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The Journal of antimicrobial chemotherapy v.72 no.2, 2017년, pp.604 - 613   SCI SCIE
본 등재정보는 저널의 등재정보를 참고하여 보여주는 베타서비스로 정확한 논문의 등재여부는 등재기관에 확인하시기 바랍니다.

Rasch analysis of the Antimicrobial Self-Assessment Toolkit for National Health Service (NHS) Trusts (ASAT v17)

Bailey, Chantelle (Manchester Pharmacy School, 1st Floor, Stopford Building, University of Manchester, Manchester M13 9PT, UK ); Tully, Mary P. (Manchester Pharmacy School, 1st Floor, Stopford Building, University of Manchester, Manchester M13 9PT, UK ); Pampaka, Maria (Manchester Institute for Education, Ellen Wilkinson Building, University of Manchester, Manchester M13 9PT, UK ); Cooke, Jonathan (Manchester Pharmacy School, 1st Floor, Stopford Building, University of Manchester, Manchester M13 9PT, UK );
  • 초록  

    Objectives The Antimicrobial Self-Assessment Toolkit for National Health Service (NHS) Trusts (ASAT) was developed to evaluate hospital-based antimicrobial stewardship programmes. Iterative validity investigations of the ASAT were used to produce a 91-item ASAT v17 utilizing qualitative methodology. Rasch analysis was used to generate question (item) behaviour estimates and to investigate the validity of ASAT v17. Methods In 2012, the partial credit model (PCM) was used to analyse ASAT responses from 33 NHS Trusts within England. WINSTEPS ® outputs such as fit statistics and respondent/item maps were examined to determine unidimensionality, item discrimination and item hierarchy. Ordinary least squares regression modelling was used to determine the predictive validity using NHS Trust ability estimates generated from the PCM and corresponding Clostridium difficile rates. Results Each domain contained items that were misfitting the PCM (with INFIT MNSQ <0.7 or >1.3), except Domain 3. Subsequent iterative item removal had a negligible effect on the fit indices within most ASAT domains. Scale analysis demonstrated that most items were productive for measurement ( n  = 81). Respondent/item maps showed ceiling effects ( n  = 3) and floor effects ( n  = 1) within ASAT domains. Ordinary least squares regression modelling identified that there was limited predictive validity due to the small positive correlation between the predictor and outcome variables for participating hospitals (ρ = 0.146; P  = 0.418). Conclusions Rasch analysis was an effective measurement technique for evaluating the validity of ASAT v17 by providing evidence that each sub-scale and the overall scale demonstrated unidimensionality (construct validity). Improved item targeting may be required to improve item discrimination within the toolkit.


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