Interprofessional learning in a student-run dental clinic: The effect on attitudes of students in oral healthcare

ABSTRACT

The purpose of this study was to gain insight into change in attitudes held by students in oral healthcare about interprofessional learning and collaboration after one year of work in a student-run dental clinic (SRDC). Third- and fourth-year bachelor of dental hygiene students (n = 221) and first- and second-year master of dentistry students (n = 203) participated in baseline and follow-up measurements and completed 570 questionnaires. The Readiness for Interprofessional Learning Scale (RIPLS) was used to measure changes in attitudes toward Interprofessional Education (IPE) during participation in the SRDC. To validate the questionnaire for the setting, professional groups, and wording of RIPLS, we performed exploratory and confirmatory factor analyses. Two modified subscales remained: “Teamwork & Collaboration” and “Negative Professional Identity.” Mixed linear models were used to assess relationships between students’ attitudes toward IPE and participation in the SRDC. Overall, the students had positive attitudes toward IPE. At baseline, the attitudes of the dental hygiene and dentistry students were almost equally positive. After one year, dental hygiene students demonstrated a significantly more positive attitude toward collaborative learning and teamwork than the dentistry students. Further research should investigate whether the positive attitudes impact behavior in professional practice.

KEYWORDS:

• Interprofessional education
• interprofessional collaboration
• attitudes
• student-run clinic
• dental hygiene student
• dentistry student

Introduction

There are demographic and cultural differences in the field of oral healthcare worldwide, with country- and region-specific challenges (Glick et al., 2021). The integration of patient-centered general health and oral healthcare – as described by the FDI World Dental Federation (FDI) in its Vision 2030: Delivering optimal oral health for all – is seen as a solution to prevent diseases and improve the quality and affordability of (oral) healthcare (Glick et al., 2021). The delivery of effective high-quality patient-centered care requires an interprofessional collaborative approach (World Health Organization, 2010). Previously, the FDI emphasized: “Interprofessional collaboration and teamwork is increasingly recognized as a means of achieving higher quality care and improving the effectiveness and efficiency of health services” (FDI World Dental Federation, 2015).

Mutual respect and a better understanding of roles and responsibilities are essential for effective collaboration and real teamwork (Evans et al., 2012). The dentist in the professional field does not always see the dental hygienist as an equal professional on the oral healthcare team (Jerkovic et al., 2010; Reinders et al., 2017). This might be due to a lack of knowledge about and insight into the professional roles of dental hygienists or a perceived threat of task shifting between professionals (Kersbergen et al., 2020; Knevel et al., 2017). Task shifting has resulted in dental hygienists taking a more independent position and an overlap of tasks between the two oral healthcare professionals (Commissie Innovatie Mondzorg, 2006).

Interprofessional education (IPE) is frequently used to develop interprofessional practice and improve services (Hammick et al., 2007). IPE occurs when “students from two or more professions learn about, from, and with each other to enable effective collaboration and improve health outcomes” (World Health Organization, 2010). In such interprofessional learning environments, students learn to practice in interprofessional clinical teams, improve their awareness of other professions, and improve highly patient-centered care (Guraya & Barr, 2018; Hammick et al., 2009; Marcussen et al., 2019; Parsell & Bligh, 1999; Pollard et al., 2008; Satter et al., 2020).

According to the review of Berger-Estilita et al. (2020), few studies have measured changes in knowledge, behavior, and attitudes toward interprofessional collaboration (IPC) in a clinical setting over a longer period of time. Previous studies have found that IPE contributes to increased knowledge of roles and responsibilities (Kersbergen et al., 2020; Parsell & Bligh, 1999). IPE can also improve attitudes toward teamwork & collaboration, leading students to offer better patient care after graduation (Berger-Estilita et al., 2020). Therefore, it is important to gain insight into the evolution of students’ attitudes toward each other in shared learning and IPC over time (D’Amour & Oandasan, 2005; Parsell & Bligh, 1999).

It is known that IPE interventions can have different effects on groups of learners with different educational backgrounds (Berger-Estilita et al., 2020; Talwalkar et al., 2016). Several theories emphasize that attitudes toward interprofessional teamwork are improved by controlled conditions like equal status, common goals, an atmosphere of mutual respect and trust, and emotional and physical safety (Bridges & Tomkowiak, 2010; Parsell et al., 1998; Watkin et al., 2009). A change in attitudes as an outcome measure in IPE evaluation is often related to intergroup contact (Hean et al., 2018).

Student-run clinics (SRCs) facilitate IPE and offer students the opportunity to develop team-based care and collaborative skills by connecting education to professional practice (Shrader et al., 2010). SRCs are clinics with real patients where students from different disciplines work together and provide healthcare. Students are primarily responsible for all aspects of clinic operations under the supervision of accredited faculty (Haggarty & Dalcin, 2014; Lie, Forest, Walsh et al., 2016). Benefits of SRCs include IPC and preparing future health professionals to offer collaborative patient care in different settings (Schutte et al., 2015).

To our knowledge, little has been published about a SRC design for collaborative working and learning by oral healthcare students in an oral healthcare setting. Further research is needed to advance the preparation of oral healthcare students for IPC and to identify interventions that contribute to interprofessional learning and future collaborative practice (Lie, Forest, Walsh et al., 2016). Studies involving long-term IPE training with follow-up measurements are scarce, which suggests a need for longitudinal follow-up of collaboration in a clinical educational setting (Berger-Estilita et al., 2020; Reeves et al., 2013; Satter et al., 2020).

To address this gap, this paper will focus on evaluating a student-run dental clinic (SRDC) in the Netherlands to study the effects of such a clinic on dental hygiene students’ and dentistry students’ attitudes toward interprofessional learning. Subsequently, we will explore whether those groups of students hold different attitudes toward IPE in the SRDC. These two groups of professionals have intergroup contact in a shared IPE intervention. Based on that intergroup contact, we expect that collaboration with each other in the SRDC will cause the students’ attitudes toward working and learning together to become more positive.

This leads to the following research questions: After one year of participating in the SRDC, is there a change in students’ attitudes about interprofessional education and collaboration in the SRDC? Second, is there a difference in attitude between the dental hygiene and the dentistry students, both when entering the SRDC and after participating it in for one year? Finally, is there a difference in the degree of attitude change after one year between the dental hygiene and the dentistry students?

Background

Since 2005, bachelor-level dental hygiene students and master-level dentistry students from HAN University of Applied Sciences (HAN) and Radboud university medical center (Radboudumc), respectively, have spent the final year of their programs learning together in a common Clinical Interprofessional Education Program (CIEP). A previous study showed that this resulted in the novice dentists and dental hygienists having greater understanding of interprofessional roles (Kersbergen et al., 2020). That study also reported that students found it difficult to maintain interprofessional collaboration in daily dental practice after graduation.

The CIEP program was further developed into the SRDC, which is an innovative longitudinal educational program (Hissink et al., 2022). The SRDC is an authentic learning environment where students of dental hygiene and dentistry learn and work together as an interprofessional team and provide oral healthcare under the professional supervision of faculty. In contrast to other undergraduate program, our SRDC is embedded in both dental hygiene and dentistry curriculums and is organized as a longitudinal cross-disciplinary clinic. In this clinic, students work in a team for two years (dental hygiene students) or three years (dentistry students). A team is entrusted with the responsibility for oral healthcare of a group of approximately 750 patients.

Eighteen teams of students work under the professional supervision of faculty, who are legally responsible for the care of approximately 13,500 patients. An SRDC team of students comprises approximately 16 students from the two institutions, of which approximately five are dental hygiene students (third- and fourth-year bachelor students) and 11 are dentistry students (first-, second-, and third-year master students). The teams hold two half-day clinic sessions per week. In addition, they attend a half day of interprofessional academic clinical reasoning per week, where treatment plans or other issues related to oral healthcare are discussed (Hissink et al., 2022).

Before entering the SRDC, the dental hygiene and dentistry students follow different curriculums at the separate institutions. The dental hygienist is trained in a paramedical discipline and performs primarily preventive oral care with responsibility for screening, monitoring, and non-complex dental treatments. The dentist is trained in a medical discipline to maintain and restore a healthy condition and normal oral function, which may require curative intervention (Commissie Raamplan Mondzorg, 2018).

Method

Research design

The present study used a survey with baseline and one year follow-up data to assess students’ attitudes toward interprofessional collaboration. This was part of a longitudinal education program evaluating the changes in attitudes while participating in a SRDC.

Study setting and participants

The study was conducted at the SRDC, a collaborative program between Radboudumc and HAN in Arnhem and Nijmegen, the Netherlands. The SRDC program started in 2017 and therefore we included the new groups of students per year and in follow-up after one year of participating in the SRDC. So we included the third- and fourth-year bachelor dental hygiene students and first- and second-year master dentistry students, as they were novices in relation to IPE.

Those students were part of 18 SRDC teams during the 2017–2019 academic years. In an effort to assess changes over time, we invited students to complete the questionnaire at the start of their participation in the SRDC and again after one year of work there. Over three academic years, we distributed 723 questionnaires to 444 unique students.

Measurement instrument

We used the Readiness for Interprofessional Learning Scale (RIPLS) to measure students’ attitudes (Parsell & Bligh, 1999). The RIPLS consists of 19 items and three subscales: “Teamwork & Collaboration,” “Professional Identity,” and “Roles & Responsibilities” (Parsell & Bligh, 1999). Although evaluations have led to concerns about the structure of this instrument, it is the most frequently used instrument. The concerns are mostly about the internal consistency of the third subscale (Berger-Estilita et al., 2020; Havyer et al., 2016; Mahler et al., 2015; McFadyen et al., 2005; Pype & Deveugele, 2016; Schmitz & Brandt, 2015; Talwalkar et al., 2016; Yu et al., 2018). For the current study data the subscale “Roles & Responsibilities” items (17, 18 and 19) had a very low reliability (Cronbach’s alpha = 0.24). Due to internal problems with the scale structure, we chose to continue with the first 16 items of the RIPLS in line with Yu et al. (2018) to ensure a stable structure and internal consistency when used in the context of the SRDC.

We used the Dutch version of the RIPLS (Aubry et al., 2014), which is a translation of the original English version (Parsell & Bligh, 1999). To align the translation and back-translation, we used the original version and adapted the RIPLS to dental terminology. Furthermore, the emphasis was on “working together” instead of “learning together” as in SRDCs students actually treat patients in these clinics. For these reasons, we validated the construct of the RIPLS, applying factor analysis as part of our data analysis. Experts checked the language and content of the adapted Dutch version for dentists and dental hygienists. Each item was scored on a Likert scale with answers ranging from 1 (strongly agree) to 5 (strongly disagree). Reverse-scoring was used for all the items except the negatively worded items (10, 11 and 12) before the data were analyzed, hence a higher score indicated more positive views.

Data collection

Before the students were given the questionnaire, each of them received an information letter about the survey. Participation was voluntary and students who agreed to participate signed an informed consent for participation. The paper-based questionnaire and consent form were handed out in a blank open envelope. An independent researcher encrypted each completed questionnaire with a unique identifier code. That code allowed us to compare the change in attitudes per student over time. Participants were resurveyed after one year in the SRDC.

Data analysis

Factor analyses

To check whether the questionnaire fitted the setting, professional groups, and wording of RIPLS items adapted to an oral healthcare setting, we performed factor analyses to validate the questionnaire. We used all complete cases of data from students participating in their second year in the SRDC because of the possible influence of experience on interprofessional learning (McFadyen et al., 2005; Parsell & Bligh, 1999). First, we measured internal consistency (Cronbach’s alpha) per subscale on the remaining first 16 items of the original questionnaire. A Cronbach’s alpha higher than 0.7 was considered satisfactory for comparing groups (Bland & Altman, 1997).

Second, we applied exploratory factor analysis (EFA) to the scores/data of students with complete data on the second measurement (one year follow-up) in the SRDC. The heterogeneity of students from both programs and possible prior experiences with IPE of the students can affect the resulting RIPLS structure (Yu et al., 2018). We chose the second measurement of students, who were more familiar with the meaning and the content of the items, which we hoped would give us an instrument with a stable factor structure to validate with EFA. EFA was used to reveal which factors exist and which RIPLS items are related to these factors. In line with other studies using the RIPLS (McFadyen et al., 2005; Yu et al., 2018), we employed principal axis factoring to extract factors. Because of the expected relatedness of students’ attitudes and behaviors when it comes to readiness for interprofessional learning, we applied an oblique rotation method to allow for correlated factors. EFA was performed using the software package IBM SPSS v27. We applied CFA to examine the goodness of fit with only two latent factors: “Teamwork & Collaboration” (items 1–9) and “Professional Identity” (items 10–16). CFA was also applied on the baseline data, in order to validate the factor solution found with EFA on the follow-up data. CFA was performed using the software package MPLUS v8 (Muthén & Muthén, 2017).

In line with Hu and Bentler (1999) and Yu et al. (2018), the goodness of fit was considered satisfactory if the ${\chi }^2$ p-value was non-significant, the $\mathrm{n}\mathrm{o}\mathrm{r}\mathrm{m}\mathrm{e}\mathrm{d}{\chi }^2$ was between 1 and 3, RMSEA < 0.06, CFI > 0.90, and TLI > 0.95. In the EFAs, items were excluded where each item loaded high on only one factor. Guidelines for excluding items when applying EFA have been previously reported (e.g., by Costello & Osborne, 2005; Howard, 2016). One of these guidelines pertains to the (absolute) primary loading, which should be higher than 0.35. In addition, the secondary loading should differ by more than 0.10 from the primary, in order to prevent cross-loaded items.

Mixed linear regression model

To measure the effects of IPE in SRDCs on students’ attitudes, we performed mixed linear regression analysis. The students’ scores on the subscales that we found using factor analyses were analyzed using a mixed linear regression model (procedure MIXED in SPSS). This is particularly suited to studying incomplete paired data (Snijders & Bosker, 2012). The model also offers options for dealing with possible forms of heteroscedasticity. The most diverse model yields a unique variance for each student group at each point in time, as well as a unique over-time correlation for each group. Using criteria AIC and BIC, we applied a parsimonious model with only one variance (and correlation) for both groups and points in time (Singer et al., 2003). Effect size Cohen’s d was calculated by dividing the model estimated differences (between groups and points in time) by the square root of this variance.

Ethical considerations

This study received ethical approval from the NVMO Ethical Review Board (NERB), which operates under commission by the Netherlands Association for Medical Education (NVMO). This research project poses no realistic risk for any subject involved in the study and no risk of them being misled or deceived (NERB file number: 2019.5.5).

Results

Of the 444 eligible student respondents, 424 (95.5%) participated in this study. Of these, 368 completed the questionnaire at baseline, 202 completed the follow-up questionnaire, and 146 completed the questionnaires at both measurements (Table 1). The total number of questionnaires available for analysis was 570.

Table 1. Number of respondents according to SRDC cohort at baseline and follow-up

Cohort	Respondents	Baseline	%	Follow-up	%	Baseline & Follow-up	%
2017-D1 2017-DH3 2017-DH4	75 62 50	60 49 50	80% 79% 100%	54 47 NA	72% 75.8%	39 34 NA	52% 54.8%
2018-D1 2018-DH3	63 72	50 57	79.4% 79.2%	44 57	69.8% 79.2%	31 42	49.2% 58.3%
2019-D1 2019-DH3	65 37	65 37	100% 100%	NA NA		NA NA
Total respondents	424	368	86.8%	202	47.6%	146	34.4%

D1 = 1^st year master of dentistry students starting in SRDC, 2^nd year at follow-up

DH3 = 3^rd year bachelor of dental hygiene students starting in SRDC, 4^th year at follow-up

DH4 = 4^th year bachelor of dental hygiene students starting in SRDC (applicable only in 2017)

% = percentage of respondents

NA = not applicable

Validation of the RIPLS: modified subscales

We applied a CFA (follow-up n = 202) based on the first 16 items with only two latent factors: “Teamwork & Collaboration” (items 1–9) and “Professional Identity” (items 10–16). This model returned an unsatisfactory fit (χ² = 348, p < .001, normed χ² = 3.32, RMSEA = 0.107, CFI = 0.699, TLI = 0.656). The two factors were highly correlated (r = 0.835), making a distinct interpretation of each factor less credible.

Given these results, we subjected the 16 items to an EFA, using the students’ scores/data of the second measurement (follow-up n = 202). We first tried an EFA without specifying the number of factors to be extracted. Although intermediate results of this analysis seemed to suggest the existence of four factors, definitive convergence was not reached. We then ran a new EFA with three factors to be extracted. Convergence was reached, but the solution we obtained was difficult to interpret: one factor covered the “Negative Professional Identity” (items 10–12), but the other two factors contained a mixture of “Positive Professional Identity” (items 13–16) and “Teamwork & Collaboration” (items 1–9). Although the scree-plot showed one dominating factor, we continued with a two-factor EFA. After removing two cross-loading items one-by-one, the following 14 items remained: items 1–9, 13, and 15 loaded highest on factor 1 (“Teamwork & Collaboration”) and items 10–12 loaded highest on factor 2 (“Negative Professional Identity”). For this solution, all (absolute) loadings on the primary factor were higher than 0.36 and those on the secondary factor were lower than 0.20.

We validated the EFA solution found for the follow-up data by applying a CFA to the students’ scores/data of the first measurement (baseline n = 368), using the 14 items selected and with only the primary factor loadings estimated. The fit was not optimal and we removed item 5 because of the lower loading value (0.28). The fit was satisfactory after allowing 4 correlations of item residuals (item 3 and item 15, item 7 and item 8, item 13 with items 1 and 2): χ² = 87, p = .01, normed χ² = 1.45 CFI = 0.975, TLI = 0.967, RMSEA = 0.035. The goodness of fit was also satisfactory for the second measurement (follow-up) after removing item 5 (χ² = 82, p = .06, normed χ² = 1.28 CFI = 0.968, TLI = 0.961, RMSEA = 0.037).

For the two modified subscales of “Teamwork & Collaboration” (items 1–4, 6–9, 13 and 15) and “Negative Professional Identity” (items 10–12), the Cronbach’s alpha reliability were 0.80 and 0.70 respectively.

We continued working with these modified subscales in the mixed linear regression model and used the mean value of the items of the given subscale as the student’s score for that subscale. Except for item 13 and 15, the items in our modified scales cluster together in a similar way to those in the original subscales. Hence, we applied the modified subscale names: “Teamwork & Collaboration” and “Negative Professional Identity.” Table 2 shows the observed means and standard deviations of the modified subscales for both groups of students at baseline and follow-up.

Table 2. Means and standard deviations (dental hygiene vs. dentistry students) and exposure (baseline vs. follow-up) for the two subscales underlying the RIPLS

subscale	Respondents	Mean (SD) T0	Mean (SD) T1
Teamwork & Collaboration	D	3.98 (0.3)	3.98 (0.4)
	DH	4.02 (0.4)	4.12 (0.4)
Negative Professional Identity	D	4.22 (0.5)	4.26 (0.5)
	DH	4.23 (0.6)	4.36 (0.5)

DH = dental hygiene students, D = dentistry students, SD = Standard Deviation

T₀ = baseline, T₁ = follow-up

Group differences in attitudes

The mixed linear regression model yields the over-time change from baseline to follow-up for both groups of students. Table 3 shows these results of the model, along with significances and effect sizes.

Table 3. Regression coefficients and effect sizes of group (dental hygiene vs. dentistry students) and exposure (follow-up vs. baseline) for the two subscales underlying the RIPLS

	Teamwork & Collaboration		Negative Professional Identity
Difference	Value	Effect Size	Value	Effect Size
Between-group comparison
DH – D at T0	0.0446	0.11	0.024	0.05
DH – D at T1	0.1513*	0.38	0.108	0.21
Within-group comparison
T1 – T0 for DH	0.1103*	0.28	0.132*	0.25
T1 – T0 for D	0.0036	0.01	0.047	0.09

*P = 0.05

DH = dental hygiene students, D = dentistry students

T₀ = baseline, T₁ = follow-up

The attitude for “Teamwork & Collaboration” differed significantly between the two groups at follow-up. A significantly higher score indicates that the dental hygiene students consider teamwork to be more important than dentistry students do. The dental hygiene students’ attitudes toward “Teamwork & Collaboration” were significantly more positive at follow-up than at baseline. The same can be observed for the “Negative Professional Identity” scale, where the high score means a positive attitude toward collaborative learning. The effect sizes of the significant effects were “small” (0.28) to “medium” (0.38) for the “Teamwork & Collaboration” scale and “small” (0.25) for the “Negative Professional Identity” scale. The scores on attitudes on both scales increased for the group of dental hygiene students, but no significant changes in scores were found for the group of dentistry students. The predicted means are visualized in Figure 1, Prediction for “Teamwork & Collaboration” and Figure 2, Prediction for “Negative Professional Identity.”

Figure 1. Prediction for “Teamwork & collaboration.”

Predicted values for entry year 2018 (for the other two entry years, the entire graph is slightly shifted in a vertical direction). Note that the range along the vertical axis corresponds to one standard deviation; if the vertical distance between two points is divided by this range, the corresponding effect size results.

Figure 2. Prediction for “Negative professional identity.”

Predicted values for entry year 2018 (for the other two entry years, the entire graph is slightly shifted in a vertical direction). Note that the range along the vertical axis corresponds to one standard deviation; if the vertical distance between two points is divided by this range, the corresponding effect size results.

Discussion

To our knowledge, this is one of the few studies to offer insight into changes of attitude among oral healthcare students with regard to interprofessional learning and collaboration after one year of work in a SRDC. Overall, this study found positive attitudes toward readiness for interprofessional learning and collaboration, as measured by our modified RIPLS. At baseline, the attitudes of the dental hygiene students and the dentistry students were almost equally positive. At follow-up, the dental hygiene students showed a significant increase toward a more positive attitude to interprofessional learning and collaboration, whereas the dentistry students’ attitudes did not change over time.

Despite the positive attitudes toward IPE/IPC we found in this study, we noticed subtle differences in the attitudes of dental hygiene students and dentistry students to the “Teamwork & Collaboration” and “Negative Professional Identity” subscales. Previous studies have shown that educational background, institutions, and profession can influence the outcomes of an IPE intervention (Berger-Estilita et al., 2020; Talwalkar et al., 2016). When compared to these studies, our results provide new support for the existence of differences between groups of students. After participating in the SRDCs for one year, the dental hygiene students exhibited a more positive attitude toward interprofessional learning than the dentistry students. Possibly, working with the dentistry students offered the dental hygiene students a greater challenge in clinical patient problems with different approaches, which they would not experience when only educated within their own scope of practice. This argument was not applicable the other way around because the dentistry students are also qualified to perform the dental hygiene students’ tasks.

Due to changes in legislation at the time of the educational intervention, there is an increased overlap in scope of practice between the dental hygiene students and dentistry students. This may explain why the dentistry students, though still with positive attitudes, scored less positive than dental hygiene students. The independent position of the dental hygienists and overlap in tasks between the two professionals could pose a threat to the dentistry students in this case (Kersbergen et al., 2020; Knevel et al., 2017; Reinders et al., 2017). Changes were made to legislation regarding the independent performance of reserved procedures by dental hygienists, such as drilling and filling cavities, administering anesthesia without a special referral from the dentist, and evaluating x-rays (“Besluit van 17 mei, 2019”, 2019). These developments in oral healthcare could affect professional attitudes toward each other in “Teamwork & Collaboration.” In contrast, our finding that the dental hygiene students’ attitudes were more positive may also be due to the expansion of their scope of practice.

We found a different over-time change in attitude for the two groups. Whereas the dental hygiene students’ attitude scores significantly increased, we did not find a similar change over time for the dentistry students, on either scale. One explanation may be that an important condition for improving the attitude toward collaborative learning was not (or not completely) met: namely, that both groups should experience an equal status (Bridges & Tomkowiak, 2010). Our study did not investigate whether this equal status applies (or was experienced) here. Another explanation might be a difference in education phase between the groups. While the dentistry students had started a master-level program, the dental hygiene students were still following a bachelor-level program. However, for both groups, this was their first experience with IPE. That might explain the quite similar scores at baseline.

In comparison to clinical practicum experiences, students experience the SRC as a unique learning experience (Huang et al., 2021). Our findings are consistent with those previous findings and could offer an explanation for the positive attitude toward interprofessional learning and collaboration, as the reality of practice acted as a mechanism for positive outcomes (Hammick et al., 2007). This IPE setting enables students to learn in a team and to observe other professionals during patient care. The results of our study match those of earlier studies (Reinders et al., 2018) and are consistent with prior literature examining intergroup contact in the interprofessional field (Hean et al., 2018). The contact between both groups contributes to a better understanding of each other’s roles (Kersbergen et al., 2020; Lie, Forest, Kysh et al., 2016).

Methodological considerations

Our study is the first longitudinal study to report on students’ attitudes toward interprofessional learning and collaboration in oral healthcare after participating in an SRDC setting for one year. The main strengths of this study are: 1) that the educational intervention was embedded in the curriculum applied in a clinical setting, and 2) that a large number of eligible students responded initially and at follow-up after their first year of education in the SRDC. Until now, there has been little research involving long-term IPE training with follow-up of collaboration in a clinical educational setting (Berger-Estilita et al., 2020; Reeves et al., 2013; Satter et al., 2020).

Whether the positive attitudes toward collaborative learning also contribute to different behavior in professional practice is an important question for future research. We have commenced a study to measure attitudes one year after graduation. Furthermore, research in other settings in which both professions learn and work together in a similar way in an educational setting would give more opportunities for comparing the effects of IPE in professional practice.

A limitation of this study is the reliability and validity of the RIPLS. In many studies in which the RIPLS has been applied, the low internal consistency of the subscales has been a topic of discussion (Berger-Estilita et al., 2020; Mahler et al., 2015; McFadyen et al., 2005; Schmitz & Brandt, 2015). Therefore, we applied EFA and CFA analyses to validate our translated RIPLS. We applied CFA in baseline and follow-up to ascertain the fit of a stable subscale structure. A possible impact on the factor analysis (EFA) is our choice for the data of the second measurement (follow-up). These students have more experience with IPE than the students in previous research (McFadyen et al., 2005; Yu et al., 2018).

By eliminating all the items for the “Roles and Responsibilities” subscale and some items for the other subscales, the fit of the resulting factor solution and the internal consistency of the (modified) subscales became satisfactory. However, it should be noted that the modified subscales are not completely comparable with those used in other studies. Therefore, opportunities for comparison between studies using the RIPLS are limited.

We did not include faculty in our study. Additional research involving faculty would be necessary to determine role models in IPE. Previous research asserts that educators’ professional beliefs and attitudes with respect to collaborative practice play a critical role in student training (D’Amour et al., 2009).

Conclusion

At the start of their IPE, on average the oral healthcare students expressed positive attitudes about collaboration in the SRDC. Over time, dental hygiene students expressed a significant increase in their positive attitude toward collaborative learning and teamwork while dentistry students did not significantly change their attitudes. Further research should investigate whether positive attitudes in an educational learning environment in IPE will affect collaborative behavior in professional practice.

Acknowledgments

The researchers thank all the participants for contributing to this study. We also acknowledge the students Nina Rougoor, Sabeau Peters, Bonita van Eekelen, Senna Boer, Manal Rubio, Ivana Palavra, Liza de Wit, Audrey van Veelen, Charlotte Nguyen, Rocio Wagener, Noortje van der Vleuten, and Esther Voncken, who contributed to the data collection over the last three years as part of their graduation scientific assignment. Thanks are also due to Arjan Doolaar for the APA check and Thomas Pelgrim for support in the deposit of data.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.