Major Depressive Disorder
Conditions
Keywords
Major Depressive Disorder, Tourism, MMD
Brief summary
Empirically investigating how natural tourism activities alleviate symptoms in patients with Major Depressive Disorder through multidimensional pathways of physiological, psychological, and social functioning.
Detailed description
This study is an interventional randomized controlled trial aimed at evaluating whether natural tourism activities can improve the clinical symptoms of patients with Major Depressive Disorder and exploring the multidimensional mechanisms involving physiological, psychological, and social functioning. The target participant population is adult patients aged 18-60 who meet the DSM-5 diagnostic criteria for a major depressive episode. The core question to be addressed is whether the natural tourism intervention can significantly reduce the MADRS scores of patients with Major Depressive Disorder. Researchers will compare the intervention group (receiving structured tourism activities + conventional drug therapy) with the control group (receiving conventional drug therapy only) to verify the improvement effect of the tourism intervention on depressive symptoms and its potential mechanisms. Participants will complete the following tasks: * Participate in a one-day structured natural tourism activity; * Complete multiple scale assessments (including MADRS, HAMD-17, GAD-7, etc.) at baseline, on the day of intervention, and at one week and two weeks after the intervention; * Wear smart wearable devices to monitor physiological indicators such as sleep, heart rate and stress levels. From a theoretical perspective, this study promotes the transformation of tourism research from a pleasure consumption paradigm to a neurobiological intervention paradigm, aiming to propose an interdisciplinary mechanistic research pathway that reveals the positive therapeutic effects of tourism experiences on the pathology of Major Depressive Disorder. From a policy perspective, validating the clinical utility of tourism may reshape social prescription systems. While countries such as New Zealand and the United Kingdom have piloted nature prescription programs, there remains a lack of disease-specific protocols and efficacy evidence. Therefore, structured tourism interventions are expected to become a cost-effective complement to traditional treatments. As an interdisciplinary product integrating tourism and medicine, tourism therapy may emerge as a promising non-pharmacological prevention and treatment strategy. For tourism academia, it facilitates a theoretical transition from enhancing general well-being to clinical therapeutic applications; for mental health practice, it has the potential to break away from conventional treatments and establish itself as a novel therapeutic modality. Thus, in-depth exploration of the mechanisms through which tourism benefits patients with Major Depressive Disorder holds significant theoretical and practical implications. Employing a randomized controlled trial design, this study transcends the inherent limitations of cross-sectional research, aiming to provide innovative solutions to the global mental health crisis. The findings are expected to not only enrich guidelines for non-pharmacological interventions but also advance the transformation of the tourism industry toward a healing economy paradigm.
Interventions
BEHAVIORALTourism-based intervention
Following the acquisition of participant consent and the signing of (electronic) informed consent forms, subjects were randomized into either an intervention group or a control group using a computer-generated randomization list. The intervention group received a tourism-based intervention, while the control group continued to receive usual care without any structured modifications to their daily living patterns or treatment plans. Both groups maintained a foundational treatment regimen of antidepressant medication.
Sponsors
Shandong University
Shandong Provincial Hospital
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
TREATMENT
Masking
SINGLE (Outcomes Assessor)
Eligibility
Sex/Gender
ALL
Age
18 Years to 59 Years
Healthy volunteers
No
Inclusion criteria
1. Voluntarily participate in the study and sign the informed consent form; 2. Age between 18 (inclusive) and 60 (exclusive) at the screening period; 3. Meet the DSM-5 diagnostic criteria for a Major Depressive Episode (MDE) at enrollment, based on medical records, clinical assessment, and the Mini-International Neuropsychiatric Interview (MINI version 7.0.2); 4. Hamilton Depression Rating Scale 17-item (HAMD-17) score ≥ 17 at both screening and baseline; 5. Physically stable based on medical history and vital signs (including blood pressure); 6. Deemed by the investigator to be capable of independently completing all assessment tools required by the study protocol and willing to comply with the trial procedures throughout the study period.
Exclusion criteria
1. Current or past diagnosis of: schizophrenia, psychotic disorders (unless substance-induced or due to another medical condition), bipolar disorder, delusional disorder, paranoid personality disorder, schizoaffective disorder, borderline personality disorder, or other severe psychiatric comorbidities confirmed by medical history and structured clinical assessment using the Mini-International Neuropsychiatric Interview (MINI version 7.0.2); 2. Current or history of alcohol or substance abuse within the past year; 3. A score of ≥3 on item 3 (suicide) of the HAMD-17, suicide attempt within the past year, or clinically assessed significant suicide risk; 4. Depression secondary to other severe medical conditions (e.g., hypothyroidism, Parkinson's disease, etc.); 5. Cardiovascular diseases: stroke or myocardial infarction within the past year, hypertension (blood pressure \>140/90 mmHg), or clinically significant arrhythmia; 6. Other significant comorbid diseases that may interfere with the interpretation of study results or pose risks to participant health (e.g., cardiovascular, respiratory, gastrointestinal, hepatic, renal, or other systemic diseases), as determined by the investigator; 7. Current participation in an interventional study for Major Depressive Disorder, or participation in such a study within 30 days prior to screening; 8. Having visited Wulongtan Park, Baotu Spring Park and Daming Lake Park for a prolonged period (single stay ≥1 hour) within the past three years.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Change in Depressive Symptoms | Baseline, intervention day 1 | MADRS (Clinician-focused), Change from baseline in MADRS total score (range 0-60; higher = worse) |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Remission from Depression | Baseline, 2-week follow-up | MADRS (Clinician-focused), MADRS total score ≤10 |
| Response from Depression | Baseline, 2-week follow-up | MADRS (Clinician-focused), ≥50% reduction from baseline in MADRS total score |
| Change in Depressive Symptoms | Baseline, intervention day 1, 1-week follow-up, and 2-week follow-up | Change from baseline in HAM-D-17 (Clinician-focused), total score(higher = worse) |
| Change in Anxiety Symptoms | Baseline, intervention day 1, 1-week follow-up, and 2-week follow-up | GAD-7 (Patient-centered), Change from baseline in GAD-7 total score(higher = worse) |
| Clinical Improvement | Baseline, 2-week follow-up | CGI-I response (defined as a CGI-I score of very much improved or much improved). |
Other
| Measure | Time frame | Description |
|---|---|---|
| Change in cognitive function | Baseline, 2-week follow-up | Change from baseline in PDQ-D-20 total score (higher = worse) |
| Physiological Variability | Baseline, intervention day 1, 1-week follow-up, and 2-week follow-up | stress score change from baseline (higher = worse). Monitoring the stress levels of enrolled participants using smart wearable devices. The Heart Rate Variability (HRV) data collected by smart wearable devices is input into a specialized stress calculation model. This model comprehensively considers parameters such as the time-series features and frequency-domain features of the Heart Rate Variability. Utilizing machine learning or statistical analysis methods, the model establishes a mapping relationship between HRV and stress state to estimate the user's current stress level, which is then presented in the form of a stress score. |
| Change in functional impairment | Baseline, 2-week follow-up | Change from baseline in WSAS total score (higher = worse) |
| Change in quality of life | Baseline, 2-week follow-up | Change from baseline in Q-LES-Q-SF total score(higher = better) |
Countries
China
Contacts
Primary ContactShuping Shen
Outcome results
None listed