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Physical Self-Concept Changes in Adults and Older Adults: Influence of Emotional Intelligence, Intrinsic Motivation and Sports Habits

Javier Conde-Pipó
Eduardo Melguizo-Ibáñez
Miguel Mariscal-Arcas
Félix Zurita-Ortega
Jose Luis Ubago-Jiménez
Irwin Ramírez-Granizo
1 and
Gabriel González-Valero
Department of Didactics of Musical, Plastic and Corporal Expression, University of Granada, Campus Universitario de Cartuja s/n, 18071 Granada, Spain
Department of Nutrition and Food Science, University of Granada, Campus Universitario de Cartuja s/n, 18071 Granada, Spain
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2021, 18(4), 1711;
Submission received: 24 January 2021 / Revised: 7 February 2021 / Accepted: 8 February 2021 / Published: 10 February 2021


Lifespan is increasing globally as never before, and leading to an aging world population. Thus, the challenge for society and individuals is now how to live these years in the best possible health and wellbeing. Despite the benefits of physical activity for both are well documented, older people are not active enough. Physical self-concept is correlated with high levels of sports practice, although its evolution across one’s life span is not clear. The aim of this research has been to analyze the physical self-concept in older adults and its relationship with emotional intelligence, motivation and sports habits. The sample of 520 adults aged between 41 and 80 was clustered in ranges of age; 70.96% were men (n = 369; 57.34 years (SD: 7.97)) and 29.04% women (n = 151; age = 55.56 years (SD: 9.12)). Questionnaires adapted to Spanish were used to measure physical self-concept (Physical Self-Perception Profile), motivation (Sport Motivation Scale), and emotional intelligence (Trait Meta-Mood Scale). Regarding physical self-concept, the youngest group obtained the highest mean values and the oldest group the lowest. Physical self-concept correlated positively with emotional regulation and intrinsic motivation. Initiation to sports in childhood, the practice of sports activities for more than 150’ per week, and the practice of three or more sports, were associated with a higher score of physical self-concept. The findings reveal that physical self-concept declines in older adults, slightly at first, and sharply between 71 and 80 years, being intrinsic motivation, emotional regulation, and sports habits, factors to consider in favoring a positive physical self-concept and adherence to sporting activities.

1. Introduction

The world is experiencing a great demographic revolution. Facilitated by socioeconomic progress and the most recent advances in public health, life expectancy has increased significantly, which, together with a sharp drop in the birth rate, is leading to an aging world population. For the first time in history, the number of people aged over 65 is greater than under 5, and by 2050 the UN [1] expects this gap to double. Paradoxically, this great achievement of humanity presents new challenges, not only for society, which is seeing its workforce shrink or the pressure and costs of health and care services increase, but also for the individual who is faced with how to live through these times in the best possible health and quality of life [2,3,4,5].
It is now well established from a variety of studies that these problems can be mitigated by promoting a healthier and more active life among older people, an action that also impacts on quality of life, since the practice of physical activity (PA), in addition to reducing the risk of death from all causes, contracting cancer, diabetes or cardiovascular disease, has a direct impact on one of its main components, physical and mental functional capacity [4,6,7,8,9,10]. However, despite the many benefits of physical activity and the fact that the current older generation are healthier and feel younger than similarly aged individuals of past generations [6], older people are not active enough, with less than a third practicing PA regularly, so it is necessary to seek urgent measures to reverse this situation and increase participation [11,12,13,14].
The practice of PA also has benefits on the mental health of older people, positively affecting one of the most important psychosocial factors that influences an individual’s well-being and health habits, the self-concept [15,16,17,18,19]. The before-mentioned is defined as the collection of beliefs about one’s self and is also associated with health behaviors [15], and following the multidimensional and hierarchical model proposed by Shavelson [20], it is divided into academic, social, family, emotional and physical dimensions [15,21]. The physical self-concept (PSC) is therefore the set of ideas that we believe define us physically [22], and is in turn made up of four other dimensions, physical condition (PC), sports competence (SC), physical attractiveness (AT) and physical strength (ST) [23].
While the reciprocal relationship between PA and PSC is widely documented [12,24,25,26], the evolution of PSC across a lifespan is not clear. Longitudinal studies are still scarce, with comparisons between age-groups prevailing, mainly focusing on child and adolescent stages, and there is no consensus on the results [13,14,22,27,28,29]. In studies that have addressed this issue in adulthood and old age, the results are inconsistent. Some prominent longitudinal studies, such as Amesberguer et al. [30], Finkenzeller et al. [31], or Sweeney et al. [19], show that PSC is stable or slightly decreasing. Among the cross-sectional studies reviewed, Esnaola [32] reported an increase in PSC with age, while Infante et al. [33], Molero et al. [34], and Putnick et al. [35], reported that it remains stable.
Sports motivation (SM) plays an important role in the adherence to the practice of PA, determining the initiation, continuation and abandonment of it, since what pushes older individuals to practice is important, as is analyzing what factors determine it [36]. Currently, little is known about the specific reasons that might lead sedentary people to regular PA practice [37]. Despite the lack of studies on the older population, for which interest is growing, there is a body of recent research based on the theory of self-determination, which considers self-determined motivation as a predictor of positive psychological, social and emotional consequences in physically active older adults [38,39,40]. These authors suggest that it is mainly intrinsic motivation, such as the enjoyment or consideration of sports as a significant part of one’s lifestyle, that help the adherence to PA among the adult population, giving a secondary role to extrinsic motivation, such as competition or social recognition.
Emotional intelligence (EI) is another important factor that impacts on people’s social and psychological well-being [41,42]. As a personality trait, it encompasses emotion-related self-perceptions and dispositions, concerning how people manage emotions and understand the impact of their emotions on social interactions, and is measured via self-report [43,44]. Concerning the area of aging, research is still limited and inconsistent, although recent evidence suggests that EI is not stable over time, decreasing in some dimensions that can be compensated by increases in others, with a positive final balance [45,46,47,48]. Emotional regulation skills seem to increase with age due to personal experiences accumulated throughout life, and interpersonal relationships, generating greater emotional control, with less physiological activation in negative conditions and more positive emotional experiences [48,49]. However, due to age-specific cognitive decline, which leads to loss of attention, memory, and speed of information processing, older people may have more difficulty in accurately recognizing the emotions of others in facial gestures and vocabulary. They are also less expressive, making it more difficult to identify emotions in their faces [48,49,50].
There are numerous references found in the literature that describe the relationship between physical self-concept and sports habits, specifically the time of dedication to sports practice, as positive and reciprocal [12,18,24,25,26,51,52]. Nevertheless, the studies concerning the relationship between physical self-concept and intrinsic motivation are scarce, and their results are contradictory. Some of them consider this relationship to be positive [12,51,53], and others consider it negative [54]. Recent literature reviews published on the relationship between emotional intelligence and sports [55,56,57] show that a higher level of EI generates a more positive attitude towards the practice of PA, a greater frequency of practice, more fun and enjoyment, and a lower level of anxiety and competitive stress. Although the relationship with PSC has not yet been explored, indirectly, EI could contribute to higher levels of PSC.
Therefore, once the scientific literature has been reviewed, and the insufficiency of studies and the inconsistency of results have been proven, the aims of this research are the following: (a) to analyze the levels of physical self-concept in different age groups; (b) to establish the relationships between physical self-concept and sports motivation, emotional intelligence and sports habits, and (c) to examine the predictive capacity of the variables and physical self-concept in the Spanish population over the age of 40.

2. Materials and Methods

2.1. Design and Subjects

The study design was cross-sectional, descriptive, comparative and correlational. The sample was initially composed of 543 subjects, all of them Spaniards from different regions, with a single inclusion criterion, namely, being between 41 and 80 years old. In total, 23 participants were discarded for not meeting the age criteria or not completing the questionnaires properly. Of the 520 remaining (Table 1), 70.96% were men (n = 369; 57.34 years (SD: 7.97); height = 1.74 m (SD: 7.78); weight = 80.79 kg (SD: 11.69)) and 29.04% were women (n = 151; age = 55.56 years (SD: 9.12); height = 1.61 m (SD: 7.98); weight = 64.24 kg (SD: 13.13)). Following the statistical criteria, the sample was clustered in ranges of age. Thus, 22.30% of the subjects were between 41 and 50 years old (n = 116), 43.5% were between 51 and 60 years old (n = 225), 25.96% were between 61 and 70 years old (n = 135), and 8.24% were between 71 and 80 years old (n = 44).

2.2. Instruments and Variables

Ad-hoc questionnaire: this instrument was created by the researchers to collect the sociodemographic data and sports habits of the subjects participating in this research. They were asked about their sex, age, weight and height (from which the BMI was estimated), the hours of weekly sports practice, the age at which they began to practice sports, the number of sports practiced and which ones they were, grouped into outdoor sports (hiking, running, cycling, skiing, etc.), fitness sports (swimming, weights, pilates, yoga, dance, etc.) or opponents sports (tennis, paddle tennis, team sports). Based on the hours of weekly sports practice declared, all those who met the recently published recommendations for PA practice for older adults (≥150‘ per week) were labeled as “active” [6,58,59] and those who did not, as “not active”.
Physical Self-Concept Questionnaire (PSC-Q): this is based on the PSPP 30 (Physical Self-Perception Profile) questionnaire by Fox and Corbin [23] and was adapted to the adult Spanish population by Goñi [60]. It is made up of 30 items, and is valued using a Liker scale of four response options, from “Totally disagree” to “Totally agree”. It is divided into five dimensions: physical condition (PC, α = 0.84), sports competence (SC, α = 0.88), physical attractiveness (AT, α = 0.88), physical strength (ST, α = 0.83) and general physical self-concept (PSC, α = 0.88).
Sports Motivation Scale questionnaire (SMS): the original is by Pelletier [61], and it was adapted into Spanish by Balaguer et al. [62]. It is composed of three main dimensions, intrinsic motivation (IM, α = 0.79), extrinsic motivation (EM, α = 0.69) and demotivation (NM, α = 0.75), and consists of 28 items valued via a Likert scale that oscillates between values of 1 (“It has nothing to do with me”) and 7 (“It totally fits me”). It is an instrument with adequate psychometric properties, reliable and valid for the study of different types of motivational regulations in sport [36].
Emotional Intelligence Questionnaire (TMMS-24): the original is by Salovey et al. [63], and it was adapted to the Spanish language by Fernández-Berrocal et al. [64]. It assesses each person’s knowledge of their own moods using 24 items grouped in three dimensions: emotional attention (EA, α = 0.90), emotional understanding (EU, α = 0.90) and emotional regulation (ER, α = 0.86). It rates the responses using a Likert scale of 5 response options, from “Not at all agree” to “Strongly agree”.

2.3. Procedure

All subjects were recruited through social networks, participating voluntarily and showing their written informed consent. All of them were informed of the aims of this research and the data-protection provided was assured. The surveys were completed electronically and completely anonymously. The research complies with the principles of the Declaration of Helsinki and has the approval of the Research Ethics Committee of the University of Granada, with code 1230/CEIH/2020.

2.4. Analysis of Data

The statistical analysis was performed with the statistical computing software R (R Core Team, Vienna, Austria). For the basic descriptions, frequencies, means and standard deviations were used. For the study of comparisons between groups of continuous variables, the non-parametric tests for independent samples’ U of Mann–Whitney and Kruskal–Wallis were used. In the cases of lack of homoscedasticity and/or presence of outliers, the YUEN and robust ANOVA tests were chosen. The differences between groups were obtained with the Wilcoxon post hoc test with Bonferroni correction and the Lincon one. The level of effect in group comparisons was obtained using the standardized Cohen’s d and eta-squared indices, and in the case of bivariate correlations, Spearman’s rho. The association between categorical variables was evaluated using the chi-square test and its magnitude with Cramer’s V coefficient. The normality of data was assessed using the Kolmogoro–Smirnov test, using the Lillieforts correction, and homoscedasticity was assessed using the Levene test. The internal reliability of the instruments used was assessed using Cronbach’s alpha coefficient. All reported p values are based on a two-tailed test and the level of statistical significance set for all tests was 95%.

3. Results

Table 1 shows the characteristics of the sample according to classification by sex and age. Statistically significant differences were observed (p < 0.05) when comparing the variables of height and BMI by age groups, obtaining for both the greatest differences between the 41–50-year-old group and the 71–80-year-old group (p < 0.05). When comparing between sexes, statistically significant differences (p < 0.001) were obtained for the variables height, weight and BMI in all age groups, except for BMI in groups 61–70 (p = 0.175) and 71–80 (p = 0.537), and for weight in the 71–80 group (p = 0.100).
The sample’s sports habits by age ranges are shown in Table 2. A statistically significant relationship but weak association was found between age groups and sports initiation (p = 0.001; V = 0.171), level of activity (p = 0.001; V = 0.219), and number of sports practiced (p = 0.001; V = 0.188). The 41–50-year-old group was composed of a statistically higher percentage of active subjects (% = 93.97; p = 0.002), those initiated in childhood (% = 63.79; p = 0.004), and those practicing three or more sports (% = 55.17; p = 0.001). Contrastingly, the 71–80 group was the one with the highest percentage of non-active subjects (% = 29.55; p = 0.003) and non-practitioners (% = 15.91; p = 0.001), as well as the lowest percentage of practitioners of three or more sports (% = 25; p = 0.01). Regarding the type of sports practiced and the age groups, a significant but weak association was found both for maintenance sports (p = 0.046; V = 141) and for opponents (p = 0.001; V = 213), with statistically significant differences in the percentages of practitioners of each modality in the age group 41–50 (p ≤ 0.05).
The results of PSC-Q, TMMS-24 and SMS questionnaires are shown in Table 3. No dimensions presented a normal distribution (p > 0.05). The internal consistency analysis of PSC-Q showed acceptable values, both globally (α = 0.93) and for the different dimensions (SC, α = 0.83; PC, α = 0.87; AT, α = 0.81; ST, α = 0.72; PSC, α = 0.72). The means tests showed statistically significant differences between groups and weak association in the dimensions PSC (p = 0.022; η2 = 0.02), PC (p < 0.001; η2 = 0.03), and SC (p < 0.001; η2 = 0.03).
A different behavior was observed, whereby the youngest group obtained the highest mean values and the oldest group the lowest (Figure 1). For the PC dimension, the post hoc test with Bonferroni adjustment showed statistically significant differences between the 41–50 vs. 51–60 groups (p = 0.034) and the 41–50 vs. 71–80 groups (p = 0.039); for the SC dimension, the differences were between the 41–50 vs. 71–80 groups (p = 0.002) and the 61–70 vs. 71–80 groups (p = 0.043); for the PSC, all groups showed differences from the 71–80 group (vs. 41–50, p = 0.012; vs. 51–60, p = 0.034; vs. 61–70, p = 0.074).
No statistically significant differences (p > 0.05) were observed for the dimensions of the TMMS-24 questionnaire (α = 0.91), with the values remaining stable in the four age groups. The SMS questionnaire showed a global internal consistency of 0.93 (IM, α = 0.97; EM, α = 0.89; NM, α = 0.72), as well as statistically significant differences between groups and a mean association for the IM (p < 0.001; η2 = 0.06) and NM variables (p < 0.001; η2 = 0.06), placing the differences in the 71–80 group vs. the 41–50 (p = 0.003), 51–60 (p = 0.005) and 61–70 (p = 0.035) groups.
The analysis of the correlations between the questionnaires’ dimensions is presented in Table 4, all of them being positive except for NM. The correlation of all the scales of PSC-Q with each other was statistically significant and between moderate (r ≥ 0.5) and high (r ≥ 0.7), in contrast with those of SMS, which were small (r ≥ 0.1) to moderate, and those of TMMS-24 that ranged between null (r < 0.1) and moderate, finding no statistically significant correlation between EM and NM. The strongest correlations were obtained between PC and SC (r = 0.70), PC and ST (r = 0.64), and PC and AT (r = 0.60). The only dimension that did not correlate statistically significantly with the dimensions of other questionnaires was EA.
Table 5 shows the correlations between PSC and the rest of the PSC-Q, TMMS-24 and SMS variables by age group. The variables that present a statistically significant correlation with the PSC in all age groups are ST (r = 0.40; p ≤ 0.01), ER (r = 0.22; p ≤ 0.050) and NM (r = 0.32; p ≤ 0.002). The variables with the highest correlation with PSC were SC in groups 41–50 (r = 0.58; p < 0.001) and 51–60 (r = 0.62; p < 0.001), AT in 61–70 (r = 0.64; p < 0.001) and ST in 71–80 (r = 0.40; p = 0.010).
The association by age group between PSC and the sports habits studied is reflected in Table 6 and Figure 2. Concerning the stage of sports initiation, there were statistically significant differences in all age groups except for the 71–80 years old group (p = 0.180). Specifically, the greatest differences occurred between initiation during childhood and adulthood (41–50, p < 0.001; 51–60, p < 0.001; 61–70, p < 0.001). The strongest association was obtained in the 61–70 group (η2 = 0.23). No statistically significant differences were obtained for the variable level of activity in groups 41–50 (p = 0.362) and 71–80 (p = 0.262). In the groups in which it did occur, the association was large (51–60, p < 0.001, d = 0.50; 61–70, p < 0.001, d = 0.73). Regarding the number of sports practiced, an association with PSC was found in groups 51–60 (p < 0.001; η2 = 0.17) and 61–70 (p = 0.002; η2 = 0.24), with the greatest differences in those who practice three or more sports (p < 0.050) (Figure 3). No statistically significant differences were obtained depending on the type of sports practiced (p > 0.05).

4. Discussion

The main aim of this study has been to investigate the changes in PSC in the different age groups, covering the age range between 40 and 80 years, as well as its relationship with EI, SM and various sports habits.
Statistically significant differences in the behavior of PSC and its dimensions according to the age group were partially found. Despite the limitations of a cross-sectional study, the results obtained in relation to age in subjects over 40 indicate that the perception of PSC decreases with age, since a descending behavior is observed, especially in the older age group. However, statistically significant differences were only found for the group over 70 years of age, but not between the rest of the groups. Regarding the PC and SC dimensions, the differences occurred between the youngest and oldest age groups. As in other previous analogous studies, no statistically significant differences were found for the AT and ST dimensions [32,33,34], which indicates that the interest in both remains constant from the point of reaching adulthood.
These results are in line with those obtained in the few existing studies with the older population, both longitudinal [30,31] and transversal [32,33,34]. Based on this and previous research on PSC carried out with younger populations [32,60,65,66], we suggest that PSC throughout lifespan behaves in the shape of an inverted U, developing from infancy to the beginning of adulthood, followed by a period of stability until the age of 40–50, and then decreasing, first slowly, and sharply from the age of 70, concurring with the biological stage of the greatest loss of muscle strength, mobility and functional capacity [8,67,68]. The differentiated analysis of the PC and SC dimensions shows a behavior similar to the PSC but with a small rebound in the 61–70 age group, whose origin may be in the increase in free time to dedicate to sports and new physical activities after retirement, as well as the escape from the cessation of activity that this implies and its negative consequences for health [69]. Unlike the PSC, these dimensions could not stabilize, and fall from reaching their peak values in adolescence [32,60,70]. Therefore, reaching and maintaining high levels of PSC in advanced adults seems to depend on the levels reached during childhood and adolescence.
We also partially found a significant relationship between PSC and the dimensions that make up EI and SM in the different age groups, despite the close relationship between EI and its components with PA [56,71,72]. ER is the only dimension of EI that maintained a correlation with PSC in all age groups, probably due to its relationship with the ability to adjust levels of stress and anxiety [55,73], favoring positive emotional experiences and inhibiting the sensations of pain and fatigue [48,49,55]. However, the accumulated experience with age or the decline in cognitive abilities does not seem to influence the ability to identify, understand and manage emotions, as the average values of three EI dimensions remained stable when comparing the different age groups, contrary to what is stated by other studies [45,47,50,74]. The discrepancies in the results may be due, among other reasons, to the fact that our sample was limited to subjects aged over 40. However, the analysis of correlations between the different variables showed a negative correlation between NM and ER, which indicates that enhancing ER learning mechanisms can help prevent the abandonment of PA.
Regarding sports motivation, the IM dimension was positively correlated with the PSC except in the oldest group, and the NM dimension was negatively correlated in all groups. Regarding the dimensions of PSC, the highest correlation was obtained between IM and SC, which indicates that for this group of the population, control and dominance of the activity are important and motivating in themselves. In general terms, these results are congruent with those described in the existing literature and recently reviewed by Tang et al. [41], since they confirm the importance of intrinsic motivation and its correlation with psychological well-being and self-concept as a fundamental part of it. However, in the case of those over 71 years of age, PSC will depend to a greater extent on avoiding the loss of motivation and apathy towards sports practice than on the increase in personal satisfaction or mastery of the task, typical of intrinsic motivation.
Regarding the association between PSC and the sports habits contemplated in this study, the results obtained are in line with previous studies that have explored the relationship between the practice of PA and PSC [13,18,70,75]. In all age groups, the PSC level was higher in those who worked actively, obtaining the greatest differences in the group aged 61 to 70, possibly due to the slowing effect that physical activity has on the effects of aging, both physical and cognitive, that are very evident from this age onwards [16,76]. Regarding the type and number of sports practiced, although other studies with a younger population [77] found significant differences in the levels of PSC depending on the sport practiced, in our study these were not given, but they were regarding multidisciplinary practice. Those who practice three or more sports present higher levels of PSC in all age groups, with the differences between 50 and 69 years being statistically significant. Finally, an association was also found between the levels of PSC and the onset stage, this being higher in those sports subjects who started during the childhood stage, with the exception of the 71–80 group, possibly due to a generational effect, caused both by the lack of opportunities due to the socioeconomic context of the period and by the lack of school physical education. This finding adds one more reason to promote the practice of physical activity at an early age; not only will motor skills be developed and the foundations for optimal physical development be created, but higher levels of PSC will also be achieved that, if maintained in adulthood, will allow greater personal well-being and greater adherence to sports practice, which will ultimately translate into better physical and mental health [13,16,27].
This research has several limitations. The main one is its descriptive cross-sectional design, which does not allow us to establish a cause–effect relationship between the variables studied and the general PSC throughout older adults’ lifespans, requiring future longitudinal studies. Additionally, not all the population studied are older adults. The small sample size of both women and subjects over 70 may represent a bias when generalizing the results, and it would be interesting to expand it and complete the analysis differentiating by sex. Likewise, the absence of objective measurements for the assessment of physical activity, and the generational effect of each age group, make it necessary to take these results with prudence, and their interpretation must be cautious.
As a future perspective, the role of nutrition and other health parameters in the analysis of physical self-concept in the adult population should be considered.

5. Conclusions

The main finding of this research, despite its limitations, is that PSC decreases from the age of 40, with a sharp decline starting at the age of 70. Seen throughout the lifespan, and taking into account previous studies with younger populations, the behavior of PSC is not linear but convex, increasing from childhood until reaching adolescence, followed by a period of stability, and finally decreasing dramatically at the latter stages of life. Regarding the motivation towards sports practice and its relationship with PSC, it is in the intrinsic motivations where the older adult finds reasons for sports practice, thereby favoring higher levels of PSC. PA and higher levels of PSC are favored by EI through its ER dimension, as it reduces the effect of demotivation.
This research emphasizes the importance of practising physical activity from an early age, as well as multidisciplinary sports practice, since both are associated with higher levels of PSC in older adults. Not surprisingly, it is in childhood that motor skills and physical condition are acquired, and the more varied, stimulating and enriching these experiences are, the greater the enjoyment and adherence to PA practice will be, favoring it throughout the entire lifespan and bringing with it higher levels of health and quality of life.

Author Contributions

Conceptualization, J.C.-P. and F.Z.-O.; methodology, J.C-P., G.G.-V. and F.Z.-O.; software, J.C.-P. and I.R.-G.; formal analysis, J.C.-P. and E.M.-I.; investigation, E.M.-I. and J.L.U.-J.; data curation, J.C.-P. and I.R.-G.; writing—original draft preparation, J.C.-P.; writing—review and editing, J.C.-P., J.L.U.-J., M.M.-A. and G.G.-V.; supervision, M.M.-A. and F.Z.-O.; project administration, J.C.-P., M.M.-A. and F.Z.-O. All authors have read and agreed to the published version of the manuscript.


This research received no external funding.

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Ethics Committee of University of Granada.

Informed Consent Statement

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

Conflicts of Interest

The authors declare no conflict of interest.


  1. Population Division, Department of Economic and Social Affairs, United Nation. World Population Ageing 2017; United Nation: New York, NY, USA, 2017. [Google Scholar]
  2. Bhardwaj, R.; Amiri, S.; Buchwald, D.; Amram, O. Environmental correlates of reaching a centenarian age: Analysis of 144,665 deaths in Washington state for 2011–2015. Int. J. Environ. Res. Public Health 2020, 17, 2828. [Google Scholar] [CrossRef]
  3. Foscoloua, A.; Magriplisa, E.; Tyrovolasa, S.; Soulisa, G.; Bountzioukaa, V.; Mariolisc, A.; Piscopod, S.; Valacchie, G.; Anastasiouf, F.; Gotsisa, E.; et al. Lifestyle determinants of healthy ageing in a Mediterranean population: The multinational MEDIS study. Exp. Gerontol. 2018, 110, 35–41. [Google Scholar] [CrossRef] [Green Version]
  4. Hajat, C.; Selwyn, A.; Harris, M.; Yach, D. Preventive interventions for the second half of life: A systematic review. Am. J. Health Promot. 2018, 32, 1122–1139. [Google Scholar] [CrossRef]
  5. Sarabia-Cobo, C.M.; Pérez, V.; Hermosilla, C.; de Lorena, P. Retirement or no retirement? The decision’s effects on cognitive functioning, well-being, and quality of life. Behav. Sci. 2020, 10, 151. [Google Scholar] [CrossRef] [PubMed]
  6. Bangsbo, J.; Blackwell, J.; Boraxbekk, C.J.; Caserotti, P.; Dela, F.; Evans, A.B.; Jespersen, A.P.; Gliemann, L.; Kramer, A.F.; Lundbye-Jensen, J.; et al. Copenhagen consensus statement 2019: Physical activity and ageing. Br. J. Sports Med. 2019, 53, 856–858. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  7. Calder, P.C.; Carding, S.R.; Christopher, G.; Kuh, D.; Langley-Evans, S.C. A holistic approach to healthy ageing: How can people live longer, healthier lives? J. Hum. Nutr. Diet. 2018, 31, 439–450. [Google Scholar] [CrossRef]
  8. Landi, F.; Calvani, R.; Picca, A.; Tosato, M.; Martone, A.M.; D’Angelo, M.; Serafini, E.; Bernabei, R.; Marzetti, E. Impact of habitual physical activity and type of exercise on physical performance across ages in community-living people. PLoS ONE 2018, 13, 0191820. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  9. Parker, P.C.; Chipperfield, J.G.; Perry, R.P.; Hamm, J.M.; Hoppmann, C.A. Attributions for physical activity in very old adults: Predicting everyday physical activity and mortality risk. Psychol. Health 2019, 34, 216–231. [Google Scholar] [CrossRef]
  10. Saint-Maurice, P.F.; Coughlan, D.; Kelly, S.P.; Keadle, S.K.; Cook, M.B.; Carlson, S.A.; Fulton, J.E.; Matthews, C.E. Association of leisure-time physical activity across the adult life course with all-cause and cause-specific mortality. JAMA Netw. Open. 2019, 2, 190355. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  11. Boulton, E.; Hawley-Hague, H.; French, D.P.; Mellone, S.; Zacchi, A.; Clemson, L.; Vereijken, B.; Todd, C. Implementing behaviour change theory and techniques to increase physical activity and prevent functional decline among adults aged 61–70: The PreventIT project. Prog. Cardiovasc. Dis. 2019, 62, 147–156. [Google Scholar] [CrossRef] [PubMed]
  12. Ensrud-Skraastad, O.K.; Haga, M. Associations between motor competence, physical self-perception and autonomous motivation for physical activity in children. Sports 2020, 8, 120. [Google Scholar] [CrossRef]
  13. Li, Y.C.; Chirico, D.; Graham, J.D.; Kwan, M.Y.W.; Cairney, J. Motor coordination and moderate-to-vigorous physical activity in emerging adults: Mediating effect of physical self-concept. International Int. J. Environ. Res. Public Health 2020, 17, 3748. [Google Scholar] [CrossRef]
  14. Utesch, T.; Dreiskämper, D.; Naul, R.; Geukes, K. Understanding physical (in-) activity, overweight, and obesity in childhood: Effects of congruence between physical self-concept and motor competence. Sci. Rep. 2018, 8, 1–10. [Google Scholar] [CrossRef] [Green Version]
  15. Babic, M.J.; Morgan, P.J.; Plotnikoff, R.C.; Lonsdale, C.; White, R.L.; Lubans, D.R. Physical activity and physical self-concept in youth: Systematic review and meta-analysis. Sports Med. 2014, 44, 1589–1601. [Google Scholar] [CrossRef]
  16. Berthelot, G.; Johnson, S.; Noirez, P.; Antero, J.; Marck, A.; Desgorces, F.D.; Pifferi, F.; Carter, P.A.; Spedding, M.; Mannoux, A.S.; et al. The age-performance relationship in the general population and strategies to delay age related decline in performance. Arch. Public Health 2019, 77, 1–9. [Google Scholar] [CrossRef] [Green Version]
  17. Hsu, Y.; Lu, F.J.H. Older adults’ physical exercise and health-related quality of life: The mediating role of physical self-concept. Educ. Gerontol. 2018, 44, 247–254. [Google Scholar] [CrossRef]
  18. Jodra, P.; Maté-Muñoz, J.L.; Domínguez, R. Percepción de salud, autoestima y autoconcepto físico en personas mayores en función de su actividad física. Rev. Psicol. Deporte 2019, 28, 127–134. [Google Scholar]
  19. Sweeney, A.M.; Wilson, D.K.; Van Horn, M.L. Longitudinal relationships between self-concept for physical activity and neighborhood social life as predictors of physical activity among older African American adults. Int. J. Behav. Nutr. Phy. 2017, 14, 1–12. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  20. Shavelson, R.J.; Hubner, J.J.; Stanton, G.C. Self-concept: Validation of construct interpretations. Rev. Edu. Res. 1976, 4, 407–441. [Google Scholar] [CrossRef]
  21. Esnaola, I.; Sesé, A.; Antonio-Agirre, I.; Azpiazu, L. The development of multiple self-concept dimensions during adolescence. J. Res. Adolesc. 2020, 30, 100–114. [Google Scholar] [CrossRef] [PubMed]
  22. González-Valero, G.; Zurita-Ortega, F.; Ubago-Jiménez, J.L.; Puertas-Molero, P. Motivation, self-concept and discipline in young adolescents who practice rhythmic gymnastics. An intervention. Children 2020, 7, 135. [Google Scholar] [CrossRef] [PubMed]
  23. Fox, K.R.; Corbin, C.B. The physical self-perception profile: Development and preliminary validation. J. Sport Exerc. Psy. 1989, 11, 408–430. [Google Scholar] [CrossRef]
  24. Chrismas, B.C.R.; Majed, L.; Kneffel, Z. Physical fitness and physical self-concept of male and female young adults in Qatar. PLoS ONE 2019, 14, e0223359. [Google Scholar] [CrossRef]
  25. Garn, A.C.; Morin, A.J.S.; White, R.L.; Owen, K.B.; Donley, W.; Lonsdale, C. Moderate-to-vigorous physical activity as a predictor of changes in physical self-concept in adolescents. Health Psychol. 2020, 39, 190–198. [Google Scholar] [CrossRef]
  26. Jekauc, D.; Wagner, M.O.; Herrmann, C.; Hegazy, K.; Woll, A. Does physical self-concept mediate the relationship between motor abilities and physical activity in adolescents and young adults? PLoS ONE 2017, 12, 1–18. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  27. Brown, D.M.Y.; Cairney, J. The synergistic effect of poor motor coordination, gender and age on self-concept in children: A longitudinal analysis. Res. Dev. Disabil. 2020, 98, 103576. [Google Scholar] [CrossRef]
  28. Klomsten, A.T.; Skaalvik, E.M.; Espnes, G.A. Physical self-concept and sports: Do gender differences still exist? Sex Roles 2004, 50, 119–127. [Google Scholar] [CrossRef]
  29. Trautwein, U.; Gerlach, E.; Lüdtke, O. Athletic classmates, physical self-concept, and free-time physical activity: A longitudinal study of frame of reference effects. J. Educ. Psychol. 2008, 100, 988–1001. [Google Scholar] [CrossRef]
  30. Amesberger, G.; Finkenzeller, T.; Müller, E.; Würth, S. Aging-related changes in the relationship between the physical self-concept and the physical fitness in elderly individuals. Scand. J. Med. Sci. Sports 2019, 29, 26–34. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  31. Finkenzeller, T.; Pötzelsberger, B.; Kösters, A.; Würth, S.; Amersberger, G.; Dela, F.; Müller, E. Aging in high functioning elderly persons: Study design and analyses of behavioral and psychological factors. Scand. J. Med. Sci. Sports 2019, 29, 7–16. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  32. Esnaola, I. El autoconcepto físico durante el ciclo vital. Ann. Psychol. 2008, 24, 1–8. [Google Scholar]
  33. Infante, G.; Goñi, A.; Villarroel, J.D. Actividad física y autoconcepto, físico y general, a lo largo de la edad adulta. Rev. Psicol. Deporte 2011, 20, 429–444. [Google Scholar] [CrossRef] [Green Version]
  34. Molero, D.; Zagalaz-Sánchez, M.L.; Cachón-Zagalaz, J. Estudio comparativo del autoconcepto físico a lo largo del ciclo vital. Rev. Psicol. Deporte 2013, 22, 135–142. [Google Scholar]
  35. Putnick, D.L.; Hahn, C.S.; Hendricks, C.; Bornstein, M.H. Developmental stability of scholastic, social, athletic, and physical appearance self-concepts from preschool to early adulthood. J. Child Psychol. Psyc. 2020, 61, 95–103. [Google Scholar] [CrossRef] [PubMed]
  36. Clancy, R.B.; Herring, M.P.; Campbell, M.J. Motivation measures in sport: A critical review and bibliometric análisis. Front. Psychol. 2017, 8, 348. [Google Scholar] [CrossRef] [Green Version]
  37. Bauman, A.E.; Reis, R.S.; Sallis, J.F.; Wells, J.C.; Loos, R.J.F.; Martin, B.W. Correlates of physical activity: Why are some people physically active and others not? Lancet 2012, 380, 258–271. [Google Scholar] [CrossRef]
  38. Derakhshanrad, S.A.; Piven, E.; Ghoochani, B.Z. A cross-sectional study to investigate motivation for physical activity in a sample of Iranian community-dwelling older adults. Health Promot. Perspect. 2020, 10, 135–141. [Google Scholar] [CrossRef] [Green Version]
  39. Lee, S.; Lee, C.; An, J. Psycho-social correlates of leisure-time physical activity (LTPA) among older adults: A multivariate analysis. Eur. Rev. Aging. Phys. Act. 2020, 17, 1–7. [Google Scholar] [CrossRef]
  40. Tang, M.; Wang, D.; Guerrien, A. A systematic review and meta-analysis on basic psychological need satisfaction, motivation, and well-being in later life: Contributions of self-determination theory. PsyCh J. 2020, 9, 5–33. [Google Scholar] [CrossRef]
  41. Lea, R.G.; Qualter, P.; Davis, S.K.; Pérez-González, J.C.; Bangee, M. Trait emotional intelligence and attentional bias for positive emotion: An eye tracking study. Pers. Indiv. Differ. 2018, 128, 88–93. [Google Scholar] [CrossRef]
  42. Szczygieł, D.; Mikolajczak, M. Why are people high in emotional intelligence happier? They make the most of their positive emotions. Pers. Indiv. Differ. 2017, 117, 177–181. [Google Scholar] [CrossRef]
  43. Petrides, K.V.; Pita, R.; Kokkinaki, F. The location of trait emotional intelligence in personality factor space. Br. J. Psychol. 2007, 98, 273–289. [Google Scholar] [CrossRef] [Green Version]
  44. Fiorilli, C.; Farina, E.; Buonomo, I.; Costa, S.; Romano, L.; Larcan, R.; Petrides, K.V. Trait Emotional Intelligence and School Burnout: The Mediating Role of Resilience and Academic Anxiety in High School. Int. J. Environ. Res. Public Health 2020, 17, 3058. [Google Scholar] [CrossRef] [PubMed]
  45. Cheshire, M.H.; Strickland, H.P.; Ewell, P.J. Measured emotional intelligence in Baccalaureate Nursing Education: A longitudinal study. Nurs. Educ. Perspect. 2020, 41, 103–105. [Google Scholar] [CrossRef] [PubMed]
  46. Dave, H.P.; Keefer, K.V.; Snetsinger, S.W.; Holden, R.R.; Parker, J.D.A. Stability and change in trait emotional intelligence in emerging adulthood: A four-year population-based study. J. Pers. Assess. 2021, 103, 57–66. [Google Scholar] [CrossRef] [PubMed]
  47. Foster, K.; Fethney, J.; McKenzie, H.; Fischer, M.; Harkness, E.; Kozlowski, D. Emotional intelligence increases over time: A longitudinal study of Australian pre-registration nursing students. Nurs. Educ. Today 2017, 55, 65–70. [Google Scholar] [CrossRef] [PubMed]
  48. Meléndez, J.C.; Delhom, I.; Satorres, E. The power of emotional intelligence on older adults’ resilience. Ansiedad y Estrés 2019, 25, 14–19. [Google Scholar] [CrossRef]
  49. Fantini-Hauwel, C.; Mikolajczak, M. Factor structure, evolution, and predictive power of emotional competencies on physical and emotional health in the elderly. J. Aging. Health 2014, 26, 993–1014. [Google Scholar] [CrossRef] [Green Version]
  50. Navarro-Bravo, B.; Latorre, J.M.; Jiménez, A.; Cabello, R.; Fernández-Berrocal, P. Ability emotional intelligence in young people and older adults with and without depressive symptoms, considering gender and educational level. PeerJ 2019, 7, 6596. [Google Scholar] [CrossRef]
  51. Martín-Albo, J.; Núñez, J.L.; Domínguez, E.; León, J.; Tomás, J.M. Relationships between intrinsic motivation, physical self-concept and satisfaction with life: A longitudinal study. J. Sports Sci. 2012, 30, 337–347. [Google Scholar] [CrossRef]
  52. Padial-Ruz, R.; Pérez-Turpin, J.A.; Cepero-González, M.; Zurita-Ortega, F. Effects of physical self-concept, emotional isolation, and family functioning on attitudes towards physical education in adolescents: Structural equation analysis. Int. J. Environ. Res. Public Health 2020, 17, 94. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  53. Fraguela-Vale, R.; Varela-Garrote, L.; Carretero-García, M.; Peralbo-Rubio, E.M. Basic psychological needs, physical self-concept, and physical activity among adolescents: Autonomy in focus. Front. Psychol. 2020, 11, 491. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  54. Ramirez-Granizo, I.; Sánchez-Zafra, M.; Zurita-Ortega, F.; Puertas-Molero, P.; González-Valero, G.; Ubago-Jiménez, J.L. Multidimensional self-concept depending on levels of resilience and the motivational climate directed towards sport in schoolchildren. Int. J. Environ. Res. Public Health 2020, 17, 534. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  55. Laborde, S.; Dosseville, F.; Allen, M.S. Emotional intelligence in sport and exercise: A systematic review. Scand. J. Med. Sci. Sports 2016, 26, 862–874. [Google Scholar] [CrossRef] [PubMed]
  56. Ubago-Jiménez, J.L.; González-Valero, G.; Puertas-Molero, P.; García-Martínez, I. Development of emotional intelligence through physical activity and sport practice. Behav. Sci. 2019, 9, 44. [Google Scholar] [CrossRef] [Green Version]
  57. Amado-Alonso, D.; León-del-Barco, B.; Mendo-Lázaro, S.; Sánchez-Miguel, P.A.; Iglesias Gallego, D. Emotional Intelligence and the Practice of Organized Physical-Sport Activity in Children. Sustainability 2019, 11, 1615. [Google Scholar] [CrossRef] [Green Version]
  58. Lamonte, M.J.; Buchner, D.M.; Rillamas-Sun, E.; Di, C.; Evenson, K.R.; Bellettiere, J.; Lewis, C.E.; Lee, I.; Tinker, L.F.; Seguin, R.; et al. Accelerometer-measured physical activity and mortality in women aged 63 to 99. J. Am. Geriatr. Soc. 2018, 66, 886–894. [Google Scholar] [CrossRef] [PubMed]
  59. World Health Organization. WHO Guidelines on Physical Activity and Sedentary Behaviour; World Health Organization: Geneva, Switzerland, 2020. [Google Scholar]
  60. Goñi, A.; Ruiz, S.; Liberal, I. Propiedades psicométricas de un nuevo cuestionario para la medida del autoconcepto físico. Rev. Psicol. Deporte 2004, 13, 195–213. [Google Scholar]
  61. Pelletier, L.; Tuson, K.M.; Fortier, M.; Vallerand, R.J. Toward a new measure of intrinsic motivation, extrinsic motivation, and amotivation in sports: The Sport Motivation Scale (SMS). J. Sport Exerc. Psy. 1995, 17, 35–53. [Google Scholar] [CrossRef] [Green Version]
  62. Balanguer, I.; Castillo, I.; Duda, J.L. Propiedades psicométricas de la escala de motivación deportiva en deportistas españoles. Rev. Mex. Psicol. 2007, 24, 197–207. [Google Scholar] [CrossRef]
  63. Salovey, P.; Mayer, J.D.; Goldman, S.L.; Turvey, C.; Palfai, T.P. Emotional attention, clarity, and repair: Exploring emotional intelligence using the Trait Meta-Mood Scale. In Emotion, Disclosure, and Health; Pennebaker, J.W., Ed.; American Psychological Association: Washington, DC, USA, 1995; pp. 125–154. [Google Scholar] [CrossRef]
  64. Fernandez-Berrocal, P.; Extremera, N.; Ramos, N. Validity and reliability of the spanish modified version of the trait meta-mood scale. Psychol. Rep. 2004, 94, 751–755. [Google Scholar] [CrossRef] [PubMed]
  65. Marsh, H.W. Age and gender effects in physical self-concepts for adolescent elite athletes and nonathletes: A multicohort-multioccasion. J. Sport Exerc. Psychol. 1998, 20, 237–259. [Google Scholar] [CrossRef]
  66. Martin, A.J.; Liem, G.A.; Coffey, L.; Martínez, C.; Parker, P.P.; Marsh, H.W.; Jackson, S.A. What happens to physical activity behavior, motivation, self-concept, and flow after completing school? A longitudinal study. J. Appl. Sport Psychol. 2010, 22, 437–457. [Google Scholar] [CrossRef]
  67. Clark, B.C. Neuromuscular changes with aging and sarcopenia. J. Frailty Aging 2019, 8, 7–9. [Google Scholar] [CrossRef]
  68. Larsson, L.; Degens, H.; Li, M.; Salviati, L.; Lee, Y.; Thompson, W.; Kirkland, J.L.; Sandri, M. Sarcopenia: Aging-related loss of muscle mass and function. Physiol. Rev. 2019, 99, 427–511. [Google Scholar] [CrossRef] [PubMed]
  69. Schwaba, T.; Bleidorn, W. Personality trait development across the transition to retirement. J. Pers. Soc. Psychol. 2019, 116, 651–665. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  70. Alemany-Arrebola, I.; Cortijo-Cantos, A.; Granda-Vera, J. La cultura, la edad y el sexo como mediadores del autoconcepto físico. Rev. Int. de Med. y Cienc. de la Act. Física y del Deporte 2020, 20, 353–368. [Google Scholar] [CrossRef]
  71. Li, G.S.F.; Lu, F.J.H.; Wang, A.H.H. Exploring the relationships of physical activity, emotional intelligence and health in Taiwan college students. J. Exerc. Sci. Fit. 2009, 7, 55–63. [Google Scholar] [CrossRef] [Green Version]
  72. Zysberg, L.; Hemmel, R. Emotional Intelligence and Physical Activity. J. Phys. Act. Health 2017, 15, 53–56. [Google Scholar] [CrossRef]
  73. Castro-Sánchez, M.; Zurita-Ortega, F.; Chacón-Cuberos, R.; López-Gutiérrez, C.J.; Zafra-Santos, E. Emotional intelligence, motivational climate and levels of anxiety in athletes from different categories of sports: Analysis through structural equations. Int. J. Environ. Res. Public Health 2018, 15, 894. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  74. Tsaousis, I.; Smaragda, K. Factorial invariance and latent mean differences of scores on trait emotional intelligence across gender and age. Pers. Indiv. Differ. 2013, 54, 169–173. [Google Scholar] [CrossRef]
  75. Clevinger, K.; Petrie, T.; Martin, S.; Greenleaf, C. The relationship of sport involvement and gender to physical fitness, self-efficacy, and self-concept in middle school students. Phys. Educ. 2020, 77, 9228. [Google Scholar] [CrossRef]
  76. Kay, A.B.; Wilson, E.L.; White, T.W.; Morris, D.S.; Majercik, S. Age is just a number: A look at “elderly” sport-related traumatic injuries at a level I trauma center. Am. J. Surg. 2019, 217, 1121–1125. [Google Scholar] [CrossRef] [PubMed]
  77. Chacón-Cuberos, R.; Zurita-Ortega, F.; García-Mármol, E.; Castro-Sánchez, M. Multidimensional self-concept depending on sport practice in university students of Physical Education from Andalucía. Retos 2020, 37, 174–180. [Google Scholar]
Figure 1. Trajectory of PSC, PC and SC with age.
Figure 1. Trajectory of PSC, PC and SC with age.
Ijerph 18 01711 g001
Figure 2. Association between PSC and sports initiation stage by age groups. **** Significatively at level 0.001. • Outliers.
Figure 2. Association between PSC and sports initiation stage by age groups. **** Significatively at level 0.001. • Outliers.
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Figure 3. Relationship between PSC and number of sports practiced by age groups. **** Significatively at level 0.001. • Outliers.
Figure 3. Relationship between PSC and number of sports practiced by age groups. **** Significatively at level 0.001. • Outliers.
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Table 1. Sample characteristics classified by age range and gender.
Table 1. Sample characteristics classified by age range and gender.
n = 52041–50 (n = 116)51–60 (n = 225)61–70 (n = 135)71–80 (n = 44)
MWpsex *MWpsex*MWpsex *MWpsex *pgroup **
Age (years)M45.5845.500.95255.6955.290.46163.2163.390.68873.8671.810.0070.001
Height (m)M1.771.640.0011.741.600.0011.731.600.0011.701.580.0010.004
Weight (kg)M82.6962.80.00181.4662.520.00179.6967.10.00175.7869.090.1000.149
BMI (kg/m2)M26.3123.300.00126.7224.520.00126.6926.000.17526.2327.710.5370.002
Note: M (man), W (woman). * U Mann–Whitney, ** Kruskal Wallis; IQM: “Inter Quartile Range”.
Table 2. Sporting habits classified by age.
Table 2. Sporting habits classified by age.
n%n%n%n%pV Cramer
Sports initiation 0.0010.171
Not practice00.00135.7864.44715.91--
PA level 0.0010.219
Not active76.034520.002216.301329.55--
Number of sports practiced 0.0010.188
3 or more6455.177734.225641.481125.00--
Table 3. Results of the PSC, TMMS-24 and SMS questionnaires and association with age.
Table 3. Results of the PSC, TMMS-24 and SMS questionnaires and association with age.
Variable41–5051–6061–7071–80Levene’s TestMeans’s TestEffect Size
M(SD)M(SD)M(SD)M(SD)FpX2pη2IC 95%
PSC-QPSC15.81(2.97)15.51(3.40)15.45(3.24)14.22(3.01)0.7750.5089.5710.0220.02(0.00, 0.04)
PC17.25(3.80)15.94(4.21)16.80(4.07)15.13(4.42)1.1170.34113.3260.0010.03(0.00, 005)
AT21.93(5.05)22.31(4.72)22.82(4.79)22.04(3.71)2.2250.0842.9550.3980.00(0.00, 0.01)
SC16.13(3.43)15.00(3.80)15.40(3.81)13.59(4.40)2.2390.08416.3440.0010.03(0.01, 005)
ST14.25(2.76)14.12(3.08)14.10(3.38)13.79(3.23)1.2650.2851.3000.2790.00(0.00, 0.00)
TMMS24EA23.99(6.86)23.96(6.88)23.00(6.66)23.20(7.66)0.4760.6982.3430.5040.00(0.00, 0.00)
EU26.19(6.88)27.57(6.46)26.52(5.73)25.54(6.09)1.8780.1324.4850.2130.01(0.00, 0.03)
ER28.12(6.10)28.67(6.48)27.34(6.44)27.45(6.58)0.7290.5354.2450.2360.01(0.00, 002)
SMSIM5.71(1.09)5.48(1.42)5.24(1.47)4.39(1.79)4.8030.0025.9990.0010.06(0.02, 0.09)
EM3.82(1.08)3.89(1.19)3.76(1.35)3.72(1.42)8.6470.0340.6870.5290.04(0.01, 0.07)
NM2.15(1.13)2.08(1.08)2.45(1.24)2.88(1.47)3.6920.0115.7170.0010.04(0.01, 0.07)
Note: PSC (physical self-concept), PC (physical condition), AT (physical attractiveness), SC (sports competence), ST (strength), EA (emotional attention), EU (emotional understanding), ER (emotional regulation), IM (intrinsic motivation), EM (extrinsic motivation), NM (demotivation).
Table 4. Bivariate correlations between the dimensions of the PSC-Q, TMMS and EMD questionnaires.
Table 4. Bivariate correlations between the dimensions of the PSC-Q, TMMS and EMD questionnaires.
(0.47, 0.60)
(0.52, 0.63)(0.54, 0.65)
AT0.56**0.57**0.49 1
(0.50, 0.63)(0.51, 0.63)(0.43, 0.56)
(0.45, 0.57)(0.58, 0.69)(0.65, 0.74)(0.55, 0.65)
EA0.02 0.06 0.02 0.01 0.06 1
(−0.06, 0.11)(−0.03, 0.15)(−0.07, 0.11)(−0.08, 0.09)(−0.03, 0.15)
(0.07, 0.24)(0.10, 0.27)(0.08, 0.24)(0.02, 0.19)(0.08, 0.24)(0.25, 0.40)
(0.23, 0.38)(0.22, 0.38)(0.21, 0.36)(0.17, 0.33)(0.23, 0.38)(0.13, 0.29)(0.41, 0.54)
(0.30, 0.45)(0.28, 0.43)(0.48, 0.60)(0.18, 0.34)(0.38, 0.52)(0.08, 0.24)(0.21, 0.36)(0.27, 0.42)
EM0.14**0.16 0.38**0.13**0.32**0.14**0.08 0.17**0.48**1
(0.05, 0.22)(0.07, 0.24)(0.31, 0.46)(0.05, 0.21)(0.24, 0.39)(0.06, 0.22)(−0.01, 0.16)(0.08, 0.25)(0.41, 0.54)
NM−0.38**−0.26**−0.28**−0.27**−0.28**0.00 −0.25**−0.25**−0.36**0.07**
(−0.45, −0.31)(−0.34, −0.26)(0.36, −0.20)(−0.35, −0.19)(−0.36, −0,20)(0.09, 0.08)(−0.33, −0.16)(−0.33, −0.17)(−0.44, 0.29)(0.01, 0.07)
Note 1: PSC (physical self-concept), PC (physical condition), AT (physical attractiveness), SC (sports competence), ST (strength), EA (emotional attention), EU (emotional understanding), ER (emotional regulation), IM (intrinsic motivation), EM (extrinsic motivation), NM (demotivation). Note 2: ** (p ≤ 0.001), * (p ≤ 0.010).
Table 5. Correlations between PSC and the dimensions of the PSC-Q, TMMS and EMD questionnaires by age groups.
Table 5. Correlations between PSC and the dimensions of the PSC-Q, TMMS and EMD questionnaires by age groups.
Dimension41–50 Years51–60 Years61–70 Years71–80 Years
ST0.51(0.36, 0.51)0.0010.54(0.44, 0.63)0.0010.56(0.43, 0.67)0.0010.40(0.12, 0.63)0.010
SC0.58(0.44, 0,69)0.0010.62(0.53, 0.69)0.0010.57(0.45, 0.68)0.0010.20(−0.10, 0.47)0.190
AT0.50(0.35, 0.63)0.0010.580.49, 0.66)0.0010.64(0.53, 0.73)0.0010.28(−0.02, 0.53)0.060
PC0.51(0.36, 0.51)0.0010.52(0.42, 0.61)0.0010.60(0.48, 0.70)0.0010.23(−0.07, 0.49)0.140
EA−0.21(−0.38, −0.21)0.0200.05(−0.08, 0.18)0.4300.09(−0.08, 0.26)0.2800.13(−0.18, 0.41)0.420
EU0.17(−0.02, 0.17)0.0700.16(0.03, 0.28)0.0010.07(−0.10, 0.24)0.4200.22(−0.08, 0.49)0.140
ER0.26(0.08, 0.42)0.0100.37(0.25, 0.48)0.0010.22(0.06, 0.38)0.0100.30(0.01, 0.55)0.050
IM0.26(0.08, 0.42)0.0010.46(0.35, 0.56)0.0010.34(0.18, 0.48)0.0010.25(−0.05, 0.51)0.100
EM0.12(−0.02, 0.34)0.1900.21(0.08, 0.33)0.0010.06(−0.11, 0.23)0.5000.07(−0.23, 0.36) 0.650
NM−0.42(0.56, −0.25)0.001−0.39(−0.50, −0.28)0.001−0.32(−0.46, −0.32)0.001−0.34(−0.58, −0.05)0.020
Table 6. Association between PSC and sports habits by age groups.
Table 6. Association between PSC and sports habits by age groups.
Variable41–50 Years51–60 Years61–70 Years71–80 Years
Sportsinitiation0.0010.19(0.08, 0.29)0.0010.19(0.11, 0.26)0.0010.23(0.13, 0.32)0.1800.12(0.00, 0.26)
Not practice--11.623.3310.173.4912.434.20
PA levelpdICpdICpdICpdIC
0.3620.20(0.56, 0.96)0.0010.50(0.17, 0.83)0.0050.73(0.26, 1.19)0.2620.51(0.15, 1.17)
Not active15.281.9714.332.9113.543.7713.153.33
Number of sportspη2ICpη2ICpη2ICpη2IC
0.1730.02(0.00, 0.07)0.0010.17(0.09, 0.24)0.0010.24(0.13, 0.33)0.4010.10(0.00, 0.22)
3 or more16.122.7516.612.5516.982.3914.732.45
0.5310.01(0.00, 0.03)0.5430.19(0.00, 0.01)0.9140.00(0.00, 0.01)0.6660.02(0.00, 0.10)
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MDPI and ACS Style

Conde-Pipó, J.; Melguizo-Ibáñez, E.; Mariscal-Arcas, M.; Zurita-Ortega, F.; Ubago-Jiménez, J.L.; Ramírez-Granizo, I.; González-Valero, G. Physical Self-Concept Changes in Adults and Older Adults: Influence of Emotional Intelligence, Intrinsic Motivation and Sports Habits. Int. J. Environ. Res. Public Health 2021, 18, 1711.

AMA Style

Conde-Pipó J, Melguizo-Ibáñez E, Mariscal-Arcas M, Zurita-Ortega F, Ubago-Jiménez JL, Ramírez-Granizo I, González-Valero G. Physical Self-Concept Changes in Adults and Older Adults: Influence of Emotional Intelligence, Intrinsic Motivation and Sports Habits. International Journal of Environmental Research and Public Health. 2021; 18(4):1711.

Chicago/Turabian Style

Conde-Pipó, Javier, Eduardo Melguizo-Ibáñez, Miguel Mariscal-Arcas, Félix Zurita-Ortega, Jose Luis Ubago-Jiménez, Irwin Ramírez-Granizo, and Gabriel González-Valero. 2021. "Physical Self-Concept Changes in Adults and Older Adults: Influence of Emotional Intelligence, Intrinsic Motivation and Sports Habits" International Journal of Environmental Research and Public Health 18, no. 4: 1711.

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