1. M.I.N.I scale rating without any mental disorder;
2. Patient Health Questionnaire (PHQ-9) < 5;
3. No history of mental illness, no family genetic history;
4. Age 18-60 years old, Males;
5. Voluntary informed consent form.

1. Patients with a first depressive disorder meeting DSM-5 criteria;
2. Age 18-60 years, Males;
3. Voluntary informed consent.

1. Clinical complaints meeting Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria for the diagnosis of depressive disorder;
2. Patients with first-episode fraudulent disease who meet the DSM-5 criteria for the diagnosis of Z76.5;
3. Age 18-60 years, Males;
4. Voluntary informed consent.

Nicotinic skin reaction, also known as nicotinic flush reaction, occurs when a solution of nicotinic acid methyl ester briefly contacts the skin. Following penetration through the skin barrier into the subcutaneous tissue, it generates nicotinic acid (vitamin B3). Under the action of phospholipase A2 (PLA2), cyclooxygenase (COX), and other enzymes, arachidonic acid (AA) on the cell membrane is cleaved to produce prostaglandins, leading to local vasodilation, increased blood perfusion, and the transient appearance of erythema on the skin.

Total niacin reaction score: It includes one value (Total Area), which refers to the sum of nicotinic acid reaction areas for each concentration (a total of 360) collected within 10 minutes from 60 images.

Total single point score for niacin reaction: It includes six values, each representing the sum of nicotinic acid reaction areas for individual concentrations (a total of 360) collected within 10 minutes from 60 images.

Niacin reaction speed: It includes one value (EC50), representing the time required for the nicotinic acid reaction of the first concentration to reach half of the plateau phase.

Niacin flush color: It includes one value (Total Color), which refers to the color value of 6 flush areas in the images captured at the 10th minute.

Evaluate the effectiveness of the classification model in identifying feigned depression patients through measures such as the area under curve (AUC), sensitivity (Sen), specificity (Sep), positive predictive value (PPV), and negative predictive value (NPV), where higher AUC, Sen, Sep, PPV, and NPV values indicate better classification performance of the model.