Health Psychology Open (Dec 2021)

Adverse childhood experiences predict reaction to multiple sclerosis diagnosis

  • Tehila Eilam-Stock,
  • Jon Links,
  • Nabil Z. Khan,
  • Tamar E. Bacon,
  • Guadalupe Zuniga,
  • Lisa Laing,
  • Carrie Sammarco,
  • Kathleen Sherman,
  • Leigh Charvet

DOI
https://doi.org/10.1177/20551029211052830
Journal volume & issue
Vol. 8

Abstract

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Objective At the time of multiple sclerosis (MS) diagnosis, identifying those at risk for poorer health-related quality of life and emotional well-being can be a critical consideration for treatment planning. This study aimed to test whether adverse childhood experiences predict MS patients’ health-related quality of life and emotional functioning at time of diagnosis and initial course of disease. Methods We recruited patients at the time of new MS diagnosis to complete self-report surveys at baseline and a one-year follow-up. Questionnaires included the Adverse Childhood Experiences (ACEs), as well as the MS Knowledge Questionnaire (MSKQ), the 36-Item Short Form Health Survey (SF-36), and Self-Management Screening (SeMaS). Results A total of n = 31 participants recently diagnosed with relapsing remitting MS (median EDSS = 1.0, age M = 33.84 ± 8.4 years) completed the study measures. The ACEs significantly predicted health-related quality of life (SF-36) at baseline (Adjusted R 2 = 0.18, p = 0.011) and follow-up (Adjusted R 2 = 0.12, p = 0.03), baseline scores on the SeMaS Depression scale (Adjusted R 2 = 0.19, p = 0.008), as well as follow-up scores on the SeMaS Anxiety (Adjusted R 2 = 0.19, p = 0.014) and SeMaS Depression (Adjusted R 2 = 0.14, p = 0.036) scales. Importantly, increased ACEs scores were predictive of increased anxiety at the one-year follow-up assessment, compared to baseline. Conclusions Childhood adversity predicts health-related quality of life and emotional well-being at time of MS diagnosis and over the initial course of the disease. Measured using a brief screening inventory (ACEs), routine administration may be useful for identifying patients in need of increased supportive services.