Next Article in Journal
Assessment of International Trade-Related Transport CO2 Emissions—A Logistics Responsibility Perspective
Next Article in Special Issue
Factor Analysis of Subjective Well-Being Sustainability through Foreign Language Learning in Healthy Older Individuals
Previous Article in Journal
CSR Reporting of Stakeholders’ Health: Proposal for a New Perspective
Previous Article in Special Issue
Energy Expenditure and Physical Activity in a University Population in the Coastal Region of Ecuador
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Sustainability
Volume 13
Issue 3
10.3390/su13031134
sustainability-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Healthy Students: Adaptation and Validation of the Instrument from the Workplace to the Educational Field

by
Ramón Gómez-Chacón
1,*,
Nicolás Fernández-Martínez
1 and
Pablo Gálvez-Ruiz
2
1
Departmental Area of Physical Activity and Sport, Centro de Estudios Universitarios Cardenal Spínola CEU, 41004 Sevilla, Spain
2
Faculty of Law and Social Sciences, Valencian Internacional University, 46002 Valencia, Spain
*
Author to whom correspondence should be addressed.
Sustainability 2021, 13(3), 1134; https://doi.org/10.3390/su13031134
Submission received: 1 December 2020 / Revised: 18 January 2021 / Accepted: 19 January 2021 / Published: 22 January 2021
(This article belongs to the Special Issue Education, Psychosocial Factors and Health in Different Educational Contexts)
Versions Notes

Abstract

:
Psychological capital (optimism, resilience, hope and self-efficacy) has been joined by a new dimension in the workplace. This is engagement, a new construct, and a research questionnaire called the healthy employee was created to assess this dimension. In this sense, the present work has the aim of adapting and validating this questionnaire of the healthy employee in the educational field, calling this person a healthy student. In total, 290 students (140 women and 150 men) undertaking different university degrees were recruited for this research. A confirmatory factor analysis was carried out to test the structure of two different models in the workplace, with five and eight dimensions, and to adapt and verify the reliability of the models in the educational setting. The results showed a poor fit for both models, suggesting the elimination of four items in the five-dimensional model and of three items in the eight-dimensional model. In addition, the five-dimensional model indicated discriminant validity, while the eight-dimensional model presented non-compliance between two dimensions. Therefore, this work generates an instrument with adequate psychometric properties in the five-dimensional model in the educational field.

1. Introduction

The Spanish University system (SUE) was made up in the 2018–2019 academic year of a total of 83 universities in operation, distributed across 235 campuses (face-to-face universities) and 113 venues (non-face-to-face and special universities). Of the total number of universities, the SUE has 50 public and 33 private universities. Of these, there are 1055 university centers between schools and faculties, to which are added 525 university research institutes, 50 doctoral schools, 54 university hospitals and 77 foundations. In addition, in the 2019–2020 academic year, 2920 undergraduate degrees were taught, 2159 in public universities, continuing their upward evolution from the 2012–2013 academic year. In the Andalusian context, there are 11 universities spread over 38 campuses and venues, offering a total of 386 undergraduate degrees [1]. These figures reveal the existence of a university system with a high volume of students, indicative of the importance of having instruments for diagnosing their psychological well-being.

2. Theoretical Framework

2.1. Psychological Capital

Psychological capital (PsyCap) is a multidimensional, personal and positive psychological resource [2,3] that is defined as a positive psychological state of individual development characterized by (1) having confidence; (2) having a positive outlook (optimism) about success now and in the future; (3) persevering toward goals and, when necessary, redirecting paths to goals (hope) to be successful; and, (4) when embraced by problems and adversities, sustaining and rebounding and even beyond (resilience) to achieve success [2]. These four dimensions of PsyCap can, according to Luthans et al. [2] (p. 2), interact synergistically and create differentiated manifestations in time and across contexts.
In the educational context, there are studies that indicate that PsyCap has an important role in the educational field [4,5] by relating it to academic performance [4,6,7,8,9], intrinsic motivation [5], the empowerment of learning [6], engagement [4,5,10,11] and even with the well-being of students [10,12]. In addition, various studies relate the dimensions of PsyCap individually, a line of work in which a positive relationship has been established between self-efficacy and academic performance [13] as well as between hope and optimism concerning academic performance [14,15,16,17,18]. On the other hand, it has been found that positive emotions influence student learning [19]; a recent work showed that students who experience positive emotions in their academic studies are associated with high levels of PsyCap [8].
At the same time, in the workplace, PsyCap is composed of the same four dimensions mentioned above [20,21] and predicts performance and satisfaction better than the four dimensions separately [22], being positively related to leadership, trust, creativity and performance [22,23,24].
The PsyCap measurement is based on the questionnaire developed by Luthans et al. [22], composed of four dimensions of six items that showed adequate internal consistency, and which has been adapted to the Spanish context in the workplace [25]. This scale has a reduced version called Psychological Capital Questionnaire (PCQ)-12 [26], with three items to measure self-efficacy, four for hope, three for resilience and two for optimism, and that has been adapted to workers [27] and also to the educational context [28], obtaining adequate psychometric properties in a sample of Spanish and Portuguese students [29].

2.2. Engagement

Engagement is defined as a positive affective state, relatively persistent, of fullness that is characterized by vigor, dedication and absorption or concentration at work [30] (p. 74). According to Hallberg and Shaufeli [31], it is a positive state of well-being or satisfaction which gives people high levels of energy, enthusiasm and a strong identification with their tasks [32,33]. In the educational context, focusing on students, those who have engagement feel energetic, strongly identify with their studies and are deeply involved in their academic life [29]. For this reason, engagement in student groups is related to higher group performance [34] as well as higher academic performance [29]. Furthermore, it predicts longitudinal changes in motivation, satisfaction and self-efficacy [35], and according to Salanova et al. [36], self-efficacy and engagement influence each other through the experience of positive emotions. However, the contextualization of engagement in the work context requires naming the model of demands and labor resources (DRL) of Bakker and Demerouti [37], which arises within the psychology of occupational health and introduces two types of psychosocial well-being: burnout (or being burned out by work) and engagement, defined, at work, as a positive, satisfactory and work-related mental state, characterized by vigor, dedication and absorption, and referring to an affective–cognitive state [30] (p. 74). In this sense, engagement is related to employees being more satisfied with their jobs and more committed to them [37], employees with more proactive behaviors and creative ideas [38,39] and higher performance [37,39].
The instrument most used in the literature in the evaluation of work engagement is the Utrecht Work Engagement Scale (UWES-17) [30], whose dimensions are vigor (six items), dedication (five items) and absorption (six items). This three-dimensional structure has shown a better fit than the one-dimensional model in studies with samples from the Netherlands, Spain and Portugal [40,41,42]. The UWES-17 also has a version adapted to the educational context, maintaining the number of items (UWES-S) [43], which has been used in different contexts such as Ecuador, where the three-dimensional structure was maintained [44], and, recently, in the Spanish context, obtaining a re-specified two-dimensional model [45].

2.3. Healthy Employee and Healthy Student

At first, the healthy employee was defined as psychological capital (PsyCap) with the characteristics of self-efficacy, hope, optimism and resilience [20,21]; it was later called the healthy employee, and the engagement dimension was added [46,47], thus resulting in the two constructs that are currently validated. In fact, healthy employees are one of the three components that a healthy and resilient organization should have [47,48]. The healthy employee questionnaire [48] was validated along the same lines. This assesses eight different variables: engagement vigor, engagement dedication and engagement absorption, self-efficacy, resilience, optimism, mental competence and emotional competence. A recent study [49] adapted and validated the questionnaire, reducing it from eight to five dimensions using Salanova’s theoretical concept of the healthy employee construct [47]. Both models, the eight-dimensional [48] and the five-dimensional [49], have a structure with adequate psychometric properties in the context of the healthy employee in the workplace. Therefore, following this line of work, the present study has the objective of adapting the questionnaire of the healthy employee in the workplace to the educational context, analyzing the structures of the eight and five dimensions to obtain evidence of reliability and validity that allows its applicability in this context.

3. Materials and Methods

3.1. Sample Profile

The participants were 290 students (140 women and 150 men). The mean of age of the study’s participants was 21.70 years (SD (Standard Deviation) = 3.73), with a range from 19 to 45, with a majority age of 20 (n = 73; 25.2%), and similar percentages with ages of 21 (n = 47; 16.2%), 19 (n = 45; 15.5%) and 22 (n = 39; 13.4%), while people aged over 23 formed a minority in the sample. Regarding the means of transport, a vast majority travel by car (n = 202; 69.7%) while a quarter do so by bus (n = 73; 25.1%), with a minority using a motorcycle and other means (bicycle, electric scooter, etc.). With regard to the academic degree in progress, two thirds are degree students (n = 195; 67.2%) and 25.2% (n = 73) of the participants study under the sports education cycle. Among undergraduate students, 31.4% study Sports Sciences degrees, 25.9% belong to Primary degrees, and 13.8% to Childhood degrees, while the majority study under the higher sports education cycle (n = 68) (Table 1).

3.2. Measures

For the present study, we started from the Health and Resilient Organization (HERO) [48] questionnaire, a heuristic and theoretical model that has empirical evidence from studies on work stress, human resources management and organizational behavior as well as from the psychology of occupational health [50,51]. Specifically, the healthy employees questionnaire was used, which is one of the three axes of the HERO model, adapting it to the educational context. For example, item ENG1 in the work context is “during work, we feel full of energy”, and its version in the educational context is “during the academic day, we feel full of energy”. The questionnaire used is made up of forty items, where six correspond to the optimism scale measured in the healthy employee questionnaire for the concept of positive emotions (EMO_1–EMO_6); eighteen items to the engagement scale (ENG_7–ENG_24) that is structured in three dimensions, namely engagement vigor (seven items; ENG-V_7–ENG-V_13), engagement dedication (four items; ENG-D_14–ENG-D_17) and engagement absorption (seven items; ENG-A_18–ENG-A_24); seven items correspond to the resilience scale (RES_25–RES_31); three items to the self-efficacy scale (S-E_32–S-E_34) and six items to the scale of hope measured in the healthy employee questionnaire through competence (COMP_35–COMP_40), which is subdivided into two dimensions of three items each, namely mental competence (M-COMP_35–M-COMP_37) and emotional competence (E-COMP_38–E-COMP_40) (Appendix A). All the items were evaluated with a 7-point Likert scale ranging from (0) “never” to (6) “always”.

3.3. Procedure

A group of experts made up of three teachers, three students and the researchers of the present study was created, with the aim of adapting the items of the healthy employee questionnaire to the educational context. The modifications carried out were only made to guide the content of the items. All the data were collected online, asking the participants to respond anonymously and honestly and guaranteeing confidentiality in the data treatment, and all the participants gave their consent (this was the first response to the online questionnaire), without the need for an external ethics committee as the study did not violate the principles established in the Declaration of Helsinki. The questionnaire took 10–12 min to complete, and data for this study were collected during February 2020.

3.4. Data Analysis

First, the frequency and descriptive statistics analysis consisted of mean, standard deviation, skewness and kurtosis and was conducted to identify the general sample’s characteristics and the study’s main variables. An assessment of the psychometric properties was conducted through several statistical processes, analyzing two different models. To do this, a confirmatory factor analysis (CFA) was carried out to test the structure of the five-dimensional model (Model 1), where engagement and competition are unifactorial, and the eight-dimensional model (Model 2), which includes the three engagement factors (vigor, dedication and absorption) and the two factors of competence (mental and emotional). We assessed the measurement model with the SPSS Amos 21.0 package, using a maximum likelihood estimation and evaluating the adjustment by following the fit indices χ2/df, the comparative fit index (CFI), the incremental fit index (IFI), the Tucker–Lewis index (TLI), the parsimony comparative of fit index (PCFI) and the root mean square of approximation (RMSEA). We considered the fit indicators to be adequate when the χ2/df was below 3 [52], the CFI, IFI and TLI were equal to or above 0.90, the values were above 0.60 for the PCFI [53,54] and the RMSEA was below 0.08 [55,56]. The same statistical criteria were used for the two models, following the three-step procedure to evaluate the measurement model established by Götz et al. [57]: individual items’ reliabilities, convergent validity and discriminant validity. Additionally, modification indices (MIs) were used to locate any problematic item that contributed to a misfit of the data [58]. For item reliabilities, these were maintained with a factor loading (λ) greater than the conservative threshold of 0.50 [53]; for convergent and discriminant validity we checked Cronbach’s alpha (α; values higher than 0.70) [59], composite reliability (CR; values higher than 0.70) [56] and average variance extracted (AVE; values higher than 0.50) [60].

4. Results

4.1. Descriptive Statistics

The values for univariate skewness and kurtosis were satisfactory for all the variables within the conventional criteria for normality; the skewness value ranged from −1.5 to +1.5 and the kurtosis values were between −3 and +3, confirming the normality of the sample data [61,62] (Table 2).

4.2. Confirmatory Factor Analysis

The results of the initial analysis of the factor structures proposed for Models 1 and 2 showed a poor adjustment (Table 3), presenting goodness-of-fit indices below the established threshold, thus supporting the need to refine the models using the same statistical procedure for both cases through the analysis of factorial weights and modification indices.
The analysis of the factor weight suggested the elimination of four items from Model 1 (EMOT_1: 0.49; ENG_4: 0.47; ENG_12: 0.46; ENG_17: 0.46) and three items from Model 2 (EMOT_1: 0.49; ENG-V_12: 0.47; ENG-D_17: 0.46). The remaining factor loadings were statistically significant and exceeded the established criteria of 0.50. Through the analysis of the modification indices, the covariances between diverse pairs of errors were identified, being very similar between the two models, as happened with the factorial loads. Thus, for Model 1, covariances were introduced between the errors of four pairs of items, specifically ENG 2–3 (MI: 39.48), ENG 9–10 (MI: 37.41), ENG 13–14 (MI: 43.07) and RES 5–6 (MI: 22.60). As for Model 2, the covariances were included between the errors of two pairs of items, specifically ENG-V 2–3 (MI: 19.99) and RES 5–6 (MI: 22.57). Following the revision of the two models, all the fit indices of Models 1 and 2 were situated within the recommended values, offering an adequate fit (Table 4).
The next step was the reliability and validity tests. First, Cronbach’s alpha statistic was used to assess internal consistency, and the associated alpha values were higher than 0.70 in all the dimensions of Models 1 (ranging between 0.82 and 0.93) and 2 (ranging between 0.77 and 0.89). Additionally, the CR values of each dimension of Models 1 and 2 were higher than the threshold of 0.70. The AVE for all the dimensions ranged from 0.52 to 0.65 in Model 1 and from 0.50 to 0.65 in Model 2, thus exceeding the generally accepted value of 0.50 (Table 5).
Lastly, to test the discriminant validity, we examined the AVE and compared the square root of the AVE with the correlations between the constructs, according to the criterion of Fornell and Larcker [56]. In Model 1, the square correlation values ranged from 0.403 to 0.627, indicating discriminant validity in all the dimensions. However, Model 2 showed a breach of discriminant validity between the factors of the engagement and competence dimensions, where the square correlations between each construct were higher than the AVE values (Table 6).

5. Discussion

The creation of organizations or work environments that promote the welfare of workers is a major challenge for organizations and an area of academic study [63]. Therefore, studies concerning health improvement programs in organizations have been increasing in recent years, with approaches from different perspectives as shown by different studies [64,65,66,67], even going so far as to relate improved health and lower costs [68]. In short, this growing interest gives rise to a greater awareness of the benefits of implementation of health programs that consider different variables; even models of healthy organization development have emerged in the last decade [68,69].
In the field of the educational community, several studies have been carried out with an orientation toward healthy lifestyle habits based on the importance of this stage of life in order to consolidate these habits and their reflection in adult life [70,71]. However, there is a gap in the academic literature regarding the psychosocial evaluation of students, especially through instruments that provide adequate psychometric properties (reliability and validity). It is, therefore, an area that requires further research, analysis and development. In this sense, using a sample of students from different academic degrees, the present work starts from the HERO instrument [48] to make an adaptation to the educational context and check if the measurement model intended for the evaluation of healthy students meets the pertinent psychometric requirements to be considered a reliable and valid instrument.
The analyses performed on the original structure of the instrument showed a poor fit for both the five-dimensional and eight-dimensional models. The refinement needs of the instrument suggested eliminating various items, specifically four items of the five-dimensional model and three of the eight-dimensional model, with the elimination of the same item from the emotions scale and two items of the engagement scale coinciding for the two models, resulting in instruments of 36 items for the five-dimensional model and 37 items for the eight-dimensional model. There were, therefore, less items compared to the original scale and studies carried out in the labor field [48,49].
The use of complementary measures in the confirmatory factor analysis made it possible to verify a discriminant validity problem in the eight-dimensional model, despite the fact that both the composite reliability and the average variance extracted were adequate in the two models. These results showed the five-dimensional model as being the most appropriate for the evaluation of healthy students, indicating a factorial structure with fewer items and better psychometric properties compared to that obtained in the workplace by Gómez-Chacón et al. [49]. Here, the five-dimensional model did not show an adequate mean variance extracted in the engagement and resilience dimensions, in addition to presenting problems in the discriminant validity of its dimensions.
Hence, the contributions of this research are the basis for the development of future research in the educational context. In this sense, having simple and quickly applicable instruments will enable continuous evaluation and will facilitate the development of appropriate action plans as well as educational policies aimed at achieving healthy students.

5.1. Managerial and Practical Implications

We consider that this work has different implications. First of all, the academic literature has been provided with an optimized instrument with 36 items, which has a simple application and adequate psychometric properties in terms of reliability and validity. Moreover, the tool has the advantage of having a small number of items and can be responded to in a short, estimated time of about 10 min and can therefore be easily applied. Thus, on the one hand, this study provides a clear implication for the management of students, specifically concerning the evaluation of their psychosocial health. The evaluation and detection of students with inappropriate psychosocial well-being will enable establishing intervention programs and even the elaboration of orientation plans focused on the different dimensions evaluated by the tool. On the other hand, educational centers, from schools to universities, will be offered an instrument which will allow them to carry out an evaluation of the dimensions of the healthy student, thus facilitating the learning process as well as the students’ academic performance. These facts indicate that a theoretical construct called healthy student is obtained, which is composed of the four dimensions of the PsyCap and engagement. This construct can be used in current research since it has been updated to include engagement.

5.2. Limitations and Future Investigations

Despite the fact that participants undertaking different university degrees were included, more studies are necessary to obtain a larger sample that makes it possible to carry out more statistical tests, such as a factorial invariance analysis. Furthermore, the participants in this study did not cover all educational levels, which is another important limitation. However, both limitations offer new possibilities for conducting future research that allows for a more in-depth understanding of the psychometric behavior of the instrument and covers a broader educational spectrum. On the other hand, future lines of research should be oriented toward the achievement of an integral healthy student construct, related to the concept given by the World Health Organization, including the second of the two components of the current healthy student; that is, the physical component. In addition, the research should be focused on knowing whether the practice of physical activity influences the healthy student, as well as relating the strengths of the healthy student with less studied functions such as executive skills.

6. Conclusions

The present work uses an instrument validated in a different study context, obtaining adequate psychometric properties and offering a five-dimensional model that is perfectly adapted to the theoretical concept. In this sense, having this instrument permits quickly and simply detecting the psychosocial well-being of the students, with this being of great importance for the possible application of specific intervention programs with enough flexibility to adapt to the needs detected in the students.

Author Contributions

Conceptualization, R.G.-C. and N.F.-M.; methodology, P.G.-R.; software, P.G.-R.; validation, R.G.-C. and P.G.-R.; formal analysis, P.G.-R.; investigation, P.G.-R.; R.G.-C. and N.F.-M.; data curation, P.G.-R; writing—original draft preparation, R.G.-C.; writing—review and editing, R.G.-C., N.F.-M. and P.G.-R. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Table
Table A1. Survey items.
Table A1. Survey items.
Healthy Student Questionnaire
Positive emotions
EMO_1During the last year, we have shown ourselves to be: tense/overwhelmed–relaxed/calm
EMO_2Over the past year, we have been: discouraged–excited
EMO_3During this last year, we have shown ourselves to be: upset–at ease
EMO_4During this last year, we have shown ourselves to be: pessimistic–optimistic
EMO_5During this last year, we have shown ourselves to be: vulnerable–resistant
EMO_6During this last year, we have shown ourselves: to be satisfied–dissatisfied
Engagement
ENG_7During the academic day we feel full of energy (ENG-V_7)
ENG_8We can continue active for long periods of time (ENG-V_8)
ENG_9We remain active even when things are not going well (ENG-V_9)
ENG_10Studying hard is not too much effort for us (ENG-V_10)
ENG_11We feel very persistent during the academic day (ENG-V_11)
ENG_12We feel strong and vigorous during the academic day (ENG-V_12)
ENG_13When the academic day is over, we have enough energy to get involved in other activities (ENG-V_13)
ENG_14We are involved in academic work (ENG-D_14)
ENG_15We are excited about our academic training (ENG-D_15)
ENG_16We enjoy doing academic work (ENG-D_16)
ENG_17We are motivated to do good academic work (ENG-D_17)
ENG_18When we study, we forget everything that happens around us (ENG-A_18)
ENG_19We take new initiatives (ENG-A_19)
ENG_20We are immersed in our academic work (ENG-A_20)
ENG_21Time “flies by” during the academic day (ENG-A_21)
ENG_22We are happy during the academic day (ENG-A_22)
ENG_23It is difficult to disconnect from the academic day (ENG-A_23)
ENG_24We “get carried away” by academic training (ENG-A_24)
Resilience
RES_25We try to find the positive side of difficult situations
RES_26We adapt positively to the changes that emerge, and we also become “stronger” when we overcome them
RES_27We make sure we have resources (e.g., information, emotional support, practical help, and financial resources) to overcome crises and difficult times
RES_28We support each other in difficult situations
RES_29We believe that the educational center has sufficient financial solvency to overcome difficult moments
RES_30We are not afraid of uncertainty; we know how to face it well and even be strengthened by it.
RES_31We can function well even if some of the members of the academic work group are missing
Self-efficacy
S-E_32Although unexpected situations appear
S-E_33Although we come across many obstacles
S-E_34Although we spend a lot of time and energy
Competence
COMP_35We pay close attention to and concentrate on our academic work (M-COMP_35)
COMP_36We are aware and remember many things at the same time (M-COMP_36)
COMP_37We work with a lot of written and verbal information (M-COMP_37)
COMP_38We objectively and directly face problems with the people with whom we do educational work (E-COMP_38)
COMP_39We deal with difficult or special people (E-COMP_39)
COMP_40We persuade or convince others (E-COMP_40)

References

  1. Gobierno de España. Datos y Cifras del Sistema Universitario Español. Publicación 2019–2020. Available online: https://www.ciencia.gob.es/stfls/MICINN/Universidades/Ficheros/Estadisticas/Informe_Datos_Cifras_Sistema_Universitario_Espanol_2019-2020.pdf (accessed on 11 January 2021).
  2. Luthans, F.; Youssef-Morgan, C.M.; Avolio, B.J. Psychological Capital and Beyond; Oxford University Press: Oxford, UK, 2015. [Google Scholar]
  3. Luthans, F.; Youssef-Morgan, C.M. Psychological Capital: An evidence-based positive approach. Rev. Organ. Psychol. Organ. Behav. 2017, 4, 339–366. [Google Scholar] [CrossRef] [Green Version]
  4. Datu, J.A.D.; King, R.B.; Valdez, J.P.M. Psychological capital bolsters motivation, engagement, and achievement: Cross-sectional and longitudinal studies. J. Posit. Psychol. 2018, 13, 260–270. [Google Scholar] [CrossRef]
  5. Siu, O.L.; Bakker, A.B.; Jiang, X. Psychological capital among university students: Relationships with study engagement and intrinsic motivation. J. Happ. Stud. 2014, 15, 979–994. [Google Scholar] [CrossRef]
  6. Liao, R.; Liu, Y. The impact of structural empowerment and psychological capital on competence among Chinese baccalaureate nursing students: A questionnaire survey. Nurs. Educ. Today 2016, 36, 31–36. [Google Scholar] [CrossRef]
  7. Vanno, V.; Kaemkate, W.; Wongwanich, S. Relationships between academic performance, perceived group psychological capital and positive psychological capital of Thai undergraduate students. Soc. Behav. Sci. 2014, 116, 3226–3230. [Google Scholar] [CrossRef] [Green Version]
  8. Carmona-Halty, M.; Salanova, M.; Llorens, S.; Schaufeli, W.B. How psychological capital mediates between study-related positive emotions and academic performance. J. Happ. Stud. 2019, 20, 605–617. [Google Scholar] [CrossRef]
  9. Carmona-Halty, M.; Schaufeli, W.B.; Salanova, M. Good relationships, good performance: The mediating role of psychological capital—A three-wave study among students. Front. Psychol. 2019, 10, 306. [Google Scholar] [CrossRef] [Green Version]
  10. Datu, J.A.D.; Valdez, J.P.M. Psychological capital predicts academic engagement and well-being in Filipino high school students. Asia-Pac. Educ. Res. 2016, 25, 399–405. [Google Scholar] [CrossRef]
  11. Luthans, B.C.; Luthans, K.W.; Jensen, S.M. The impact of business school students’ psychological capital on academic performance. J. Educ. Bus. 2012, 87, 253–259. [Google Scholar] [CrossRef]
  12. Nielsen, I.; Newman, A.; Smyth, R.; Hirst, G.; Heilemann, B. The influence of instructor support, family support and psychological capital on the wellbeing of postgraduate students: A moderated mediation model. Stud. High. Educ. 2017, 42, 2099–2155. [Google Scholar] [CrossRef]
  13. Honicke, T.; Broadbent, J. The influence of academic self-efficacy on academic performance: A systematic review. Educ. Res. Rev. 2016, 17, 63–84. [Google Scholar] [CrossRef]
  14. Gallagher, M.W.; Marques, S.C.; Lopez, S.J. Hope and the academic trajectory of college students. J. Happ. Stud. 2016, 18, 341–352. [Google Scholar] [CrossRef]
  15. Rand, K.L.; Martin, A.D.; Shea, A.M. Hope, but not optimism, predicts academic performance of law students beyond previous academic achievement. J. Res. Pers. 2011, 45, 683–686. [Google Scholar] [CrossRef]
  16. Curry, L.A.; Snyder, C.R.; Cook, D.L.; Ruby, B.C.; Rehm, M. Role of hope in academic and sport achievement. J. Pers. Soc. Psychol. 1997, 73, 1257–1267. [Google Scholar] [CrossRef]
  17. Peterson, C.; Barrett, L.C. Explanatory style and academic performance among university freshman. J. Pers. Soc. Psychol. 1987, 53, 603–607. [Google Scholar] [CrossRef]
  18. Prola, M.; Stern, D. Optimism about college life and academic performance in college. Psychol. Rep. 1984, 55, 347–350. [Google Scholar] [CrossRef]
  19. Villavicencio, F.T.; Bernardo, A.B.I. Positive academic emotions moderate the relationship between self-regulation and academic achievement. Brit. J. Educ. Psychol. 2013, 83, 329–340. [Google Scholar] [CrossRef]
  20. Luthans, F.; Youssef-Morgan, C.M. Human, social and now positive psychological capital management: Investing in people for competitive advantage. Organ. Dyn. 2004, 33, 143–160. [Google Scholar] [CrossRef]
  21. Stanjovic, A.D. Development of a core confidence-higher order construct. J. Appl. Psychol. 2006, 91, 1208–1224. [Google Scholar]
  22. Luthans, F.; Avolio, B.J.; Avey, J.B.; Norman, S.M. Positive psychological capital: Measurement and relationship with performance and satisfaction. Pers. Psychol. 2007, 60, 541–572. [Google Scholar] [CrossRef] [Green Version]
  23. Clapp-Smith, R.; Vogelgesang, G.R.; Avey, J.B. Authentic leadership and positive psychological capital: The mediating role of trust at the group level of analysis. Organ. Stud. 2009, 15, 227–240. [Google Scholar] [CrossRef]
  24. Rego, A.; Sousa, F.; Marques, C.; e Cunha, M.P. Authentic leadership promoting employees’ psychological capital and creativity. J. Bus. Res. 2012, 65, 429–437. [Google Scholar] [CrossRef]
  25. Azanza, G.; Domínguez, Á.J.; Moriano, J.A.; Molero, F.J. Capital psicológico positivo. Validación del Cuestionario PCQ en España. An. Psicol. 2014, 1, 294–301. [Google Scholar] [CrossRef] [Green Version]
  26. Avey, J.B.; Avolio, B.J.; Luthans, F. Experimentally analyzing the impact of leader positivity on follower possibility and performance. Leadersh. Quar. 2011, 22, 282–294. [Google Scholar] [CrossRef] [Green Version]
  27. León-Pérez, J.M.; Antino, M.; León-Rubio, J.M. Adaptation of the short version of the Psychological Capital Questionnaire (PCQ-12) into Spanish. Int. J. Soc. Psychol. 2017, 32, 196–213. [Google Scholar] [CrossRef]
  28. Ortega-Maldonado, A.; Salanova, M. Psychological capital and performance among undergraduate students: The role of meaning-focused coping and satisfaction. Teach. High. Educ. 2018, 23, 390–402. [Google Scholar] [CrossRef]
  29. Martínez, L.M.; Youssef-Morgan, C.M.; Chambel, M.J.; Marqués-Pinto, A. Antecedents of academic performance of university students: Academic engagement and psychological capital resources. Educ. Psychol. 2019, 39, 1047–1067. [Google Scholar] [CrossRef]
  30. Schaufeli, W.B.; Salanova, M.; González-Romá, V.; Bakker, A.B. The measurement of engagement and burnout: A two sample confirmatory factor analytic approach. J. Happ. Stud. 2002, 3, 71–92. [Google Scholar] [CrossRef]
  31. Hallberg, U.E.; Schaufeli, W.B. “Same Same” but different? Can work engagement be discriminated from job involvement and organizational commitment? Eur. Psychol. 2006, 11, 119–127. [Google Scholar] [CrossRef]
  32. Bakker, A.B.; Schaufeli, W.B.; Leiter, M.P.; Taris, T.W. Work engagement: An emerging concept in occupational health psychology. Work Stress 2008, 22, 187–200. [Google Scholar] [CrossRef]
  33. Maslach, C.; Schaufeli, W.B.; Leiter, M.P. Job burnout. Annu. Rev. Psychol. 2001, 52, 397–422. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Salanova, M.; Llorens, S.; Cifre, E.; Martínez, I.M.; Schaufeli, W.B. Perceived collective efficacy, subjective well-being and task performance among electronic work groups: An experimental study. Small Group Res. 2003, 34, 43–73. [Google Scholar] [CrossRef]
  35. Lee, J.S. The relationships between student engagement and academic performance: Is it a myth or reality? J. Educ. Res. 2014, 107, 177–185. [Google Scholar] [CrossRef] [Green Version]
  36. Salanova, M.; Llorens, S.; Schaufeli, W.B. Yes, I can, I feel good, and I just do it! On gain cycles and spirals of efficacy beliefs, affect, and engagement. Appl. Psychol. 2011, 60, 255–285. [Google Scholar] [CrossRef] [Green Version]
  37. Bakker, A.B.; Demerouti, E. The job demands-resources model: State of the art. J. Man. Resour. 2007, 22, 309–328. [Google Scholar] [CrossRef] [Green Version]
  38. Gawke, J.C.; Gorgievski, M.J.; Bakker, A.B. Employee intrapreneurship and work engagement: A latent change score approach. J. Vocat. Behav. 2017, 100, 88–100. [Google Scholar] [CrossRef]
  39. Lisbona, A.; Palaci, F.; Salanova, M.; Frese, M. The effects of work engagement and self-efficacy on personal initiative and performance. Psicothema 2018, 30, 89–96. [Google Scholar]
  40. Salanova, M.; Schaufeli, W.B.; Llorens, S.; Peiró, J.M.; Grau, R. Desde el “burnout” al “engagement”: ¿una nueva perspectiva? Rev. Psicol. Trab. Org. 2000, 16, 117–134. [Google Scholar]
  41. Schaufeli, W.B.; Martínez, I.M.; Marqués-Pinto, A.; Salanova, M.; Bakker, A. Burnout and engagement in university students: A cross-national study. J. Cross-Cult. Psychol. 2002, 33, 464–481. [Google Scholar] [CrossRef] [Green Version]
  42. Schaufeli, W.B.; Taris, T.W.; Van Rhenen, W. Workaholism, burnout and engagement: Three of a kind or three different kinds of employee well-being? Appl. Psychol. Int. Rev. 2008, 57, 173–203. [Google Scholar] [CrossRef] [Green Version]
  43. Schaufeli, W.B.; Bakker, A.B. UWES Utrecht Engagement Scale; Utrecht University: Utrech, The Netherlands, 2003. [Google Scholar]
  44. Portalanza, C.A.; Grueso, M.P.; Duque, E.J. Propiedades de la Utrecht Work Engagement Scale (UWES-S 9): Análisis exploratorio con estudiantes en Ecuador. Innovar 2017, 27, 145–155. [Google Scholar] [CrossRef]
  45. Cachón-Zagalaz, J.; Lara-Sánchez, A.; Zagalaz-Sánchez, M.L.; López-Manrique, I.; González-González, C. Propiedades psicométricas de la Utrecht Work Engagement Scale en estudiantes de educación. Suma Psicol. 2018, 25, 113–121. [Google Scholar] [CrossRef] [Green Version]
  46. Salanova, M. Medida y evaluación del burnout: Nuevas perspectivas. In El Síndrome de Quemarse por el Trabajo en Servicios Sociales; Gil-Monte, P., Salanova, M., Aragón, J.L., Schaufeli, W., Eds.; Diputación de Valencia: Valencia, Spain, 2006; pp. 27–43. [Google Scholar]
  47. Salanova, M. Organizaciones saludables, organizaciones resilientes. Gestión Práctica de Riesgos Laborales 2009, 58, 18–23. Available online: http://www.want.uji.es/download/organizaciones-saludables-organizaciones-resilientes/ (accessed on 9 May 2020).
  48. Salanova, M.; Llorens, S.; Cifre, E.; Martínez, I.M. We need a HERO! Toward a validation of the healthy and resilient organization (HERO) model. Group Organ. Manag. 2012, 37, 785–822. [Google Scholar] [CrossRef]
  49. Gómez-Chacón, R.; García-Fernández, J.; Morales-Sánchez, V.; Hernández-Mendo, A. Adaptación y validación del cuestionario del empleado saludable del modelo HERO. An. Psychol. 2020, 36, 361–369. [Google Scholar] [CrossRef]
  50. Llorens, S.; del Líbano, M.; Salanova, M. Modelos teóricos de salud ocupacional. In Psicología de la Salud Ocupacional; Salanova, M., Ed.; Síntesis: Madrid, Spain, 2009; pp. 63–93. [Google Scholar]
  51. Vandenberg, R.J.; Park, K.-O.; DeJoy, D.M.; Wilson, M.G.; Griffin-Blake, C. The healthy work organization model: Expanding the view of individual health and well being in the workplace. In Historical and Current Perspectives on Stress and Health (Research in Occupational Stress and Well Being, Vol. 2); Perrewe, P.L., Ganster, D.C., Eds.; Emerald Group Publishing Limited: Bingley, UK, 2002; pp. 57–115. [Google Scholar]
  52. Kline, R.B. Principles and Practice of Structural Equation Modeling, 2nd ed.; The Guilford Press: New York, NY, USA, 2005. [Google Scholar]
  53. Hair, J.F.; Black, W.C.; Babin, B.J.; Anderson, R.E. Multivariate Data Analyses, 7th ed.; Prentice-Hall: New York, NY, USA, 2009. [Google Scholar]
  54. Harrington, D. Confirmatory Factor Analysis; The Oxford University Press: New York, NY, USA, 2009. [Google Scholar]
  55. Arbuckle, J. Amos18 Reference Guide (Version 18); Statistica: Chicago, IL, USA, 2009. [Google Scholar]
  56. Blunch, N.J. Introduction to Structural Equation Modeling Using SPSS and AMOS; SAGE: Thousand Oaks, CA, USA, 2008. [Google Scholar]
  57. Götz, O.; Liehr-Gobbers, K.; Krafft, M. Evaluation of structural equation models using the partial least squares (PLS) approach. In Handbook of Partial Least Squares; Springer: Heidelberg/Berlin, Germany, 2010; pp. 691–711. [Google Scholar]
  58. Wang, J.; Wang, X. Structural Equation Modeling Applications Using Mplus; John Wiley & Sons Ltd.: Chichester, UK, 2012. [Google Scholar]
  59. Chin, W.W. How to write up and report PLS analyses. In Handbook of Partial Least Squares; Vinzi, V.E., Chin, W.W., Henseler, J., Wang, H., Eds.; Springer: Heidelberg/Berlin, Germany, 2010; pp. 665–690. [Google Scholar]
  60. Fornell, C.; Larcker, D.F. Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 1981, 18, 39–50. [Google Scholar] [CrossRef]
  61. Kline, R.B. Beyond Significance Testing: Reforming Data Analysis Methods in Behavioral Research; American Psychological Association: Washington, DC, USA, 2004. [Google Scholar]
  62. Marôco, J. Análise de Equações Estruturais. Fundamentos Teóricos, Software & Aplicações; Rolo y Filhos II, SA: Pero Pinheiro, Portugal, 2010. [Google Scholar]
  63. Grueso-Hinestroza, M.P.; Rey-Sarmiento, C.F.; González-Rodríguez, J.L.; Ardila-Becerra, A.; Pineda-Castro, C. Actions to promote organizational health and their relationship to structural variables and welfare of workers: An analysis from a model of healthy organizations. Inf. Psicológicos 2013, 13, 59–78. [Google Scholar]
  64. Zarei, E.; Ahmadi, F.; Sial, M.S.; Hwang, J.; Thu, P.A.; Usman, S.M. Prevalence of Burnout among Primary Health Care Staff and its predictors: A study in Iran. Int. J. Environ. Res. Public Health 2019, 16, 2249. [Google Scholar] [CrossRef] [Green Version]
  65. Scanlan, J.N.; Meredith, P.; Poulsen, A.A. Enhancing retention of occupational therapists working in mental health: Relationships between wellbeing at work and turnover intention. Aus. Occup. Ther. J. 2013, 60, 395–403. [Google Scholar] [CrossRef]
  66. Gutiérrez-Bolaño, E.N.; Bermúdez-Lugo, M.; Moreno-Chaparro, J.; Guzmán-Suárez, O.B. Transformation strategies for healthy organizations. Rev. Bras. Med. Trab. 2019, 17, 394–401. [Google Scholar]
  67. Rivera, D.A.; Carrillo, S.M.; Forgiony, J.O.; Nuván, I.L.; Rozo, A.C. Organizational culture, challenges and challenges for healthy organizations. Espacios 2018, 39, 27–40. [Google Scholar]
  68. Baicker, K.; Cutler, D.; Song, Z. Workplace Wellness Programs can generate savings. Health Aff. 2010, 9, 304–311. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  69. Wilson, M.G.; DeJoy, D.M.; Vandenberg, R.J.; Richardson, H.A.; McGrath, A.L. Work characteristics and employee health and well-being: Test of a model of healthy work organization. J. Occup. Organ. Psych. 2004, 77, 565–588. [Google Scholar] [CrossRef]
  70. Organización Mundial de la Salud. Entornos laborales saludables: Fundamentos y Modelo de la OMS. Contextualización, Prácticas y Literatura de Apoyo. Available online: https://www.who.int/occupational_health/evelyn_hwp_spanish.pdf (accessed on 9 May 2020).
  71. Cecilia, M.J.; Atucha, N.M.; García-Estañ, J. Estilos de salud y hábitos saludables en estudiantes del Grado de Farmacia. Educ. Médica 2017, 19, 294–305. [Google Scholar] [CrossRef]
Table
Table 1. The profile of participants.
Table 1. The profile of participants.
VariableN%
Gender
Male15051.7
Female14048.3
Transport
Car20269.7
Motorcycle82.8
Bus7325.1
Others72.4
Study level
High school diploma93.1
Sports education cycle7325.2
Degree19567.2
Post-graduate degree134.5
Degree
Sport Sciences degree9131.4
Primary degree7525.9
Childhood degree4013.8
Higher sports education cycle6823.4
Other teaching cycles20.7
Sport-related post-graduate degree103.4
Others41.4
Table
Table 2. Descriptive statistics.
Table 2. Descriptive statistics.
Scale and DimensionsMeanStandard DeviationSkewnessKurtosis
Emotions (EMOT)5.181.070.5590.285
Engagement (ENG)4.971.010.4490.308
Engagement vigor (ENG-V)4.761.010.2250.285
Engagement dedication (ENG-D)5.371.150.6210.029
Engagement absorption (ENG-A)4.721.060.4060.136
Resilience (RES)5.051.100.5190.235
Self-efficacy (S-E)5.301.070.4030.237
Competence (COMP)5.091.000.3420.158
Mental competence (M-COMP)4.971.110.2320.230
Emotional competence (E-COMP)5.211.070.5580.058
Table
Table 3. Goodness of fit indices for Models 1 and 2.
Table 3. Goodness of fit indices for Models 1 and 2.
Modelχ2/glCFIIFITLIPCFIRMSEA
1 (5 dimensions; 40 items)2.210.870.870.860.810.065 (CI = 0.061, 0.069)
2 (8 dimensions; 40 items)1.950.900.900.890.820.057 (CI = 0.053, 0.062)
Table
Table 4. Goodness-of-fit indices for refinement of Models 1 and 2.
Table 4. Goodness-of-fit indices for refinement of Models 1 and 2.
Modelχ2/glCFIIFITLIPCFIRMSEA
1 (5 dimensions; 36 items)2.000.910.910.900.830.059 (CI = 0.054, 0.064)
2 (8 dimensions; 37 items)1.850.920.920.910.820.054 (CI = 0.049, 0.059)
Table
Table 5. Cronbach’s alpha (α), composite reliability (CR) and average variance extracted (AVE).
Table 5. Cronbach’s alpha (α), composite reliability (CR) and average variance extracted (AVE).
Scale and DimensionsModel 1Model 2
αCRAVEαCRAVE
Emotions (EMOT)0.820.830.530.820.830.52
Engagement (ENG)0.930.940.53
Engagement vigor (ENG-V) 0.860.860.50
Engagement dedication (ENG-D) 0.870.880.64
Engagement absorption (ENG-A) 0.860.870.57
Resilience (RES)0.890.890.550.890.890.56
Self-efficacy (S-E)0.840.850.650.840.850.65
Competence (COMP)0.860.870.52
Mental competence (M-COMP) 0.820.820.60
Emotional competence (E-COMP) 0.770.770.53
Table
Table 6. Correlation and square root of the average variance extracted (AVE) for Models 1 and 2.
Table 6. Correlation and square root of the average variance extracted (AVE) for Models 1 and 2.
Model 112345
1. Emotions (EMOT)0.53
2. Engagement (ENG)0.480.53
3. Resilience (RES)0.400.480.55
4. Self-efficacy (S-E)0.360.450.460.65
5. Competence (COMP)0.480.510.520.620.52
Model 212345678
1. Emotions (EMOT)0.52
2. Engagement vigor (ENG-V)0.610.50
3. Engagement dedication (ENG-D)0.560.740.64
4. Engagement absorption (ENG-A)0.430.690.820.57
5. Resilience (RES)0.400.540.490.540.56
6. Self-efficacy (S-E)0.750.510.570.520.510.65
7. Mental competence (M-COMP)0.390.380.400.530.520.750.60
8. Emotional competence (E-COMP)0.360.350.460.420.460.530.520.53
Note: below the diagonal—estimated correlation between the factors; diagonal—AVE.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Gómez-Chacón, R.; Fernández-Martínez, N.; Gálvez-Ruiz, P. Healthy Students: Adaptation and Validation of the Instrument from the Workplace to the Educational Field. Sustainability 2021, 13, 1134. https://doi.org/10.3390/su13031134

AMA Style

Gómez-Chacón R, Fernández-Martínez N, Gálvez-Ruiz P. Healthy Students: Adaptation and Validation of the Instrument from the Workplace to the Educational Field. Sustainability. 2021; 13(3):1134. https://doi.org/10.3390/su13031134

Chicago/Turabian Style

Gómez-Chacón, Ramón, Nicolás Fernández-Martínez, and Pablo Gálvez-Ruiz. 2021. "Healthy Students: Adaptation and Validation of the Instrument from the Workplace to the Educational Field" Sustainability 13, no. 3: 1134. https://doi.org/10.3390/su13031134

APA Style

Gómez-Chacón, R., Fernández-Martínez, N., & Gálvez-Ruiz, P. (2021). Healthy Students: Adaptation and Validation of the Instrument from the Workplace to the Educational Field. Sustainability, 13(3), 1134. https://doi.org/10.3390/su13031134

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop