Relationship between interprofessional teamwork and intention to leave among acute care hospital staff: a cross-sectional study

We investigated the relationship between interprofessional teamwork assessed using the TeamSTEPPS Teamwork Perceptions Questionnaire (T-TPQ) and intention to leave among healthcare staff in a Japanese municipal hospital. A cross-sectional survey was conducted using the T-TPQ and an intention to leave scale. Participants included nurses, allied health professionals (rehabilitation therapists, radiologic technologists, clinical engineers, and pharmacists), and physicians. In assessing the relationship between teamwork and the intention to leave, logistic regression modeling was used to adjust for confounding factors identified through a directed acyclic graph. Among 296 respondents (response rate, 63.4%), 47 (15.9%) reported a high level of intention to leave. Multivariate analysis using the first quartile as the reference showed that higher T-TPQ scores (i.e. higher perception of teamwork) were associated with lower odds of intention to leave. The adjusted odds ratios of the T-TPQ for intention to leave were 0.67 (95% confidence interval [CI] 0.27 to 1.66) for the second quartile, 0.31 (95%CI 0.10 to 0.91) for the third quartile, and 0.44 (95%CI 0.13 to 1.45) for the fourth quartile. Higher teamwork perception, as measured by T-TPQ, was associated with a lower intention to leave, highlighting the potential importance of teamwork in retention strategies.

Authors

Institutions

Publication Details

Journal
Journal of Interprofessional Care
Published
2026-02-24
DOI
https://doi.org/10.1080/13561820.2026.2633619
Primary Topic
Interprofessional Education and Collaboration
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Relationship between interprofessional teamwork and intention to leave among acute care hospital staff: a cross-sectional study

Sunao Mikura, Shunichi Fukuhara, Toshihiko Takada, Sayaka Shimizu
Journal of Interprofessional Care
Interprofessional Education and Collaboration
article

Relationship between interprofessional teamwork and intention to leave among acute care hospital staff: a cross-sectional study

Sunao Mikura, Shunichi Fukuhara, Toshihiko Takada, Sayaka Shimizu
article en

Abstract

We investigated the relationship between interprofessional teamwork assessed using the TeamSTEPPS Teamwork Perceptions Questionnaire (T-TPQ) and intention to leave among healthcare staff in a Japanese municipal hospital. A cross-sectional survey was conducted using the T-TPQ and an intention to leave scale. Participants included nurses, allied health professionals (rehabilitation therapists, radiologic technologists, clinical engineers, and pharmacists), and physicians. In assessing the relationship between teamwork and the intention to leave, logistic regression modeling was used to adjust for confounding factors identified through a directed acyclic graph. Among 296 respondents (response rate, 63.4%), 47 (15.9%) reported a high level of intention to leave. Multivariate analysis using the first quartile as the reference showed that higher T-TPQ scores (i.e. higher perception of teamwork) were associated with lower odds of intention to leave. The adjusted odds ratios of the T-TPQ for intention to leave were 0.67 (95% confidence interval [CI] 0.27 to 1.66) for the second quartile, 0.31 (95%CI 0.10 to 0.91) for the third quartile, and 0.44 (95%CI 0.13 to 1.45) for the fourth quartile. Higher teamwork perception, as measured by T-TPQ, was associated with a lower intention to leave, highlighting the potential importance of teamwork in retention strategies.

Journal of Interprofessional Care
Fukushima Medical University (JP), Johns Hopkins University (US), Kyoto University (JP), National Patient Safety Foundation (US)
Openalex Percentile: Top 46%
Interprofessional Education and Collaboration
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.