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Related Experiment Videos

Response to the commentary "to the bone".

Shannon A McMahon1, Adamson S Muula2, Manuela De Allegri3

  • 1Heidelberg Institute of Global Health at Heidelberg University, Germany.

SSM - Population Health
|July 13, 2019
PubMed
Summary

Presenting process data offers timely insights into complex programs, even without outcome data. This study

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Area of Science:

  • Program Evaluation
  • Complex Systems Analysis

Background:

  • Understanding new, complex programs often requires timely data.
  • Traditional outcome data may be delayed, hindering early assessment.

Purpose of the Study:

  • To explore the utility of process data for understanding complex programs.
  • To investigate the role of moderators in program complexity.

Main Methods:

  • Analysis of process data from new, complex programs.
  • Emphasis on data-driven identification of moderators.

Main Results:

  • Process data provides valuable insights in the absence of outcome data.
  • Program complexity was characterized by a gap between initial feasibility and mid-intervention feasibility.

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  • Moderators were identified through data analysis, not solely by pre-existing frameworks.

    • Conclusions:

    • Process data is crucial for the timely understanding of complex programs.
    • Data-driven approaches are effective for identifying program moderators and understanding complexity.