title: [The use of propensity score matching for evaluation of the effects of nursing interventions].
abstract: BACKGROUND
  Nursing intervention studies often suffer from a selection bias introduced by failure of random assignment. Evaluation with selection bias could under or over-estimate any intervention's effects. PS matching (PSM) can reduce a selection bias through matching similar Propensity Scores (PS). PS is defined as the conditional probability of being treated given the individual's covariates and it can be reused to balance the covariates of two groups.
  
  
  OBJECTIVE
  This study was done to assess the significance of PSM as an alternative evaluation method of nursing interventions.
  
  
  METHODS
  An intervention study for patients with some baseline individual characteristic differences between two groups was used for this demonstration. The result of a t-test with PSM was compared with a t-test without matching.
  
  
  RESULTS
  The level of HbA1c at 12 months after baseline was different between the two groups in terms of matching or not.
  
  
  CONCLUSIONS
  This study demonstrated the effects of a quasi-random assignment. Evaluation using PSM can reduce a selection bias impact that affects the result of the nursing intervention. Analyzing nursing research more objectively to reduce selection bias using PSM is needed.
authors.affiliation: Red Cross College of Nursing, Korea. LSJ1109@redcross.ac.kr
authors.forename: Suk Jeong
authors.initials: SJ
authors.lastname: Lee
authors.forename: Ji Soo
authors.initials: JS
authors.lastname: Yoo
authors.forename: Mikyung
authors.initials: M
authors.lastname: Shin
authors.forename: Chang Gi
authors.initials: CG
authors.lastname: Park
authors.forename: Hyun Chul
authors.initials: HC
authors.lastname: Lee
authors.forename: Eun Jin
authors.initials: EJ
authors.lastname: Choi
mesh_terms: D015986:Confounding Factors, Epidemiologic; D003627:Data Interpretation, Statistical; D003924:Diabetes Mellitus, Type 2 / Q000453:epidemiology / Q000451:nursing*; D006442:Glycated Hemoglobin / Q000032:analysis; D006801:Humans; D015233:Models, Statistical; D017063:Outcome Assessment, Health Care / Q000379:methods*; D015983:Selection Bias
chemical_list: D006442:Glycated Hemoglobin; C517652:hemoglobin A1c protein, human