Modeling the effect of social interdependence in interprofessional collaborative learning

Figures & data

Table 1. Factor analysis of SOCS and RIPLS.

A. SOCS
Items		Factors
		Boundary Interdependence	Means Interdependence	Outcome Interdependence
4	I incorporate the advice of others when preparing a study plan.	0.792	−0.018	−0.009
5	Group members should carefully summarize each other’s arguments.	0.717	0.088	−0.126
1	I hope my learning group is superior to others.	0.679	0.059	−0.042
3	For me, it is important to maintain harmony within the group.	0.591	−0.039	0.040
7	I try to share my own thoughts and materials if they are useful to other students.	0.514	−0.043	0.278
2	When there are different opinions, I would like to coordinate them.	0.505	−0.154	0.119
6	Discussions with other members who have different opinions will improve me.	0.373	0.216	−0.056
12	We learn numerous important things from one another.	−0.090	0.882	0.016
10	I can learn important things from other students.	−0.077	0.771	−0.018
11	It is a good idea for students to help one another in their studies.	−0.064	0.673	0.159
9	It is a good idea to share the tasks for more efficient group work.	0.116	0.504	−0.048
8	I have respect for the others with whom I interact.	0.286	0.452	−0.076
14	My peers rely on my presence as well as my help and support.	−0.099	0.001	0.990
15	I draw conclusions from information in group discussions.	0.318	−0.029	0.588
13	My peers rely on my information and advice.	0.208	0.124	0.573
B. RIPLS
Items		Factors
		Interprofessional Collaboration	Interprofessional Roles/Identity
3	Shared learning with other health care students will increase my ability to understand clinical problems	0.890	−0.010
1	Learning with other students will help me become a more effective member of a health care team	0.865	−0.002
4	Learning with health care students before qualification would improve relationships after qualification	0.858	−0.118
2	Patients would ultimately benefit if health care students worked together to solve patient problems	0.829	0.045
16	Shared learning before qualification will help me become a better team worker	0.813	0.009
6	Shared learning will help me to think positively about other professionals	0.785	0.022
13	Shared learning with other health care students will help me to communicate better with patients and other professionals	0.781	0.058
7	For small group learning to work, students need to trust and respect each other	0.768	0.004
15	Shared learning will help to clarify the nature of patient problems	0.762	−0.008
9	Shared learning will help me to understand my own limitations	0.733	−0.095
5	Communication skills should be learned with other health care students	0.700	−0.068
14	I would welcome the opportunity to work on small-group projects with other health care students	0.649	0.012
8	Team-working skills are essential for all health care students to learn	0.611	0.229
19	I have to acquire much more knowledge and skills than other health care students	0.404	−0.289
11	It is not necessary for undergraduate health care students to learn together	0.020	0.941
10	I do not want to waste my time learning with other health care students	0.097	0.812
18	I am not sure what my professional role will be	0.033	0.655
12	Clinical problem solving skills can only be learned with students from my own department	−0.115	0.603
17	The function of nurses and therapists is not mainly to provide support for doctors	−0.174	0.475

Extraction Method: Maximum Likelihood. Rotation Method: Promax with Kaiser Normalization.

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Table 2. Determination of numbers of factors.

A. Determination of the number of factors in SOCS
Number of factors (up to 5)	Eigenvalues	Cumulative contribution ratio (%)	MAP	Parallel analysis (Eigenvalues)	SMC diagonal	Parallel analysis (SMC diagonal)
1	5.341	38.147	0.039	1.484	4.847	0.539
2	2.128	53.350	0.029	1.369	1.615	0.434
3	1.079	61.059	0.026	1.279	0.519	0.339
4	0.930	67.703	0.040	1.203	0.350	0.272
5	0.714	72.800	0.056	1.131	0.110	0.205
B. Determination of the number of factors in RIPLS
Number of factors (up to 3)	Eigenvalues	Cumulative contribution ratio (%)	MAP	Parallel analysis (Eigenvalues)	SMC diagonal	Parallel analysis (SMC diagonal)
1	8.621	47.893	0.033	1.559	8.276	0.631
2	2.299	60.666	0.020	1.439	1.814	0.535
3	0.996	66.197	0.027	1.361	0.421	0.459

Table 3. Results on the instruments.

Factors	Means	Standard deviation	Number of items	alpha
SOCS
Boundary interdependence	28.87	3.75	7	0.863
Means interdependence	15.75	3.51	5	0.795
Boundary interdependence	12.41	1.95	3	0.807
RIPLS
Interprofessional collaboration	54.15	7.45	13	0.810
Interprofessional identity	23.11	3.80	6	0.931

Figure 1. Standardised coefficients and explained percentage variance for structural constructs.