Theoretical background: Facing serious physical illness can be understood as a traumatic experience. Patients’ narratives of their illness can help to structure the physical and psychological burdens, that are difficult to narrate, reinterpret the experience of illness as a psychological stressor, thereby reducing psychological distress and improving coping and thus recovery. For this reason, the practice of health psychology requires the use of methods that can accurately and effectively explore the narratives of the illness trajectory based on simple tools. Objective: The aim of our study was the Hungarian adaptation of the Emotional Graph of Illness Trajectory, a tool for exploring the emotional perspective of the illness narrative, in patients operated on for chronic disease or malignant tumour. Methods: Our mixed methods study involved 120 patients. In addition to the Emotional Graph of Illness Trajectory based on the visual elicitation technique, we used the Spielberger State -Trait Anxiety Inventory, the short form of Beck Depression Inventory, the short form of Perceived Stress Scale, the EQ-5D-3L questionnaire and the Brief Illness Perception Questionnaire. Results: The main results of the convergent validity test showed that the total intensity value of the graphical emotion showed a significant, positive, moderate-strength correlation with the depression score (r = 0.33; p < 0.001). For those who depicted negative emotion, there was a moderate-strength, positive directional correlation between the mean value of the intensity of the graphically depicted emotion with the scores for state (r = 0.31; p = 0.004) and trait anxiety (r = 0.30; p = 0.004), illness perception (r = 0.35; p = 0.001), perceived stress (r = 0.37; p < 0.001) and depression (r = 0.41); p < 0.001), and there was also a moderately strong, positive, significant relationship between the total intensity value of the graphical emotion and the perception of illness (r = 0.34; p = 0.001), the level of perceived stress (r = 0.32; p = 0.002) and depression (r = 0.40; p < 0.001), and between the emotion intensity score of final event and the state anxiety (r = 0.33; p = 0.002) and depression (r = 0.31; p = 0.003) scores. Results for individuals depicting positive emotion showed a significant, negative direction, moderate strength correlation between the intensity value of the graphically depicted emotion associated with the closing event and the score of state (r = -0.36; p = 0.048) and trait anxiety (r = -0.36; p = 0.045). The main results of the test of concurrent validity showed a significant, positive, moderate-strength correlation between the mean value of the intensity of the emotion depicted in the graph and the score of the emotional dimension of illness perception (r = 0.35; p =0.001) in a sample of individuals who depicted a negatively charged emotion in their graph and the total score of the graphical emotion intensity and the score of the emotional dimension of quality of life (r = 0.30; p = 0.005). An outstanding finding of our research is that the three disease narratives identified by the two independent coders (i.e: chaos, restitution and quest story), there was a significant difference in the mean intensity of the graphically depicted emotion (F(2, 117) = 4.254; MSE = 403.528; p = 0.016; η2 = 0.07), the value of the closing event emotion intensity (H(2) = 10.297); p = 0.006; η2 = 0.10), trait anxiety (F(2, 117) = 4.070; MSE = 102.556; p = 0.020; η2 = 0.07), perceived stress (F(2, 117) = 5.895; MSE = 34.058; p = 0.004; η2 = 0.09) and perception of illness (F(2, 117) = 4.807; MSE = 175.871; p = 0.010, η2 = 0.08). Conclusions: The Emotional Graph of Illness Trajectory has adequate psychometric properties and its validity in the population studied in the present research is considered good. The technique has been shown to be an effective tool in exploring the emotional perspective associated with the illness narrative.