Chinese Version of Psychometric Evaluation of Self-Reflection and Insight Scale on Taiwanese Nursing Students : Journal of Nursing Research

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ORIGINAL ARTICLES

Chinese Version of Psychometric Evaluation of Self-Reflection and Insight Scale on Taiwanese Nursing Students

Chen, Shu-Yueh1; Lai, Chen-Chun2; Chang, Hui-Mei3; Hsu, Hui-Chen4; Pai, Hsiang-Chu5*

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doi: 10.1097/JNR.0000000000000132
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Abstract

Introduction

Reflection and critical thinking are highly desired characteristics in professional practice (National League for Nursing, 1992; United Kingdom Central Council for Nursing Midwifery and Health Visiting, 1999). Critical thinking is one of the eight core values promoted by the Taiwanese Nursing Accreditation Council (Chao, Dai, & Yeh, 2010; Hsu & Hsieh, 2009). Although reflection is not in the list of core values, it is a “habit of mind” (Epstein, 2008) or capacity that should be cultivated to support lifelong learning.

Critical thinking includes both critical thinking skills and a disposition toward critical thinking. Critical thinking skills are considered higher-order cognitive skills, that is, analysis, interpretation, inference, explanation, self-regulation, and evaluation (Facione, 2013). A critical thinking disposition refers to the characteristics and motivations of a critical thinker, that is, inquisitive, open-minded, systematic, analytic, truth-seeking, self-confident, and mature (Kim, Moon, Kim, Kim, & Lee, 2014; Krupat et al., 2011). Reflective thinking is identified as a critical thinking skill (Vacek, 2009) and is often used as a surrogate term for critical thinking (Turner, 2005). Furthermore, reflective thinking and reflection are often used interchangeably (Kuiper & Pesut, 2004; Mann, Gordon, & MacLeod, 2009). Reflective thinking in nursing practice depends on developing both cognitive and metacognitive skills, which are necessary for effective clinical reasoning (Kuiper & Pesut, 2004). The float model offers a useful metaphor to help health educators visualize the concept of reflection (Aukes, Cohen-Schotanus, Zwierstra, & Slaets, 2009). In this model, which is based on a fisherman’s float, the visible component or portion above the water represents behavior, for example, caring for a patient or participating in a classroom, and the hidden component or the portion under water represents the mental components of maintaining balance in work and learning, that is, thinking or reasoning, personal reflection, and unconscious thoughts. Each mental component helps the reflective person to maintain balance in learning and working. Thinking includes critical thinking, which has been well studied in nursing and evidence-based practice (Chiang, 2014). However, reflection, a mechanism for appraising one’s self, is less visible (particularly its mental components) and remains an abstract notion that is difficult to comprehend, utilize, and apply. According to Aukes et al. (2009), reflection should be the base on which clinicians build scientific thinking and clinical reasoning, with the goal of improving the quality of patient care. To date, reflection has not been studied as much as evidence-based practice or critical thinking, which limits knowledge about reflection. Thus, reflection must be better understood by educators to effectively apply reflection-related knowledge to nursing education.

Reflection has been explored in several classic studies (Boud, Keogh, & Walker, 1985; Mezirow, 1991; Schon, 1983). For example, reflection in the context of learning was generically defined as intellectual and affective activities that explore personal experiences to develop new understandings (Boud et al., 1985). Mezirow (1991) described reflection as the process by which individuals transform their meaning schemes and meaning perspectives, resulting in transformational learning.

Despite these numerous definitions, reflection is generally agreed to involve a process rather than short-lived thoughts or impressions (Asselin, Schwartz-Barcott, & Osterman, 2013). The process of reflection may also lead to insights or awareness of personal achievements as well as to an ability to compare these achievements with the achievements of other people (Hays et al., 2002; Papp et al., 2014). Gaining insight has been described as the third phase in a four-phase process of nurses’ clinical reflection, with the fourth phase being to formulate intentions for change (Asselin et al., 2013). Because intention to change comes from within an individual, this intention may involve a change in perspective or attitude, which may in turn motivate a series of educational changes, including acquisition of knowledge, skills, and behaviors (Ferris & von Gunten, 2007). In other words, the process of reflection may trigger self-regulated learning to achieve a goal or perform better. This process conforms to the three phases of Zimmerman’s (2002) cyclical model of self-regulatory processes: forethought, performance, and self-reflection.

Similar to Zimmerman (2002), Grant, Franklin, and Langford (2002) conceptualized a generic model of self-regulation and goal attainment. This model captures the process of setting a goal, developing an action plan, and taking action. Through this process, an individual monitors performance (through self-reflection), evaluates performance in comparison with a standard (gaining insight), and uses this evaluation to change actions to enhance performance and better achieve personal goals. Self-reflection refers to inspecting and evaluating personal thoughts, feelings, and behaviors, whereas insight refers to a clear understanding of personal thoughts, feelings, and behaviors (Grant et al., 2002). On the basis of this model, the three psychologist authors (Grant, Franklin, and Langford) developed the Self-Reflection and Insight Scale (SRIS) to assess the concepts of self-reflection and insight.

Initially, Grant et al. (2002) constructed items they considered likely to load on two proposed factors: insight (10 items) and self-reflection (20 items). The self-reflection domain was assumed to be composed of two subscales: need for self-reflection (10 items) and engagement in self-reflection (10 items). The SRIS was validated in two studies with two separate groups of psychology students at an Australian university. Overall, 20 items were generated by exploratory factor analysis (EFA) and yielded two factors: “self-reflection” (12 items) and “insight” (eight items). In a later study, EFA (principal component analysis with promax rotation) of the SRIS identified three factors: engagement in self-reflection, need for self-reflection, and insight (Roberts & Stark, 2008), which was consistent with the initial conceptualization (Grant et al., 2002). Moreover, confirmatory factor analysis (CFA) showed that this model fits the data after the deletion of one item (Roberts & Stark, 2008).

The SRIS insight subscale was found to predict all six dimensions of psychological well-being (Harrington & Loffredo, 2011) and has been used to assess the positive impacts of life coaching on mental health, quality of life, and goal attainment (Grant, 2003). Furthermore, the SRIS has been used to assess the self-regulatory behavior of students and professionals in the health professions. For example, the SRIS was used to estimate the readiness for self-directed change in the professional behaviors of undergraduate-entry medical students at a U.K. medical school (Roberts & Stark, 2008). Similarly, the SRIS has been used to evaluate the academic performance of medical students, with fifth-year students exhibiting a significantly higher recognition of the need for reflection than their fourth-year peers (Carr & Johnson, 2013). In a study of occupational therapists (Lowe, Rappolt, Jaglal, & Macdonald, 2007), only scores on the self-reflection dimension of the SRIS and statements on commitment to change were used to purposively select participants for an interview study exploring the role of reflection in integrating learning from continuing education into practice. In nursing, experienced clinical registered nurses were found to have higher SRIS scores on engagement in self-reflection after participating in a reflective-practice continuing education program than beforehand (Asselin & Fain, 2013).

Apparently, the SRIS provides a tool for educators to increase their awareness of student approaches to learning. However, no version of the SRIS has been made available in the Chinese language. In addition, as nurse educators in Taiwan, we must consider ways to promote reflective thinking in our nursing students. Developing and studying the effectiveness of teaching strategies that promote self-reflection and insight requires that these processes be measured by an instrument. Exploring the properties of such an instrument may be one way to provide a platform for nurse educators to share and discuss how to promote students’ self-reflection and insight.

Therefore, the goal of this study was to translate the SRIS into Chinese, to create the Chinese-version SRIS (SRIS-C), and to evaluate its psychometric properties. Specifically, we had three aims: (a) to explore the factor structure of the SRIS-C among Taiwanese nursing students, (b) to confirm the factor model by testing its fit with data from Taiwanese nursing students who completed the SRIS-C, and (c) to examine the associations among Taiwanese nursing students’ SRIS-C scores and their scores in terms of measures of critical thinking disposition and perceived identity as a nurse. We hypothesized that SRIS-C scores would correlate positively with critical thinking disposition (scores on the Taiwan Critical Thinking Disposition Inventory [TCTDI]) and with perceived identity as a nurse (i.e., having the goal of becoming a nurse).

Methods

Study Design and Sample

This study was conducted in two phases, with data collected at two separate times (December 2012 and May 2013). In Phase 1, the factor structure of the SRIS-C was examined by EFA. In Phase 2, the factor model from Phase 1 was tested using CFA to determine the goodness of fit with the study data.

Participants were students from two 5-year nursing colleges in southern Taiwan. In Phase 1, participants were 361 fourth-year nursing students from College A. In Phase 2, participants were 703 fifth-year nursing students (342 from College A and 361 from College B). Five-year nursing programs were chosen because these programs are the most popular nursing preparatory programs in Taiwan. We enrolled fourth- and fifth-year students because of their different practicum experiences. This strategy of sampling different groups and different times has been recommended to ensure study validity (Brown, 2006; Hurley et al., 1997). Students entered these colleges after graduating from high school. At the time of study instrument completion, all of the participants were 19–20 years old, and most (n = 1001, 94.1%) were female. The study was approved by the institutional review board (DMR101-IRB1-128).

Phase 1

Students from nursing College A participated in Phase 1 in December 2012. The research assistant recruited participants during a prepracticum orientation meeting for nursing students. The research assistant distributed the self-administered questionnaire. Consent to participate was implied by voluntary return of the questionnaire to the assistant. Participation was anonymous. Of the 388 fourth-year nursing students who filled out the questionnaires, 361 submitted valid returns, giving a completion rate of 93.0%.

Phase 2

Colleges A and B participated in Phase 2 in May 2013. Participants were recruited from among nursing students who were currently attending the class “Professional Issues in Nursing.” A research assistant distributed a self-administered questionnaire, and consent to participate was implied as in Phase 1. Participation was anonymous. Of the 731 fifth-year student nurses who filled out these questionnaires, 703 submitted valid returns, giving a completion rate of 96.2%.

Measurements

The original 20-item SRIS has two dimensions: self-reflection (SRIS-SR, 12 items) and insight (SRIS-IN, eight items; Grant et al., 2002). The SRIS measures self-reflection using items such as “I frequently examine my feelings” and “I frequently take time to reflect on my thoughts,” whereas insight is measured using items such as “My behavior often puzzles me” and “Thinking about my thoughts makes me more confused.” The SRIS was translated into Chinese and then back-translated. A panel of four experts that included two nurse educators, one clinical nurse, and one doctorally prepared English teacher educated in an English-speaking country was invited to resolve any discrepancies. This SRIS-C was reviewed for content validity by a panel of six experts in nursing education, liberal arts education, career counseling, and tool development. The content validity index (Grant & Davis, 1997) determined by these experts was .83. The experts recommended changes pertaining to clarity and the formatting of the questionnaire. For example, the 6-point Likert scale for item responses was changed from the two-dimensional statement format of 6 (strongly agree) to 1 (strongly disagree) to the more nuanced statement format of 6 (highly matched) to 1 (least matched). Higher scores indicated greater self-reflection and insight, that is, more inspection and evaluation of personal thoughts, feelings, and behaviors as well as clearer understanding of personal thoughts, feelings, and behaviors.

The TCTDI is a 20-item self-report Chinese-language measure of one’s critical thinking nature or disposition (Yeh, 1998). The TCTDI has four subscales: systematicness/analyticity (nine items), open-mindedness (four items), inquisitiveness (three items), and reflective thinking (four items). Sample items from these subscales include “I can understand others’ feelings and thoughts through discussion or observation” (systematicness/analyticity), “I don’t tend to make judgments without adequate evidence” (open-mindedness), “I try to apply some new perspectives or concepts” (inquisitiveness), and “To make decisions, I consider all of the influencing factors” (reflective thinking). The TCTDI has been found to be a reliable and valid measure, with a Cronbach’s alpha of .88 (Feng, Chen, Chen, & Pai, 2010). Furthermore, the correlation coefficients between the subscales were deemed significant (r = .31–.60, p < .01). In this study, responses to the TCTDI items were measured using a 6-point Likert scale, from 6 (highly matched) to 1 (least matched), with higher scores associated with a higher tendency toward critical thinking.

Perceived identity as a nurse was measured using two researcher-developed questions: “I am aware of the relationship between my traits and the nursing profession” and “I am aware of my role in the nursing profession.” Responses to these questions were measured using a 6-point Likert scale that ranged from 6 (highly matched) to 1 (least matched). The higher the score, the greater the respondent’s perceived identity as a nurse. The two questions were chosen to capture participants’ forethoughts, referring to beliefs that guide efforts to learn, that is, holding the goal of becoming a nurse and having an intrinsic interest in the nursing profession (Zimmerman, 2002).

Statistical Analysis

EFA of the data from Phase 1 was conducted using SPSS Version 18.0 (IBM, Armonk, NY, USA). CFA of the data from Phase 2 was conducted using LISREL Version 8.52 (Scientific Software International, Skokie, IL, USA). For EFA, principal component extraction and varimax rotation were used to determine the number of factors in the SRIS-C. The minimum number of extracted factors was evaluated using multiple criteria as follows: the Kaiser–Meyer–Olkin criterion, Bartlett’s test, Cattell’s scree test criterion, Kaiser’s eigenvalue > 1, and factor loading > .5. After the factor model structure was extracted using EFA, we tested the model with CFA to determine whether it fits the Phase 2 data. Model fit was evaluated using the most commonly reported fit indices: root mean square error of approximation (RMSEA), standardized root mean squared residual (SRMR), goodness-of-fit index (GFI), comparative fit index (CFI), and normed fit index (NFI). The overall internal consistencies of the total scale and its subscales were evaluated using alpha coefficients (Hu & Bentler, 1999; Tabachnick & Fidell, 2007).

Results

EFA (Phase 1)

EFA was used to determine the factor structure of the 20-item SRIS-C. The Kaiser–Meyer–Olkin value was .87, which was above .60 (Tabachnick & Fidell, 2007), and Bartlett’s test of sphericity was significant, indicating support for the factorability of the correlation matrix. Principal component analysis presented four factors (eigenvalues > 1) that explained 61.72% of the total variance, with individual factors contributing 22.77%, 19.48%, 10.73%, and 8.73%, respectively.

However, we found that some of the items (1, 2, 3, 6, 8, 13, 15, and 20) that were assigned to the third and fourth factors also loaded on the first and second factors. Therefore, we attempted to run only two factors. A second principal component analysis with varimax rotation found a two-factor structure. Of the 20 initial SRIS-C items, five (Items 3, 8, 13, 15, and 20) were eliminated because they loaded onto two factors, indicating that their factor loadings were above .30 (Hair, Black, Babin, Anderson, & Tatham, 2006). Of the 15 retained items, three loaded onto two factors and were inconsistent with the original SRIS (Grant et al., 2002). In other words, Items 1 and 2 loaded primarily on Factor 1 (self-reflection) on the original SRIS but loaded primarily on Factor 2 (insight) on the SRIS-C, and Item 6 loaded primarily on Factor 2 (insight) on the original SRIS but loaded primarily on Factor 1 (self-reflection) on the SRIS-C. Hence, the three items were subsequently deleted to assure scale validity. Finally, the rotated component matrix showed two components with strong loadings of the individual items (.69–.80; Table 1). Thus, 12 items were kept, with seven items loaded onto one component, named “self-reflection,” and the other five items loaded on another component, named “insight.” These two factors explained 58.32% of the total variance and were internally stable (Cronbach’s alpha = .79). Cronbach’s alpha coefficients for the self-reflection and insight subscales were .87 and .83, respectively. In addition, we retested participants using the original 20-item instrument at 3 weeks after the first test. On the basis of the findings in Phase 1, we used the retained 12 items to calculate the 3-week test–retest reliability of the SRIS-C, which was .74.

CFA (Phase 2)

On the basis of the initial EFA model (12 items), first-order CFA was used with the maximum likelihood solution to test whether the model was consistent with the data. Findings indicated that the two-factor baseline model fits the Phase 2 data quite well (x2/df = 3.92, GFI = .95, CFI = .97, NFI = .96, RMSEA = .065, and SRMR = .049). However, the model modification indices recommended that the fit would be better if the residuals of Items 18 and 19 were correlated (x2/df = 3.29, GFI = .96, CFI = .98, NFI = .97, RMSEA = .057, and SRMR = .064). The schematic representation (path diagram) of the model is shown in Figure 1. Convention dictates that squares signify measured variables (e.g., S18 is Item 18 in the SRIS-C) and that ovals indicate latent variables (e.g., self-reflection, insight). Single-headed arrows show the effect of one variable on another, and double-headed arrows show relationships between pairs of variables. CFA revealed a model with a correlation between the self-reflection and insight variables of .17 (95% CI [0.08, 0.26]; t = 3.891, p < .001). The confidence interval for the correlation coefficient did not include 1, indicating that the model had two dimensions.

F1
Figure 1.:
Factor structure of the Self-Reflection and Insight Scale. Note. Model fit indices: χ2 = 170.32 (df = 52, p = .000), root mean square error of approximation = .057. Item numbers correspond to those in Table 1.
T1
TABLE 1.:
Factor Loading for Results of Exploratory Factor Analysis: Two-Factor Solution (N = 361)

Convergent Validity of the SRIS-C (Phase 2)

This study found that SRIS-C scores correlated positively with TCTDI scores (critical thinking disposition) and that these scores provided an effective measure of perceived identity as a nurse. Thus, the study hypothesis was supported. Correlation coefficients for the self-reflection and insight factors with the TCTDI scores were both statistically significant at .613 (p = .000) and .096 (p = .011), respectively. These two SRIS-C factors were also significantly and positively correlated with perceived identity as a nurse (r = .543, p = .000, for self-reflection; r = .157, p = .000, for insight). These significant correlations of the TCTDI and perceived identity as a nurse with the SRIS-C indicate the good convergent validity of the SRIS-C.

Discussion

The results of this study validate the constructs of the Chinese-version SRIS (SRIS-C) for Chinese-speaking nursing students. The final SRIS-C was pared down from the original SRIS to only 12 items. Although eight items were deleted, each SRIS-C subscale (self-reflection and insight) includes items that address thoughts, feelings, and behaviors. Two subscales of the original SRIS, engagement in reflection and need for reflection, clustered into one subscale of the SRIS-C (i.e., self-reflection), implying that the original subscales could not be differentiated in the Chinese language. That is, our finding contradicts the belief that the act (engagement in reflection) and motive (need for reflection) for self-reflection are theoretically independent (Grant et al., 2002; Trapnell & Campbell, 1999). However, Roberts and Stark (2008) found that the SRIS had three factors (need for reflection, engagement in reflection, and insight), with a strong relationship (r = .77) between “engagement in reflection” and “need for reflection” although they loaded onto different factors. These disparities in the self-reflection construct require further study, either from the perspective of cultural differences (Salsali, Tajvidi, & Ghiyasvandian, 2013) or item wordings (Ben-Artzi, 2003). For example, all items on the insight subscale of the SRIS-C are reverse worded (oppositely stated). Whether this wording affects the validity of the measure also requires further study. Moreover, the relationship between self-reflection and insight (r = .113, p < .01) was weak, and the corresponding factors of the original SRIS (SRIS-SR and SRIS-IN) were not significantly correlated (r = −.03; Grant et al., 2002). These results echo a report of an ambiguous relationship between self-reflection and insight (Burnkrant & Page, 1984) and suggest that students are unlikely to gain insight only through reflection, as confirmed by Roberts and Stark.

Moreover, our final version of the SRIS-C, developed through a series of analytic procedures including expert content validity as well as verification of EFA and CFA, contains 12 items, with a positive relationship between the SRIS-SR and SRIS-IN subscales. This outcome seems to fit the generic model of self-regulation on which the original SRIS was based (Grant et al., 2002). That model proposed that self-reflection should correlate positively with level of insight. They explained this correlation as because of individuals being engaged in a related program when they complete the SRIS (Grant et al., 2002). In the current study, participants who completed the questionnaires were involved in a nursing clinical practicum. Thus, our 12-item SRIS-C fits the self-regulation model (Grant et al., 2002), supporting the deletion of eight items that were in the original SRIS.

Our hypothesis that there would be a positive correlation between perceived identity as a nurse (i.e., having the goal of becoming a nurse) and scores on the SRIS-C was supported, providing evidence for the generic model of self-regulation and goal attainment. Furthermore, this positive correlation between scores on the SRIS-C and perceived identity as a nurse indicates that students who intend to be or become a nurse have higher levels of self-reflection. This finding echoes the structure and function of self-regulatory processes (Zimmerman, 2002), indicating that beliefs (forethought phase) guide the effort to learn, whereas self-reflection (self-reflection phase) occurs after each learning effort.

Similarly, the significantly positive correlation between TCTDI and SRIS-C scores implies that both scales measure a common concept, which may reflect thinking or a “critical spirit” (Facione, 2013, p. 10). This result conforms to the idea that critical thinking and reflective thinking are inextricably linked (Kuiper & Pesut, 2004) but implies that understanding the self-reflection and insight of nurses may be a stepping stone to cultivating their critical thinking disposition. For example, if nursing students’ SRIS-C scores are low, indicating a weak disposition toward critical thinking, the course designers may respond with strategies such as an emphasis on cultivating caring behaviors, which has been shown to improve critical thinking about nursing practice (Pai, Eng, & Ko, 2013). Another situation worth mentioning is that the North American Nursing Diagnosis Association classification of nursing diagnoses, which is considered appropriate for all patients and cultures, has been used in Taiwan for decades (Lai, Chao, Yang, Liu, & Chen, 2013). Using such a one-size-fits-all system of nursing diagnoses may restrict the reflective thinking of nurses in Taiwan. The SRIS-C may thus be used to evaluate the degree to which the reflective thinking of domestic nurses is limited. On the other hand, some students may self-reflect excessively, which may create feelings of uncertainty (Roberts & Stark, 2008) and have a negative impact on learning. In these cases, the SRIS-C may be used to assess the self-reflection levels of students and to provide appropriate counseling services to improve self-reflection and thinking habits.

In contrast to the pragmatic problem-solving nature of evidence-based practice, metacognitive factors such as self-reflection and insight have been seen as an abstract issue that makes these factors difficult to monitor and teach (Krupat et al., 2011; Vacek, 2009). Self-reflection and insight are usually seen as the innate attitudes or traits of nurses that are necessarily outside the professional and educational domains. However, this does not imply that nurse educators should avoid encouraging self-reflection and insight in their students. To effectively promote these activities and facilitate self-regulation in nursing students and nurses, a more precise understanding of self-reflection and insight is needed. Using measures of self-reflection and insight such as the SRIS-C may help educators and teachers understand better why students have a limited ability to learn by reflecting on their experiences. Thus, student SRIS-C scores will help highlight a lack of metacognitive knowledge and skills.

This study has several limitations. First, the sample was recruited using a convenience method. Second, the two questions used to measure perceived identity as a nurse may not be adequately sensitive to capture the setting or possession of goals. A more powerful tool is thus necessary to capture the concept of goal setting. Third, given that reflection is a process rather than a short-lived thought, the SRIS-C should be used with caution, especially in cross-sectional studies. In other words, because reflection involves a process that occurs over time (Asselin et al., 2013), its trajectory cannot be captured using a one-time measure. To resolve this problem, we suggest that a longitudinal study design be used in future studies.

Conclusions

The SRIS-C has sound psychometric properties. To enhance the experiential learning of nurses through reflection, both nurse educators and nursing students must become more conscious of self-reflection and insight. In this regard, the validated SRIS-C provides a tool to assess the current self-reflection and insight capabilities of Chinese-speaking nursing students and to suggest ways to promote these capabilities to facilitate self-regulatory lifelong learning. However, to improve the validity and reliability of SRIS-C, we recommend that future studies include various groups of participants who have participated together in a specific activity such as a course, a competition, or a simulation program. This strategy will help ensure that the reflections of participants all relate to the same activity experience and will help confirm the relationship between the SRIS-SR and the SRIS-IN.

Acknowledgments

We would like to thank the nursing students for their participation and the National Science Council for funding this study (NSC 100-2511-S-542-001).

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Keywords:

factor structure; insight; nursing student; self-reflection; self-regulated learning

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