. \u003c/li\u003e\n\u003cli\u003eLuedtke A, Sadikova E, Kessler RC. Sample Size Requirements for Multivariate Models to Predict Between-Patient Differences in Best Treatments of Major Depressive Disorder. Clin Psychol Sci. 2019 May 1;7(3):445\u0026ndash;61. \u003c/li\u003e\n\u003cli\u003eKroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001 Sep;16(9):606\u0026ndash;13. \u003c/li\u003e\n\u003cli\u003eSpitzer RL, Kroenke K, Williams JBW, L\u0026ouml;we B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med. 2006 May 22;166(10):1092\u0026ndash;7. \u003c/li\u003e\n\u003cli\u003eKounali D, Button KS, Lewis G, Gilbody S, Kessler D, Araya R, et al. How much change is enough? Evidence from a longitudinal study on depression in UK primary care. Psychol Med. 2022 Jul;52(10):1875\u0026ndash;82. \u003c/li\u003e\n\u003cli\u003eRichards DA, Ekers D, McMillan D, Taylor RS, Byford S, Warren FC, et al. Cost and Outcome of Behavioural Activation versus Cognitive Behavioural Therapy for Depression (COBRA): a randomised, controlled, non-inferiority trial. The Lancet. 2016 Aug 27;388(10047):871\u0026ndash;80. \u003c/li\u003e\n\u003cli\u003eJulious SA. Sample sizes for clinical trials with Normal data. Stat Med. 2004 Jun 30;23(12):1921\u0026ndash;86. \u003c/li\u003e\n\u003cli\u003eRitola V, Lipsanen JO, Pihlaja S, Gummerus EM, Stenberg JH, Saarni S, et al. Internet-Delivered Cognitive Behavioral Therapy for Generalized Anxiety Disorder in Nationwide Routine Care: Effectiveness Study. J Med Internet Res. 2022 Mar 24;24(3):e29384. \u003c/li\u003e\n\u003cli\u003eSaarni SE, Rosenstr\u0026ouml;m T, Stenberg JH, Plattonen A, Holi M, Ekelund J, et al. Finnish Psychotherapy Quality Register: rationale, development, and baseline results. Nord J Psychiatry. 2023 Jul 3;77(5):455\u0026ndash;66. \u003c/li\u003e\n\u003cli\u003evan Buuren S. Flexible Imputation of Missing Data [Internet]. 2nd edition. 2018 [cited 2025 Jun 10]. Available from: https://stefvanbuuren.name/fimd/\u003c/li\u003e\n\u003cli\u003ePoisot T. The digitize package: extracting numerical data from scatterplots. The R Journal. 2011;3(1):25\u0026ndash;6. \u003c/li\u003e\n\u003cli\u003eLaan MJ van der, Rose S. Targeted learning: causal inference for observational and experimental data. New York: Springer Verlag; 2011. \u003c/li\u003e\n\u003cli\u003eConnor 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 Apr;176:379\u0026ndash;86. \u003c/li\u003e\n\u003cli\u003eFurukawa TA, Katherine Shear M, Barlow DH, Gorman JM, Woods SW, Money R, et al. Evidence-based guidelines for interpretation of the Panic Disorder Severity Scale. Depress Anxiety. 2009;26(10):922\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eKriston L, H\u0026ouml;lzel L, Weiser AK, Berner MM, H\u0026auml;rter M. Meta-analysis: are 3 questions enough to detect unhealthy alcohol use? Ann Intern Med. 2008 Dec 16;149(12):879\u0026ndash;88. \u003c/li\u003e\n\u003cli\u003eAllen JP, Litten RZ, Fertig JB, Babor T. A review of research on the Alcohol Use Disorders Identification Test (AUDIT). Alcohol Clin Exp Res. 1997 Jun;21(4):613\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eBerman AH, Berman H, Palmstierna T, Schlyter F. Drug Use Disorders Identification Test (DUDIT) [Internet]. 2024 [cited 2024 Nov 11]. Available from: file:///C:/Users/HUS672~1/AppData/Local/Temp/MicrosoftEdgeDownloads/37be8d7a-a787-4455-b2f8-e3232829d4ed/FI_DUDIT%20suomalainen%20versio.pdf\u003c/li\u003e\n\u003cli\u003eFoa EB, Huppert JD, Leiberg S, Langner R, Kichic R, Hajcak G, et al. The Obsessive-Compulsive Inventory: development and validation of a short version. Psychol Assess. 2002 Dec;14(4):485\u0026ndash;96. \u003c/li\u003e\n\u003cli\u003eSchaufeli W, De Witte H, Desart S. Burnout Assessment Tool (BAT) \u0026ndash; Test Manual [Internet]. 2020. Available from: https://burnoutassessmenttool.be/wp-content/uploads/2020/08/Test-Manual-BAT-English-version-2.0-1.pdf\u003c/li\u003e\n\u003cli\u003eBrewin CR, Rose S, Andrews B, Green J, Tata P, McEvedy C, et al. Brief screening instrument for post-traumatic stress disorder. Br J Psychiatry. 2002 Aug;181:158\u0026ndash;62. \u003c/li\u003e\n\u003cli\u003eGon\u0026ccedil;alves MM, Lutz W, Schwartz B, Oliveira JT, Saarni SE, Tishby O, et al. Developing a European Psychotherapy Consortium (EPoC): Towards adopting a single-item self-report outcome measure across European countries. Clin Psychol Eur. 2024 Sep 30;6(3):e13827. \u003c/li\u003e\n\u003cli\u003eMikkonen K, Bombino A, Villa A, Nurminen S, Roiha RM, Roslund P, et al. Guided Self-help in the Treatment of Common Mental Health Disorders - The development of the Finnish guided self-help (F-GSH) model. Psychiatr Fenn. 2024(55):30\u0026ndash;41\u003c/li\u003e\n\u003cli\u003eRosenstr\u0026ouml;m TH, Saarni SE, Saarni SI, Tammilehto J, Stenberg JH. Efficacy and effectiveness of therapist-guided internet versus face-to-face cognitive behavioural therapy for depression via counterfactual inference using naturalistic registers and machine learning in Finland: a retrospective cohort study. Lancet Psychiatry [Internet]. 2025 Feb 12 [cited 2025 Feb 13];0(0). Available from: https://www.thelancet.com/journals/lanpsy/article/PIIS2215-0366(24)00404-8/fulltext#fig1\u003c/li\u003e\n\u003cli\u003eMikkonen K, Saarni SE, Nurminen S, Stenberg JH, Ekelund J, Villa A, et al. Cognitive brief therapy provides help in a mental health crisis. [Kognitiivinen lyhytterapia tuo apua mielenterveyskriisiin]. Suom L\u0026auml;\u0026auml;k\u0026auml;ril 2024;79:e39914. Available from: www.laakarilehti.fi/e39914 \u003c/li\u003e\n\u003cli\u003eHarris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)\u0026mdash;A metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009 Apr;42(2):377\u0026ndash;81. \u003c/li\u003e\n\u003cli\u003eMcMillan D, Gilbody S, Richards D. Defining successful treatment outcome in depression using the PHQ-9: A comparison of methods. J Affect Disord. 2010 Dec;127(1\u0026ndash;3):122\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eToussaint A, H\u0026uuml;sing P, Gumz A, Wingenfeld K, H\u0026auml;rter M, Schramm E, et al. Sensitivity to change and minimal clinically important difference of the 7-item Generalized Anxiety Disorder Questionnaire (GAD-7). J Affect Disord. 2020 Mar;265:395\u0026ndash;401. \u003c/li\u003e\n\u003cli\u003eFinnish Institute for Health and Welfare (THL). Healthy Finland Survey [Internet]. 2025 [cited 2025 Jun 5]. Available from: https://thl.fi/en/research-and-development/research-and-projects/healthy-finland-survey\u003c/li\u003e\n\u003cli\u003eM\u0026auml;klin S, Kokko P. The unit costs of health and social care in Finland in 2017 [Internet]. 2021 [cited 2025 Jun 5]. Available from: https://www.julkari.fi/handle/10024/142882\u003c/li\u003e\n\u003cli\u003eSzuhany KL, Simon NM. Anxiety Disorders: A Review. JAMA. 2022 Dec 27;328(24):2431. \u003c/li\u003e\n\u003cli\u003ePowell CLYM, Chiu CY, Sun X, So SH wai. A meta-analysis on the efficacy of low-intensity cognitive behavioural therapy for generalised anxiety disorder. BMC Psychiatry. 2024 Jan 2;24(1):10. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bpsy","sideBox":"Learn more about [BMC Psychiatry](http://bmcpsychiatry.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bpsy/default.aspx","title":"BMC Psychiatry","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Depression, Anxiety, Randomized controlled trial, Cognitive behavioral therapy, Guided self-help, Internet-delivered CBT, Stepped care, Cost-effectiveness, Waiting-time","lastPublishedDoi":"10.21203/rs.3.rs-7039628/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7039628/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLow-intensity cognitive behavioral therapy (CBT) based guided self-help (GSH) and therapist-guided internet-delivered CBT (iCBT) have demonstrated equivalent effectiveness and superior cost-efficiency compared to traditional face-to-face CBT (fCBT) for treating depression and anxiety. This study aims to address critical gaps in the current understanding of the effectiveness and cost-effectiveness of various CBT interventions for depression and anxiety within a stepped care model.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis paper outlines FLT-step, a multi-center randomized controlled trial (RCT) study with four parallel study protocols for examining widely used CBT interventions in public healthcare using a stepped care approach. The objective is to compare the effectiveness and cost-effectiveness of three treatment approaches for depression (protocol 1) and anxiety (protocol 2) in a non-inferiority setting within the Finnish public healthcare: A) a stepped care model (GSH followed by fCBT for non-responders), B) fCBT, and C) therapist-guided iCBT. The non-inferiority margin was based on patient-detectable improvement and is set at 1.7 points on the Patient Health Questionnaire (PHQ-9, protocol 1) and 1.5 points on the Generalized Anxiety Disorder 7-item scale (GAD-7, protocol 2). We plan to recruit 948 adults (≥ 16 years old) with depression (PHQ-9 ≥ 10 p) and 948 adults with anxiety (GAD-7 ≥ 10 p). A randomized sub study will examine the effect of waiting time (≤4 or ≥ 5 weeks) for the treatment outcomes of depression (n = 115, protocol 3) or anxiety (n = 115, protocol 4), comparing the stepped care model (A) and fCBT (B). In all four RCTs, the primary outcome measures are the within-individual change in depression (PHQ-9) or anxiety (GAD-7) symptoms at six months. Secondary outcomes include wellbeing, work and social ability, costs associated with illness, and quality of life. The follow-up is planned to span up to 20 years. Finnish national registry data will be used to supplement participant data and create population-matched controls to evaluate whether the interventions can prevent clinical episodes, reduce long-term societal costs, and decrease somatic morbidity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiscussion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis extensive RCT aims to deliver new insights into comparative effectiveness and cost-effectiveness of widely utilized low-intensity CBT treatments for depression and anxiety, and the impact of waiting times on outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial Registrations (Registration date):\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eISRCTN14296278 (18 Sep 2024), ISRCTN63914711 (8 Oct 2024), ISRCTN10064801 (20 Sep 2024), ISRCTN14990924 (8 Oct 2024)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIssue date:\u003c/strong\u003e 3 Jul 2025\u003c/p\u003e\n\u003cp\u003eEeva-Eerika Helminen and Suoma E. 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