IDEAS home Printed from https://ideas.repec.org/a/eee/epplan/v102y2024ics0149718923001544.html
   My bibliography  Save this article

Ensuring the “health” of a curricular program evaluation: Alignment and analytic quality of two instruments for use in evaluating the effectiveness of an interprofessional collaboration curriculum

Author

Listed:
  • Sampson, Shannon
  • Nelson, Andrew
  • Cardarelli, Roberto
  • Roper, Karen L.

Abstract

To cultivate competencies in interprofessional collaboration (IPC) for patient-centered, team-based care, a multi-faceted training enhancement initiative was implemented at our academic primary care residency site. Evaluation of the activities from previously collected survey data occurred upon a 2-year review. First, the evaluation team scrutinized the instruments for alignment and appropriateness with planned IPC educational learning and behavior objectives. We found the two instruments were well supported by the literature and with appropriate evidence for validation, but were not well aligned to the objectives of this IPC training initiative, reducing appropriateness of potential inferences of the findings for this context. Second, the team assessed the analytic quality of survey results in item difficulty distribution and item fit to the requirements of a Rasch measurement model. This revealed low person separation due to high overall item agreement. Most residents agreed with most items, so the measures lacked the precision necessary to capture change in residents’ IPC competency. Our instrument review serves as a reminder of the need to gather validity evidence for the use of any existing tool within a new context, and offers a generalizable strategy to evaluate data sources for appropriateness and quality within a specific program.

Suggested Citation

  • Sampson, Shannon & Nelson, Andrew & Cardarelli, Roberto & Roper, Karen L., 2024. "Ensuring the “health” of a curricular program evaluation: Alignment and analytic quality of two instruments for use in evaluating the effectiveness of an interprofessional collaboration curriculum," Evaluation and Program Planning, Elsevier, vol. 102(C).
  • Handle: RePEc:eee:epplan:v:102:y:2024:i:c:s0149718923001544
    DOI: 10.1016/j.evalprogplan.2023.102377
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0149718923001544
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.evalprogplan.2023.102377?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. David Andrich, 1978. "A rating formulation for ordered response categories," Psychometrika, Springer;The Psychometric Society, vol. 43(4), pages 561-573, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Eun-Young Park & Soojung Chae, 2020. "Rasch Analysis of the Korean Parenting Stress Index Short Form (K-PSI-SF) in Mothers of Children with Cerebral Palsy," IJERPH, MDPI, vol. 17(19), pages 1-11, September.
    2. P. A. Ferrari & S. Salini, 2008. "Measuring Service Quality: The Opinion of Europeans about Utilities," Working Papers 2008.36, Fondazione Eni Enrico Mattei.
    3. Chang, Hsin-Li & Yang, Cheng-Hua, 2008. "Explore airlines’ brand niches through measuring passengers’ repurchase motivation—an application of Rasch measurement," Journal of Air Transport Management, Elsevier, vol. 14(3), pages 105-112.
    4. Ivana Bassi & Matteo Carzedda & Enrico Gori & Luca Iseppi, 2022. "Rasch analysis of consumer attitudes towards the mountain product label," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 10(1), pages 1-25, December.
    5. Antonio Caronni & Marina Ramella & Pietro Arcuri & Claudia Salatino & Lucia Pigini & Maurizio Saruggia & Chiara Folini & Stefano Scarano & Rosa Maria Converti, 2023. "The Rasch Analysis Shows Poor Construct Validity and Low Reliability of the Quebec User Evaluation of Satisfaction with Assistive Technology 2.0 (QUEST 2.0) Questionnaire," IJERPH, MDPI, vol. 20(2), pages 1-19, January.
    6. Wanke, Peter Fernandes & Chiappetta Jabbour, Charbel José & Moreira Antunes, Jorge Junio & Lopes de Sousa Jabbour, Ana Beatriz & Roubaud, David & Sobreiro, Vinicius Amorim & Santibanez Gonzalez‬, Erne, 2021. "An original information entropy-based quantitative evaluation model for low-carbon operations in an emerging market," International Journal of Production Economics, Elsevier, vol. 234(C).
    7. Hua-Hua Chang, 1996. "The asymptotic posterior normality of the latent trait for polytomous IRT models," Psychometrika, Springer;The Psychometric Society, vol. 61(3), pages 445-463, September.
    8. Curt Hagquist & Raili Välimaa & Nina Simonsen & Sakari Suominen, 2017. "Differential Item Functioning in Trend Analyses of Adolescent Mental Health – Illustrative Examples Using HBSC-Data from Finland," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 10(3), pages 673-691, September.
    9. Wang, Luming & Finn, Adam, 2014. "A psychometric theory that measures up to marketing reality: An adapted Many Faceted IRT model," Australasian marketing journal, Elsevier, vol. 22(2), pages 93-102.
    10. Qiu-Yue Zhong & Bizu Gelaye & Alan M Zaslavsky & Jesse R Fann & Marta B Rondon & Sixto E Sánchez & Michelle A Williams, 2015. "Diagnostic Validity of the Generalized Anxiety Disorder - 7 (GAD-7) among Pregnant Women," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-17, April.
    11. Cristante, Francesca & Robusto, Egidio, 1999. "Assessing dependence among subjects' responses," Mathematical Social Sciences, Elsevier, vol. 38(3), pages 259-274, November.
    12. Amy Snyder & Kenneth Royal, 2016. "Investigating the Financial Awareness and Behaviors of Veterinary Medical Students," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 8(7), pages 201-201, July.
    13. Nicole Gideon & Nick Hawkes & Jonathan Mond & Rob Saunders & Kate Tchanturia & Lucy Serpell, 2016. "Development and Psychometric Validation of the EDE-QS, a 12 Item Short Form of the Eating Disorder Examination Questionnaire (EDE-Q)," PLOS ONE, Public Library of Science, vol. 11(5), pages 1-19, May.
    14. Huang, Jen-Hung & Peng, Kua-Hsin, 2012. "Fuzzy Rasch model in TOPSIS: A new approach for generating fuzzy numbers to assess the competitiveness of the tourism industries in Asian countries," Tourism Management, Elsevier, vol. 33(2), pages 456-465.
    15. Geofferey Masters & Benjamin Wright, 1984. "The essential process in a family of measurement models," Psychometrika, Springer;The Psychometric Society, vol. 49(4), pages 529-544, December.
    16. Salzberger, Thomas & Newton, Fiona J. & Ewing, Michael T., 2014. "Detecting gender item bias and differential manifest response behavior: A Rasch-based solution," Journal of Business Research, Elsevier, vol. 67(4), pages 598-607.
    17. Karen M. Conrad & Kendon J. Conrad & Lora L. Passetti & Rodney R. Funk & Michael L. Dennis, 2015. "Validation of the Full and Short-Form Self-Help Involvement Scale Against the Rasch Measurement Model," Evaluation Review, , vol. 39(4), pages 395-427, August.
    18. Rasmus A. X. Persson, 2023. "Theoretical evaluation of partial credit scoring of the multiple-choice test item," METRON, Springer;Sapienza Università di Roma, vol. 81(2), pages 143-161, August.
    19. Wendy L. Martin & Alexander McKelvie & G. T. Lumpkin, 2016. "Centralization and delegation practices in family versus non-family SMEs: a Rasch analysis," Small Business Economics, Springer, vol. 47(3), pages 755-769, October.
    20. Chang, Hsin-Li & Wu, Shun-Cheng, 2008. "Exploring the vehicle dependence behind mode choice: Evidence of motorcycle dependence in Taipei," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(2), pages 307-320, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:epplan:v:102:y:2024:i:c:s0149718923001544. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/evalprogplan .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.