Exploring self-esteem during expressive writing about trauma predicts decreased depression in people with HIV.
Rachel M VerhagenAdam W CarricoEmily M HyltonRick StuetzleGail IronsonPublished in: AIDS care (2023)
Self-esteem is often negatively impacted by trauma. Low self-esteem has been related to significantly worse depression in people with HIV (PWH). This study explores whether the expression of words related to self-esteem during a 4-session augmented trauma writing intervention predicted post-traumatic stress, depressive symptoms, and health outcomes 6-months later. Ninety-five PWH completed four 30-minute augmented trauma writing sessions in the intervention arm of a randomized controlled trial. One augmented session was devoted to self-esteem. Two individuals coded trauma essays for number of self-esteem words. CD4+ and viral load data were collected, and the Davidson PTSD Scale and the Hamilton Depression Rating Scale were administered at baseline, one-, and six-month follow-up. Greater total self-esteem words were related to lower depressive symptoms at 6-months, controlling for depressive symptoms at study entry, age, race, and education (t(80) = -2.235, ß = -0.239, SE = 0.283, p < 0.05, 95% CI [-1.195, -.069). Total self-esteem words were not predictive of PTSD, viral load, or CD4+ at 6-months. Exploring self-esteem when writing about and processing a traumatic event could be an important mechanism for decreasing depressive symptoms among PWH. Research is needed to test augmented expressive writing interventions that support efforts to bolster self-esteem in PWH.
Keyphrases
- depressive symptoms
- social support
- sleep quality
- trauma patients
- hiv infected
- antiretroviral therapy
- randomized controlled trial
- human immunodeficiency virus
- hiv positive
- healthcare
- hiv testing
- hepatitis c virus
- spinal cord injury
- electronic health record
- quality improvement
- physical activity
- high intensity
- virtual reality
- big data
- binding protein
- working memory
- transcranial direct current stimulation
- machine learning
- artificial intelligence