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The Use of Propensity Score Matching for Evaluation of the Effects of Nursing Interventions

Suk Jeong Lee, Ji Soo Yoo, Mikyung Shin, Chang Gi Park, Hyun Chul Lee, Eun Jin Choi

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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. PURPOSE: This study was done to assess the significance of PSM as an alternative evaluation method of nursing interventions. METHOD: 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. CONCLUSION: 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.

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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. PURPOSE: This study was done to assess the significance of PSM as an alternative evaluation method of nursing interventions. METHOD: 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. CONCLUSION: 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.

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Available 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. PURPOSE: This study was done to assess the significance of PSM as an alternative evaluation method of nursing interventions. METHOD: 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. CONCLUSION: 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.

Key concepts: Propensity score matching, Matching (statistics), Random assignment, Selection bias, Selection (genetic algorithm), Psychological intervention, Covariate, Intervention (counseling)

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