Sistema Regional de Información
en línea para Revistas Científicas de América Latina,
el Caribe, España y Portugal

Interview with Elisa McCausland

On the basis of the heterogeneous casuistry that characterizes the students who refuse going to school, it is useful to have a classification of this population in homogeneous groups. For this, the aim of this study was, first, to identify by cluster analysis the profiles of school refusal behavior based on the functional model evaluated through the School Refusal Assessment Scale-Revised (SRAS-S). Secondly, it is intended to analyze if there are differences in social functioning scores according to the school refusal profiles identified. This study involved 1212 Spanish children between 8 and 11 years old (M=9.12, SD=1.05) who completed the SRAS-R to evaluate the school refusal behavior and the Child and Adolescent Social Adaptive Functioning Scale (CASAFS) to assess social functioning. Four profiles were identified: Non-school refusers, School refusers by mixed reinforcements, School refusers by tangible reinforcements and School refusers by negative reinforcements. The profile of Non-school refusers achieved the highest average scores in social functioning, while School refusers by mixed reinforcements group obtained the lowest average scores in social functioning. In general, the profiles found support the clusters identified in previous studies. The implications of social functioning on school refusal behavior are discussed.

Difficulties with attending school are common in children referred to anxiety disorders clinics. Although parental factors have been posited as playing an important predictive role, little is known about which parental factors are associated with school attendance difficulties (SADs). We address this gap by examining family accommodation, parental psychological control, parental anxiety, and parental depression as possible predictors of SADs in children (N=343; ages 6 to 17 years, M=10.40 years, SD=2.93; 84% mothers; M=41.20 years, SD=5.49) who presented to a childhood anxiety disorders clinic. Forty-eight percent (n= 166) had SADs including not attending school, arriving to school late and/or leaving early, not staying in the classroom during school hours, or behavior problems associated with attending school (e.g. morning tantrums). Logistic regression analyses using child and parent ratings revealed that of the parental variables examined, family accommodation and parental depression were significant predictors of SADs after controlling for the effects of parental psychological control, parental anxiety, child age, child anxiety and child depression. The study’s findings suggest that high levels of family accommodation and high levels of parental depression increase the odds of SADs in anxious children.

Current advances on school refusal and other attendance problems: An international perspective. Introduction to the Special Issue. The school attendance problems affect a larger number of students worldwide than desired. Important negative effects on academic, social and personal development are associated with this phenomenon. The aim of this special issue is to present the most recent advances in this field of research from an international perspective. For this, this special series has six investigations framed in the context of Spain, France, the United States, Japan, Malaysia and the Netherlands. Among the main contributions, the works compiled here have managed to reflect on the school refusal behavior reaching three levels of analysis: (1) legal and political level, (2) personal level of the child or young person affected and (3) family level. Based on the findings obtained, it is concluded that promoting prevention and reducing the school attendance problems are activities that have no limits geographically. It is a purpose shared by all the studies that make up this special issue to encourage reflection and promoting new lines of research.

School absenteeism is a serious problem among youths, varying in etiology and presentation. Youths presenting high levels of absence have previously been linked to mental health problems, academic difficulties and dropout, highlighting the need for early identification and intervention. The aim of this study is twofold: first, to identify profiles among a community sample of secondary school students based on school absence, internalizing and externalizing behavior using the Child Behavior Checklist (CBCL-YSR). Second, to examine the relationship between profiles regarding mental health problems based on the dimensions of the CBCL-YSR, the function of their school absence using the School Refusal Assessment Scale (SRAS) and school refusal using the SChool REfusal EvaluatioN (SCREEN). The profiles are compared on demographic variables, family characteristics, school performance and bullying. A community sample of 469 youths (10-16 year, M=12.1 years, SD=1.2) from six French secondary publics schools participated in this study. Using cluster analysis, four distinct profiles were identified. The clusters differed significantly on school absence, internalizing problems, externalizing problems, dimensions of the CBCL-YSR, and their function of absence on the SRAS. Clusters differed significantly on several demographic variables, school level, grade, repetition and bullying. The distinctions between the four profiles and their relevance are discussed.

Low perceived self–efficacy (SE) for responding to school–related situations is posited to be associated with school refusal. This study examined the validity and reliability of the Malay version of the Self–Efficacy Questionnaire for School Situations (SEQ–SS) among early adolescents in Kota Bharu. The English version of the 25–item SEQ–SS was translated into Malay. Employing a cross–sectional design, students (10-11 years) from five randomly selected public primary schools were recruited via proportionate cluster sampling. Two hundred and fifteen students, 65% female, mean age of 10.3 years (SD=0.5), completed the Malay SEQ–SS. Validity was examined with exploratory factor analysis (EFA). Cronbach’s alpha was used to determine internal consistency. Means and standard deviations were used to describe the total and subscale scores. EFA analyses retained 19 items which clustered into four factors: ‘SE in socially challenging situations’, ‘SE in personally challenging situations’, ‘SE in separation situations’, and ‘SE in situations of disengagement from school’. Internal consistencies were low, approaching moderate, with Cronbach’s alpha values between 0.64 and 0.69. The four–factor solution of the Malay SEQ–SS appears to permit identification of specific domains of low SE which could inform individualized interventions targeting early adolescents in primary school.

University life can be associated to mental and emotional pressure. The aim of this research was to explore if the perception of the academic context as stressful can be associated to health symptoms (physical and mental) in higher education students enrolled in different degrees. Method. 728 students were recruited from a Spanish university. An academic stressors questionnaire (E-CEA) and response to the stress questionnaire (R-CEA) were used to assess academic stress and health symptoms. We conducted a t-test, Pearson correlation test and hierarchical multiple regression analysis. Results. Academic stress is moderate correlated to health symptoms (r?.40 in all cases). Specifically, academic stress reported by students is positively associated to physical exhaustion (r=.533; p<.001), sleeping disorders (r=.429; p<.001), irascibility (r=.467; p<.001), negative thoughts (r=.558; p<.001) and feeling nervous (r= .474; p< .001). Significant differences in E-CEA and R-CEA were found for age and major (p?0.001). We observed a model which accounted for 40.3% of the variance of health symptoms reported by students, being academic stress the strongest predictive variable. Conclusions. The results from this study support the assumption that academic stress has a negative impact on college students´ health.

There is a good deal of research about the predictors of aggressive and antisocial behaviour in children, adolescents, and adults. Additionally, previous work has established a link between psychopathic personality and disruptive behaviours among youth, with clear links to bullying. However, little is known about the role of psychopathic personality traits in the manifestation of bullying in young adults. In order to shed additional understanding on the nature of the relationship between bullying and psychopathy, the current investigation proposes to compare psychopathic personality traits in relation to participants’ roles in bullying and to examine the relationships between bullying and psychopathy. The sample comprised here involves 273 college students (Mage=25.5; SD=6.1), who responded to measures of psychopathy and bullying behaviours. With the exception of Carefree Non-Planfulness, Fearlessness, Stress Immunity and Social Influence, all other psychopathic domains measured by the PPI-R-40 were positively correlated with victimisation (rrange=.07-.35). Higher self-reporting of bullying others was linked with higher levels of Blame Externalisation, Machiavellianism, Rebellion Nonconformity, Self-Centred Impulsivity factor, Social Influence, and total psychopathy (rrange=.08-.38). Significant differences between participants’ involvement with bullying for Blame Externalisation, Machiavellian Egocentricity, Rebellion Nonconformity, Social Influence, Total Psychopathy and Self-Centred Impulsivity factor. Implications of the study, along with limitations and directions for future research are discussed.

The identification of emerging school attendance problems (SAPs) is highly important. Early identification permits early intervention, which reduces the likelihood of SAPs becoming established and contributing to additional problems. In the short term, SAPs can contribute to academic and social-emotional problems for the young person and stress for the family, and they place extra demands upon school resources. In the longer-term, SAPs can lead to school drop-out which contributes to problems for the community at large. Local, national, and international efforts aimed at the identification of emerging SAPs are thus a priority. This paper commences with a review of national laws and policies in the Netherlands that have a bearing on the identification of SAPs. Two Dutch protocols relevant to the identification of SAPs are also considered. Thereafter, we discuss the strengths and weaknesses of Dutch laws, policies, and protocols, paying particular attention to the question of whether they satisfactorily stimulate early identification of SAPs. The paper concludes with recommendations about ways to improve early identification in the Netherlands. These recommendations can stimulate thinking among educational professionals and policy-makers in other countries.

Psychological well-being seems to be associated with healthy lifestyle habits, with positive personality variables and absence of relevant clinical symptoms. This study aims to: (1) describe the differences of gender and age in the variables: life habits, positive psychological variables and clinical variables; (2) analyze correlations between the variables studied and psychological well-being; (3) investigate the predictive variables of psychological well-being. It was worked with 1075 participants of both sexes of 13 -18, 514 men (47.8%), 542 of 13 - 15 (50.4%) They were evaluated with the psychological well-being scale, Life habits survey, Selfesteem scale of Rosenberg (1965); Scale of body self-esteem; Inventory of psychopathological symptoms SCL 90-R. The results confirm statistically significant differences in life habits, with higher scores for males and younger age. In positive personality variables, males significantly exceed the women and in the negatives to the inverse. It is confirmed that to the better academic performance, the more physical exercise, the better nutrition, the good sleep quality and less consumption of tobacco, alcohol and drugs, the better psychological well-being. Higher scores in positive variables greater psychological well-being. The 56% of psychological well-being is predicted: self-concept, low depression, good sleep quality, body self-esteem, low emotion and high academic performance.