Psicología Educativa -  Educational Psychology Psicología Educativa -  Educational Psychology
Psicología Educativa 20 (2014) 47-52 - Vol. 20 Núm.1 DOI: 10.1016/j.pse.2014.05.006
Academic stress as a predictor of chronic stress in university students
El estrés académico como predictor del estrés crónico en estudiantes universitarios
Blanca Elizabeth Pozos-Radilloa,??, , María de Lourdes Preciado-Serranoa, Martín Acosta-Fernándeza, María de los Ángeles Aguilera-Velascoa, Diemen Darwin Delgado-Garcíab
a University of Guadalajara, México
b Clínica Rio Blanco, Los Andes, Chile
Abstract

The aim of this study was to examine the correlation and predictive value between the Academic Stress Inventory (ASI) and the Stress Symptom Inventory (SSI) in university students and its association with age and gender in both inventories. We evaluated a representative and random sample of 527 students at a public university in 2012. A multiple regression analysis was carried out. The results showed that IEA situations that correspond to classroom intervention, mandatory work, and doing an exam predict high- level chronic stress; being a female and 18, 23, and 25 years old were associated mostly to stress. We conclude that accurate identification of stressors could help understand stress and its harmful effects on college students.

Resumen

El objetivo de este estudio fue examinar la correlación y el valor predictivo entre el Inventario de Estrés Académico (IEA) y el Inventario de Síntomas de Estrés (ISE) en estudiantes universitarios, así como su aso- ciación con la edad y género en ambos inventarios. Se evaluó una muestra representativa y aleatoria de 527 estudiantes de una universidad pública en el año 2012. Se usó análisis de regresión múltiple. Los resultados mostraron que las situaciones del IEA que corresponden a intervención en clase, trabajos obligatorios y la realización de un examen predicen un nivel elevado de estrés crónico; el género femenino y las edades de 18, 23 y 25 años se asociaron mayormente con el estrés. Se concluye que la identificación exacta de estresores podría ayudar a entender el estrés y sus efectos dañinos en estudiantes universitarios.

Keywords
Academic stress, Chronic stress, College students, Logistic regression
Palabras clave
Estrés crónico, Estrés académico, Estudiantes universitarios, Regresión logística

Stress is considered to be a physiological reaction of an organism where diverse defense mechanisms come into play in order to confront a situation which is perceived as threatening or of increased demand. Under the “cognitive-transactional model”, psychological stress according to Lazarus and Folkman (1986, p. 63) is defined as “a particular relationship between the individual and his surroundings which is judged by him to be threatening or to overwhelm his resources and which puts his well being at risk”. Specifically, facing the typical problems which may be present for students in their academic environment, stress may be a natural and necessary reaction for survival in these areas, where different factors are involved including academic overload, group projects, competitiveness, lack of technological resources, lack of supervision, or insufficient organization of time which produces what is called chronic stress. (Tapia, Guajardo, & Quintanilla, 2008)

The symptoms of academic stress result in a particularly worrisome health concern. Not only adults are at risk for stress, the demands of modern life, even during grade school, have caused the appearance of this malady more and more frequently in children and teens, in which both endogenous and exogenous demands interact to negatively influence the academic performance and achievement of the students. (e.g., Caldera, Pulido, & Martínez, 2007; Segredo, Veloso, & Rodríguez, 2004). Specialized literature indicates that academic stress has been studied in diverse university circles (Aselton, 2012; Berrío & Mazo, 2011), developing different focuses and models. One study analyzed the potential explanatory-predictive effect of daily stress on somatic symptomology of neuroticism (Santed, Sandín, Choron, & Olmedo 2000). Another study performed in Mexico by Preciado-Serrano and Vázquez-Goñi in 2010 explores the relationship between the stress profile and burnout in Mexican university students, using a statistical regression model in which the existence of a significant correlation is reported. Other studies are directly related to perception, life events and school activities (e.g., Díaz, 2010; Matheny et al., 2008; Matheny, Roque-Tovar, & Curlette, 2008; Pulido et al., 2011; Román, Ortiz, & Hernández, 2008), as well as academic strategies and school performance (e.g., Broc & Gil, 2008; Caldera et al., 2007; Díaz, 2010; Martínez, 2010; Sohail, 2013). These studies conclude that timely evaluations favor the application of efficient interventions in order to lower the stress levels, lower the associated worrisome thoughts and prevent the deterioration of performance of the students (Caldera et al., 2007).

Based on these conclusions, the objective of this study was to examine the correlation predictive value of the Academic Stress Inventory (ASI) over the Stress Symptoms Inventory (SSI) in university students, as well as their association with age and gender in both inventories.

It is appropriate to mention on one hand that in the bibliographic research no predictive studies reporting the relationship between ASI and SSI were discovered, and particularly studies related to university students. Therefore, this study is considered groundbreaking in the exploration of this relationship.

On the other hand, because the symptoms associated with stress are present in a high percentage of the population of Mexico, this study is important in order to support evidence for the transactional theory of stress and its negative manifestations in academic fields. We hope that in the near future models can be constructed to explain the role of the situations and components of academic stress in order to be able to predict the presence of chronic stress.

The present study has as its purpose to prove the following hypothesis: the ASI situations (test taking, oral presentations, classroom participation, seeking help from tutors, academic overload, overly large class size, lack of time, obligatory assignments, homework, group projects, and competition among students) are predictive of a high level of chronic stress (SSI) and are associated to age and gender of university students.

MethodSample and Procedure

A cross-sectional and analytical study was performed during the 2012 school year with university students with physical education and sports majors from a public university in Guadalajara, Mexico. Total enrollment was 976 students (63% men and 37% women) from which a simple random selection with an expected prevalence of 64.5% (Marty, Lavín, Figueroa, Larraín, & Cruz, 2005), a 70% accepted minimum frequency and with 99% precision (Lwanga & Lameshow, 1991), which produced 527 individual interviews of university students.

The selection of this university population was carried out by random and proportional numbers, taking into consideration gender and scholastic cycles. The list of students registered for the 2012 school year was used to select those who would voluntarily answer the surveys under an informed consent status. The investigative protocol and informed consent form were reviewed and approved with reference number IISO/CI/11/2012-2013 in adherence to the Helsinki Declaration of 2008 in terms of the ethics of investigation of human beings.

Measures

The Academic Stress Inventory was used (ASI; Polo, Hernández, & Pozo, 1999) validated by the Spanish Society of Anxiety and Stress. This is a questionnaire with eleven situations which were considered potential stress generators in students in the academic arena. Each one of the situations offers a scaled answer of 5 points (1 no stress, 5 high stress) where each participant gives a value according to his or her perception of whether or not it produces stress.

The eleven situations considered to be potential stress generators are: test taking (EA1), oral presentations (EA2), class participation (EA3), seeking help from tutors (EA4), academic overload (EA5), overly large class size (EA6), lack of time (EA7), obligatory assignment (EA8), homework (EA9), group projects (EA10), and competition among classmates (EA11). The reliability in terms of internal consistency corresponds to an alpha coefficient by Cronbach of .90, which is considered satisfactory. In order to establish association, the score is converted from ordinal values into a cardinal level of academic stress in the following way: if the value was 1-2 it was considered low level; a value of 3, moderate level; and between 4-5, high level.

The Stress Symptom Inventory (SSI), a questionnaire which was developed and approved by Lipp and Guevara (1994), contains a list of 42 psycho-physiological symptoms characteristic of chronic stress which is based on a three phase model developed by Selye (alarm, resistance, and exhaustion). In 1988, Dominguez adapted it for use in Mexico by means of a content validation and reported an alpha internal consistency rating by Cronbach of .94, which indicates an acceptable degree of reliability. The classification of high, moderate, and low levels of chronic stress was carried out by mean and standard deviation (SD). Furthermore, high level is considered two and three SD above mean, medium level ± 1 SD and low level stress 2 and 3 SD below mean (Pozos-Radillo, Torres, Aguilera, Acosta, & González, 2008). Variables gender and age (in five year increments) are also presented.

Data Analysis

Pearson's analysis of correlation was used to pinpoint the information about the predictive value and, in order to determine the validity of the measurements obtained, we carried out an analysis of regression by steps for the ASI and SSI by simultaneously introducing the equation of measurement to the level of significance (p < .05). In these analyses, the variables appear in order in the equation according to the percentage of the explained variance.

Afterwards, a hierarchical analysis of multiple regression was applied to determine the predictive value of the situations of the ASI in which the Introduce method was used with the ASI situations. With this procedure, an incremental value of prediction of the variable included in third place (ASI) was obtained, once the effect of the second and the first was controlled.

In order to explore the statistically significant difference of gender and age in chronic stress (SSI), as it relates to academic stress situations (ASI), the bi-variant associations were tracked through an analysis of the contingency charts. In these contingency charts the categories of the ASI and SSI (high, moderate and low) were evaluated and were transformed into dichotomies, with values of “0” or “1”; a high level rating was considered as risk. In order to carry out the association of risk calculation the Odds Ratio (OR) was estimated with a CI of 95% and a level of significance of p < .05. The data was tabulated and processed using SPSS (Statistical Package for Social Sciences), Version 15 for Windows XP, with university license.

ResultsDescriptive Statistics and Correlations

In order to carry out this study, 527 students from a public university were interviewed, of whom 311 (59%) were women and 216 (41%) men; the age range was 18-33 years with an average age of 21.07 (± 1.80) years. The descriptive analysis of the SSI, according to the levels present, showed that 35.3% (186) of the students showed a high level of chronic stress, 44.8% (236) moderate levels, and 19.9% (105) low levels. After the analysis of the situations of the ASI, 32.8% (173) showed high levels of stress when taking a test; 25.4% (134) from competitiveness among classmates; 18.6% (98) from lack of time; 18% (95) from oral presentations; 17.8% (94) from overly large class size; 17.5% (82) from seeking help from tutors; 17.1% (90) from homework; 16.7% (88) from obligatory assignments; 15.9% (84) from group projects; and 15.5% (82) from class participation, academic overload or both. The breakdown and description of this data, according to gender, is shown in Table 1; the age distribution is shown in Table 2.

Table 1.

Distribution of chronic stress levels according to the levels of academic stress situations and gender of college students at a public university, Guadalajara, Mexico, 2012.

    Chronic stress levels           
    High Gender    Medium GenderLow Gender
Academic stress    Fem  Mal  Fem  Mal  Fem  Mal 
situations  Levels  Fx  Fx  Fx  Fx  Fx  Fx 
(EA1)  High  46  26  47  24  20  10 
Realization  Medium  50  19  40  35  21  16 
test  Low  25  20  42  48  20  18 
(EA2)  High  32  10  32  10 
Exhibition  Medium  51  28  49  45  31  10 
jobs  Low  38  27  48  52  25  28 
(EA3)  High  21  19  26  11 
Intervention  Medium  41  18  46  39 
in class  Low  59  28  57  57  49  33 
(EA4)  High  30  26  21 
Attend tutorials  Medium  32  25  40  34  13  14 
  Low  59  32  63  52  42  29 
(EA5)  High  23  15  26  11 
Academic  Medium  38  21  32  31  16  12 
Overload  Low  60  29  71  65  40  30 
(EA6)  High  29  10  26  19 
Overcrowding in  Medium  38  28  26  30  16  13 
the classroom  Low  54  27  77  58  38  28 
(EA7)  High  27  12  29  19 
Lack of time  Medium  37  27  40  34  21  11 
  Low  57  26  60  54  34  28 
(EA8)  High  33  22  19 
Jobs  Medium  37  20  41  39  10  11 
mandatory  Low  51  38  66  49  45  32 
(EA9)  High  23  14  35 
Tasks  Medium  38  17  26  27  17  14 
study  Low  60  34  68  71  35  30 
(EA10)  High  28  18  22 
Work  Medium  27  29  24  10 
group  Low  66  39  78  76  44  34 
(EA11)  High  26  22  40  26  13 
Competitiveness  Medium  38  18  42  31  26  23 
between mates  Low  57  25  47  50  22  14 

Note. Post. Questionnaire data SSI and ASI, Fem = female, Mal = male.

Table 2.

Distribution of high levels of chronic stress and academic stress according to the age of college students at a public university. Guadalajara, Mexico, 2012.

High level of academic stress situationsHigh levels of chronic stress
  Age  Age 18 -21Age 22 - 25Age 26 y +
    Fx  Fx  Fx 
(EA1)  18 - 21  44  8.3  34  6.5  17  3.2 
Realization  22 - 25  28  5.3  37  7.0  13  2.5 
test  26 y + 
(EA2)  18 - 21  22  4.2  23  4.4  1.5 
Exhibition jobs  22 - 25  16  3.0  19  3.6  0.6 
  26 y +  0.2 
(EA3)  18 - 21  33  6.3  23  4.4  0.6 
Intervention in class  22 - 25  1.3  14  2.7  0.4 
  26 y + 
(EA4)  18 - 21  27  5.1  26  4.9  0.9 
Attend tutorials  22 - 25  11  2.1  20  3.8  0.4 
  26 y +  0.2 
(EA5)  18 - 21  29  5.5  22  4.2  0.9 
Academic  22 - 25  1.7  15  2.8  0.4 
overload  26 y + 
(EA6)  18 - 21  25  4.7  29  5.5  1.3 
Overcrowding in  22 - 25  14  2.6  16  3.0  0.6 
the classroom  26 y + 
(EA7)  18 - 21  28  5.3  28  5.4  1.7 
Lack of time  22 - 25  11  2.1  19  3.6  0.4 
  26 y +  0.2 
(EA8)  18 - 21  28  5.3  25  4.7  0.9 
Jobs mandatory  22 - 25  12  2.3  15  2.8  0.4 
  26 y +  0.2 
(EA9)  18 - 21  28  5.3  26  4.9  1.5 
Tasks study  22 - 25  1.7  18  3.4  0.2 
  26 y + 
(EA10)  18 - 21  36  6.8  16  3.0  0.9 
Work group  22 - 25  10  1.9  13  2.5  0.8 
  26 y + 
(EA11)  18 - 21  38  7.2  33  6.3  14  2.7 
Competitiveness  22 - 25  10  1.9  30  5.7  0.9 
between mates  26 y +  0.2  0.2 

Note. Post. Questionnaire data SSI and ASI.

Predictive Value of the ASI as it relates to the SSI

Table 3 indicates the correlations between the SSI scores and the ASI situations. The analysis reveals that the positive correlations, which indicated a moderate strength, were situation EA3 (r = .63, p < 01), followed by EA8 (r = .49, p < .01); the situation EA1 showed a weak correlation (r = .21, p < .01). Other situations presented a non- significant correlation with r less than .20: r = 12 for EA2, r = .13 for EA4, r = .16 for EA5, r = .14 for EA6, r = .11 for EA7, r = .10 for EA9, r = 16 for EA10. Situation EA11 yielded r = .01, which was considered a very low correlation and was therefore not included.

Table 3.

Matrix of correlations between the scores on college students to the Stress Symptom Inventory (SSI) and the Academic Stress Inventory (ASI).

  ISE  EA1  EA2  EA3  EA4  EA5  EA6  EA7  EA8  EA9  EA10  EA11 
ISE  ---                       
EA1  .21**  ---                     
EA2  .12**  .38**  ---                   
EA3  .63**  -.30  -.14  ---                 
EA4  .13**  .08*  .14**  .35**  ---               
EA5  .16**  .01  .17**  .40**  .29**  ---             
EA6  .14**  .02  .10**  .38**  .46**  .22**  ---           
EA7  .11**  .08*  .15**  .33**  .31**  .37**  .25**  ---         
EA8  .49*  .06  .09  .05  1.00**  .74**  1.00**  .74**  ---       
EA9  .10**  -.00  .19**  .41**  .29**  .38**  .32**  .39**  .43**  ---     
EA10  .16**  .05  .06  .33**  .29**  .29**  .34**  .26**  .34**  .43**  ---   
EA11  -.01**  .11**  .08*  .14**  .08*  .19**  .10*  .10**  .18**  .16**  .20**  --- 

Note. SSI = chronic stress, EA1 = conducting test, EA2 = exhibition of works, EA3 = classroom intervention, EA4 = Attend tutorials, EA5 = academic overload, EA6 = overcrowding in the classroom, EA7 = lack of time, EA8 = compulsory labor, EA9 = study tasks, EA10 = workgroups, EA11 = competition among peers.

*p < .05, **p < .01.

The correlation coefficient obtained by analysis of chronic stress through regression by steps, initially revealed that the situations of classroom participation (EA3), obligatory homework (EA8), and test taking (EA1) met the predictive criteria with a significant value (R2 = 26, F = 13.3, p < .05). The EA3 situation presented a stronger correlation according to the adjusted R2; in the first model, the last situation had a 21% SSI prediction, with an F = 25.2 and a p < .05. Nevertheless, when EA8 and EA1 situations were introduced the prediction only increased by 5%. The rest of the situations were excluded because they had either an insignificant or a negative correlation. The results showed a significant increase in the explanation of the ASI and SSI, as appraised by the university students. When the EA3 equation was introduced the additional predictive value related to the situations EA8 (p < .01) and EA1 (p < 05), as reported in Table 4.

Table 4.

Hierarchical multiple regression analysis of SSI (Stress Symptom Inventory) on each of the academic stress situations ASI (Academic Stress Inventory).

ISE  Beta  ET  (pRF 
Model 1        .21**  25.2 
EA3  .21  .04  < .01     
Model 2        .24**  16.9 
EA3  .18  .04  < .01     
EA8  .12  .04  < .01     
Model 3        .26*  13.3 
EA3  .17  .04  < .01     
EA8  .12  .04  < .01     
EA1  .10  .03  < .05     

Note. Questionnaire Data SSI and ASI, EA3 = classroom intervention, EA8 = compulsory labor, EA1 = conducting test.

*p < .05, **p < .01.

Analysis of Association for the ASI and SSI with Age and Gender

In the exploration to determine the association between high levels of the SSI and the ASI situations, with the variable of gender and age (Table 5) it was found that the high level of chronic stress (SSI) was related by means of the OR with the feminine gender variables (OR = 1.47) and with the age of 25 years (OR = 6.3) The academic stress situations (ASI) that were found to have a significant association were EA1 with feminine gender (OR = 1.48) and with the age of 23 (OR = 2.09); for EA3 the association was established with the age of 18 (OR = 2.89) and for EA8 only the feminine gender was significant with an OR = 1.70. The other situations did not show any significance with the variables of age and gender.

Table 5.

Association between high levels of chronic stress (SSI) and academic stress (ASI) in relation to age and gender of university students from a public university in Guadalajara, Mexico.

Variables  High level  p  OR  CI (95%) 
SSI (Chronic stress)         
Gender female  125  .03*  1.47  1.02 - 2.14 
Age 25 years  .00**  5.06  1.32 - 19.32 
ASI (Academic Stress)         
EA1         
Gender female  113  .04*  1.48  1.01 - 2.16 
Age 23 years  29  .00**  2.09  1.21 - 3.61 
EA3         
Age 18 years  16  .01*  2.18  1.19 - 7.01 
EA8         
Gender female  61  .03*  1.70  1.04 - 2.79 

Note. Questionnaire Data SSI and ASI, EA3 = classroom intervention, EA8 = compulsory labor, EA1 = conducting test. OR = Odds Ratio, CI = Confidence Interval.

*p < .05, **p < .01.

With regard to these analyses, we have made various contrasts relative to the supposed independence, normality, and homoscedasticity. In this sense, we must review the data, which does not show multicollinearity among the predictor variables. The average of the statistical values of “tolerance” carried out for the physical, psychological, and behavioral factors was set at .79, with no value below .71. The proximity of these values and the maximum value (range 0-1) indicates the independence of the contributions of the predictor variables over the values of the eleven academic stress indicators, thereby showing that the variance of the residuals is constant, proving that the residuals were distributed normally. The average of the value (VIF = 1.24), with no value below 1.05, shows that there was no a collinearity problem.

Discussion

The study demonstrated that a positive correlation exists between the ASI and some situations of the SSI, including class participation, obligatory homework and test taking. The ratings show a dependency among the variables, that is, when one increases the other does as well in constant proportion. These results permit us to validate our hypothesis. To our knowledge, this is the first predictive study which identifies the existence of a relationship between the situations which make up the ASI with the level of SSI in university students. The resulting model of this investigation helps to confirm the transactional theory of social cognitive focus, where the interaction of the stress variables was emphasized, based on the cognitive processes which developed around a stressful situation as the internal representation of the evaluations which are peculiar to and problematic for the students and their academic environment.

Studies about stress (e.g., Arreola-Quiroz & Stucchi, 2010; Matheny et al., 2008; Silva, 2009) mention that Mexico is considered among the countries with elevated stress levels. In the United States, 70% of medical visits are for problems which are caused by stress, and a quarter of the medications which are sold in that country are antidepressants or other types of drugs which affect the central nervous system (Aselton, 2012; Cox & Mackay, 1981). Regarding academic stress, previous studies have proven that stress is present in educational environments and furthermore that it is more frequent with homework and tests, the lack of time to complete assignments, and not having understood the material (e.g., Díaz, 2010; Pulido et al., 2011; Román et al., 2008). Some factors are the cause of important differences in results such as those related to the different study plans of the educational institution the students attend and which is the objective this study, since the educational model is oriented to professional competence, where not the tests but the students’ classroom participation is considered to be the best means of evaluation. Another probable cause for these differences is the variation in the study design, most importantly those who were involved in other situations which tackled the issues differently, and the tendency of the students to have poor academic achievement (e.g., Broc & Gil, 2008; Caldera et al., 2007; Celis et al., 2001; Díaz, 2010; Martínez, 2010; Navea, 2012; Sohail, 2013).

In our study we also observed a significant association according to the OR between the levels of chronic and academic stress (EA1 and EA8) in women as compared to those of men, which therefore implies that closer attention should be given to this population of students. In other studies it has been found that the feminine gender present a higher risk of stress (e.g., Costarelli & Patsai, 2012; Leiner & Jiménez, 2011; Pozos et al., 2008; Pulido et al., 2011). In terms of age, it was found that a relationship exists between a high chronic stress level and 25 years of age; furthermore, for a high level of academic stress, a significant association was found between situation EA1 and 23 years of age, and between situation EA3 and 18 years of age. Other studies differ with these results, indicating that 21-year-old students are at an increased risk for stress (e.g., Leiner & Jiménez, 2011; López and López, 2011). The difference between these authors and the work presented here stems from the fact that the association between the situations was more specific both for chronic stress as well as for the different situations of academic stress. Nevertheless, the average age in this study was 21 years. The age range which showed significant association was 18-25 years. Also, it was discovered that there is a higher frequency of moderate levels of chronic stress, with a difference of 9.5% over high levels, which should be considered an alarming situation. The instrument used (SSI) is based on symptomatic evidence, which thereby shows that if no intervention strategy to reduce stress levels from moderate to low is put into place, these rates could elevate to high levels at any moment, putting health and academic performance at risk. This could result in low scholastic achievement or desertion by the students.

This study has among its strengths the large and representative sampling of students. In this sample 54% of total enrollment for physical education and sports majors of this university were interviewed. This includes more students than other studies concerning academic stress (e.g., Díaz, 2010; Pulido et al., 2011; Román et al., 2008). It is likewise important to mention the limitations of this study, which lie principally in the existence of other factors which could have an influence on chronic and academic stress at the time the survey was taken, such as the social, economic, and cultural characteristics which were not evaluated in this study.

In conclusion, our study determined that only the following situations of the Academic Stress Inventory (ASI), class participation, obligatory assignments and test taking, are predictive of the Symptoms of Stress Inventory (chronic stress). Twenty-five-year-old women are at an increased risk to develop high levels of chronic stress; also, the 23-year-old female has a higher risk of developing high levels of academic stress during test taking and for obligatory assignments. Eighteen-year-old students are at higher risk to develop high levels of academic stress when faced with class participation in comparison to males and other ages.

With these results, our work hypothesis is accepted: a positive relationship of the ASI and the SSI has been determined. A model of predictive variables such as the association of the variables of 25 and 23 years of age, the female gender having an increased risk of developing high levels of chronic stress (SSI), and of the situations EA1, EA3, and EA8 of academic stress ASI, has been established. The exact identification of the stressors could help reduce and understand the stress, thereby eliminating the harm they cause, which negatively affects the academic performance of the students. Therefore the implementation of educational programs oriented towards the prevention of stress and its negative effects is recommended in order to further the capacity of the students to withstand stressful situations.

Conflict of interest

The authors of this article declare no conflict of interest.

References
Arreola-Quiroz and Stucchi, 2010
I. Arreola-Quiroz,P. Stucchi
Depresión en estudiantes de medicina: Una aproximación bibliométrica
Revista Médica de Chile, 138 (2010), pp. 388-389 http://dx.doi.org//S0034-98872010000300022
Aselton, 2012
P. Aselton
Sources of stress and coping in American college students who have been diagnosed with depression
Journal of Child and Adolescent Psychiatric Nursing, 25 (2012), pp. 119-123 http://dx.doi.org/10.1111/j.1744-6171.2012.00341.x
Berrío and Mazo, 2011
N. Berrío,Z. Mazo
Estrés Académico
Revista de Psicología de la Universidad de Antioquia, 3 (2011), pp. 65-82
Broc and Gil, 2008
C.M. Broc,C.C. Gil
Predicción del rendimiento académico en alumnos de ESO y Bachillerato mediante el Inventario Clínico para adolescentes del Millon (Escala MACI)
Anales de Psicología, 24 (2008), pp. 158-167
Caldera et al., 2007
M. Caldera,C. Pulido,G. Martínez
Niveles de estrés y rendimiento académico en estudiantes de la carrera de Psicología del Centro Universitario de Los Altos
Revista de Educación y Desarrollo, 7 (2007), pp. 77-82
Celis et al., 2001
J. Celis,M. Bustamante,D. Cabrera,M. Cabrera,W. Alarcón,E. Monge
Ansiedad y estrés académico en estudiantes de medicina humana del primer y sexto año
Anales de la Facultad de Medicina, 62 (2001), pp. 25-30
Costarelli and Patsai, 2012
V. Costarelli,A. Patsai
Academic examination stress increases disordered eating symptomatology in female university students
Eating and Weight Disorders, 17 (2012), pp. 64-69
Cox and Mackay, 1981
Cox, T., & Mackay C. (1981). A transactional approach to occupational stress. In E. N. Corlett & J. Richardson (Eds.), Stress, work design, and productivity (pp. 91-113). Chichester, UK: Editorial Wiley.
Díaz, 2010
M. Díaz
Estrés académico y afrontamiento en estudiantes de Medicina
Revista de Humanidades Médicas, 10 (2010), pp. 2-10
Lazarus and Folkman, 1986
Lazarus, R.S., & Folkman, S., (1986). Cognitive theories of stress and the issue of circularity. In M. H. Appley & R. Trumbull (Eds.), Dynamics of Stress. Physiological, Psychologcal, and Social Perspectives (pp. 63-80). New York, NY: Plenum.
Leiner and Jiménez, 2011
C.M. Leiner,T.P. Jiménez
Un estudio comparativo del estrés percibido en estudiantes de ciencias administrativas y biológicas en tiempos de violencia
Contaduría y Administración, 233 (2011), pp. 105-125
Leon, 2010
J.A. Leon
La Comprensión de la Causalidad Narrativa Mediante el Análisis de una Tarea de Resumen
Un Estudio Comparativo entre Universitarios y Estudiantes de 4° de ESO. Psicología Educativa, 16 (2010), pp. 157-176
Lipp and Guevara, 1994
M.E. Lipp,A.J. Guevara
Validação empírica do Inventário de Sintomas de Stress (ISS)
Estudios de Psicología, 11 (1994), pp. 43-49
López and López, 2011
V.F. López,M.M. López
Situaciones generadoras de estrés en los estudiantes de enfermería en las prácticas clínicas
Ciencias de la Enfermería, 17 (2011), pp. 47-54
Lwanga and Lameshow, 1991
Lwanga, S.K., & Lameshow, S. (1991). Sample size determination in health studies. World HealthOrganization.Recuperadodehttp://whqlibdoc.who.int/publications/9241544058_ (p1-p22).pdf.
Martínez, 2010
G. Martínez
Estrategias de afrontamiento ante el estrés y rendimiento académico en estudiantes universitarios
Cuadernos de Educación y Desarrollo, 2 (2010), pp. 4-14
Marty et al., 2005
M. Marty,G. Lavín,M. Figueroa,D. Larraín,C. Cruz
Prevalencia de estrés. en estudiantes del área de la salud de la Universidad de los Andes y su relación con enfermedades infecciosas
Revista Chilena de Neuro-psiquiatría, 43 (2005), pp. 25-32
Matheny et al., 2008
K.B. Matheny,B.E. Roque-Tovar,W.L. Curlette
Perceived stress, coping resources, and life satisfaction among US and Mexican college students: A cross- cultural study
Anales de Psicología, 24 (2008), pp. 49-57
Navea, 2012
M.A. Navea
Un Estudio sobre las Metas Académicas en Estudiantes Universitarios de Enfermería
Psicología Educativa, 18 (2012), pp. 83-89
Polo et al., 1999
A. Polo,J. Hernández,C. Pozo
Evaluación del estrés académico en estudiantes universitarios
Ansiedad y Estrés, 2 (1999), pp. 159-172
Pozos-Radillo et al., 2008
B.E. Pozos-Radillo,L.T. Torres,V.M. Aguilera,F.M. Acosta,P.G. González
Stress-associated factors in Mexican dentists
Brazilian Oral Research, 22 (2008), pp. 223-228
Preciado-Serrano and Vázquez-Goñi, 2010
L. Preciado-Serrano,J.M. Vázquez-Goñi
Perfil de estrés y síndrome de burnout en estudiantes mexicanos de odontología de una universidad pública
Revista Chilena de Neuro-psiquiatría, 48 (2010), pp. 11-19
Pulido et al., 2011
R. Pulido,S. Serrano,C. Valdés,M. Chávez,M. Hidalgo,G. Vera
Estrés académico en estudiantes universitarios
Psicología y Salud, 21 (2011), pp. 31-37
Román et al., 2008
C. Román,R. Ortiz,R. Hernández
El estrés académico en estudiantes latinoamericanos de la carrera de Medicina
Revista Iberoamericana de Educación, 46 (2008), pp. 2-8
Santed et al., 2000
M.A. Santed,B. Sandín,P. Chorot,M. Olmedo
Predicción de la Sintomatología Somática a partir del estrés diario: un estudio prospectivo controlando el efecto del neuroticismo
Revista de Psicopatología y Psicología Clínica, 5 (2000), pp. 164-178
Segredo et al., 2004
Segredo, P.A., Veloso, P.E., & Rodríguez, S.R. (2004). El estrés, su comportamiento en la Atención Primaria de Salud. Revista Cubana de Medicina General e Integral. Recuperado de http://www.bvs.sld.cu/revistas/mgi/vol20_4_04/mgi01404.htm.
Silva, 2009
Silva, T.A. (2009). Perfil de estrés académico en alumnos de licenciatura en psicología de la universidad autónoma de Hidalgo en la escuela superior de Actopan (tesis de licenciatura, publicada). Universidad Autónoma de Hidalgo, Actopan. Hidalgo.
Sohail, 2013
N. Sohail
Stress and academic performance among medical students
Journal of the College of Physicians and Surgeons Pakistan, 23 (2013), pp. 67-71 http://dx.doi.org/01.2013/JCPSP.6771
Tapia et al., 2008
Tapia, V.A., Guajardo, C., & Quintanilla, A.C. (2008). Estilos cognitivos en el bienestar y el estrés [número monográfico]. Revista Mexicana de Psicología, 388-389.
Corresponding author. Dra. Blanca Elizabeth Pozos Radillo. Paseo de los Virreyes 706 A-19. Virreyes Residencial. Zapopan, Jalisco, México. C. P. 45110. (Blanca Elizabeth Pozos-Radillo litaemx@yahoo.com.mx)
Psicología Educativa 20 (2014) 47-52 - Vol. 20 Núm.1 DOI: 10.1016/j.pse.2014.05.006