Abstract: Mental Health Recovery after Hurricane Harvey (Society for Social Work and Research 26th Annual Conference - Social Work Science for Racial, Social, and Political Justice)

Mental Health Recovery after Hurricane Harvey

Saturday, January 15, 2022
Liberty Ballroom K, ML 4 (Marriott Marquis Washington, DC)
* noted as presenting author
Holly Davies, MSW, Doctoral Research Associate, University of Houston, TX
Isabel Torres-Vigil, MPH, DrPH, Associate Professor, University of Houston, Houston, TX
Background/Purpose: Limited postdisaster research suggests that 25% to 75% of survivors experience PTSD. However, little research has been conducted on other forms of mental health sequalae or factors which may impact mental health risk and recovery after disasters. Historically, disaster recovery research typically evaluates physical and financial recovery. This study aims to identify demographic, psychosocial and clinical factors which predict mental health recovery in a group of survivors from Hurricane Harvey.

Methods: Data from two cross-sectional surveys (#311647 and #311688) conducted by Roper Institute for Public Opinion Research at 3 months and 1 year after Hurricane Harvey were compiled into one dataset. A subsection (n = 2,114) of all respondents (n = 3,286) impacted by Harvey were asked additional questions on mental health. A dichotomous composite variable “Mental Health Recovery” was created from 3 questions: (1) Worsening of self-reported mental health (SMRF) since Harvey, (2) New prescription for mental health issues, and (3) Unmet needs for mental health. This item was regressed using a binomial logistic regression with demographic (age, gender, race/ethnicity), psychosocial (federal income poverty level (FIPL) below 200%) and clinical proxy measures (general assessment of self-reported mental health (SRMH), inability to control temper, increased alcohol usage). Multiple imputation was utilized for missing data. Bivariate associations were evaluated with independent t-tests and chi-square tests. Logistic regression analysis using the Enter data entry method was then conducted to identify factors most likely to predict poor mental health recovery in the sample.

Results: Of the 2,114 respondents, 25% percent were classified as poor mental health recovery. The final regression model accounted for 28% to 42% of the variance in mental health with a success rate of 82%. Factors that significantly predicted poor mental health recovery were: increased alcohol usage (odds ratio [OR] 3.03; 95% confidence interval [CI] 1.73-5.29); inability to control temper post disaster (OR 7.16; CI 5.28-9.72); female gender (OR 1.63; CI 1.23-2.11); and lower level of SRMH (OR 1.92; CI 1.71-2.15). Factors found to be not significant included race/ethnicity, age and poverty level.

Conclusions/Implications: The study found that a substantial portion of respondents reported poor post disaster mental health outcomes, which were influenced by alcohol usage, inability to control temper, being female, and lower SRMH levels.

This study addresses important research gaps in disaster research and may provide useful risk-related information for practitioners working in the area of postdisaster mental health recovery. Researchers should develop validated, standardized disaster assessments and tools to accurately measure postdisaster mental health needs. Findings from this study may inform future evaluations of substance use, emotional lability regarding temper, and general SRMH in disaster survivors. Due to large unmet mental health in this population, it is imperative that mental health and disaster relief agencies develop better methods for addressing these gaps. Although important variables such as race/ethnicity, socioeconomic status and age were not significant predictors of mental health in this study, future research should evaluate these factors given their importance as predictors in postdisaster physical recovery and other health studies.