Advantages and disadvantages of using theory-based versus data-driven models with social and behavioral determinants of health data

Research output: Contribution to journalArticlepeer-review


OBJECTIVE: Theory-based research of social and behavioral determinants of health (SBDH) found SBDH-related patterns in interventions and outcomes for pregnant/birthing people. The objectives of this study were to replicate the theory-based SBDH study with a new sample, and to compare these findings to a data-driven SBDH study. MATERIALS AND METHODS: Using deidentified public health nurse-generated Omaha System data, 2 SBDH indices were computed separately to create groups based on SBDH (0-5+ signs/symptoms). The data-driven SBDH index used multiple linear regression with backward elimination to identify SBDH factors. Changes in Knowledge, Behavior, and Status (KBS) outcomes, numbers of interventions, and adjusted R-squared statistics were computed for both models. RESULTS: There were 4109 clients ages 13-40 years. Outcome patterns aligned with the original research: KBS increased from admission to discharge with Knowledge improving the most; discharge KBS decreased as SBDH increased; and interventions increased as SBDH increased. Slopes of the data-driven model were steeper, showing clearer KBS trends for data-driven SBDH groups. The theory-based model adjusted R-squared was 0.54 (SE = 0.38) versus 0.61 (SE = 0.35) for the data-driven model with an entirely different set of SBDH factors. CONCLUSIONS: The theory-based approach provided a framework to identity patterns and relationships and may be applied consistently across studies and populations. In contrast, the data-driven approach can provide insights based on novel patterns for a given dataset and reveal insights and relationships not predicted by existing theories. Data-driven methods may be an advantage if there is sufficiently comprehensive SBDH data upon which to create the data-driven models.

Original languageEnglish (US)
Pages (from-to)1818-1825
Number of pages8
JournalJournal of the American Medical Informatics Association : JAMIA
Issue number11
StatePublished - Oct 19 2023

Bibliographical note

Publisher Copyright:
© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email:


  • Omaha System
  • data analysis
  • impact analysis
  • other clinical informatics applications
  • public health
  • social determinants of health

PubMed: MeSH publication types

  • Journal Article


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