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This study aims to evaluate the efficacy of a specially developed internet-based Cognitive Behavioural Therapy (CBT) programme with human interaction-referred to as the 3D programme-tailored specifically for women experiencing mild to moderate depressive symptoms. We hypothesise that participation in the intervention will lead to greater improvements in depression severity, compared to receiving only brief psychoeducational videos, when used as an add-on to treatment as usual (TAU) in this population.
The 3D programme is a 10-week blended intervention that includes ten weekly online self-guided modules focused on depression and women's health, along with six individual video sessions with a health/clinical psychologist. The modules cover topics such as mood changes across the menstrual cycle, body image, stress, caregiving, and the impact of gender-based experiences on mental health.
To explore how biological factors may influence how participants respond to treatment, the study will collect biological samples. These will be analysed to track hormone and metabolic changes, with the goal of identifying biological markers that might predict who benefits most from the intervention.
Ultimately, the results of this study aim to improve access to effective and personalised mental health care for women by evaluating whether a structured and personalised online CBT programme can provide meaningful benefits.
Full description
OBJECTIVES Primary objective: To assess the impact of the 3D programme on depressive symptom severity compared to a psychoeducational control condition.
Secondary objectives: To evaluate improvements in overall functioning, quality of life, perceived stress, and menstruation-related distress. Additionally, the study will investigate metabolic signatures associated with treatment response, focusing on tryptophan and steroid hormone pathways.
HYPOTESES Main hypothesis: Participation in the 3D programme will lead to greater improvements in depression severity (measured by HDRS-17) compared to receiving only informational materials when used as an add-on to Treatment As Usual (TAU) in women experiencing mild to moderate depressive episodes.
Secondary hypotheses:
SAMPLE SIZE ESTIMATION AND RECRUITMENT The optimal sample size is estimated to be 60 participants per group. This calculation is based on a Cohen's d effect size of 0.2, a 95% confidence interval, a statistical power of 90%, and an anticipated attrition rate of 20%. Sample size estimation was conducted using G* Power 3.1.7 software.
All patients meeting the inclusion and exclusion criteria will be invited to participate in the study by their treating team at the outpatient mental health facilities within Hospital del Mar. Additionally, gynaecologists at Hospital del Mar will be encouraged to refer patients suspected of experiencing depressive symptoms. In such cases, patients will be screened by the study psychologist/psychiatrist to confirm these symptoms. Recruitment will conclude upon reaching the target of 120 participants with complete data.
RANDOMISATION AND BLINDING Participants will be randomised in a 1:1 ratio using the REDCap randomisation module, which will automatically assign participants to either the experimental or control group through simple randomisation with equal allocation.
This study will implement single blinding. Due to the nature of the intervention, participants will be aware of their group assignment (experimental or control) following randomisation. Likewise, therapists delivering the intervention will be aware of the assigned group, as is standard practice in psychological intervention trials. To uphold the integrity of the blinding process, the following measures will be applied:
STUDY DESING Part 1. Randomised controlled trial The study follows a naturalistic treatment approach, ensuring that all participants continue their usual care. The study will be conducted in accordance with the CONSORT guidelines.
PART 2. Metabolic signature of treatment response The metabolic signature of treatment response will be characterised through the analysis of tryptophan and steroid-related pathways. All analyses will be conducted using methods developed and validated by the Applied Metabolomic Research Group at Hospital del Mar Research Institute, ensuring proper sample handling protocols as outlined in previous studies.
Tryptophan Metabolism:
Tryptophan pathway metabolites-including tryptophan, kynurenine, serotonin, 3-hydroxykynurenine, 5-hydroxyindoleacetic acid, and kynurenic acid-will be quantified using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The analysis will follow the protocol established by Marcos et al.
Analysis will focus on the kynurenine/tryptophan (K/T) ratio, a marker of indoleamine-2,3-dioxygenase (IDO) activity, which plays a key role in immune regulation and inflammatory responses.
Additionally, serotonin synthesis and its relationship with tryptophan availability will be assessed, alongside the tryptophan/large neutral amino acid (LNAA) ratio, which serves as an indicator of tryptophan's availability for serotonin production. Data will be integrated using network analysis to identify potential associations between these metabolites and treatment response.
Steroid Hormones:
The steroid profile will be analysed to monitor key sex hormones (e.g., estradiol, testosterone, progesterone) and glucocorticoids (e.g., cortisol, 20α-DHE, and 20β-DHE), along with their metabolites. These hormones play a pivotal role in modulating inflammation and metabolic pathways, with altered levels linked to physiological stress responses and treatment outcomes. These measurements will be performed by LC-MS/MS, following the method previously outlined by the research group.
Biological Samples:
Analysis will be conducted using various biological matrices, including blood, saliva, urine, nails, and hair, to provide complementary insights. Saliva, blood, and urine samples will capture acute metabolic changes at the time of the visit, while nails and hair will reflect chronic metabolite production.
ASSESSMENTS Assessments will be carried out at baseline (T0), immediately following the intervention (3 months after baseline, T1), and at a follow-up assessment (6 months after baseline, T2).
The baseline assessment will include:
Clinical data and biological samples will be collected at all time points.
DATA MANAGEMENT All the data will be text-based (.docx) or numeric format (.xlsx). For all published files, a document record and change track will be included (author contact information, status, version, change reason and date, contents" description, title, origin of the data including a description of the measurement and/or experiment setup) in a separate metadata file for each characterization action called METADATA.ODS.
Data will be stored on a secure server at the Hospital del Mar Research Institute, in compliance with EU and Spanish data protection regulations (General Data Protection Regulation, GDPR, of May 25, 2018; and Organic Law 3/2018 of December 5, on the Protection of Personal Data and Guarantee of Digital Rights).
STATISTICAL ANALYSIS
Primary and Secondary Outcomes:
Analyses will follow an intention-to-treat (ITT) approach, including all participants according to their randomized allocation, regardless of adherence to the intervention.group. Linear mixed-effects models (LMMs) will be used to examine changes over time and between groups for the HDRS-17, WHO-DAS 2.0, EQ-5D-5L, PSS, and MEDI-Q scores. These models will include fixed effects for group, time, and their interaction, and a random intercept for participants to account for within-subject correlation over time. Where appropriate, subscale-level analyses and models using change scores will also be conducted for secondary outcomes. To further explore the temporal dynamics of the intervention's effects, post hoc simple effects analyses will be performed to probe significant interactions.
Additional Analyses:
LLMs and multiple linear regression models will be employed to identify predictors of clinical improvement. Additionally, moderator analyses using linear mixed models will assess whether levels of perceived stress (PSS), or menstrual distress (MEDI-Q) influence treatment response as measured by changes in HDRS-17 scores over time.
Exploratory Biomarker Analyses:
Partial Least Squares Regression (PLSR) and multiple regression will be conducted to model associations between metabolite profiles, their changes over time, and changes in depressive symptoms. Variable Importance in Projection (VIP) scores and cross-validation techniques will be applied to evaluate model performance and identify key predictive biomarkers. Additionally, metabolomic evolution will be assessed through exploratory factor analysis, grouping variables into latent factors.
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120 participants in 2 patient groups
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Data sourced from clinicaltrials.gov
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