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The difficulties of studying children's pain at home

Debra M Van Kuiken1, Li Lin, Myra Martz Huth

  • 1Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229-3039, USA. debra.vankuiken@cchmc.org

Western Journal of Nursing Research
|June 1, 2007
PubMed

Insights

Analyzing children's post-tonsillectomy pain is challenging due to inconsistent pain diary entries. Hierarchical linear modeling (HLM) offers a solution for analyzing this unbalanced data and controlling for analgesic use.

Area of Science:

  • Pediatric Pain Management
  • Clinical Research Methodology

Background:

  • Tonsillectomy surgery in children often results in moderate to severe pain.
  • Accurate pain assessment is crucial for effective post-operative care and research.

Purpose of the Study:

  • To address challenges in analyzing pediatric pain data from inconsistent post-tonsillectomy diaries.
  • To identify appropriate statistical methods for handling unbalanced data and analgesic use in pain research.

Main Methods:

  • Data analysis of pain diaries collected 24 hours after ambulatory tonsillectomy.
  • Conversion of opioid analgesics to morphine equivalents and non-opioids as separate covariates.
  • Application of Hierarchical Linear Modeling (HLM) to analyze unbalanced and incomplete repeated-measures data.

Main Results:

  • Inconsistent diary entries and analgesic use complicated group comparisons.
  • HLM demonstrated the ability to analyze unbalanced data effectively.
  • HLM provided a method to control for analgesic interventions in pain research.

Conclusions:

  • Standard pain diary protocols may yield inconsistent data in pediatric post-tonsillectomy studies.
  • Hierarchical Linear Modeling (HLM) is a suitable statistical approach for analyzing incomplete and unbalanced pain data in pediatric home-based research.
  • Controlling for analgesic use is essential for maintaining the construct validity of pain assessment research in children.

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