Predictors of social integration for individuals with brain injury: An application of the ICF model

Brain Inj. 2016;30(13-14):1581-1589. doi: 10.1080/02699052.2016.1199900. Epub 2016 Sep 14.


Objective: People with brain injury often experience significant challenges to social and community engagement following injury. The purpose of this study was to investigate factors impacting social integration for adults with brain injury using the International Classification and Functioning, Disability and Health (ICF) as a conceptual model.

Methods: Adults with brain injury (n = 103) recruited through two US state brain injury associations participated in a survey study. Hierarchical regression analysis was used to examine the predictive impact of components of the ICF model on social integration outcomes. Specifically, demographic (age, gender, SES), disability (severity of functional limitations), personal (disability acceptance, social self-efficacy) and environmental (neighbourhood climate, stigma, social support network) factors were entered as four conceptual groups of predictors to examine the incremental contribution of the variance in social integration explained by each set.

Results: As hypothesized, the inclusion of each block of predictors significantly improved the model. The overall regression model explained 41% of the variance in social integration. Specifically, SES (β = 0.25), severity of functional limitations (β = 0.29) and social support network (β = 0.29) emerged as the strongest independent predictors.

Conclusion: Findings from this study highlight the importance of adopting a biopsychosocial approach to understanding social integration for people with brain injury.

Keywords: Brain injury; ICF; biopsychosocial; community integration; participation.

Publication types

  • Multicenter Study

MeSH terms

  • Adult
  • Brain Injuries / diagnosis*
  • Brain Injuries / psychology*
  • Community Integration / psychology*
  • Disabled Persons / psychology
  • Female
  • Humans
  • International Classification of Diseases
  • Male
  • Middle Aged
  • Patient Participation / psychology*
  • Regression Analysis
  • Self Efficacy*
  • United States