Connections among physical activity,motivation,and depressive symptoms in adolescent girls

Abstract

Adolescence can be a difficult period of life characterised, among many other things, by a significant increase in depressive symptoms among girls. Recent studies have suggested that sedentary habits and self-determined motivation can be associated with depressive symptoms. The main goal of the present study was to examine the associations between physical activity levels, sedentary behaviours, and self-determined motivation and depressive symptoms in girls during adolescence. A total of 714 adolescent girls (16.53 ± 1.01 years) agreed to participate in the study. They completed a questionnaire including the scale of depressive symptoms, the International Physical Activity Questionnaire, and the Situational Motivation Scale. Participants’ smoking habits and body mass index were also assessed. Results showed that those adolescents who performed physical activity of moderate (odds ratio (OR): 0.55; 95% confidence interval (CI): 0.31, 0.99) or high intensity level (OR: 0.22; 95% CI: 0.10, 0.21) had a significantly lower probability of suffering from depressive symptoms. Accordingly, the most sedentary group had a higher probability of suffering from depressive symptoms (OR: 4.90; 95% CI: 2.00, 11.54). Vigorous self-determined motivation was also a significant predictor of the lowest levels of depressive symptoms. In conclusion, results seemed to indicate that educators should promote the most self-determined types of motivation and physical activity habits in their students if they want to help prevent depressive symptoms.

Keywords

Depressive symptoms physical activity sedentary habits self-determination women

Introduction

Adolescence can be a very difficult period of life characterised by, among many other things, a significant increase in depressive symptoms (Morgan et al., 2013). A recent review has pointed out that the prevalence of depression among adolescents and young adults has increased in recent years (Mojtabai et al., 2016). This increase has been even more prominent among girls (Angold et al., 2002). To make things worse, most of the adolescents at high risk of depression do not attend specialised mental health services (Sayal et al., 2014). Depressive symptoms have been connected to negative consequences such as functional deficiencies (Lyness et al., 2007) and social disorders (Yayanthi et al., 2015). Adolescents are often exposed to daily life stress (i.e. school, family, friends, work) and many individuals are not aware of their condition. Some adolescents develop major health problems such as depression, which some research links to suicide (American Psychological Association, 2016; Beardslee and Knitzer, 2004).

There is ample evidence of the benefits derived from regular leisure-time physical activity during adolescence (Warburton et al., 2007), which indicates that healthy lifestyle habits should be promoted among youngsters. Moreover, there is a growing body of research on the association between physical activity and depression (Adamson et al., 2015; Cecchini et al., 2017; Cecchini-Estrada et al., 2015; Patrick and Williams, 2012). However, research is scarce in adolescents, and results have been inconsistent (Dale et al., 2019; Sabiston et al., 2013; Stavrakakis et al., 2013). Raudsepp and Neissaar (2012), in a study conducted with adolescent girls (12–13 years), found that increased physical activity was inversely associated with the initial state and the negative changes in depressive symptoms, and both associations were totally independent of the individuals’ body mass index. In a recent review and meta-analysis of randomised controlled trials, Bailey et al. (2016) concluded that physical activity seems to be an encouraging element for adolescents with depression, but they concluded that more robust research is needed. Moreover, Sabiston et al. (2013) highlighted the need to examine the intensity and type of physical activity to understand the connection with depressive symptoms in adolescents. Recently, there has been a call for more research and moderator analyses to determine the type of physical activity that may produce better mental health outcomes for youth (Dale et al., 2019).

Self-determination theory has been a major framework for understanding human behaviour (Deci and Ryan, 1985). The major types of behavioural regulations have been positioned along a continuum ranging from intrinsic to extrinsic motivation and amotivation (Vallerand, 2001). Intrinsic motivation is the willingness to perform an activity for the interest, gratification, and pleasure that the activity provides to the individual. Extrinsic motivation is the disposition to perform an activity for the external rewards that it can provide. From higher to lower levels of self-determination, it can be classified in four different types (Vallerand, 2001): (a) integrated: perform an activity because it is consistent with the individual’s standard of living; (b) identified: perform an activity showing inner perceptions of causality; (c) introjected: perform an activity to avoid feelings of culpability and strengthen personal ego; and (d) external: perform an activity to obtain a compensation or avoid a penalty. Finally, amotivation is the lack of motivation for doing an activity. Within this theory, three basic psychological needs have been considered fundamental for ‘optimal motivated behaviour and psychological well-being’ (Vlachopoulos et al., 2011: 264): (a) autonomy: seeing one’s behaviour as self-endorsed; (b) competence: feelings of operative interaction with the context; and (c) relatedness: feelings of effective association with others (Niemec and Ryan, 2009). Over the past 15 years, a growing body of research has showed interest in the connection between self-determination theory of motivation and health. The results of these studies have shown the positive impact of autonomy support and self-regulation (self-determined motivation) on a variety of mental and physical health problems, including depression (Patrick and Williams, 2012) and depressive symptoms (Cecchini et al., 2017; Cecchini-Estrada et al., 2015). Nevertheless, more research is needed to understand the connection between the different types of motivation and these negative health problems in adolescent girls.

The main goal of this study was to examine the associations between physical activity levels, sedentary behaviours, and self-determined motivation and depressive symptoms in girls during adolescence (aged 15–18). A second goal was to assess the association between adolescents’ self-determined motivation and their depressive symptoms. The first hypothesis was that there will be a negative connection between physical activity levels and depressive symptoms. The second hypothesis was that there will be a negative link between autonomous regulation and depressive symptoms.

Method

Participants

A total of 714 adolescent girls (aged 15–18; mean 16.53 ± 1.01 years) agreed to participate in the study. They were enrolled in different secondary schools located in northern Spain. An informed written consent form was signed by all participants or their parents/tutors. The research design complied with the Declaration of Helsinki, and the protocols were approved by the ethics committee of the researchers’ university. Participants were informed that they could withdraw from the study at any time, and that their responses were going to be treated confidentially. They were asked to answer honestly when completing different questionnaires, and informed that their responses would not affect their school grades.

Instruments

Depressive symptoms

Depressive symptoms were assessed using the six-item scale of depressive symptoms validated by Kandel and Davies (1982). The psychometric properties of this instrument have been reviewed (Sabiston et al., 2013). In the present study, the Cronbach’s alpha obtained was .72, which can be considered satisfactory (Vincent, 2005). Following Hambleton et al. (2005), every item of the scale was translated into Spanish by a professional, and then again into English to examine its correspondence with the original. Participants answered the question: ‘During the past 12 months, how often have you…’ in a four-point Likert scale ranging from one: ‘never’ to four: ‘often’ (e.g. ‘felt too tired to do things’). Self-reported depressive symptoms are considered the strongest predictive measure for the appearance of major depressive disorders in youngsters (Kovacs and Lopez-Duran, 2010). Therefore, it is considered a reliable instrument. To provide a depressive symptomatology mark, all responses were added. Following Choi et al. (1971) the score was increased in 10 points, to produce a range between 16 and 34 points, and the results were used to provide participants’ depressive symptomatology. Choi et al. (1997: 43) considered ‘adolescents who achieve a score of 29 or greater as having notable depressive symptoms’. Therefore, the same cutoff score was used in this study.

The International Physical Activity Questionnaire

The International Physical Activity Questionnaire (IPAQ) (Booth, 2000) was designed to measure physical activity and inactivity at a cross-national level. The IPAQ has shown reasonable measurement properties for the analysis of physical activity levels of individuals between 15 and 65 years of age (Hagstro¨mer et al., 2006). In this study, the short version ‘seven-day recall’ was used (Craig et al., 2003). The Spanish validated version was obtained from www.ipaq.ki.se. It provides information on the time the individual spends in three physical activity intensity levels (walking, moderate, and vigorous), and in sedentary activities. The Metabolic Equivalent of Task (MET) was used to indicate physical activity intensity. It represents 3.5 mlO₂/kg.min^–1 (energy needed for the basal metabolic rate), and it was grouped in three levels: (a) light (< 3 METs); (b) moderate (3–5.9 METs); and (c) high (> 6 METs) (Ainsworth et al., 2000). MET-minutes were calculated by multiplying the number of Met-minutes/week (minutes performing physical activity at a certain intensity level). Finally, MET-minute/week was also calculated for data analyses.

The Situational Motivation Scale

The Spanish validated version (Martin-Albó et al., 2009) of the Situational Motivation Scale (SIMS) (Guay et al., 2000) was used in the present study. It was designed to assess situational (state) motivation towards an activity. Participants answered the question: ‘Why are you engaged in physical activity’ to each one of the three intensity levels measured by the IPAQ: walking, moderate, and vigorous, independently. The instrument measured intrinsic motivation (i.e. ‘Because I think that this activity is interesting’), identified regulation (i.e. ‘Because I am doing it for my own good’), external regulation (i.e. ‘Because I am supposed to do it’), and amotivation (i.e. ‘There may be good reasons to do this activity, but personally I don’t see any’). Each one of these subscales contained four items. Every item was rated on a seven-point Likert scale from one (does not correspond at all) to seven (corresponds exactly). Since the subscales of the SIMS assess types of motivation of the entire range of the self-determination continuum, a self-determined index (SDI) can be calculated (Lonsdale et al., 2009). Some criticisms have been raised about how this index has been calculated (Chemolli and Gagné, 2014; Ünlü, 2016); therefore, in this study, following Lemyre et al. (2006), the SDI was obtained by multiplying each subscale by a factor that represents the position of each construct on the previously mentioned self-determination continuum (SDI = 2 * intrinsic motivation + identified regulation – external regulation – 2 * amotivation). Based on the participants’ responses to each of the three intensity levels measured using the IPAQ (walking, moderate, and vigorous), and following procedures previously and successfully tested (Cecchini et al., 2017: 604): ‘Three independent SDIs were calculated (SDIWalking, SDIModerate, and SDIVigorous) to try to explain why people are currently engaged in one type of physical activity (walking, moderate PA [physical activity], and vigorous PA). High scores meant high levels of autonomous motivation’. The goal was to assess participants’ self-determined motivation towards three different levels of physical activity: vigorous, moderate, and walking.

Anthropometry

Following standardised recommendations (Kushner et al., 1996), participants were measured twice with a five-minute interval between scores. Weight and body mass index were obtained using a calibrated digital scale (SECA Model 861; Vogel and Halke, Hamburg, Germany, precision = 100g, range = 0–150kg). Students wore no shoes when measured. Height was evaluated using a wall-mounted stadiometer (SECA Model 222; Vogel and Halke, Hamburg, Germany, precision = 0.1cm, range = 6–230cm): children stood straight against the wall with no shoes on to align the spine with the instrument; the head was positioned with the chin parallel to the floor. The mean of the two measurements of weight and height was used to calculate each participant’s body mass index: weight in kilograms divided by the square of the height in metres (BMI: kg / m²). Again, following standardised recommendations (Dinsdale et al., 2011: 3), scores obtained were used to classify participants according to ‘a specific z score, or centile, on a child growth reference’. In this case, the Spanish population 0–18 years described in the Bilbao study was used (Fernandez et al., 2011).

Smoking habits

Participants’ smoking habits were assessed through a question included in the final questionnaire used. A dichotomous response (yes/no) was selected to obtain the information.

Statistical analyses

First, descriptive statistics were obtained from all the variables under study: means, standard deviation, and percentages where needed. Second, binary logistic regression analyses were performed to examine the associations of MET-minutes/week and sedentary time with depressive symptoms. The results are presented adjusted by age, smoking, and body mass index (Model 1) and fully fitted (age, smoking, body mass index, and SDI; Model 2), and they are reported as odds ratio (OR) with 95% confidence intervals (CI), and the p value for the linear trend.

Results

Participants’ characteristics

Most of the participants (82.8%) had a normal body mass index (M = 23.01, SD = 9.73), but 17.2% were considered obese or overweight. Notable depressive symptoms were present in 15.7% of the participants (no significant difference was found based on age). 21.4% of them were considered obese or overweight (only 15.3% among individuals not having notable depressive symptoms), 32.1% were smokers, they had lower MET scores in all the different categories (vigorous, moderate, walking), and in SDI vigorous, moderate, and sedentary. At the bivariate level, participants with this symptomatology showed statistically significant differences in the previously mentioned demographic and behavioural characteristics compared with those who reported no significant depressive symptoms (Table 1).

Table 1.

Participants’ demographic, behavioural and health characteristics.

	Global(n = 714)	Depressive symptoms*(n = 112)	No depressive symptoms(n = 602)	p**
Age
15	169 (23.7)	20 (17.9)	149 (24.8)
16	172 (24.1)	25 (22.3)	147 (24.4)
17	199 (27.9)	32 (28.6)	167 (27.7)
18	174 (24.4)	35 (31.3)	139 (23.1)	.20
Smoking
Yes	166 (23.2)	36 (32.1)	130 (21.6)	.03
Body mass index^a
Normal	591 (82.8)	87 (77.7)	504 (83.7)
Overweight	107 (15.0)	20 (17.9)	87 (14.5)
Obese	16 (2.2)	5 (4.5)	11 (1.8)	.13
METs^b
Vigorous	1666.76 (1893.94)	725.01 (1095.24)	1839.40 (1958.26)	<.001
Moderate	356.72 (635.35)	224.28 (364.24)	381.36 (671.20)	<.001
Walking	1119.72 (1257.59)	892.03 (1051.61)	1162.08 (1288.63)	.02
Total	3148.80 (2544.90)	1854.15 (1789.56)	3386.15 (2592.08)	<.001
SDI
Vigorous	11.54 (3.84)	9.50 (3.99)	11.80 (3.75)	<.001
Moderate	10.12 (4.61)	8.78 (4.38)	10.32 (4.62)	.03
Walking	5.41 (5.59)	4.65 (5.20)	5.55 (5.65)	.11
Sedentary	7.17 (2.91)	8.39 (3.17)	6.91 (2.79)	<.001

Note. N (%) or mean (SD).

MET: Metabolic Equivalent of Task

* Students who achieved a score of 29 or higher were defined as having notable depressive symptoms.

**p difference between participants with and without depressive symptoms (in weighted analyses with linearised variance estimation).

^a Normal < 25 kg.m^–2; Overweight = 25–29.9 kg.m^–2; Obese ≥ 30 kg.m^–2).

^b Vigorous MET-minutes/week = 8.0; moderate MET-minutes/week = 4.0; walking MET-minutes/week = 3.3; total = walking + moderate + vigorous MET-minutes/week.

Associations between MET-minutes/week and depressive symptoms

Both Model 1 and Model 2 showed significant linear trends in depressive symptoms among the different levels of MET-minutes/week (Table 2). In the fully adjusted model, the association was significant: participants at level three of MET-minutes/week (high) were 4.5 times less likely to report from depressive symptoms than participants at level one (low). Similarly, SDIVigorous was a significant predictor of lower levels of depressive symptoms.

Table 2.

Adjusted odds of depressive symptoms across MET-minutes/week and sedentary time.

	Model 1^a			Model 2^b
	Depressive symptoms			Depressive symptoms
	No	Yes	OR (95% CI)	No	Yes	OR (95% CI)
MET-minutes/week
1 Low	54	30	1.00	54	30	1.00
2 Moderate	260	64	.43 (.25, .73)**	260	64	.55 (.31, .99)*
3 High	286	18	.12 (.06, .24)***	286	18	.22 (.10, .21)***
Age
15			1.00			1.00
16			1.13 (.59, 2.18)			1.09 (.56, 2.11)
17			1.29 (.69, 2.64)			1.24 (.66, 2.33)
18			1.42 (.76, 2.65)			1.47 (.78, 2.74)
Smoking
Yes			1.49 (.94, 2.37)			1.45 (.90, 2.33)
Body mass index^b
Normal			1.00			1.00
Overweight			1.28 (.72, 2.26)			1,27 (.71, 2.47)
Obese			2.13 (.69, 6.55)			2.23 (.70, 7.01)
SDI
Vigorous			–			.95 (.91, .99)*
Moderate			–			.99 (.96, 1.04)
Walking			–			.97 (.93, 1.01)
P			p < .001			p < .01

MET: Metabolic Equivalent of Task; OD: odds ratio; CI: confidence interval; Low: lowest level of physical activity (individuals who did not meet criteria for categories 2 or 3 were considered low/inactive). Moderate: minimum of at least 600 MET-min/week. High: minimum of 3000 MET-min/week

^a Model 1: odds ratios were adjusted for age, smoking and body mass index.

^b Model 2: odds ratios were adjusted for age, smoking, body mass index, vigorous self-determined index (SDI), moderate SDI, walking SDI, and sedentary time or MET-minutes/week.

*p < .05. **p < .01. ***p < .001 for association with depression.

Associations between sedentary time, SDI, and depressive symptoms

Model 1 showed a significant linear trend between sedentary time and depressive symptoms: p < .001 (Tables 2 and 3): participants who spent 11 or more hours/day performing sedentary activities were almost 5.1 times more likely to report depressive symptoms than participants who spent less than 4 hours/day. In the fully fitted model, this association was just slightly lower (4.9 times). In Model 2, SDIVigorous was also a significant predictor of lower levels of depressive symptoms.

Table 3.

Adjusted odds of depressive symptoms across sedentary time.

	Model 1^a			Model 2^b
	Depressive symptoms			Depressive symptoms
	No	Yes	OR (95% CI)	No	Yes	OR (95% CI)
Sedentary time
1 (< 4 hours/day)	76	12	1 (referent)	76	12	1 (referent)
2 (4–8 hours/day)	204	22	.69 (.32, 1.48)	204	22	.81 (.37, 1.79)
3 (8–11 hours/day)	220	52	1.52 (.76, 3.07)	220	52	1.67 (.81, 3.46)
4 (> 11 hours/day)	36	26	5.13 (2.26, 11.63)***	36	26	4.90 (2.0, 11.54)***
Age
15			1			1
16			1.51 (.78, 2.93)			1.44 (.73, 2.86)
17			1.60 (.85, 3.00)			1.45 (.76, 2.79)
18			1.85 (.99, 3.44)			1.84 (.97, 3.49)
Smoking
Yes			1.81 (1.13, 2.89)*			1.54 (.94, 2.53)
Body mass index^b
Normal			1			1
Overweight			1.24 (.70, 2.20)			1,14 (.63, 2.06)
Obese			2.84 (.93, 8.68)			2.54 (.79, 8.17)
SDI
Vigorous			–			.91 (.87, .95)***
Moderate			–			.98 (.94, 1.03)
Walking			–			.97 (.93, 1.01)
			p < .001			p < .01

OD: odds ratio; CI: Confidence Interval; Low: lowest level of physical activity; individuals who did not meet criteria for categories 2 or 3 were considered low/inactive. Moderate: minimum of at least 600 MET-min/week. High: minimum of 3000 MET-min/week.

^a Model 1: odds ratios were adjusted for age, smoking, and body mass index.

^b Model 2: odds ratios were adjusted for age, smoking, body mass index, vigorous SDI, moderate SDI, walking SDI, and sedentary time or Metabolic Equivalent of Task-minutes/week. *p < .05. **p < .01. ***p < .001 for association with depression.

Discussion

The main goal of this study was to examine the associations between physical activity levels, sedentary behaviours, and self-determined motivation and depressive symptoms in girls during adolescence (15–18 years). Results showed that participants at level three of MET-minutes/week (high physical activity levels) were 4.5 times less likely to report from depressive symptoms than participants at level one (low physical activity levels). A second goal was to assess the association between adolescents’ self-determined motivation and their depressive symptoms. Results showed that SDIVigorous was also a significant predictor of lower levels of depressive symptoms.

The first hypothesis was that there will be a negative connection between physical activity levels and depressive symptoms, and the results confirm this hypothesis. The group of adolescent girls who showed notable depressive symptoms had significantly lower MET scores in all the different categories (vigorous, moderate, walking). Moreover, a strong association between MET-minutes/week and depressive symptoms (after controlling for relevant confounding variables such as age, smoking habits, and body mass index) was found in the present study. Interestingly, a decreased probability of suffering from depressive symptoms was observed even at moderate levels of physical activity. Results from the present study also provided evidence of a positive association between sedentary time and depressive symptoms in adolescent girls (age range 15–18 years). In this case, the highest probability of suffering from depressive symptoms was observed in the group of 11 or more hours/day of sedentary time. There exists some evidence of the positive impact of physical activity on depressive symptoms in the general population (Adamson et al., 2015; Teychenne et al., 2008), in adolescents (Dale et al., 2019; Pastor et al., 2003; Skrove et al., 2013), and in college students (Cecchini et al., 2017). The same association between individuals’ sedentary time and depressive symptoms was also observed in previous studies (Ussher et al., 2007). In all participants, higher levels of physical activity (vigorous) were inversely associated with the initial state and the negative changes experienced in depressive symptoms. However, results from the present study expand the benefits of physical activity to include moderate physical activity, and even walking. Previous studies have found physical activity to be an encouraging element for adolescents with depression (Bailey et al., 2016; Nyström et al., 2015). Moreover, there has been a call for more research and moderator analyses to determine the type of physical activity that may produce better mental health outcomes for youth (Dale et al., 2019), and results from the present study showed that it is significantly associated with depressive symptoms at all intensity levels. In a recent cross-sectional study conducted on adolescents, Halliday et al. (2019) found that the strong association between mental health and physical activity did not significantly vary according to gender. It was just a matter of quantity of physical activity, and girls reported less physical activity than boys and, consequently, poorer mental health. Results from the present study showed the associations between physical activity an adolescent girls’ depressive symptoms even at low intensity levels. In the present study, the strong connection between MET-minutes/week and depressive symptoms was present, even after controlling for other relevant confounding variables such as age, smoking habits, and body mass index. Regarding body mass index, previous studies have shown that the association between physical activity and depressive symptoms was totally independent of the individuals’ body mass index (Raudsepp and Neissaar, 2012), and results from the present study have confirmed it. Therefore, physical activity (or inactivity) could be considered a stronger predictor of depressive symptoms than the individuals’ body mass index, and it should be promoted by teachers and health educators.

The second hypothesis was that there will be a negative association between autonomous regulation and depressive symptoms and results confirmed this connection. Higher SDI levels (vigorous and moderate) were significantly lower in individuals with notable depressive symptoms, while in individuals with lower SDI (walking) the depressive symptoms were significantly higher. Moreover, binary logistic regression analyses showed that SDIVigorous significantly predicted lower depressive symptoms in both tested models. High levels of SDI were associated with low levels of depression. Therefore, individuals’ degree of self-determined motivation has been associated to depressive symptoms. Previous studies have shown the positive impact of autonomy support and self-regulation (self-determined motivation) on a variety of mental and physical health problems, including depression (Patrick and Williams, 2012) and depressive symptoms (Cecchini et al., 2017, 2019; Cecchini-Estrada et al., 2015). Similarly, participants’ perceived autonomy support and autonomous motivation while enrolled in a treatment programme were powerful predictors of treatment outcome (Kaap-Deeder et al., 2014). Therefore, the results seem to indicate that self-determined motivation (self-regulation) could be a positive factor influencing depression and depressive symptoms, which is consistent with self-determination theory: when individuals’ behaviour is self-determined, the regulatory process includes choice, and when it is controlled, it includes compliance (Deci and Ryan, 2000). Consequently, physical and health educators should try to promote self-determined motivation among their adolescent students. Nevertheless, more research is needed to be able to establish a true cause and effect between this type of motivation and depressive symptoms.

To our knowledge, this study is the first one to examine the associations among physical activity, self-determined motivation, and sedentary time with depressive symptoms in adolescent girls (aged 15–18). These connections have been previously observed in only one study conducted in college students (Cecchini et al., 2017). In a large sample of university students, self-determined motivation predicted the intensity of physical activity, which, in turn, predicted depressive symptoms. The same connection has been observed in the present study, showing that individuals’ self-regulated behaviours and physical activity levels have been associated to depressive symptoms.

The main finding of this study was the strong association between MET-minutes/week (even at moderate levels) and depressive symptoms, regardless of confounding factors such as age, smoking habits, and body mass index. Primary and secondary health and physical educators should promote the most self-determined types of motivation (i.e. intrinsic motivation, identified regulation), as well as physical activity habits in their students, to avoid the development of depressive symptoms in the early stages of their life.

The study has some limitations. First, the number of participants could limit the ability to generalise the results. Similar research works should be conducted in larger samples of adolescent girls to confirm the results. Second, the study was conducted on adolescent females only. Other studies should also be conducted in adolescent males to be able to compare the results and obtain a wider view of the problem, regardless of gender. Third, the study followed a cross-sectional research design. Intervention studies should be conducted to find out if the links found in this study can be reinforced or changed. Finally, the present study cannot establish cause and effect. More research is needed to understand the different factors that contribute to individuals’ motivation, and, indirectly, to depressive symptoms.

Footnotes

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Javier Fernandez-Rio

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