Clinical Psychology & Psychotherapy, Год журнала: 2024, Номер 31(5)

Опубликована: Сен. 1, 2024

ABSTRACT Background Depression is generally perceived from the perspective of common‐cause disease model. However, network assumes mutual influence individual symptoms and stresses importance investigating symptom dynamics. Gaining a better understanding dynamics within individuals might contribute to more effective treatments. Methods Current exploratory longitudinal research studied associations directionality between 43 generic questionnaire Symptom Questionnaire‐48 (SQ‐48) using dynamic time warp (DTW) analyses, in which trajectories with similar time‐dependent patterns can be identified. Data were analysed first, yielding distance matrices for all trajectories, after data aggregated. Results The 148 included patients admitted treatment their clinical depression. Undirected DTW analyses three longer series but otherwise randomly chosen showed large variability among individuals. Group‐level undirected numerous significant edges symptoms, largely clustering according eight pre‐existing subscales SQ‐48. directed five outstrength: ‘hopeless’, ‘restless’, ‘down/depressed’, ‘feeling tense’ ‘no enjoyment’, meaning that change these key preceded other symptoms. Limitations SQ‐48 primarily focus on internalizing problems severely depressed inpatients, potentially limiting generalizability. Conclusions networks provided us based scores. Future studies could explore whether process‐based therapy targeted at high outstrength result effectivity as part personalized treatment.

Язык: Английский