Relatives of patients with severe brain injury: Growth curve analysis of anxiety and depression the first year after injury

Research output: Contribution to journalJournal articleResearchpeer-review

PRIMARY OBJECTIVE: To investigate trajectories and predictors of trajectories of anxiety and depression in relatives of patients with a severe brain injury during the first year after injury.

RESEARCH DESIGN: A prospective longitudinal study with four repeated measurements.

SUBJECTS: Ninety relatives of patients with severe brain injury.

METHODS: The relatives were assessed on the anxiety and depression scales from the Symptom Checklist-90-Revised and latent variable growth curve models were used to model the trajectories. The effects of patient's age, patient's Glasgow Coma Score, level of function and consciousness, gender and relationship of the relatives were modelled.

RESULTS: Improvement was found in both symptoms of anxiety and depression during the 12-month study period. The analysis revealed different trajectories for symptoms of anxiety and depression, as anxiety had a more rapid improvement. Higher initial level of symptoms of depression was seen in female relatives. Higher initial level of anxiety was associated with younger patient age, lower level of function and consciousness in the patient and the relative being female or the spouse.

CONCLUSION: Future research and interventions should focus not only on specific deficits in the patient, but also on how the emotional state and well-being of the relatives evolve, while trying to adjust and cope with a new life-situation.

Original languageEnglish
JournalBrain Injury
Volume29
Issue number7-8
Pages (from-to)822-829
Number of pages8
ISSN0269-9052
DOIs
Publication statusPublished - 2015

    Research areas

  • Adaptation, Psychological, Adolescent, Adult, Anxiety, Brain Injuries, Depression, Emotions, Family, Female, Humans, Longitudinal Studies, Male, Middle Aged, Prospective Studies, Quality of Life, Stress Disorders, Post-Traumatic, Stress, Psychological, Time Factors

ID: 162717231