Journal of Interprofessional CareISSN: 1356-1820 (Print) 1469-9567 (Online) Journal homepage: https://www.tandfonline.com/loi/ijic20

Psychometric item analysis and validation of
the Indonesian version of the Readiness forInterprofessional Learning Scale (RIPLS)
Dwi Tyastuti, Hirotaka Onishi, Fika Ekayanti & Kiyoshi Kitamura
To cite this article: Dwi Tyastuti, Hirotaka Onishi, Fika Ekayanti & Kiyoshi Kitamura (2014)
Psychometric item analysis and validation of the Indonesian version of the Readiness forInterprofessional Learning Scale (RIPLS), Journal of Interprofessional Care, 28:5, 426-432, DOI:
10.3109/13561820.2014.907778
To link to this article: https://doi.org/10.3109/13561820.2014.907778

Published online: 14 Apr 2014.

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ISSN: 1356-1820 (print), 1469-9567 (electronic)
J Interprof Care, 2014; 28(5): 426–432! 2014 Informa UK Ltd. DOI: 10.3109/13561820.2014.907778

ORIGINAL ARTICLE

Psychometric item analysis and validation of the Indonesian version of
the Readiness for Interprofessional Learning Scale (RIPLS)
Dwi Tyastuti1, Hirotaka Onishi1, Fika Ekayanti2 and Kiyoshi Kitamura1
1

Faculty of Medicine, International Research Center for Medical Education (IRCME), The University of Tokyo, Bunkyo-ku, Tokyo, Japan andFaculty of Medicine and Health Sciences, State Islamic University Syarif Hidayatullah Jakarta, Indonesia, Jakarta, Indonesia

2

Abstract

Keywords

Complex health care needs in developing countries are stimulating development andimplementation of interprofessional education (IPE). To better understand IPE, it is necessary
to develop and evaluate an educational program that focuses on interprofessional learning(IPL) in Indonesia. However, no instrument in the Indonesian language has been developed tomeasure attitudes toward IPL. The aim of this study is to describe the process of a cross-cultural
adaptation of the Readiness for Interprofessional Learning Scale (RIPLS) in an Indonesianversion including determining its reliability and validity. The study was conducted among
students enrolled in medical, nursing, pharmacy and public health courses at the State Islamic
University, Jakarta, Indonesia, in 2012. The completed responses to RIPLS were collected from755 students. The psychometric properties were analyzed by both exploratory factor analysis(EFA) and confirmatory factor analysis (CFA). EFA on 18-items revealed three factors accountingfor 59.9% of the total variance. CFA resulted in a three-factor model over 16 items withsatisfactory reliability (alpha coefficients 40.7), construct validity and acceptable indices ofgoodness of fit. We conclude that this Indonesian version of RIPLS with a three-factor modelover 16 items is a valid tool to measure students’ attitudes toward IPL.

Cross-cultural, factor analysis,
interprofessional education, reliability,
validity

Introduction
Currently in developing countries, the health sector faces several
issues such as the double-burden diseases, a shortage of healthprofessionals and low quality of health services (WHO, 2010).
Moreover, globalization has caused increasingly complex healthcare needs (Loxley, 1997; Mickan, Hoffman, & Nasmith, 2010).
Those conditions have stimulated the development and implementation of interprofessional education (IPE) and collaborative
practices in many areas worldwide (WHO, 2010).
It is important to develop and apply IPE in Indonesia in
accordance with the movement launched by WHO, a strategy ofFramework for Action on Interprofessional Education and
Collaborative Practice (WHO, 2010). It is part of WHO’s
longstanding commitment to improve health professional education through IPE (Barr, 2010).
To understand interprofessional learning (IPL) and the bestmodel for collaborative practice among health providers inIndonesia, it is necessary to develop an initial program that
focuses on IPL in community-based settings. The reasons are as
follows: primary healthcare is at the forefront of health services inIndonesia; home care services have become necessary inIndonesia due to increased life expectancy and the prevalence

Correspondence: Dwi Tyastuti, Faculty of Medicine, International
Research Center for Medical Education (IRCME), The University ofTokyo, Central Building, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033,
Japan. E-mail: dwityastuti@uinjkt.ac.id

History
Received 22 August 2013
Revised 21 January 2014
Accepted 20 March 2014
Published online 11 April 2014of chronic diseases; students can learn about patient caremanagement in integrated and holistic approaches; and students
can work with a large number of other health professions in thecommunity such as paraprofessionals (educators and lawyers),
community volunteers and indigenous workers (Islamic scholars,traditional birth attendants, non-registered nurses, etc.) who haveunique roles in supporting the health programs in Indonesia.
One of the indicators of success of an IPL program is highscores on measures of students’ knowledge, skills and attitudes.
We presume that the assessment of students’ attitude is the mostimportant element in promoting IPL in Indonesia since attitudes
are the biggest barriers to overcome (Gilbert, 2005; Parsell &Bligh, 1999). Many scales have been constructed to measurevarious aspects of attitude in IPL since IPE was initiallyintroduced 30 years ago. A scale used to evaluate students’attitude toward IPE with a good level of validity (Freeth, Reeves,Hammick, Koppel, & Barr, 2005) is the Readiness forInterprofessional Learning Scale (RIPLS) published by Parsell
and Bligh in 1999. It is an important instrument for evaluatinginterprofessional activities (Reid, Bruce, Allstaff, & McLernon,
2006).
The RIPLS is preferred to other existing measures of IPE since
the scale has been examined and reported in the peer-reviewed
literatures (Thannhauser, Russell-Mayhew, & Scott, 2010), thus
the scale is used widely in the IPE literatures (Williams, Brown,& Boyle, 2012) and has been adapted for use in different
languages such as in Swedish and Japanese (Lauffs et al., 2008;
Tamura, Seki, Usami, Taku, & Bontje, 2012). The Indonesianversion of RIPLS is needed as an instrument to evaluate students’Validation of RIPLS scale in Indonesian version

DOI: 10.3109/13561820.2014.907778

attitudes toward IPL in various educational programs inIndonesia. To our knowledge, there is no information on the
RIPLS scale in Indonesia.
Parsell and Bligh performed validation tests on the RIPLS
scale in 1998 (n ¼ 914 respondents) and in 1999 (n ¼ 120
respondents), and both studies yielded different factors (Parsell& Bligh, 1999; Parsell, Stewart, & Bligh, 1998). The first study(1998) generated a RIPLS scale that consisted of 19 items andwas grouped into two main constructs: teamwork and collaboration (TWC) and professional identity (PI) (Parsell et al., 1998).
The second study (1999) yielded three subscales including a
subscale of TWC (item 1–9), PI (item 10–16) as well as roles andresponsibilities (RR; items 17–19) (Parsell & Bligh, 1999). The
study bt Lauffs et al. (2008) generated constructs similar toParsell& Bligh’s study (1999) and other studies yielded different
constructs (McFadyen, Webster, & Maclaren, 2006; McFadyen
et al., 2005; Tamura et al., 2012). El-Zubeir, Rizky, and Al-Khalil(2006) and Reid et al. (2006) modified RIPLS to adjust forexisting conditions, and this modified RIPLS yielded a satisfactory reliability. The validation of the RIPLS Japanese version
generated a three-factor model, but the items that constructed
these factors were different from other models (Tamura et al.,2012).
The aim of the study presented in this article is to describe thepsychometric properties, reliability and validity of the Indonesianversion of the RIPLS scale, adapted from the original scale
through a cross-cultural process, in order to be able to assess thereadiness of undergraduate students to engage in interactive andcollaborative learning during community-based health care.

427

Hidayatullah Jakarta, Indonesia, in February 2012. First to
third-year students from four courses (medicine, nursing, pharmacy, and public health) participated in the study. We distributed
800 questionnaires. Of the 776 questionnaires returned byparticipants, 21 (2.8%) questionnaires were invalid and excluded.
The sample size of 755 met the minimum criteria (Hair, 2005;
Kline, 2005).
Instrument
We only translated and used 18 items from the original scale inthis study. We omitted item 17 (the function of nurses andtherapists is mainly to provide support for doctors). The reasonsfor omitting this question are as follows: (1) there are no therapist
students who participated in this study and (2) the term‘‘therapist’’ is used ambiguously in Indonesian society, since
the term is used in fields other than the medical one.
Item answers were given on five-point Likert scales (1 ¼strongly disagree, 2 ¼ disagree, 3 ¼ neutral, 4 ¼ agree and 5 ¼
strongly agree) with higher scores indicating more positive
attitudes. Table 1 described the reliability coefficient of the
RIPLS from previous studies in both the original version andmodified versions.
Data collection
Data were collected by distributing the questionnaire in classrooms over a two-week period. A faculty member made aschedule to set the day, time and length of time required to fill out
the questionnaire. Faculty members who were not involved inteaching activities assisted in the distribution and collection ofquestionnaires.

Methods
Cross-cultural adaptation process

Data analysis

Translation into the Indonesian language and cross-cultural
adaptation of the original version of the RIPLS was conductedaccording to guidelines (Guillemin, Bombardier, & Beaton,
1993). The process of adaptation started with forward andbackward translations (van de Vijver & Hambleton, 1996). The
first phase was the translation of the questionnaire (forward
translation) by two language experts. The second phase aimed toassess the consistency between the original version and thetranslated version. The scale in the Indonesian version was retranslated into English (backward translation) by different
language experts to check for inconsistencies.

To ensure validity and to determine the best factor structure of the
RIPLS scale in the Indonesian version, both exploratory factor
analysis (EFA) and confirmatory factor analysis (CFA) wereconducted. EFA was run to identify latent variables or factors of aset of variables (Harrington, 2009), whereas CFA was performed
to assess the fit of a model obtained from the EFA result or apreviously existing theoretical model and to confirm convergent
and discriminant validity of a fit model (Hair, 2005; Harrington,2009).
The total samples (n ¼ 755) were randomly divided into two
split-half samples by SPSS, version 16.0 (SPSS Inc., Chicago, IL),
one for EFA (n ¼ 377) and one for CFA (n ¼ 378). Data from thesub-sample (n ¼ 377) were analyzed by EFA on 18 items of theIndonesian version with maximum likelihood methods andoblique rotation. Acceptance of EFA was checked with three

Participants
The main study was carried out at the Faculty of Medicine and
Health Sciences (FMHS), State Islamic University, Syarif

Table 1. Summarize of the internal consistency of the RIPL scale from previous studies.
Internal coefficient (Cronbach’s alpha)Study
Parsell, Stewart, & Bligh (1998)
Parsell & Bligh (1999)
McFadyen (2005), data 2003a
McFadyen (2005), data 2004a
McFadyen (2006)a
Lauffs et al. (2008)
Reid et al. (2006)b
El-Zubeir et al. (2006)b
Tamura et al. (2012)ba

Number of samples

Number of items

914
120
308
247
65
214
66
178
132

19
19
19
19
19
19
23
20
19

Total

TWC

PI

RR

0.90
0.84
0.89
0.89

0.85
0.88
0.79
0.88
0.71
0.89

0.46
0.63
NPI ¼ 0.60; PPI ¼ 0.76
NPI ¼ 0.76; PPI ¼ 0.81
NPI ¼ 0.38; PPI ¼ 0.61
0.48

–
0.32
0.40
0.43
0.62
0.34

0.76
0.61
0.74

McFadyen’s studies produced a four-factor model.
All of these studies yielded three factors, but the items that made up these factors were different from other studies.
NPI ¼ negative professional identity; PPI ¼ positive professional identity.

b

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D. Tyastuti et al.

well-recognized criteria for EFA analysis, the Kaiser–Meyer–
Olkin (KMO), Bartlett’s test of sphericity and the diagonals of theanti-image correlation matrix. Two criteria were set up to retain
factors produced by EFA, i.e. eigenvalues 41 and scree plot
evidence (DeVellis, 2012).
The second sub-sample (n ¼ 378) was used for the analysis offactor structure using CFA. In this study, the CFA procedure withmaximum likelihood estimates (Hair, 2005), and the goodness-offit (GOF) of the model was evaluated by multiple criteria (Hair,
2005; Harrington, 2009). To indicate a fit model, the criteria for
GOF include the Normed Fit Index (NFI), the Goodness of Fit
Index (GFI), the Tucker–Lewis fit index (TLI) and theComparative Fit Index (CFI) all of which are acceptable if
40.90. The Standardized Root Mean Square and the Root Mean
Square Error of Approximation (RMSEA) are also acceptable if
50.08 (Browne & Cudeck, 1993; Byrne, 2001; Schumacker &Lomax, 2004). Reliability of the Indonesian version was assessedby internal consistency, item reliability and composite reliability(CR) (Fornell & Larcker, 1981; Hair, 2005). The validity of thescale was tested by calculating construct and discriminant
validity. All analyses were conducted using SPSS version 16.0
and AMOS version 18.
Ethical considerations
All students gave written and oral informed consent after
receiving both written and oral information about this study.
The Ethics Committees of both the University of Tokyo and theState Islamic University, Syarif Hidayatullah Jakarta, Indonesia,
approved the research. The University of Tokyo collaborates with
the State Islamic University to improve the quality of teaching
staff at FMHS.

Results
Descriptive and statistical assumptions
Among 800 questionnaires distributed, 776 questionnaires werecollected. A total of 21 questionnaires were excluded because(1) eight questionnaires had missing items, and the result of themissing value analysis showed that the values of missing
completely at random were 40.05; and (2) 13 questionnaires
showed outliers (Z-score values of less than 3 or more than +3)(Kline, 2005). Valid questionnaires were 755 and the response
rate was 94.4%. The proportion of female student (n ¼ 557,
73.8%) was higher than male students. Students who participatedin this study are from public health (33.6%), medicine (30.5%),
pharmacy (29.8%) and nursing (6.1%) courses. Participantsconsisted of first-year students (45.8%), second-year students(28.7%) and third-year students (25.5%).
Factor analysis
EFA on 18 items was accepted because three measures met thecriteria. The KMO (0.905) and Bartlett’s test of sphericity(p50.001) indicated a factorable correlation matrix. Third, thediagonals of the anti-image correlation matrix for all items were
between 0.799 and 0.944, above the standard of 0.5 (Hair, 2005).
Initially, EFA was performed by using maximum likelihood
and promax rotation, and we found the cross loading of someitems on some factors. Subsequently, we performed direct oblimin
rotation, which produced factors that were free of cross loading(Table 2). The EFA showed 59.9% of the total variance including
37.3% for the first factor (F1), 10.8% from the second factor (F2),
6.1% from the third factor (F3) and 5.7% from the fourth factor(F4). The composition of items for each sub-scale in theIndonesian version was unlike the previous studies. The results
showed that F1 covered items 1–6, F2 did items 10–12 and 18, F3

J Interprof Care, 2014; 28(5): 426–432

did items 13–16 and 19 and F4 covered items 7–9. The factor
loadings for item 19 was 0.255, whereas the other 16 items weremore than 0.4 (between 0.401 and 0.905).
Measurement models
The CFA was conducted for the Indonesian version to examine
reliability and validity of the scale and generate a fit model. The
maximum likelihood method of estimation was chosen since thenormality assumption was not violated (Kline, 2005).
Initial model
The initial model was a measurement model derived from theresults of the EFA. The four-factor model with 18 items (F1: items
1–6; F2: item 7–9; F3: items 10–12 and 18; F4: items 13–16 and19) showed that the t-value of all items were significant by thecriterion of p50.05. However, a Heywood case was found withitem 19 [communality41] (Hair, 2005; Kline, 2005). The loading
factors of items 1–16 were more than 0.5, but item 18 and 19 hadloadings of 0.433 and 0.133, respectively, suggesting that items
18 and 19 were not represented in the measured constructs(Figure 1).
The initial model was not a fit model because items 18 and 19
had loading factors of less than 0.5, and there was a Heywoodcase on item 19 (Hair, 2005; Kline, 2005). Hence, we eliminateditems 18 and 19 from the model and reconstructed a 16 item
model for the next analysis by using previously existing theoretical models.
Three-factor version
We conducted CFA on several models to find the fit model andthe three-factor model with 16 items was a satisfactory model forthis study. The three-factor model with 16 items showed thatfactor loadings for all items ranged from 0.55 to 0.86. Although
Hair (2005) suggested that the best factor loading was more than
0.7 (Hair, 2005), factor loading more than 0.5 was alsosatisfactory, especially in explorative research (Johnson &Stevens, 2001) (Figure 2).
Therefore, we retained all items (16 items) for model
modification and further analysis. Furthermore, a three-factor
model with 16 items yielded an acceptable Normed chi-square of
2.485, and all other GOF indices met criteria such as GFI (0.92),
NFI (0.91), TLI (0.93), CFI (0.94), Standardized Root Mean
Square Residual (SRMR) (0.043) and RMSEA (0.063) (Table 3).
Assessment of internal structure of a model
Reliability analysis showed that the overall alpha coefficient of
the initial model (0.69) was lower than modified models (0.87).
Table 3 shows that three alpha coefficients of the modified model
were more than 0.70.
Furthermore, average variance extracted (AVE) and CR were
calculated to check construct validity of the measurement model.
CR values for each construct of the modified model were satisfied(40.7) (Fornell & Larcker, 1981). AVE of each factor is expected
to be 40.5. AVE for two factors, negative professional identity(NPI) and positive professional identity (PPI), met the criterionand AVE for TWC factor was close to the criterion (see Table 3).
Thus, the modified version had good construct validity.
Discriminant validity upon a scale was tested to check theconfidence in subsequent research findings (Fornell & Larcker,1981) to confirm unidimensionality of each construct.
Discriminant validity is demonstrated if the AVEs of bothconstructs are greater than the squared correlation (Chau, 1997;
Fornell & Larcker, 1981). This study used this method todetermine whether the constructs in the three-factor model wereValidation of RIPLS scale in Indonesian version

DOI: 10.3109/13561820.2014.907778

429

Table 2. Results of data normality, loading factor and reliability on EFA samples (n ¼ 377).

Statement
1. Learning with other students/professionals will make me a more effective member ofa health and social care team
2. Patients would ultimately benefit if health and social care students/professionals
worked together
3. Shared learning with other health and social care students/professionals will increase
my ability to understand clinical problems
4. Communications skills should be learned with other health and social care students/
professionals
5. Team-working skills are vital for all health and social care students/professionals
to learn
6. Shared learning will help me to understand my own professional limitations
7. Learning between health and social care students before qualification and for
professionals after qualification would improve working relationships after
qualification/collaborative practice
8. Shared learning will help me think positively about other health and social care
professionals
9. For small-group learning to work, students/professionals need to respect and trust
each other
10. I don’t want to waste time learning with other health and social care students/
professionals
11. It is not necessary for undergraduate/postgraduate health and social care students/
professionals to learn together
12. Clinical problem solving can only be learnt effectively with students/professionals
from my own school/organization
13. Shared learning with other health and social care professionals will help me tocommunicate better with patients and other professionals
14. I would welcome the opportunity to work on small group projects with other healthand social care students/professionals
15. I would welcome the opportunity to share some generic lectures, tutorials orworkshops with other health and social care students/professionals
16. Shared learning and practice will help me clarify the nature of patients’ or clients’problems
18. I am not sure what my professional role will be/is
19. I have to acquire much more knowledge and skill than other students/professionals
in my own faculty/organization
Cronbach’s a
Total variance explained (59.9)

Sub-scales/factor

Mean
(SD)

1*

2*

3*

4*

1.88 (0.58)

0.762

0.052

0.025

0.172

1.59 (0.52)

0.567

0.003

0.0730.124

1.72 (0.55)

0.656

0.058

0.012

0.093

1.82 (0.60)

0.403

0.031

0.130

0.288

1.68 (0.52)

0.446

0.0100.0490.323

1.86 (0.59)
1.72 (0.53)

0.520
0.058

0.0060.033

0.007
0.027

0.089
0.729

1.69 (0.49)

0.200

0.103

0.025

0.602

1.64 (0.53)

0.201

0.054

0.0820.496

3.41 (1.23)

0.073

0.006

0.651

0.146

3.92 (0.95)

0.043

0.0270.760

0.0883.46 (1.02)

0.112

0.052

0.727

0.064

1.84 (0.57)

0.270

0.401

0.007

0.073

1.88 (0.54)

0.152

0.546

0.020

0.034

1.86 (0.52)

0.0110.945

0.048

0.123

1.82 (0.52)

0.060

0.668

0.008

0.227

4.03 (0.87)
1.92 (0.69)

0.200
0.015

0.037
0.255

0.475
0.072

0.327
0.178

0.84
37.3

0.77
10.8

0.72
6.1

0.59
5.7

*Loading treshold  0.4.

different from the others. Focusing on Table 4, the results showsquestionable discriminant validity for constructs of TWC since
the AVE of TWC (0.46) was lower than the square correlation
between TWC and PPI (0.59). Only the constructs of NPI and PPI
indicated acceptable discriminant validity because the AVE wasgreater than the squared correlation. The results demonstrated that
NPI and PPI were unidimensional.

Discussion
In this study, the original RIPLS was translated and adapted to an
Indonesian setting, and the Indonesian version proved to be amodel with three constructs on 16 items by EFA and CFA. It wasalso demonstrated to be a reliable and valid scale. This final
model is as McFadyen et al. (2005) without the RR sub-scale.
EFA on the Indonesian version was run for 18 items by using
direct oblimin, and this produced four-factor model. The total
variance of this study was higher than the previous study(McFadyen et al., 2005; Parsell & Bligh, 1999; Parsell et al.,1998). However, this study only used 18 of 19 items from theoriginal study, and the sample study was first to third year
students. It was different from previous studies.
Through CFA processes, the four-factor model of EFA result
was tested and did not offer the most desirable fit to our data (seeTable 3). Reconstructing the measurement model by omitting
items 18 and 19, due to low and negative loading factors,

generated a three-factor model, which can be labeled as TWC,
PPI and NPI, because these factors have the same formation as
McFadyen’s study (2005, 2006). Referring to criteria of the fitted
CFA model (Brown, 2006), we can conclude that the final CFA
with this three-factor model showed satisfactory data. Absolute fit
indices in this study consisted of Normed chi-square, GFI, NFI,TLI, CFI, RMSEA and SRMR, and all generated acceptable
results.
Each absolute fit index was unique and cannot be used
individually because the indices are sensitive to several factors
such as the number of samples, whether the data is based on
population or not, parsimony or complexities of a model andnumber of parameters of a model (Bagozzi & Yi, 1988; Tanaka,
1993). As for the comparative fit indices (Brown, 2006), also
referred to as incremental fit indices (Hu & Bentler, 1998), we
analyzed three indices, i.e. indices of CFI, TLI and NFI, which
generate satisfactory data (CFI ¼ 0.94, NFI ¼ 0.91 and
TLI ¼ 0.93). Although NFI is very sensitive to sample size lessthan 200, CFI is an index that is not affected by sample size andalso can be used as an indicator to ensure no misspecification
models. TLI is an important index to compensate for the effect ofthe model complexity (Brown, 2006).
Internal consistency, as determined by the alpha coefficientfor each factor, was adequate in this study (alpha coefficient ¼ 0.71 for the instrument; 0.75–0.88 for each factor). The
results presented in Table 3 attested to the high internal

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D. Tyastuti et al.

Figure 1. A measurement model of 18 items four-factor model (initialmodel).

consistency of the instrument in which all values were above thesuggested 0.70 level for scale robustness (Nunnally & Bernstein,1994).
Construct validity of a three-factor model showed that the AVE
and CR of all constructs yielded acceptable values, but the test of
discriminant validity resulted in unidimensional constructs for
NPI and PPI, whereas the construct of TWC was two-dimensional. A high alpha value does not necessarily indicate that afactor is unidimensional. The alpha coefficient is not sufficient formeasuring the dimensionality of a construct or factor (Tavako &Dennick, 2011). This is evidenced by TWC’s factor in this study
in which the alpha coefficients of this factor was high but TWC’s
factor was multidimensional. Several factors contributed to theemergence of discriminant validity problems and low factor
loading. In this study, the existence of cultural diversity among
respondents such as gender, ethnicity, belief and local cultures(Pashaei, Razaghi, Foroushani, & Tabatabaei, 2013) as well as
students’ experiences in multi disciplinary work (McFadyen et al.,2005) may have influenced the responses to the items on theIndonesian version. In addition, the health and education systems
prevailing in Indonesia and the effect of translation into aparticular language played a significant role in this study. The
important issue is that when translating an instrument to anotherlanguage and testing its validity, the role of cultural differencesmust be considered (Pashaei et al., 2013).
Several studies on the validation of the RIPL scale showed thatthe factor of RR is unstable. Parsell and Bligh’s study (1998) only
generated two factors (TWC and PI), and the study on 1999
produced three factors (TWC, PI and RR) but the internal

J Interprof Care, 2014; 28(5): 426–432

consistency of RR factor was unacceptable (50.3). Similar results
were also found in subsequent studies (Lauffs et al., 2008;
McFadyen et al., 2005) and generated an inadequate internalconsistency of RR factor, and another study failed to establish RR
factor (Tamura et al., 2012; Williams et al., 2012). Only the study
by McFadyen et al. (2006) yielded an adequate internal coefficient RR factor (RR ¼ 0.62). This condition may be related to theability of the respondents to comprehend the meaning of role andresponsibilities in clinical setting (McFadyen et al., 2005). In thisstudy, we failed to produce an RR factor, and this may have been
due to omitting item 17. It may have affected the items 18 and 19
as they load on the same factor (RR factor).
In the main study, items 18 and 19 had low loadings andindicated that both items were not appropriate in Indonesiancontext. Item 18, ‘‘I am not sure what my professional role willbe/is’’, had loadings of 0.436 by CFA. It is possible that the item
wording introduced error variance. The participants in this study
were first- to third-year students. The first-year students could
answer this question by seeing this statement as contrary to theirunderstanding. Many studies of students’ perception about careerand profession show that first-year students give positive
responses about their future career as a physician, nurses or
pharmacist (Kritikos, Watt, Krass, Sainsburry, & BosnicAnticevich, 2003; Law & Arthur, 2003; Rudland & Mires,
2005; Watmough, Waddelove, & Jaeger, 2009), whereas theadvanced students’ views toward their profession or otherprofessions were acquired from teachers, media or prior work
experiences. If students encountered unclear tasks and theoverlapping of RR, then students would think that their professional role is not clear (Hall, 2005). Furthermore, the understanding of the term ‘‘role and professional responsibility’’ in theclinical field may not be so obvious to young professionals ascompared to the advanced students (McFadyen et al., 2005).
Item 19, ‘‘I have to acquire much more knowledge and skill
than other students/professionals in my own faculty/organisation’’, had loadings of 0.255 on factor 2 by EFA and had loadingof 0.133 by CFA. The wording of this question might have beena problem, because having confident in one’s performance on‘‘much more knowledge and skills’’ measure not only academic
self-efficacy but also generalized self-esteem. In social learningtheory, self-efficacy reflects an individual’s understanding ofwhat knowledge and skills he/she can offer to the members in agroup setting (Ormrod, 1999). However, item 19 implied not only
high self-efficacy but also implied the meaning ‘‘to be more
superior than the others’’ in Indonesian context. The meaning of
this statement is contrary to the concept of equanimity inIndonesian society. The concept of ‘‘equanimity’’ in Indonesiansociety is influenced by beliefs and religion and implies doing
everything for the good of humanity and nature and not for selfish
purposes. More than two-thirds of the participants in this study
were from the countryside, and they studied in Islamic boarding
schools so this concept is deep-rooted.
Reconstructing the measurement model in an Indonesianversion was successful because the fit model, 16 items threefactor model, yielded the highest reliability and construct validity
and the acceptable GFI when compared to the initial model(18 items four-factor model). Although the 16 items three-factor
model of Indonesian version is favorable, there are several
limitations. First, our sample was confined to a school of healthprofessionals in Indonesia that might not represent all Indonesianstudents. The findings may be difficult to generalize because thesample was only derived from one institution. Second, thesampling method was non-probability which may produce
sampling bias. Nonetheless, the sample represented students
from various multicultural and social backgrounds, which isreassuring. Finally, this study only validated 18 items of 19 items

Validation of RIPLS scale in Indonesian version

DOI: 10.3109/13561820.2014.907778

431

Figure 2. Standardized factor loading of 16
items three-factor model (modified model).

Table 3. Confirmatory factor analysis: reliability, validity and fit indices of initial and modified models (N ¼ 378).
Reliability–validity
Indicator
A. Initial model (18 items)
FA1 (items 1–6)
FA2 (items 7–9)
FA3 (items 10–12, 18)
FA4 (items 13–16, 19)
B. Modified model (16 items)
Three factors
TWC (items 1–9)
NPI (items 10–12)
PPI (items 13–16)

a

CR

AVE

(0.69)
0.84
0.77
0.72
0.59
(0.87)

0.85
0.77
0.74
0.68

0.48
0.43
0.42
0.45

0.88
0.73
0.86

0.89
0.75
0.86

0.46
0.51
0.62

Index fit
CMIN (df)

CMIN/df

GFI

NFI

TLI

CFI

RMSEA

SRMR

AIC

234.08 (113)

2.07

0.93

0.91

0.94

0.95

0.053

0.050

314.08251.07 (101)

2.48

0.92

0.91

0.93

0.94

0.063

0.043

321.67

Table 4. Analyzing of discriminant validity in the three-factor model(N ¼ 378).

of the RIPLS original scale among four courses (medicine,
nursing, pharmacist and public health).

Three factor model

Conclusion comments

TWC
NPI
PPI
a

TWC

NPI

PPI

0.51a
0.18

a

a

0.46
0.14
0.59

0.62

Diagonal elements report of the AVE and other matrix entries report thesquared correlation estimation between two factors.

This study contributed to the literature in a number of ways. First,
to our knowledge, it is the first study to investigate RIPLS in theIndonesian context. Second, the translation and adaptation of the
RIPLS into the Indonesian language by a cross-cultural adaptation
process was successful, and the Indonesian version produced a432

D. Tyastuti et al.

valid and reliable scale as verified by structural equation
modeling. Third, two RIPLS items in the Indonesian version
exhibited misfit measurement within the model and were
excluded. Consequently, further revision and assessment of the
RIPLS’ psychometric properties in the Indonesian version isrecommended.

Declaration of interest
The authors report no conflicts of interest. The authors alone areresponsible for the writing and content of this paper.
The research was funded from the University of Tokyo.

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