Introduction
According to Manzano-Sánchez and Valero-Valenzuela (2019), there is great social demand for general education to provide school students with necessary skills to adapt to societal changes. When one of the most important tasks is to create a respectful and caring learning environment (Li et al., 2008), avoiding exposure to environments that Garbarino (1997) classified as socially toxic. Physical education classes play important roles in developing not only physical capacities but also cognitive, affective, attitudinal, and social domains, thus contributing to the formation of the whole person (Mujica and Orellana, 2019). Importantly, in the context of PE, the affective domain (through positive emotions) promotes motivation to adhere to health-related physical activity (Cachón-Zagalaz et al., 2023). Sandford et al. (2006) suggested that developing personal and social responsibility among primary and secondary school students would positively influence their behaviour. Personal and social responsibility can be developed through school physical education, and in other curricular and extracurricular activities, such as summer sports camps (Hellison, 2003).
Instructional situations offer ideal domains for personal and social responsibility to be demonstrated, observed, and applied. However, to successfully promote this knowledge to students, those who educate and train them must also acquire the necessary information and skills. Likewise, if teachers are aware of motivational theories, then they are more likely to employ strategies that offer better motivational results i.e. teachers who give autonomy to their students enjoy better outcomes than those who use controlled interpersonal teaching styles (Hagger et al., 2014). According to the Self-Determination Theory (SDT), Deci and Ryan (1985) purported that autonomous motivations is developed by offering students the opportunity to self-direct or select their behaviours. In contrast, controlled motivation results from teacher-led didactic approaches with little, if any choice, being selected by the student.
Positive behaviours inculcated by teaching personal and social responsibility skills, values, and virtues offer opportunities for a successful transition to adulthood (Escartí et al., 2010; Martins et al., 2017). According to Gordon (2010), social responsibilities include respecting others, participating and trying hard in activities, using positive self-direction, caring for team or classmates, and transferring personal and social responsibilities to other areas of life, such as studies and work. Hellison’s Model of Personal Responsibility (Hellison and Martinek, 2006) provides guidance to indicate points at which individuals are accountable for their behaviours. They asserted that the lowest level, Irresponsibility, is the point at which individuals are unmotivated, often exhibiting behaviour that might include interrupting, verbally abusing, intimidating, or degrading other people. Self-control sits above the lowest level, suggesting that individuals may participate partially with their behaviours controlled sufficiently such that they do not disrupt others from learning or participating in activities (e.g., sports). Next in the hierarchy sits Involvement in which individuals are actively involved in the subject matter and willing to participate in new activities while the fourth level, Self-responsibility, recognises that there are situations in which individuals can work without supervision and gradually take responsibility for their actions. Finally, Caring, at top of the model’s hierarchy, suggests that individuals extend their sense of responsibility by cooperating with others, providing support, demonstrating concern, and aiding others (Hellion and Martinek, 2006).
Within education, as in other areas of life, young people experience stressful or challenging situations (Martin and Marsh, 2009). To deal with these events, students need to develop resilience (Richardson, 2002). Resilience is an individual characteristic that dynamically utilises personal strengths and capacities to moderate adverse effects of stress and promote positivity by (Charney, 2004). As an individual construct, resilience varies by age, sex, social support, family environment, and culture (Masten and Wright, 2010), with individuals requiring skills that protect them against feelings of vulnerability as well as influencing positive adaptation to risk (Fletcher and Sarkar, 2012). The development of resilience and protection from threatening factors are associated with self-determined motivation (Trigueros et al., 2019), and motivational processes that influence positive emotions (Bekerman et al., 2018).
The enhancement of academic performance and motivation of students is also influenced by positive emotions that play a protective role in controlling anxiety (Yli-Piipari et al., 2009). While emotional intelligence is positively linked to the psychological well-being of secondary school students (Por et al., 2011), emotional well-being, academic performance, and social relationships are interrelated (Song et al., 2010). Also, emotional intelligence is related to the adaptive employability of emotions, application to cognitions (e.g., thinking), and problem resolution (Trigueros et al., 2019). Physical education (PE) is an important subject area in which these pedagogical goals can be achieved, thus motivating young people to engage in PE (Simons et al., 2003) and develop intentions to be physically active (Manzano-Sanchez, 2019). With this in mind, it is hoped that, in the first instance, university students undertaking PE teacher training or delivering sports activities should adopt a physically active lifestyle (Haerens et al., (2010). Doing so may encourage them to incorporate and apply personal and social responsibility model-based programmes in their teaching as the benefits would be more obvious to them through their own lived experiences (Manzano-Sánchez et al., 2019).
Cross-cultural comparative studies have been lacking in the fields of motivation and personal and social responsibilities. However, it is important to study cultural differences to challenge and stimulate thinking, seek new knowledge, affirm current beliefs or practices, and provide a medium through which reflection can occur. Significantly, cross-cultural research can provide important avenues for future studies in a global world, as well as allow researchers to re-evaluate and perhaps re-interpret previous findings. One way of contemplating cross-cultural findings is by examining differences of particular concepts, beliefs, practices, or behaviours by country. Data can be categorised by delineating those countries into geographical regions where variations might be identified due to differing cultures (Beins, 2019).
According to Kitayama et al. (1997) day-to-day situations generate specific learned expectations that systematically vary from one culture to another. People who follow their acquired cultural values and social expectations exhibit behavioural tendencies that are consistent with those values and expectations. Cultural differences also exist in the strength of the compliance with social–political norms (Gelfand et al., 2011), and in patterns of physical activity across nations (World Health Organisation Regional Office for Europe, 2016a, b).
With specific reference to education, Spain and Hungary, with quite different socio-historical backgrounds, have different educational systems. The differences occur in the structure of education, curricular approaches, and philosophical pathways followed be each country. Comparisons based on those two countries, each with its own distinct historical and contemporary political backdrop, can be justified from the work of Triandis (1995, 2001). Indeed, Triandis argues that such work is essential for fuller understanding of our world and its people.
Hungary, which has changed politically and socially from the pre-1989 days of Soviet domination, took a distinctly vocational route based on meeting a direct-labour market (see OECD (2020), Education Policy Outlook: Hungary).
A strong centralised structure with focus on nationally standardised assessments and vocational education has been a central tenet of the curriculum in Hungary. This was heavily geared towards traditional subjects such as mathematics and Hungarian history and literature. Likewise, at HE, the programmes are more centralised than in Spain (OECD, 2020, Education Policy Outlook: Hungary. OECD Report; European Commission, July 2024. https://eurydice.eacea.ec.europa.eu/national-education-systems/hungary/overview).
Although Hungarian education has been changing since the late-90s, change has been slower with past political experiences being manifest in decision-making gives less room for teachers to effect change in their own classrooms (Gábor Halász, Erika Garami, Péter Havas and Irén Vágó Edited by: Gábor Halász, 2001, The Development of the Hungarian Educational System. National Institute for Public Education Budapest, February. ftp://ftp.oki.hu/bie/bie.pdf).
On the other hand, Spain, on leaving behind its polical landscape shaped by fascism, followed an academic pathway to prepare students for higher education. Since the 1970s, Spain has allowed for more decentralised education, including regional variations to enable historical and cultural differences to be addressed. For example, Catalonia and the Basque Country are autonomous regions and the curriculum in those regions may include region-specific subjects (European Commission, 2020; Spain Education and Training Monitor).
In Spain, schooling at primary level highlights the development of general knowledge, language, and social skills while at secondary level, languages, social studies, natural sciences, mathematics, and physical education are strong core subjects (European Commission, December 2024) https://eurydice.eacea.ec.europa.eu/national-education-systems/spain/overview). Given that major political change took place in Spain in the mid- to late-1970s and educational change followed quickly thereafter, it would seem likely that educational outcomes in terms of students’ knowledge, skills, behaviour and thinking might also have changed more rapidly in a move for its society to become more inclusive and tolerant.
While this early and secondary school background in Spain may lend to Spanish school students exhibiting greater PSR and resilience, recent years have seen Hungary moving away from the centralisation of knowledge with Hungarian education now embracing the personal development and social orientation of students. Priorities have shifted to developing the student’s personality through the teaching of adaptive and flexible behavior, physical and psychological fitness, and cooperation skills.
This background makes a cross-cultural comparison of Hungary and Spanish students important as it will evidence if the early differences between a communist-bloc, centralised education system (Hungary) and a more student-centred socially inclusive system of a once fascist now Western democracy (Spain) have now merged. Importantly, it will determine if the thinkings and behaviour of youths who have grown up in the present-day systems in those two countries are also aligned despite the chronological timescales of political change.
With the above in mind, this study had three aims:
To identify the academic motivational profiles (autonomous motivation vs. controlled motivation) of university students taking sports-related courses, as well as establish if there were any differences between motivational groups.
To define relationships within the students’ motivational profiles, in connection with basic psychological need satisfaction (autonomy, competence, relatedness and also an overall sum of psychological mediators index (PMI): emotional intelligence (EI attention, EI clarity, EI repair); resilience; personal and social responsibility; as well as the students’ intentions to maintain physically active lifestyles after graduation.
To investigate whether there are differences between Spanish (Southern European culture) and Hungarian (Central European culture) students as well as male and female students’ motivation, personal and social responsibility, emotional intelligence and resilience.
As such, the following hypotheses were developed for testing:
| H1 | Differences will be established between university students in this sample identifying with autonomous motivation compared with those identifying with controlled motivation. |
| H2 | Positive relationships will be found between motivational profiles of university students in this sample with respect to an overall sum of psychological mediators index (PMI): emotional intelligence (EI attention, EI clarity, EI repair); resilience and personal and social responsibility |
| H3 | Positive relationships will be found between motivational profiles of university students in this sample with respect to the students’ intentions to maintain physically active lifestyles after graduation |
| H4 | Differences will be found by motivation and personal and social responsibility in Spanish (Southern European) and Hungarian (Central European) culture |
| H5 | Differences will be found by motivation and personal and social responsibility in male and female students. |
Methods
Research design
The University of Murcia Research Ethics Committee approved this study (ethics ID number: 2913/2020). All participants were treated in agreement with the ethical guidelines with respect to consent, confidentiality, and anonymity. Each participant completed an informed consent form.
Participants
Following ethical approval, a cross-sectional, cross-cultural comparative quantitative study was conducted with university students studying sport-related courses at the Hungarian University of Sport Sciences, Budapest, Hungary, and University of Murcia, Spain being invited to participate. Volunteers were randomly selected to fill out the data collection instruments. One hundred and sixty-three Spanish (n = 109 males, 67%) and two-hundred and five Hungarian (n = 108 males) university students (total n = 368) participated (see Figure 1). The mean age was 22.7 years (s = 4.9), with an age range 19.3–48.4 years and sport age [years spent participating in sport] of 14.1 years (s = 5.2).
Figure 1
Participants by nationality and sex.
Instruments
A set of seven closed-ended questionnaires were used in this study. One questionnaire was employed to collect socio-demographic variables, and six validated scales were used for study-specific data collection (see below 1–6). The six validated questionnaires were translated from English into Spanish and English into Hungarian by bi-lingual speakers in each country (namely Spain and Hungary). The results were checked for language accuracy and equivalence by a second bilingual speaker in each country and any conflicting issues consensually agreed.
1. Academic Motivation Scale (AMS)
The Academic Motivation Scale (AMS) was developed to measure motivation across the full motivational spectrum including those who are most self-determined, those who are most extrinsically motivated, and those who are amotivated. In Spain, the Spanish version of the Echelle de Motivation en Education (Vallerand et al., 1989), validated by Nuńez et al. (2005), was used. In Hungary, the Canadian version of AMS (Vallerand et al., 1989) was translated into Hungarian.
As recommended by Sánchez-Oliva et al. (2015), a formula was employed to identify whether respondents showed greater extrinsic motivation or more intrinsic motivation: controlling motivation (external regulation + introjected regulation, α = .922), autonomous motivation (identified regulation + intrinsic motivation, α = .830) and amotivation (α = .809).
2. The Basic Psychological Needs in Exercise Scale (BPNES)
The BPNES is a self-report instrument designed to assess perceptions of innate needs for autonomy, competence, and relationships (relatedness) (Deci and Ryan, 2000). The scale was adapted and validated for Spanish speakers and an educational context by Moreno et al. (2011).
Reliability in the pre-test was α = .789 for autonomy, α = .787 for competence and α = .797 for relationships. The psychological mediator index (PMI) was applied to evaluate the three variables jointly, yielding an internal consistency of α = .880.
3. Trait Meta-Mood Scale-24 (TMMS-24)
The TMMS was developed to assess the mood regulation process, the ‘meta-mood experience’ that is involved in monitoring, evaluating, and regulating feelings and emotions (Salovey et al., 1995). Cronbach alpha inter-reliability coefficient ranged from .766 to .803 in the subscales.
4. Resilience Scale-14 (RS-14)
The degree of an individual’s resilience (a positive personality characteristic that allows individuals to adapt to adverse situation) is measured by The Resilience Scale-14 (RS-14) (Damásio et al., 2011). The reliability for the entire scale was α = .876.
5. Personal and Social Responsibility Questionnaire (PSRQ)
The PSRQ measures personal and social responsibility levels (Watson et al., 2003). It was adapted for school contexts by Li et al. (2008), translated into Spanish by Escartí et al. (2011), and validated in a sample of school students. Reliability in the pre-test was α = .846 for social responsibility and α = .736 for personal responsibility.
6. Intention to be Physically Active After School (IPA)
A five-item questionnaire was developed by Escartí and Gutiérrez (2001) to measure young people’s intentions to practice physical activity in the immediate future. This instrument was developed using the Theory of Planned Behaviour (TPB), as attitude influences intention when considering participation in physical activity (Ajzen, 1985). Goudas et al’s., (1995) and Papaioannou’s (2000) studies confirmed that a positive attitude towards exercise should be a positive predictor of young people’s exercise behaviour. Cronbach alpha inter-reliability coefficient accounted for .713 variation.
Data Collection
All seven paper-based questionnaires were administered to participants in quiet classroom environments in each country.
Data analysis
Initially, the validation of the instruments was carried out by analysing the internal consistency of both the pre-and post-test of each scale, using Cronbach’s alpha to calculate the reliability (the results have already been stated). Then, an exploratory analysis of the data was carried out through Box-Whisker diagrams and descriptive measures, in which it was detected that the results could differ between Sex and Age. This was considered in subsequent inferential analyses.
A MANCOVA (multivariate analysis of covariance) was selected to analyse the data as it fits to cross-sectional studies with multiple quantitative dependent variables that may be related to each other and wants to examine whether there are significant differences based on one or more categorical independent variables (country and sex).
The analysis was carried out on the 13 variables from the different questionnaires (autonomy, competence, relatedness, PMI, autonomous and controlled motivation, attention, clarity and repair emotional intelligence, resilience, social and personal responsibility and IPA), in which the between-subject factors were Country (with two levels: Hungary and Spain) and Sex (with two levels: male and female). Additionally, Age as a control variable was added, since it was found that it can significantly affect the measured variables. P-value and eTa (eta-squared) were checked following the recommendations of Richardson (2011), considering that small, medium, and large effect sizes were designated as 0.01, 0.06, and 0.14, respectively. An analysis of the residuals revealed the non-fulfilment of the hypothesis of normality and homoscedasticity of some variables, so it was decided to carry out the analysis also using non-parametric tests. The results obtained with both procedures were very similar, with no significant differences showing in the controlled motivation when the Mann-Whitney U test was used. Therefore, the non-parametric test results were not included for brevity.
The statistical package IBM SPSS 29.0 (New York: USA) was used for all analyses.
Results
Scale reliability, descriptive and bivariate correlation analyses were conducted. Table 1 shows the study’s variables’ means, standard deviation, skewness, kurtosis, and correlation matrix. The skewness and kurtosis values were all <3 and <10, respectively, which is within the limits established as normal (Field, 2017). The scales were presented as having reliability values above .70, which means they are acceptable (Table 1). Furthermore, the correlations between most variables were significant, with values <.80, supporting the absence of multicollinearity between them (Hair et al., 2018). Exceptions are noted for personal responsibility with social responsibility, and for PMI with autonomy, competence, and relatedness. This makes sense as PMI is an index calculated from autonomy, competence, and relatedness. At the same time, this could make more difficult to identify the individual effect of each variable on the dependent variable.
Table 1
Sample descriptive analysis, correlations, and reliability for all variables across all participants.
| M | SD | S | K | A | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Autonomy | 3.973 | 0.759 | –0.565 | –0.134 | .802 | .600** | .419** | .806** | .348** | .150*** | .180** | .186** | .292** | .140** | .184** | .155** | .187** |
| 2 | Competence | 3.924 | 0.741 | –0.619 | –0.106 | .818 | .562** | .864** | .295** | .189** | .136** | .290** | .289** | .211** | .207** | .229** | .283** | |
| 3 | Relatedness | 4.137 | 0.826 | –1.153 | 1.054 | .880 | .812** | .218** | .172** | .085 | .204** | .233** | .092 | .140** | 0.82 | .274** | ||
| 4 | PMI | 4.011 | 0.641 | –0.783 | 0.646 | .884 | .345** | .206** | .160** | .273** | .323** | .176** | .213** | .185** | .301** | |||
| 5 | Autonomous Motivation | 4.947 | 1.066 | –0.316 | –0.233 | .761 | .536** | .252** | .216** | .389** | .387** | .458** | .478** | .250** | ||||
| 6 | Controlled Motivation | 4.658 | 1.146 | –0.175 | –0.480 | .758 | .224** | .116* | .147** | –.042 | .054 | .119* | .085 | |||||
| 7 | EI Attention | 3.273 | 0.756 | 0.103 | –0.351 | .835 | .228** | .280** | .206** | .271** | .294** | .070 | ||||||
| 8 | EI Clarity | 3.495 | 0.752 | –0.426 | 0.202 | .879 | .397** | .284** | .192** | .203** | .096 | |||||||
| 9 | Repair | 3.383 | 0.697 | –0.072 | –0.387 | .778 | .552** | .501** | .465** | .208** | ||||||||
| 10 | Resilience | 4.778 | 1.110 | 0.233 | –0.777 | .963 | .736** | .748** | .332** | |||||||||
| 11 | Social Responsibility | 4.761 | 0.853 | –0.236 | –0.533 | .927 | .815** | .375** | ||||||||||
| 12 | Personal Responsibility | 4.207 | 0.884 | –0.016 | –0.484 | .876 | .333** | |||||||||||
| 13 | IPA | 4.593 | 0.514 | –1.669 | 3.032 | .800 |
[i] Note: * p < .05; ** p < .01; M = mean, SD = standard deviation; s = skewness; K = kurtosis; PMI = psychological mediators index; EI = Emotional intelligence; IPA = Intention to be physically active.
In the MANCOVA at the multivariate level, where significant differences were obtained at the between-subjects factor Country (Wilks Lambda = 0.254, F (13, 340) = 76.938, p < 0.001), it can also be shown how the Age covariate (Wilks Lambda = 0.855, F (13, 340) = 4.429, p < 0.001) was significant. This result shows that it was appropriate to include this variable to control its effect. There were no significant differences for Sex (Wilks Lambda = 0.944, F (13, 340) = 1.561, p = 0.094), nor for the interactions between Country and Sex (Wilks Lambda = 0.943, F (13, 340) = 1.580, p = 0.089).
Subsequently, the results were analysed at the univariate level (Table 2), showing significant differences by Country at the level of relatedness (p = 0.008), autonomous motivation (p < 0.001), controlled motivation (p = 0.038), emotional intelligence attention (p < 0.001), emotional intelligence repair (p < 0.001), resilience (p < 0.001), social responsibility, personal responsibility (p < 0.001) and intention to be physically active (p = 0.003). In the covariate Age, significant differences were found at autonomy (p = 0.002), controlled motivation (p = 0.043), emotional intelligence attention (p = 0.012), emotional intelligence clarity (p = 0.009), emotional intelligence repair (p = 0.014), and resilience (p = 0.010). There were significant differences at the level of relatedness and controlled motivation in favour of the Hungarian group, while autonomous motivation, emotional intelligence attention, emotional intelligence repair, resilience, personal responsibility, social responsibility, and the intention to be physically active showed significant differences in favour of the Spanish group. Although there were no significant differences at the multivariate level in the Sex factor, the univariate analysis showed significant differences at social responsibility (p = 0.004). There were also significant differences for the interaction between Country and Sex factors at controlled motivation (p = 0.009) and personal responsibility (p = 0.045).
Table 2
Univariate analysis of country, age, sex, and country × sex interactions.
| VARIABLE | COUNTRY | AGE | SEX | COUNTRY x SEX | ||||
|---|---|---|---|---|---|---|---|---|
| F (13,340) | p-VALUE | F (13,340) | p-VALUE | F (13,340) | p-VALUE | F (13,340) | p-VALUE | |
| Autonomy | 0.438 | 0.509 | 9.403 | 0.002** | 0.373 | 0.542 | 0.222 | 0.638 |
| Competence | 0.008 | 0.931 | 1.455 | 0.228 | 0.373 | 0.542 | 0.032 | 0.858 |
| Relatedness | 7.077 | 0.008* | 0.051 | 0.822 | 0.003 | 0.960 | 0.280 | 0.597 |
| PMI | 2,051 | 0.153 | 3.127 | 0.078 | 0.253 | 0.615 | 0.231 | 0.631 |
| Autonomous Motivation | 33,664 | <0.001** | 0.005 | 0.944 | 1,789 | 0.182 | 0.233 | 0.629 |
| Controlled Motivation | 4.346 | 0.038* | 4.129 | 0.043* | 0.578 | 0.447 | 8.279 | 0.004* |
| EI Attention | 18,822 | <0.001** | 6.312 | 0.012* | 3.255 | 0.072 | 2.074 | 0.151 |
| EI Clarity | 0,334 | 0.564 | 6.638 | 0.009** | 0.246 | 0.620 | 0.168 | 0.682 |
| EI Repair | 54.844 | <0.001** | 6.058 | 0.014* | 0.316 | 0.574 | 0.045 | 0.833 |
| Resilience | 484.861 | <0.001** | 6.638 | 0.010* | 0.074 | 0.786 | 0.257 | 0.613 |
| Social Responsibility | 364.859 | <0.001** | 0.003 | 0.954 | 8.552 | 0.004* | 2.283 | 0.132 |
| Personal Responsibility | 362.237 | <0.001** | 2.914 | 0.089 | 2.585 | 0.109 | 4.058 | 0.045* |
| IPA | 8.702 | 0.003* | 0.912 | 0.340 | 0.049 | 0.825 | 1.075 | 0.300 |
[i] Note: * p < .05; ** p < .001; PMI = psychological mediators index; EI = Emotional intelligence; IPA = Intention to be physically active.
Because there were differences in the Sex variable and interactions between Country and Sex, a pairwise comparison was realised (Table 3). There were significant differences at the level of relatedness for males (p = 0.011) and in controlled motivation for females (p = 0.002) in favour of Hungary. Significant differences were found in autonomous motivation for males and females (p < 0.001), emotional intelligence attention (p < 0.001), emotional intelligence repair for males and females (p < 0.001), resilience for males and females (p < 0.001), personal responsibility and social responsibility for males and females (p < 0.001), and intention to be physically active for females (p = 0.011), in favour of Spain. In all these cases with significant differences, the eTa-squared of univariate analysis showed large effect size. Figure 2 presents the differences in motivation and satisfaction of the basic psychological needs by country and sex.
Table 3
Pairwise comparisons with sex comparisons presented by rows and comparisons between countries presented by columns.
| COUNTRY | MALES | FEMALES | MALE-FEMALE COMPARISON | ||||
|---|---|---|---|---|---|---|---|
| MEAN | DT | MEAN | DT | p-VALUE | DIF (DT) | ||
| Autonomy | Hungary | 3.998 | 0.073 | 4.009 | 0.077 | 0.913 | –0.012 (0.106) |
| Spain | 3.903 | 0.074 | 3.994 | 0.105 | 0.483 | –0.090 (0.128) | |
| p-value + eTa | 0.365 | 0.002 | 0.904 | 0.000 | |||
| Competence | Hungary | 3.915 | 0.072 | 3.951 | 0.076 | 0.728 | –0.037 (0.105) |
| Spain | 3.893 | 0.072 | 3.959 | 0.103 | 0.603 | –0.066 (0.127) | |
| p-value + eTa | 0.832 | 0.000 | 0.953 | 0.000 | |||
| Relatedness | Hungary | 4.267 | 0.080 | 4.223 | 0.084 | 0.708 | 0.044 (0.116) |
| Spain | 3.978 | 0.081 | 4.030 | 0.114 | 0.706 | –0.053 (0.140) | |
| p-value + eTa | 0.011* | 0.018 | 0.174 | 0.005 | |||
| PMI | Hungary | 4.060 | 0.062 | 4.061 | 0.066 | 0.986 | –0.002 (0.090) |
| Spain | 3.925 | 0.063 | 3.994 | 0.089 | 0.523 | –0.070 (0.109) | |
| p-value + eTa | 0.127 | 0.007 | 0.544 | 0.001 | |||
| Autonomous Motivation | Hungary | 4.569 | 0.099 | 4.774 | 0.105 | 0.155 | –0.205 (0.144) |
| Spain | 5.277 | 0.100 | 5.373 | 0.142 | 0.580 | –0.096 (0.174) | |
| p-value + eTa | <0.001** | 0.067 | <0.001** | 0.032 | |||
| Controlled Motivation | Hungary | 4.610 | 0.110 | 4.875 | 0.116 | 0.098 | –0.265 (0.160) |
| Spain | 4.710 | 0.111 | 4.254 | 0.157 | 0.019* | 0.455 (0.193) | |
| p-value + eTa | 0.523 | 0.001 | 0.002* | 0.028 | |||
| EI Attention | Hungary | 2.997 | 0.071 | 3.257 | 0.075 | 0.012* | –0.261 (0.103) |
| Spain | 3.461 | 0.071 | 3.490 | 0.101 | 0.815 | –0.029 (0.124) | |
| p-value + eTa | <0.001** | 0.057 | 0.065 | 0.010 | |||
| EI Clarity | Hungary | 3.472 | 0.073 | 3.465 | 0.077 | 0.946 | 0.007 (0.106) |
| Spain | 3.554 | 0.073 | 3.479 | 0.104 | 0.557 | 0.075 (0.127) | |
| p-value + eTa | 0.430 | 0.002 | 0.915 | 0.000 | |||
| EI Repair | Hungary | 3.127 | 0.063 | 3.182 | 0.066 | 0.546 | –0.055 (0.091) |
| Spain | 3.670 | 0.063 | 3.695 | 0.090 | 0.820 | –0.025 (0.110) | |
| p-value + eTa | <0.001** | 0.095 | <0.001** | 0.057 | |||
| Resilience | Hungary | 4.002 | 0.069 | 4.064 | 0.073 | 0.542 | –0.061 (0.101) |
| Spain | 5.747 | 0.070 | 5.728 | 0.099 | 0.878 | 0.019 (0.121) | |
| p-value + eTa | <0.001** | 0.471 | <0.001** | 0.342 | |||
| Social Responsibility | Hungary | 4.086 | 0.057 | 4.374 | 0.060 | <0.001** | –0.288 (0.083) |
| Spain | 5.425 | 0.058 | 5.516 | 0.082 | 0.360 | –0.092 (0.100) | |
| p-value + eTa | <0.001** | 0.436 | <0.001** | 0.264 | |||
| Personal Responsibility | Hungary | 3.530 | 0.059 | 3.773 | 0.062 | 0.005* | –0.243 (0.086) |
| Spain | 4.940 | 0.060 | 4.912 | 0.084 | 0.790 | 0.027 (0.103) | |
| p-value + eTa | <0.001** | 0.446 | <0.001** | 0.252 | |||
| IPA | Hungary | 4.548 | 0.050 | 4.502 | 0.052 | 0.523 | 0.046 (0.072) |
| Spain | 4.656 | 0.050 | 4.727 | 0.071 | 0.414 | –0.071 (0.087) | |
| p-value + eTa | 0.127 | 0.007 | 0.011* | 0.018 | |||
[i] Note: * p < .05; ** p < .001; PMI = psychological mediators index; EI = Emotional intelligence; IPA = Intention to be physically active; eTa = effect size of MANCOVA.
Figure 2
Differences in motivation and satisfaction of the basic psychological needs by country and sex.
Two differing analyses were conducted. The first, a MANCOVA, took place at the multivariate level. Significant differences were obtained at the between-subjects factor Country (Wilks Lambda = 0.254, F (13, 340) = 76.938, p < 0.001). The Age covariate also showed significant differences (Wilks Lambda = 0.855, F (13, 340) = 4.429, p < 0.001).
Results showed that university students’ academic motivations were influenced both by internal and external reasons; however, autonomous motivation demonstrated a medium correlation with personal responsibility, social responsibility repair, and resilience. Positive relationships were revealed between personal responsibility and social responsibility, motivation (especially autonomous motivation) and the desire for being physically active. Differences were found by country and by sex.
There were significant differences at the level of relatedness and controlled motivation in favour of the Hungarian group compared with the Spanish group. However, autonomous motivation, emotional intelligence attention, emotional intelligence repair, resilience, personal responsibility, social responsibility, and the intention to be physically active showed significant differences in favour of the Spanish group.
While the multivariate level showed no differences in the Sex factor, the univariate analysis showed significant differences at social responsibility (p = 0.004). There were also significant differences for the interaction between Country and Sex factors at controlled motivation (p = 0.009) and personal responsibility (p = 0.045).
Following analysis of the data, the results showed that the following hypotheses were accepted:
| H1 | Differences were established between university students in this sample identifying with autonomous motivation compared with those identifying with controlled motivation. |
| H2 | Positive relationships were found between motivational profiles of university students in this sample with respect to an overall sum of psychological mediators index (PMI): emotional intelligence (EI attention, EI clarity, EI repair); resilience and personal and social responsibility |
| H3 | Positive relationships were found between motivational profiles of university students in this sample with respect to the students’ intentions to maintain physically active lifestyles after graduation |
| H4 | Differences were found by motivation and personal and social responsibility in Spanish (Southern European) and Hungarian (Central European) culture |
| H5 | Differences were found by motivation and personal and social responsibility in male and female students. |
Discussion
According to the first aim of the study, both autonomous motivation (AM) and controlled motivation (CM) were found to be high in participants, with AM figuring higher than CM. Also, these two variables revealed a strong correlation. It shows that university students’ academic motivation is influenced both by internal and external reasons.
However, according to the second aim, autonomous motivation demonstrated medium correlation with personal responsibility, social responsibility, EI repair, and resilience. The rest of the variables (EI attention, EI clarity, and intention to be physically active after graduation) had weak relationships with autonomous motivation. Controlled motivation demonstrated weak correlation with all other variables, except the earlier mentioned autonomous motivation.
Our third aim was to identify if there were any differences by Country and by Sex. As such, Hungarian students, experienced more controlled motivation and favoured relatedness more than Spanish counterparts. However, Spanish students, demonstrated higher levels of autonomous motivation, emotional intelligence attention, emotional intelligence repair, resilience, personal responsibility, social responsibility, and the intention to be physically active.
In connection with Sex differences, controlled motivation was significantly higher in Spanish male students (Southern European country). This reflects the findings of some studies (e.g., Manzano-Sánchez et al., 2021) that have shown males to have higher values of self-determined academic motivation than females. EI attention, personal responsibility, and social responsibility were significantly higher in Hungarian female students (Central European country), as opposed to Spanish female students. These affirm that there seems to be some relationships between culture and motivation, with Hungarian students being drawn generally towards group or communal motives, possibly due to their country’s more recent past where collectivist ideals were more prevalent. Spanish students seem to be more personally motivated which may align with the earlier development of social sciences and personal development in schools. However, some differences by Sex are noted due to what can be termed dominant groupings e.g., in EI attention, Spanish students overall showed a significant difference compared with Hungarian students, but Hungarian females scored significantly higher as an individual grouping in the same variable (with Hungarian male students). There is no sound rationale for the sex difference among Hungarian students, but it could be hypothesised that females, generally show higher overall EI than males and this is a manifestation of that.
Positive relationships were revealed between motivation (especially autonomous motivation) and both personal responsibility and social responsibility, and the desire for being physically active. This is heartening as it seems to bear out the premise that physically active people will have had more experiences of developing and abiding by communal goals, both in training and in sport. According to Ward and Parker (2013) self-determined motivation has a strong influence on the positive development of young people. Self-determination consists of a high level of intrinsic motivation and commitment that can guide young people when they decide to participate in an activity freely, with pleasure and satisfaction (Deci and Ryan, 2000; Vallerand and Thill, 1993).
The results for females showed better values than corresponding male results in terms of intrinsic motivation and introjected motivation, as well as personal responsibility and social responsibility. This may be a reflection of general emotional maturity of females compared with ales of a similar age.
Teaching and developing personal and social responsibility skills in pre-service teachers or sport leaders is important in order that they can transfer their values, knowledge, and skills to primary and secondary school-age pupils/students. However, it is imperative to ensure that the work in schools is reinforced in other domains such as with the family (parents and older siblings), as well as with appropriate social organisations (or social agents), and to reduce the opportunities for mixed messages. Our data suggests that autonomous motivation for general education and learning, as well as for sport and sport related activities will manifest itself in the improvement of learning performance in both university students and younger school-age students. Likewise, increases in personal and social responsibility will provide similar outcomes. It is hypothesised that, at the same time, decrements in behavioural patterns of bullying and misbehaviour will be observed.
Students have demanding study loads which often apply stresses. With resilience being defined as the dynamic process of returning to normal functioning after stressful events (Den Hartigh et al., 2022), then understanding and improving students’ resilience is of key importance to prevent any deterioration of sport or academic performances and psychological or physical problems. This study found generally high levels of resilience among the cohort but identified that those who scored highly in controlled motivation correlated negatively with resilience, highlighting that students who perceive controlled motivation in an academic environment are less resilient. It is likely that this association reflects their need to be directed and thus less willing or able to make decisions for themselves in times of stress or duress.
According to Manzano-Sánchez et al. (2021), one of the most important tools in education is teaching pre-service teachers Hellison’s model of personal and social responsibility (TPSR) (Hellison and Martinek, 2006). They believed that ensuring pre-service teachers develop an awareness and understanding of the model will help them to behave better in their social environment and teaches them to be responsible for themselves and others. In due course, this can then be transmitted by them on graduation to their school students (Martins et al, 2017). This model is considered one of the most powerful methodologies for the development of adolescent values and resilience to stressful situations in academia, as well as life in general (Martin and Marsh, 2009). As such, there is a need for this model of teaching to be rolled out in teacher/coach training to ensure that the education and sports training of young people has personal and social responsibility embedded in practices.
Moreover, recent trends in TPSR research, includes the aim of integrating Hellison’s model (Hellison and Martinek, 2006) into a hybridised model with the Sports Education Model (SEM). Fernandez-Rio & Menendez-Santurio (2017) hybridised TPSR with the SEM cooperative learning model and concluded that this was a highly suitable method to meet the requirements of current education systems, develop social responsibility, reduce bullying and violence, and improve individual’s perceived competence and social relationships. It promotes the philosophy and behaviour of not only standing up for oneself, but also standing up for others. We suggest that it is only through effective training on this model, and other similar models, will teachers and sports leaders of the future have the tools to embed personal and social responsibility philosophies and teaching into their classes.
Limitations and Future Research
There are several limitations in this study, of which the main one reflects the sample population. More studies are needed to ameliorate key limitations, as our results were obtained based on a cross-sectional study. While offering comparisons with other cultures, the results were not completely consistent or straightforward. As such, the sample size should be increased to provide greater power and, therefore, representativeness. It would also be useful to gather data from a greater variety of countries to allow for increased cross-cultural representation as cross-cultural comparative studies have been lacking in the fields of motivation and personal and social responsibilities. This is necessary to challenge and stimulate thinking, seek new knowledge, affirm current beliefs or practices, and provide a medium through which reflection can occur.
Moreover, and very importantly, this study has shown the need for the development of a major intervention study. We have provided an insight into the motivational profiles of future teachers and sports leaders that indicate positive support for teaching of personal and social responsibility, alongside motivational strategies that may be employed. It now behoves the academic community to move beyond the theoretical testing of models to experimental interventions that test the validity of those models in practice. This would require substantial resources to enable the gathering of baseline data, development of resources, appropriate teaching, and follow-up. By the very nature of such a study, it would have to be longitudinal to allow for teacher/sports leader selection and training (e.g. four groups using one of TSPR, SEM, the hybrid model (TSPR/SEM), and a control group), subsequent time in the field collecting baseline data of student’s behaviours and perceptions, delivering PE and sport to school students, and subsequent data collection of subsequent students’ behaviours.
Conclusions
If Hellison’s model of teaching personal and social responsibility with SEM is accepted as a strategic hybridised pedagogical model for teacher education, co-operative learning will be extended. However, this requires increased emphasis on developing self-motivation in university students to encourage them to improve their personal and social responsibility. As such, the use of autonomous motivational strategies is recommended in order to promote healthy habits, such as physical activity behaviour. This is especially the case if focusing on young males, among whom the prevention of bullying behaviour is a primary task. With sports education and PE being ideal disciplines in which caring and supporting others can be extended and normalised, these positive behaviours could be transferred more broadly outside the sports domain and into wider society. Above all, the development of personal and social responsibilities in students of all ages should assist them to become better people in life.
Funding Information
Project no. TKP2021-NKTA-55 has been implemented with the support provided by the Ministry of Culture and Innovation of Hungary from the National Research, Development and Innovation Fund, financed under the TKP2021-NKTA funding scheme. Project title: Sports culture and sports family: prevention and safeguarding of children, youth and professional staff members in sports. Victimisation and its social, organisational, and individual risk factors in Hungary.
Competing Interests
The authors have no competing interests to declare.