Skip to main content
Download PDF

Validation of the Chinese version of academic goals orientation questionnaire in nursing student: a study based on SEM and IRT multidimensional models

BMC Nursing volume 22, Article number: 465 (2023) Cite this article

Abstract

Objective

To translate the Academic Goals Orientation Questionnaire (AGOQ) into Chinese and to determine the validity and reliability of the (AGOQ) in Chinese nursing students based on SEM and IRT multidimensional models.

Methods

The participants were 654 nursing students with an age range of 17–26 years (mean age 21.61 ± 1.73 years). The psychometric properties of AGOQ were investigated based on a dual analytical perspective of structural equation modeling (SEM) and item response theory (IRT).

Results

The Cronbach’s α value of the questionnaire is 0.895. A four-factor model was obtained by exploratory factor analysis, which explained the variance of 71.892%. With confirmatory factor analysis, a new four-factors model was built and showed an acceptable goodness-of-fit, chi-square/degree of freedom (CMIN/DF) = 4.008, goodness of fit index (GFI) = 0.932, adjusted goodness of fit index (AGFI) = 0.905, comparative fit index (CFI) = 0.952, incremental fit index (IFI) = 0.952, Tucker Lewis index (TLI) = 0.941. In the analysis part of IRT, according to the comparison between Akek’s information criterion (AIC) and Bayesian information criterion (BIC), we choose the Graded Response Model (GRM) for analysis. The results show that the difficulty value is monotonically increasing, and the discrimination of all items is greater than 0.19, which shows that 16 items can be retained.

Conclusions

This study tested the psychometric characteristics of AGOQ of nursing students in China. The results confirmed that the Chinese version of AGOQ has good psychometric characteristics and can be used to measure the academic goal orientation of nursing students in China.

Peer Review reports

Introduction

The national standard for teaching quality of undergraduate majors in colleges and universities [1] required that nursing students should have the basic ability of independent learning and innovative development, and be able to adapt to the changing social health care needs. At the same time, it is necessary to mobilize teachers’ subjective initiative, improve students’ active learning, and actively carry out student-centered teaching aimed at improving students’ autonomous learning ability and innovation ability. In China, the role of learning goal orientation has also been brought into play in teaching in various fields. For example, when setting course objectives, the learning objectives of nursing specialty will be divided into three aspects: knowledge objectives, skills objectives and attitude objectives. Through the evaluation of the effect of achieving the goal, teachers can know the students’ mastery and curriculum preference in time and give professional guidance to the greatest extent.

Academic goals were defined as the content and direction of one’s motivation for academic success or failure [2, 3], which were divided into four types of goals [4]: (i)learning or task goals, (ii)ego self-enhancement goals, (iii)ego self-frustration goals, and (iv)work avoidance goals. Research on different types of academic goals has traditionally considered learning and performance [5]. Goal orientation was based on achievement motivation goal theory. The goal perspective theory of achievement motivation [4] focused on identifying different types of goal orientations among students. The view that there were two goals had received special attention. These viewpoints were called task-oriented and self-oriented [6, 7]. However, some researchers also suggested that students may be avoidance-oriented in learning situations. Factor analysis showed that task orientation, self orientation and avoidance orientation are different goal orientation factors. In 1997, Norwegian scholars [4] studied a prediction among Norwegian students in grades 6 and 8, that was, self-orientation had different dimensions (self-frustration and self-enhancement), which may be separated from other goal orientations. There was a weak correlation between self-frustration and self-enhancement, and both dimensions were independent of task orientation. And they were related to academic achievement. In addition, Nicholls et.al [7] suggested that, as mentioned above, students may be evasive in learning situations. The measurement of job avoidance showed high reliability [7], and factor analysis also showed that it can be separated from task orientation and self-reinforcement orientation. The above results were verified by students in 2012 [8] and 2020 [9], and the final academic goal orientation was determined as four dimensions, namely, ego self-frustration goal, ego self-enhancement goal, work avoidance goal and learning or task goals.

First, students with Type I goals (learning or task goals) focused on intrinsic stimuli and sought to absorb knowledge, acquired skills, and gained a true understanding of the problem [10]. In short, they wanted to learn and improve their skills, so they were also called task-focused goals. Second, students with Type II and III goals (ego self-enhancement goals, ego self-frustration goals) were social in nature and students tried to satisfy external needs through academic achievement. Ego self-enhancement referred to seeking favorable outcomes, and ego self-frustration referred to having a defensive attitude and seeking to avoid setbacks and unfavorable images [4]. Both types of academic orientation had a social component. In other words, students sought social, academic, or family approval either to be better than their peers or to conceal mediocre performance, rather than to satisfy their intellectual needs [11]. Finally, the Type IV goals (work avoidance goals) referred to students avoiding learning activity engagement by using customary avoidance behaviors, such as expending minimal effort and avoiding complex tasks [12].

Barkur et al. [13] examined the correlation between learning goal orientation and academic performance and concluded that students with lower grades tended to engage in work avoidance compared to students with higher grades. The result was similar to those obtained by Palos et al. [14] among nursing students.

However, no Chinese studies on this topic were found during the literature search, possibly due to a lack of validated tools to measure students’ orientation toward academic goals. Academic goals orientation questionnaire (AGOQ) was first developed by a Norwegian scholar [4], and was translated into Spanish in 2012 [8] and applied to nursing students for the first time. In 2020, Manrique-Abril FG et al. [9] conducted a second verification on nursing students in Colombia (the official language is Spanish). The results showed that the questionnaire has sufficient validity and reliability in the Colombian context and can be applied to nursing students. In addition, the research on the academic goals of nursing students was helpful helpful in determining their academic orientation, thus becoming an auxiliary tool for teachers to select students and adjust the course content accordingly.

Therefore, this study aims to translate the Spanish version of the academic goals orientation questionnaire (AGOQ) into Chinese and evaluate the psychometric properties of the AGOQ in Chinese nursing students based on SEM and IRT multidimensional models.

Methods

Design and sample

Cross-sectional design and multi-stage sampling design were adopted in this study. From March to June 2023, a survey was conducted among nursing students in medical schools in Jinzhou, Liaoning Province, China. The investigators of this study are mainly nursing graduate students who conducted this study. They received unified training on how to use standardized language and guidance (Supplementary material 1 is the training guidance of investigators). All participants completed the test voluntarily. Inclusion criteria: (1) Full-time nursing students in school; (2) informed permission and voluntary involvement in this study; (3) Students who understand and voluntarily join this study. Exclusion criteria: (1) Students who are dropping out of school; (2) Students who are unwilling to participate in this study [15, 16].

According to Kendall’s working principle [17], the sample size is calculated using a rough estimation method of 10–20 times the number of variables. The survey questionnaire for this study includes 4 general demographic data items, 16 items of academic goals orientation questionnaire. A total of 20 variables needs to be analyzed. Considering the possibility of loss or invalidity during the sample recycling process, the sample size should be expanded by 20%, and the final sample size should not be less than 480 people. Finally, we collected 654 valid questionnaires.

The instrument

The AGOQ has 16 items and four factors that pose questions to guide student learning. Items were divided into four dimensions based on the type of academic goal orientation, namely (i) Ego self-frustration goal (items 4, 7, 11, 14), (ii) Ego self-enhancement goal (items 2, 6, 10, 3), (iii) Work avoidance goal (items 3, 8, 12, 15), and (iv) learning or task goals (items 1, 5, 9, 16). A five-point Likert scale was used to mark the answers that best matched the subjects’ current state (1 = strongly disagree, 5 = strongly agree). The reliability of the original scale with Cronbach’s alpha (α) > 0.8 in all dimensions was adequate [4]. The total content validity index was 0.72 and had sufficient internal consistency [8].

Translation procedure

There were various phases in the translation guide [18,19,20]. First, two multilingual expert translators translated the AGOQ from Spanish to Chinese. The Chinese version was translated into English by two more multilingual expert translators. Second, a multilingual panel of four nursing professionals and two psychologists examined each item’s cultural and language equivalency. A preliminary test was given to 30 nursing students. The AGOQ was changed based on their comments. Supplementary material 2 shows the item of AGOQ.

The stage of pre-survey

We initially conducted a pre-survey and randomly selected 50 samples, and the following are the descriptive results of the pre-survey. The results of the pre-survey showed that the total score range of the scale is 16–64 (SD: 45.62 ± 11.10). The time to filled in the questionnaire is 3–6 min, with an average of 3.86 min. Supplementary material 3 shows descriptive results of the pre-survey on 50 nursing students.

Data collection

This study was completed between March and June 2023. The questionnaire included the Chinese version of AGOQ and socio-demographic information. This study adopted multi-stage sampling design. First, Jinzhou Medical University was randomly selected from 6 nursing colleges in Liaoning Province. Next, 50% of classes in each grade (ranging from one to three grade) were selected from the university [21], including the high school undergraduate and vocational college undergraduate students. As a result, 24 classes were selected by the university. In a final step, 25–30 students in each class were selected by cluster sampling. Our investigation was conducted twice, the first was a pre-survey and the second was a formal survey. We distributed questionnaires and collected them on the spot. Everyone can only fill in one questionnaire, and each questionnaire took 3.86 min. Finally, among 696 people, we collected 654 valid questionnaires. Thanks again!

Statistical analysis

SPSS 25.0, AMOS 23.0, and R 4.3.0 were employed to analyze the statistics. Cronbach’s alpha (α) [22,23,24] was used to study the internal consistency of the questionnaire and its dimensions.

Exploratory factor analysis (the main component of Varimax rotation) [25, 26] was used to study the structural validity, and its viability was confirmed by Kaiser-Meyer-Olkin test (KMO) and Bartlett test [27, 28]. With EFA, the criteria for the load value of each item is not less than 0.40 on the common factor [29], and the additive contributing rate of the extracted common factors is higher than 40% [30].

To measure model fit in CFA, eight indices were used: chi-square/degree of freedom (χ2/df), goodness of fit index (GFI), adjusted goodness of fit index (AGFI), incremental fit index (IFI), Tucker-Lewis index (TLI) [31], and comparative fit index (CFI). GFI, AGFI, IFI, TLI, and CFI should all be greater than 0.90 [32, 33], and χ2/df should be less than 5 [34].

In order to evaluate the AGOQ, IRT models were used. Graded Response Model (GRM) and Generalized Partial Credit Model (GPCM) [35] were examined for improved model fit using Akek’s information criterion (AIC) and Bayesian information criterion (BIC), whose values are lower suggesting a better model fit [36, 37]. The AIC and BIC values for GPCM in the current study were 27,259 and 27,617, whereas those for GRM were 27,145 and 27,504, respectively. The GRM was used as a result since it had a better model fit. For each item, the discrimination parameters (α) and difficulty parameters (β) were estimated. Additionally, item characteristic curves, item information curves, and total (scale) information Curves were measured [38, 39]. The larger the area covered under the curves; the item can more accurately estimate nursing students’ academic goal orientations.

Results

Descriptive statistics

Table 1 shows the descriptive results of the questionnaire. Of the participating 654 nursing students, the ages ranged from 17 to 26 years, with an average of (21.61 ± 1.73). Most of them were females (568,86.85%), sophomores (430, 65.75%), and living in urban (342, 52.29%).

Table 2 shows descriptive results of the AGOQ by sex and grade. In the questionnaire, the average score for learning or task goal is the highest (mean = 3.59, SD = 1.05), and the average score for ego self- frustration goal is the lowest (mean = 2.60, SD = 1.08).

Table 1 Frequency distribution of demographic characteristics(n = 654)
Full size table
Table 2 Descriptive results of the Academic Goals Orientation Questionnaire by sex and grade
Full size table

Reliability

Table 3 shows Cronbach’s coefficient alpha for each item. According to the results of the reliability analysis, it can be seen that the standardized reliability coefficient of the Chinese version of AGOQ is 0.859, and the questionnaire is generally reliable. Cronbach’s Alpha value of each item after deleting the item is less than 0.859 of the whole, so no adjustment is needed.

Table 3 Cronbach’s coefficient alpha(n = 654, α = 0.05)
Full size table

Validity

Construct validity

Exploratory factor analysis

Table 4 shows the rotation sums of squared loadings. The Kaiser-Meyer-Olkin (KMO) test was 0.848, and Bartlett sphericity test was significant (χ2 = 6157.990; P < 0.001) [30]. The exploratory factor analysis (EFA) analysis, revealed four dimensions through the scree plot and eigenvalue (> 1.0) [40]. Four factors supported by the scree plot (Fig. 1) accounted for 71.892% of the variance, respectively explaining 20.256%, 19.788%, 17.099% and 14. 748%.

Table 5 shows factor load and communalities of each item in AGOQ of 16 items. According to the type of academic goal orientation, the items are divided into four dimensions, and the dimensions of the Chinese version of AGOQ are the same as those of the original version, namely (i) Ego self-frustration goal (items 4, 7, 11, 14); (ii) Ego self-enhancement goal (items 2, 6, 10, 3); (iii) Work avoidance goal (items 3, 8, 12, 15); and (iv) learning or task goals (items 1, 5, 9, 16). As a result, the load value of each project on one of the common factors is higher than 0.40, and there is no double load phenomenon [41].

Table 4 Rotation Sums of Squared Loadings
Full size table
Table 5 Factor load and communalities of each item in AGOQ of 16 Items(n = 654)
Full size table
Fig. 1
figure 1

Scree plot

Full size image
Confirmatory factor analysis

The results of confirmatory factor analysis (CFA) are shown in Table 6. With CFA, in an original four-factor model with the Chinese version of the AGOQ, the fit indices were not acceptable (Table 6 and Fig. 2). Then, modification indices were taken to improve the fit indices, and a new four-factors model was built and showed an acceptable goodness-of-fit [34, 42,43,44,45], chi-square/degree of freedom(CMIN/DF) = 4.008, goodness of fit index (GFI) = 0.932, adjusted goodness of fit index (AGFI) = 0.905, comparative fit index (CFI) = 0.952, incremental fit index(IFI) = 0.952, Tucker Lewis index (TLI) = 0.941. (Table 6 and Fig. 3).

Table 6 Evaluation of fitness of SEM model
Full size table
Fig. 2
figure 2

Standardized four-factor structural model of the Chinese version of the Academic goals orientation questionnaire (n = 654); F1(Self- frustration goal, items 4, 7, 11, 14), F2(Ego self- enhancement goal, items 2, 6, 10, 13), F3(Work avoidance goal, items 3, 8, 12, 15), and F4(Learning or task goals, items 1, 5, 9, 16)

Full size image
Fig. 3
figure 3

Standardized four-factors structural model of the modified Chinese version of the Academic goals orientation questionnaire (n = 654); F1(Self- frustration goal, items 4, 7, 11, 14), F2(Ego self- enhancement goal, items 2, 6, 10, 13), F3(Work avoidance goal, items 3, 8, 12, 15), and F4(Learning goal dimension, items 1, 5, 9, 16)

Full size image

Discriminant validity

In our study, the scores of the top (50%) and low (50%) groups were analyzed using a two-tailed independent samples t-test. As can be seen in Table 7, the difference in all scores between the two groups reached the significant level (P < 0.001).

Table 7 Discriminant validity analysis in AGOQ (n = 654)
Full size table

Item response theory models

In order to evaluate the AGOQ, IRT models were used. Graded Response Model (GRM) and Generalized Partial Credit Model (GPCM) were examined for improved model fit using AIC and BIC, whose values are lower suggesting a better model fit. The AIC and BIC values for GPCM in the current study were 27,259 and 27,617, whereas those for GRM were 27,145 and 27,504, respectively. The GRM was used as a result since it had a better model fit. According to Table 8, the range of all item discrimination factors was between 0.237 and 3.689. The parameters for difficulty ranged from − 16.603 to 6.460.

Table 8 Estimates of discrimination and threshold parameters for the Scale under the graded response model with the Graded Response Model(n = 654, α = 0.05)
Full size table

The item characteristic curves and item information curves for the Chinese AGOQ are shown in Figs. 4 and 5, respectively. The curves of the Item characteristic curves showed that the order of categories’ thresholds for all the items was as expected, which meant that all categories were adequate in terms of placing a respondent on the scale. The distributions of the item information curves were multimodal. The shapes of items 1, 5, 9 and 16 were the steepest and provided more information than the other items. Figure 6 is the total scale information curve. The peak value of the curve is between − 1 and 1, which means that nursing students with ability level between − 1 and 1 get the most information through AGOQ scale evaluation. This shows that AGOQ scale has the strongest ability to distinguish the academic goal orientation of nursing students with abilities.

Fig. 4
figure 4

Item characteristic curves

Full size image
Fig. 5
figure 5

Item information curves

Full size image
Fig. 6
figure 6

Total (scale) information curve

Full size image

Discussion

The literature in nursing research links personal characteristics (such as child care or cultural differences) and other factors (such as study intensity, clinical practice, or a lack of a consulting plan) with academic burnout [46], dropping out of school, or achieving and maintaining academic goals [47, 48]. However, little research has been conducted on education, particularly on the sorts of academic aim orientation of nursing students in China.

As far as we know, this is the first study on academic goals orientation questionnaire (AGOQ) among nursing students in China based on structural equation modeling (SEM) and item response theory (IRT) model. The test results show that the Chinese version of AGOQ has good psychometric characteristics and is an effective and reliable tool. These results are consistent with the original version developed by Skaalvik [4] and the academic goals orientation questionnaire verification conducted by Navea Martin [8] in Spain.

Previously, Elliot [49] developed and verified a similar questionnaire among psychology students. March [50] used this questionnaire consisting of the same dimensions with three items per dimension among US nursing students, but the authors did not report its psychometric properties in the sample studied. Some scholars [14, 51] used other language versions of the questionnaire, and also obtained sufficient internal consistency among nursing students (α = 0.82 and α = 0.85). Although the questionnaire showed good internal consistency, it did not examine the psychometric properties. Therefore, the present study decided to use the questionnaire developed and verified by Skaalvik [4], because the Spanish version of psychometrics has been verified by scholars before [8].

In the exploratory factor analysis (EFA) model, this study extracted four factors which are the same as the original scale. The four factors explained 71.892% of the total variance, 20.256%, 19.788%, 17.099% and 14.748%, respectively. The measured values of the model fit well (chi-square/degree of freedom (CMIN/DF) = 4.008, comparative fit index (CFI) = 0.952, incremental fit index (IFI) = 0.952, Tucker Lewis index (TLI) = 0.941). The results showed that the model has strong factor load and explanatory difference. The results of confirmatory factor analysis (CFA) confirmed that the Chinese version of AGOQ had a fitting index. There was significant difference in discriminant validity between the high group and the low group (P < 0.001). In addition, each item of AGOQ has higher load value and commonality coefficient. The results also indicated that there were strong factor loadings and explained variance in the structural equation modeling, consistent with the EFA results.

Significant differences are rarely found in the analysis of the dimensions and items of the questionnaire. The score of learning and task goal dimension is the only dimension with significant gender difference. This is consistent with previous scholars’ research [51], that is, women scored significantly higher in learning or task goals. With regard to work avoidance, freshmen scored significantly higher in job avoidance dimension than other grades. Students pursuing a work avoidance objective have been defined as individuals who constantly avoid putting in effort to meet exceptional levels of achievement, doing only the bare minimum to get by, and avoiding difficult activities [12, 52]. When freshmen enter a new learning environment, they may avoid trying difficult jobs because of their low adaptability. Among college students in China, there is a very interesting phenomenon “Buddhist-Style college students” [53], who had hoped that they could relax in college and not worry too much.

In addition, through IRT analysis, AGOQ has certain discriminating ability, and all discriminating parameters are higher than 0.2, indicating that AGOQ is easy to distinguish the academic goal orientation of nursing students in China. In terms of difficulty, the difficulty is increasing monotonically, which indicates that AGOQ has acceptable difficulty. In total scale information curve, the peak value of the curve is between − 1 and 1, which means that nursing students with ability level between − 1 and 1 get the most information through AGOQ evaluation. This shows that AGOQ has the strongest ability to distinguish the academic goal orientation of nursing students with abilities around − 1 to 1.

Limitations

Some restrictions should also be considered. Firstly, a cross-sectional study was carried out in our study, so further longitudinal study is needed to confirm these results. Secondly, The sample of this study comes from a nursing school in Liaoning Province, China. The results of this study have regional limitations, so they can’t be generalized among nursing students in China. Therefore, further efforts should be made to expand the sample coverage and take into account the adaptability of different groups and hope to continue to verify the feasibility of the subscale in other areas of China in future research. Despite these limitations, the current research can be considered as groundbreaking research. Specifically, this study is the first time that China has used SEM and IRT models to measure the psychometric characteristics of AGOQ.

Conclusions

This study tested the psychometric characteristics of AGOQ of nursing students in China. The results confirmed that China version of AGOQ has good psychometric characteristics and can be used to measure the academic goal orientation of nursing students in China.

Data Availability

The datasets generated and/or analyzed during the present study are not publicly available to preserve the anonymity of the participants but are available from the corresponding author at reasonable request.

Abbreviations

AGFI:

Adjusted goodness of fit index

AGOQ:

Academic goals orientation questionnaire

AIC:

Akek’s information criterion

BIC:

Bayesian information criterion

CFA:

Confirmatory factor analysis

CFI:

Comparative fit index

CMIN/DF:

Chi-square/degree of freedom

EFA:

Exploratory factor analysis

GFI:

Goodness of fit index

GPCM:

Generalized Partial Credit Model

GRM:

Graded Response Model

IFI:

Incremental fit index

IRT:

Item response theory

KMO:

Kaiser-Meyer-Olkin

SEM:

Structural equation modeling

TLI:

Tucker Lewis index

References

  1. Jianqing L, Wenbo X, Jingjing L. Content analysis of national standards for undergraduate professional teaching quality in colleges and universities. J High Continuing Educ. 2018;31(5):7.

    Google Scholar 

  2. Sparfeldt JR, Brunnemann N, Wirthwein L, Buch SR, Schult J, Rost DH. General versus specific achievement goals: a re-examination. Learn Individual Differences. 2015;43:170–7.

    Article  Google Scholar 

  3. Lazcano LM, González-Chordá VM, Manrique-Abril FG, Cervera-Gasch Á, Mena-Tudela D, Andreu-Pejó L. Valero-Chillerón MJ. Characteristics and determinants of the academic goals in nursing education: a cross-sectional study. Nurse Educ Today. 2022;114:105402.

    Article  PubMed  Google Scholar 

  4. Skaalvik EM. Self-enhancing and self-defeating ego orientation: relations with task and avoidance orientation, achievement, self-perceptions, and anxiety. J Educ Psychol. 1997;89(1):71–81.

    Article  Google Scholar 

  5. León-Del-Barco B, Mendo-Lázaro S, Iglesias Gallego S, Polo-Del-Río MI, Iglesias Gallego D. Academic goals and parental control in primary school children. Int J Environ Res Public Health 2019;17(1).

  6. Duda JL. Goals: A social cognitive approach to the study of achievement motivation in sport. In: 1993; 1993.

  7. Nicholls JG. The competitive ethos and democratic education. Teachers College Record; 1989.

  8. A. NM: A study on the academic goals of university nursing students. Psicologia Educativa 2012;18:83–9.

  9. Manrique-Abril FG, Herrera-Amaya GM, Morales LMM, Ospina-Rojas AF, Cervera-Gasch A, Gonzalez-Chorda VM. Academic goals orientation questionnaire for Colombian nursing students: validity and reliability study. Nurse Educ Today. 2020;84:104226.

    Article  PubMed  Google Scholar 

  10. Senko C, Hama H, Belmonte K. Achievement goals, study strategies, and achievement: a test of the learning agenda framework. Learn Individual Differences. 2013;24:1–10.

    Article  Google Scholar 

  11. Zong X, Zhang L, Yao M. Parental involvement and Chinese elementary students’ achievement goals: the moderating role of parenting style. Educational Stud. 2017;44(3):341–56.

    Article  Google Scholar 

  12. Deemer ED, Carter AP, Lobrano MT. Extending the 2 × 2 achievement goal framework: development of a measure of scientific achievement goals. J Career Assess. 2010;18(4):376–92.

    Article  Google Scholar 

  13. Barkur RR, Govindan S, Kamath A. Correlation between academic achievement goal orientation and the performance of Malaysian students in an Indian medical school. Educ Health (Abingdon). 2013;26(2):98–102.

    Article  PubMed  Google Scholar 

  14. Palos R. Exploring the impact of achievement goals orientation and study engagement on nursing students’ approaches to learning. Educational Stud. 2018;46(2):1–16.

    Google Scholar 

  15. Gao Z, Zhang L, Ma J, Sun H, Hu M, Wang M, Liu H, Guo L. Reliability and validity of the Chinese version of the self-directed learning instrument in Chinese nursing students. BMC Nurs. 2023;22(1):51.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Zhang D, Yang L, Wang C, Yuan T, Wei H, Li J, Lei Y, Sun L, Li X, Hua Y et al. Reliability and validity of the Chinese version of the brief emotion and regulation beliefs scale in Chinese nursing students. BMC Nurs 2022;21(1).

  17. Wolf EJ, Harrington KM, Clark SL, Miller MW. Sample size requirements for structural equation models: an evaluation of power, bias, and solution propriety. Educ Psychol Meas. 2013;76(6):913–34.

    Article  PubMed  Google Scholar 

  18. Beaton DE, Bombardier C, Guillemin F. Guidelines for the process of cross-cultural adaptation of self-report measures. Spine. 2000;25(24):3186–91.

    Article  CAS  PubMed  Google Scholar 

  19. Tsang S, Royse CF, Terkawi AS. Guidelines for developing, translating, and validating a questionnaire in perioperative and pain medicine. Saudi J Anaesth. 2017;11(Suppl 1):80–S89.

    Article  Google Scholar 

  20. Khalaila R. Translation of questionnaires into Arabic in cross-cultural research: techniques and equivalence issues. J Transcult Nurs. 2013;24(4):363–70.

    Article  PubMed  Google Scholar 

  21. DM F. Application of different statistical sampling methods in prescription evaluation. China Pharm. 2011;22(13):1240–1.

    Google Scholar 

  22. Taber KS. The use of Cronbach’s alpha when developing and reporting research instruments in science education. Res Sci Educ 2017(1):1–24.

  23. Boateng GO, Neilands TB, Frongillo EA, Melgar-Quiñonez HR, Young SL. Best practices for developing and validating scales for health, social, and behavioral research: a primer. Front Public Health 2018;6.

  24. Tavakol M, Dennick R. Making sense of Cronbach’s alpha. Int J Med Educ. 2011;2:53–5.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Barnes H, Faraz Covelli A, Rubright JD. Development of the novice nurse practitioner role transition scale: an exploratory factor analysis. J Am Association Nurse Practitioners. 2022;34(1):79–88.

    Article  Google Scholar 

  26. Streiner DL, Norman GR. HEALTH MEASUREMENT SCALES: A practical guide to their development and use. Journal of Epidemiology Community Health 2015;47(5):484.e481-484.e481.

  27. Park D-I. Development and validation of a knowledge, attitudes and practices questionnaire on COVID-19 (KAP COVID-19). Int J Environ Res Public Health 2021;18(14).

  28. Erci B, Yildirim H, Isik K. Psychometric evaluation of the patient perspective on care and rehabilitation scale in geriatric patients. Arch Gerontol Geriatr. 2019;81:84–90.

    Article  PubMed  Google Scholar 

  29. Huang F-F, Yang Q, Han XY, Zhang J-P, Lin T. Development and validation of a self-efficacy scale for postoperative rehabilitation management of Lung cancer patients. Psycho-oncology. 2017;26(8):1172–80.

    Article  PubMed  Google Scholar 

  30. kun L. The application of SPSS in medical scientifc research. Beijing, China: People’s Medical Publishing House; 2012.

    Google Scholar 

  31. LedyardRTucker CL. A reliability coefficient for maximum likelihood factor analysis. Psychometrika 1973(38–1).

  32. McDonald RP, Ho M-HR. Principles and practice in reporting structural equation analyses. Psychol Methods. 2002;7(1):64–82.

    Article  PubMed  Google Scholar 

  33. Anderson J, Gerbing D. The effect of sampling error on convergence, improper solutions, and goodness-of-fit indices for maximum likelihood confirmatory factor analysis. Psychometrika. 1984;49(2):155–73.

    Article  Google Scholar 

  34. Steiger JH. Structural model evaluation and modification: an interval estimation approach. Multivar Behav Res. 1990;25(2):173–80.

    Article  CAS  Google Scholar 

  35. Buck HG, Harkness K, Ali MU, Carroll SL, Kryworuchko J, McGillion M. The caregiver contribution to heart failure self-care (CACHS): further psychometric testing of a novel instrument. Res Nurs Health. 2017;40(2):165–76.

    Article  PubMed  Google Scholar 

  36. Huang P-H. Asymptotics of AIC, BIC, and RMSEA for model selection in structural equation modeling. Psychometrika. 2017;82(2):407–26.

    Article  PubMed  Google Scholar 

  37. Akaike HT. A new look at the statistical model identification. Automatic Control IEEE Transactions on. 1974;19(6):716–23.

    Article  Google Scholar 

  38. Jean-Pierre P, Shao C, Cheng Y, Wells KJ, Paskett E, Fiscella K. Patient satisfaction with navigator interpersonal relationship (PSN-I): item-level psychometrics using IRT analysis. Support Care Cancer. 2019;28(2):541–50.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Zhong S, Zhou Y, Zhumajiang W, Feng L, Gu J, Lin X, Hao Y. A psychometric evaluation of Chinese chronic hepatitis B virus infection-related stigma scale using classical test theory and item response theory. Front Psychol 2023;14.

  40. Huang F, Ye Han X, Chen S-L, Guo YF, Wang A, Zhang Q. Psychometric testing of the Chinese simple version of the simulation learning effectiveness inventory: classical theory test and item response theory. Front Psychol 2020;11.

  41. Y L: Department IJCMR: the application of SPSS in data process of medical scientifc research. Chin Med Rec 2011.

  42. Veilleux JC, Salomaa AC, Shaver JA, Zielinski MJ, Pollert GA. Multidimensional assessment of beliefs about emotion: development and validation of the emotion and regulation beliefs scale. Assessment. 2015;22(1):86–100.

    Article  PubMed  Google Scholar 

  43. Bollen KA. A new incremental fit index for general structural equation models. Sociol Methods Res. 2014;17(3):303–16.

    Article  Google Scholar 

  44. Li CH. Confirmatory factor analysis with ordinal data: comparing robust maximum likelihood and diagonally weighted least squares. Behav Res Methods. 2016;48(3):936–49.

    Article  PubMed  Google Scholar 

  45. Bentler PM. Comparative fit indices in structural models. Psychol Bull. 1990;28(2):97–104.

    Google Scholar 

  46. Valero-Chilleron MJ, Gonzalez-Chorda VM, Lopez-Pena N, Cervera-Gasch A, Suarez-Alcazar MP, Mena-Tudela D. Burnout syndrome in nursing students: an observational study. Nurse Educ Today. 2019;76:38–43.

    Article  PubMed  Google Scholar 

  47. Mooring QE. Recruitment, advising, and retention programs - challenges and solutions to the international problem of poor nursing student retention: a narrative literature review. Nurse Educ Today. 2016;40:204–8.

    Article  PubMed  Google Scholar 

  48. Chan ZCY, Chan HY, Chow HCJ, Choy SN, Ng KY, Wong KY, Yu PK. Academic advising in undergraduate education: a systematic review. Nurse Educ Today. 2019;75:58–74.

    Article  PubMed  Google Scholar 

  49. Elliot AJ, Mcgregor HA. A 2*2 achievement goal framework. J Personal Soc Psychol. 2001;80(3):501–19.

    Article  CAS  Google Scholar 

  50. March AL, Robinson C. Assessment of high-stakes testing, hopeful thinking, and goal orientation among baccalaureate nursing students. Int J Nurs Educ Scholarsh. 2015;12:123–9.

    Article  PubMed  Google Scholar 

  51. Filiz N, Erol F, Başaran H, Tanrikulu F, Dikmen Y. Investigation of achievement orientation of nursing and midwifery students. Curr Health Sci J. 2018;44(2):176–80.

    CAS  PubMed  PubMed Central  Google Scholar 

  52. Seifert TL, O’Keefe BA. The relationship of work avoidance and learning goals to perceived competence, externality and meaning. Br J Educ Psychol. 2001;71(Pt 1):81–92.

    Article  CAS  PubMed  Google Scholar 

  53. Xu J. Analysis of the phenomenon of buddhist-style youth from the perspective of social acceleration theory. Adv Philos. 2020;9(4):6.

    Google Scholar 

Download references

Acknowledgements

We express our great gratitude to all the respondents and all the authors of the scales that have been used in this study.

Funding

This work was supported by the Internal Medicine Nursing Teaching Team (202ljxtd02).

Author information

Authors and Affiliations

  1. Department of Graduate School, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, P.R. China

    Yuqing Li, Jiaofeng Gui, Xiaoyun Zhang & Ying Wang

  2. Department of Surgical Nursing, School of Nursing, Jinzhou Medical University, No.40, Section 3, Songpo Road, Linghe District, Jinzhou City, Liaoning Province, P.R. China

    Lei-lei Guo

  3. Student health center, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, P.R. China

    Haiyang Liu

  4. Department of Occupational and Environmental Health, Key Laboratory of Occupational Health and Safety for Coal Industry in Hebei Province, School of Public Health, North China University of Science and Technology, Tangshan, Hebei Province, P.R. China

    Jinlong Li

  5. Obstetrics and Gynecology Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, P.R. China

    Yunxiao Lei, Ting Yuan & Huanhuan Wei

  6. Department of Emergency and Critical Care Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, P.R. China

    Xiaoping Li & Lu Sun

  7. Department of Internal Medicine Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, P.R. China

    Liu Yang, Congzhi Wang & Lin Zhang

  8. Department of Pediatric Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, P.R. China

    Dongmei Zhang

  9. Department of Surgical Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, P.R. China

    Jing Li & Mingming Liu

  10. Rehabilitation Nursing, School of Nursing, Wannan Medical college, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, P.R. China

    Ying Hua

Authors
  1. Yuqing Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lei-lei Guo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jiaofeng Gui
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xiaoyun Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ying Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Haiyang Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Jinlong Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Yunxiao Lei
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Xiaoping Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Lu Sun
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Liu Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Ting Yuan
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Congzhi Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Dongmei Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Huanhuan Wei
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Jing Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Mingming Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Ying Hua
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Lin Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceived and designed the research: LZ. Wrote the paper: Y-q L. Analyzed the data: Y-q L and LZ. Revised the paper: Y-q L, L-l G, J-f G, X-y Z, XY, LZ, H-y L, J-l L, Y-x L, X-p L, LS, LY, TY, C-z W, D-m Z, H-h W, JL, M-m L, and YH. The authors read and approved the final manuscript.

Corresponding author

Correspondence to Lin Zhang.

Ethics declarations

Ethics approval and consent to participate

This study was approved by the Ethical Review Committee of Jinzhou Medical University under the approval number JZMULL2023028. The study was initiated after informed consent was obtained from all participants. Throughout the study, we strictly adhered to the principles outlined in the Declaration of Helsinki to ensure the anonymity and confidentiality of participants’ information and data.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1:

The training guidance of investigators

Supplementary Material 2:

The Academic Goals Orientation Questionnaire

Supplementary Material 3:

Descriptive results of the pre-survey on 50 nursing student (N=50)

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, Y., Guo, Ll., Gui, J. et al. Validation of the Chinese version of academic goals orientation questionnaire in nursing student: a study based on SEM and IRT multidimensional models. BMC Nurs 22, 465 (2023). https://doi.org/10.1186/s12912-023-01630-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12912-023-01630-0

Keywords

BMC Nursing

ISSN: 1472-6955

Contact us