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Comparing four methods for assessing interprofessional learning in a practice setting.

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Title: Comparing four methods for assessing interprofessional learning in a practice setting.
Authors: Alsane, Danah (AUTHOR), Lockeman, Kelly S. (AUTHOR), Mays, Darcy P. (AUTHOR), Dow, Alan (AUTHOR), Donohoe, Krista L. (AUTHOR), Kirkwood, Cynthia K. (AUTHOR), Slattum, Patricia (AUTHOR)
Source: Journal of Interprofessional Care. May/Jun2026, Vol. 40 Issue 3, p428-436. 9p.
Subjects: Teams in the workplace, Cross-sectional method, Pearson correlation (Statistics), Interprofessional relations, Medical quality control, Data analysis, Medical care, Evaluation of human services programs, Health occupations students, Universities & colleges, Geriatrics, Questionnaires, Multiple regression analysis, Statistical sampling, Educational tests & measurements, Quantitative research, Descriptive statistics, Race, Research bias, Research, Statistics, One-way analysis of variance, Patient satisfaction, Data analysis software, Health care teams, Psychosocial factors, Video recording
Abstract: Healthcare practitioners must be trained to collaborate in a dynamic environment where patients are complex and teams can change from day-to-day, but choosing the right measures to assess the effectiveness of interprofessional teamwork among learners is challenging. This study used measures representing four different perspectives to assess student teams in a practice setting where team composition varied each day. We tested the strength of the relationships between these measures, and we examined the impact of additional variables on each measure. Participants were students from different health professions at a single university and patients in a community-based wellness program. We sampled 100 wellness visits where an interprofessional student team met with a patient, and we assessed team effectiveness using student perceptions of their team, patient ratings, observer ratings, and faculty assessments of team healthcare plans for the patient. We calculated bivariate correlations between the four measures and used regression analyses to assess the impact of predictors including student, patient, and clinic/site characteristics, on each measure of team effectiveness. There were small but significant negative correlations between the assessments of faculty and observers (r = – 0.23), as well as between faculty and patients (r = – 0.14). Conversely, a small but significant positive correlation was found between the assessments of patients and observers (r = 0.15). Among the regression models, faculty and patient ratings of team effectiveness were more strongly related to the predictors measured (R-squared = 53.6% and 41.7%, respectively). Patient age and number of clinic visits, team size, and clinic site were significant factors for predicting team effectiveness across the two measures. Our findings provide evidence that different perspectives of team effectiveness measure different constructs. While all approaches have value, in IPE practice settings, team effectiveness should be evaluated with multiple measures to understand performance and identify opportunities for improvement. Teamwork in dynamic healthcare environments is complex, and simple measurement approaches may mischaracterize learning and clinical outcomes. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Interprofessional Care is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Comparing four methods for assessing interprofessional learning in a practice setting.
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  Data: <searchLink fieldCode="AR" term="%22Alsane%2C+Danah%22">Alsane, Danah</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lockeman%2C+Kelly+S%2E%22">Lockeman, Kelly S.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Mays%2C+Darcy+P%2E%22">Mays, Darcy P.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Dow%2C+Alan%22">Dow, Alan</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Donohoe%2C+Krista+L%2E%22">Donohoe, Krista L.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Kirkwood%2C+Cynthia+K%2E%22">Kirkwood, Cynthia K.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Slattum%2C+Patricia%22">Slattum, Patricia</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Interprofessional+Care%22">Journal of Interprofessional Care</searchLink>. May/Jun2026, Vol. 40 Issue 3, p428-436. 9p.
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  Data: Healthcare practitioners must be trained to collaborate in a dynamic environment where patients are complex and teams can change from day-to-day, but choosing the right measures to assess the effectiveness of interprofessional teamwork among learners is challenging. This study used measures representing four different perspectives to assess student teams in a practice setting where team composition varied each day. We tested the strength of the relationships between these measures, and we examined the impact of additional variables on each measure. Participants were students from different health professions at a single university and patients in a community-based wellness program. We sampled 100 wellness visits where an interprofessional student team met with a patient, and we assessed team effectiveness using student perceptions of their team, patient ratings, observer ratings, and faculty assessments of team healthcare plans for the patient. We calculated bivariate correlations between the four measures and used regression analyses to assess the impact of predictors including student, patient, and clinic/site characteristics, on each measure of team effectiveness. There were small but significant negative correlations between the assessments of faculty and observers (r = – 0.23), as well as between faculty and patients (r = – 0.14). Conversely, a small but significant positive correlation was found between the assessments of patients and observers (r = 0.15). Among the regression models, faculty and patient ratings of team effectiveness were more strongly related to the predictors measured (R-squared = 53.6% and 41.7%, respectively). Patient age and number of clinic visits, team size, and clinic site were significant factors for predicting team effectiveness across the two measures. Our findings provide evidence that different perspectives of team effectiveness measure different constructs. While all approaches have value, in IPE practice settings, team effectiveness should be evaluated with multiple measures to understand performance and identify opportunities for improvement. Teamwork in dynamic healthcare environments is complex, and simple measurement approaches may mischaracterize learning and clinical outcomes. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Journal of Interprofessional Care is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1080/13561820.2025.2452975
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      – Code: eng
        Text: English
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        PageCount: 9
        StartPage: 428
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      – SubjectFull: Teams in the workplace
        Type: general
      – SubjectFull: Cross-sectional method
        Type: general
      – SubjectFull: Pearson correlation (Statistics)
        Type: general
      – SubjectFull: Interprofessional relations
        Type: general
      – SubjectFull: Medical quality control
        Type: general
      – SubjectFull: Data analysis
        Type: general
      – SubjectFull: Medical care
        Type: general
      – SubjectFull: Evaluation of human services programs
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      – SubjectFull: Health occupations students
        Type: general
      – SubjectFull: Universities & colleges
        Type: general
      – SubjectFull: Geriatrics
        Type: general
      – SubjectFull: Questionnaires
        Type: general
      – SubjectFull: Multiple regression analysis
        Type: general
      – SubjectFull: Statistical sampling
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      – SubjectFull: Educational tests & measurements
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      – SubjectFull: Quantitative research
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      – SubjectFull: One-way analysis of variance
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      – SubjectFull: Patient satisfaction
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      – SubjectFull: Psychosocial factors
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      – SubjectFull: Video recording
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      – TitleFull: Comparing four methods for assessing interprofessional learning in a practice setting.
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              Text: May/Jun2026
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