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Ciência & Saúde Coletiva

Print version ISSN 1413-8123On-line version ISSN 1678-4561

Ciênc. saúde coletiva vol.22 no.9 Rio de Janeiro Sept. 2017 


Childhood and adolescent sexual abuse, victim profile and its impacts on mental health

Luiz Felipe Campos Fontes1 

Otavio Canozzi Conceição1 

Sthefano Machado2 

1 Programa de Pós- Graduação em Economia do Desenvolvimento, Pontifícia Universidade Católica do Rio Grande do Sul. Av. Ipiranga 6681, Partenon. 90619-900 Porto Alegre RS Brasil.

2 Faculdade de Medicina, Universidade Federal do Rio Grande do Sul. Porto Alegre RS Brasil.


This work aims to analyze the impact of childhood and adolescent sexual abuse on variables related to mental health and to identify the characteristics of the victims. To achieve this objective, microdata of the National School Health Survey 2015 was used, applying the methodology of Propensity Score Matching. The results show that the abused youth has a unique behavioral, familiar and socioeconomic profile and that they are more likely to use alcohol and drugs, be victim of bullying, to be in age-grade lag, to be employed and not to intend to continue studying. From a familiar point of view, they have low parental monitoring and lower probability of living with their mother. Estimates show that teenage sexual abuse can increase the youth’s chance of reporting a constant feeling of loneliness by 13.3 percent, a 7.5 percent higher chance of having few or none friends, and a 9.5 percent higher chance of reporting frequent insomnia. Significant differences in effects on men and women were also observed, with impacts on loneliness feelings and insomnia greater for the first group and greater on the number of friends for the second.

Key words: Sexual abuse; Mental health; Propensity Score Matching; National School Health Survey


Sexual violence against children and teenagers is a problem that affects many countries. According to Stoltenborgh et al.1 one out of every eight young people around the world said they had been abused. In Brazil, sexual violence is the main type of violence among individuals in the 10-14 age group, second only to physical violence2. This is a form of violence that is not usually recognized as a public health problem and requires governments to develop strategies. Teenagers who have been abused are at high risk of developing several biopsychosocial disorders, with repercussions on the physical, behavioral, and cognitive spheres.

It must be considered that the effects are felt not only by the victim but also by society. The main concerns are costs of medical assistance, the criminal and legal system, and the drop in productivity and future earnings of young people3-5. According to Saied-Tessier6, the annual cost of teenager sexual abuse in the UK amounts to 3.2 billion euros, most of which is due to a decline in productivity for society as a whole.

Despite the importance of this matter, most of the research found in the national and international literature uses data from small samples, derived from case studies, which compromises the generality of its results. This is an extremely important fact that may be associated with the increasing recognition of this problem as a matter of public relevance. As a UN report7 indicates, violence against children and teenagers is often silenced and there is a paucity of statistical data on the subject. In this sense, learning about the impact of abuse and the profile of victims is essential to reduce the number of cases.

Given this scenario, this paper seeks to identify the profile of the abused youth and the impacts of abuse on his/her mental health. To do so, we use the microdata of a national school health survey, from which IBGE (The Brazilian Institute of Geography and Statistics - Instituto Brasileiro de Geografia e Estatística)8 defines the concept of mental health based on three variables related to the feeling of loneliness, insomnia and number of friends. Some authors suggest that mental health appears to be the main variable affected by sexual violence for this part of the population, leaving marks in the development of children and teenagers, with damages that can persist throughout life9-13. Therefore, the sooner some type of abuse is disclosed, the greater the probability of providing effective treatment and solving or remedying damages14.

To our knowledge, this the first research to use a quasi-experimental methodology, which makes it possible to isolate the effects of abuse from other confounding effects, so this is a first contribution. The second is the use of a national database with a representativeness equivalent to more than 2.5 million schoolchildren, thus differing from case studies for ensuring external validity of the results.

Data and methodology

This paper draws on data from the 2015 PeNSE (National School Health Survey -Pesquisa Nacional de Saúde do Escolar). Carried out for the first time in 2009, the research aims to understand and measure the several risk factors and protection of the teenage population health. This is a three-year survey carried out with 9th graders regularly attending public and private schools located in urban and rural areas throughout Brazil.

The choice of 2015 is justified by the inclusion of a variable that allows us to identify whether the student reported having been a victim of sexual violence. Formally, the question is, “Have you ever been forced to have sexual intercourse?”. The 2015 PeNSE included questions about socioeconomic aspects, such as family background, eating habits, physical activity, use of alcohol and other drugs, sexual health, violence, among others. The results variables were turned into dummies: in the case of Loneliness, it equals 1 if the student always feels or almost always feels alone and equals 0 if he/she never, rarely or sometimes feels alone. For the Friends variable, the dummy equals 1 if the student has up to two friends or no friends and 0 if otherwise. Finally, the Insomnia variable equals 1 if the student always has or almost always has trouble sleeping because something worries him/her and 0 if he/she never, rarely or sometimes has trouble sleeping.

Given that the aim of this study is to estimate the causal impact of sexual abuse on the mental health of students, it is necessary to find the counterfactual of the abused youngsters group. In order to do this, we used the Propensity Score Matching (PSM) method, which estimates the average treatment effect on treated (ATT), seeking in the control group (non-abused youngsters) the individuals who are most similar to the group of treated (abused youngsters) in terms of observable features. This is done in two steps, the first is the estimation of the probability of individuals receiving the treatment, in case they have been abused. To do so, we use the logit model. The second step consists of a matching which associates each individual in the treatment group with an individual in the control group according to the probability of being a victim of sexual violence.

The dtt ATT estimation by the Propensity Score Matching is then obtained according to the following estimator:


where n is the number of treated, i is the subscript for treated, j is the subscript for control, m is the number of matches, C indicates common support, wi,j is the weight used for matching the individual j to the i and Y is the result variable. In this paper we used the nearest-neighbor matching, where wi,j takes value 1 for treated and their matched controls and 0 for other controls.


Table 1 presents an overview of the sample in relation to sexual violence for 9th graders, stratified by gender. As you can see, teenagers who were abused represent about 4% of the total PeNSE participants, whose sampling representativeness is equivalent to 101,901 abused youngsters. Note that the percentage of victims is higher among females (4.32%). The microdata also presents the distribution of sexually abused youngsters by type of perpetrator. It should be noted that most of the acts are committed by people known to the victim: (ex)boyfriend (25.6%), family members (19.3%), friends (19.2%) and parents (10.5% ). This is an extremely disturbing result, given that the victim may have been abused by someone he/she loves or trusts.

Table 1 Number of abused students by gender. 

Total Abused
Total 2.575.269 101.901
(%) - 3,96%
Female 1.326.688 57.328
(%) - 4,32%
Male 1.248.581 44.573
(%) - 3,57%

Source: 2015 PeNSE microdata. Note: The results were expanded from the survey’s sample weights.

When considering the proposed result variables, Table 2 shows the existence of a singular profile of the abused teenager with regard to solitude, number of friends and insomnia problems. Among non-abused students, 16% reported feeling always alone or very alone, 22.7% said they had no friends or up to two friends, and 10.9% reported problems with frequent insomnia caused by their concerns. The numbers differ greatly among those who were abused, in 35.6%, 33.7% and 26.4%, respectively. The different dynamics observed for females’ mental health, as usually indicated in the literature, can be confirmed by the results in Table 2. In all variables there is a higher predominance of symptoms related to mental health among females, both between abused and non-abused females.

Table 2 Percentage of students per abuse condition and variables associated with mental health. 

Loneliness Friends Insomnia
Total 16,00% 22,70% 10,89%
Male 9,97% 20,21% 6,70%
Female 21,66% 25,04% 14,82%


Total 35,58% 33,69% 26,40%
Male 20,01% 32,26% 16,60%
Female 46,53% 34,69% 33,28%

Source: 2015 PeNSE microdata.

Table 3 shows the results of the first stage of Propensity Score Matching, which is the estimation of the logit model for the determinants of sexual abuse among students. Results point to a framework that characterizes the victims of sexual abuse as a very particular group in behavioral, family and socioeconomic terms. Abused youngsters are more likely to have used illicit drugs (OR = 2.15), alcohol (OR = 1.80) and have friends who have already done the same (OR = 1.02). In addition, they are twice more likely to have been bullied (OR = 2.09) and more likely to have an age-grade gap (OR = 1.20). Even more serious is the fact that these students report having less intention to go further than elementary school and are more likely to be working, which is indicated by the coefficients of ‘Future in school’ and ‘Employment’ (OR = 1.54) variables.

Table 3 Logit model - probability of the student having been sexually abused. 

Variables Odds ratio (OR) Variables Odds ratio (OR)
White 0.9544 Ownership index 0.9886
(0.0394) (0.0142)
Male 0.695*** Parental monitoring (free time)
(0.0363) Rarely 0.7728***
Age 0.7889 (0.0591)
(0.273) Sometimes 0.6579***
Physical activities outside of school 1.0734* (0.0560)
(0.0365) Most times 0.5183***
Bullying 2.0933*** (0.0556)
(0.0366) Always 0.5018***
Age-grade gap 1.2020*** (0.0521)
(0.0499) Parental monitoring (homework)
Job 1.5405*** Rarely 0.7377***
(0.0430) (0.0479)
Alcohol 1.8023*** Sometimes 0.6540***
(0.0413) (0.0496)
Drugs 2.1563*** Most times 0.6943***
(0.0436) (0.0649)
Friends drink alcohol 1.0205*** Always 0.7671***
(0.00462) (0.0532)
Habit of eating fruit 0.9615 Mother smokes 1.2594***
(0.0403) (0.0462)
Hunger Father smokes 0.9830
Rarely 1.3555*** (0.0431)
(0.0510) Lives with mother 0.8633**
Sometimes 1.5299*** (0.0596)
(0.0498) Lives with father 0.9155
Most times 2.4276*** (0.0848)
(0.0837) Separated parents 1.0750
Always 2.8677*** (0.0930)
(0.105) Mother is college educated 1.0660
School future (0.0482)
High school 0.6707*** People living in the house 1.0172*
(0.0717) (0.0100)
Vocational-technical school 0.7784*** Public school 1.2405***
(0.0884) (0.0592)
Undergraduate school 0.6300*** Capital city 1.3913**
(0.0722) (0.145)
Graduate school 0.7236***
Pseudo R2 0.11
Observations 98,115

Note: Significant at 1% (***), 5% (**) e 10% (*). Standard errors in parentheses. Dummies for federation units (†) were included. Index obtained through the multiple correspondence analysis, considering the existence of the following indicators at the household: housekeeper; car; motorcycle; landline; cell phone; computer; and internet.

As for the family environment, Table 3 also reveals that the variables of parental monitoring, both the one that determines whether they knew what the scholar did in their free time and the one that indicates the frequency with which the parents checked the homework, are very relevant predictors of sexual violence. The results are very significant for children whose parents always know or usually know what they do in their free time, a fact that is associated with a 50% lesser chance of reporting abuse. According to the results we found, the variable for the number of people at home (OR = 1.01) and the dummy that indicates whether the mother smokes (OR = 1.25) are also significant, as well as whether the abused person practiced physical activities outside of school (OR = 1,07), whether he/she lives with his/her mother (OR = 0,86), and whether he/she has already felt hunger at home, this last effect increasing according to how often it happened. Finally, teenagers from public schools (OR = 1,24) and living in capital cities (OR = 1,39) are more likely to be abused.

The next step in the method consisted of matching abused and non-abused students based on the attributes considered in the logit model. Figure 1 shows the probability of suffering sexual violence for youngsters in the group of abused and non-abused before and after the matching. Note that initially the groups were very different in observable features, with a strong concentration of non-abused on the left of the distribution and abused on the right. After the matching, the estimated probability distribution became very similar between the groups, demonstrating the model’s suitability.

Figure 1 Distribution of the probability of sexual abuse, before and after the matching. 

Table 4 presents the main result of this study, which relates to the estimation of sexual violence impacts on the mental health of students. First, it is clear that the adverse effects of this event are manifested in all variables. The estimated average effect of abuse on youngsters shows that they are 13.3% more likely to feel always alone or almost always alone, 7.5% more likely to have no friends or up to two friends and 9.5% more likely to report frequent insomnia due to their concerns.

Table 4 Impact of sexual abuse on the mental health of students. 

Loneliness Friends Insomnia
Total 0.1338*** 0.0752*** 0.0959***
(0.010) (0.011) (0.009)
Female 0.1600*** 0.0500*** 0.1070***
(0.015) (0.014) (0.014)
Male 0.0644*** 0.0869*** 0.0578***
(0.013) (0.016) (0.012)

Note: Significant at 1% (***). Standard errors in parentheses.

As already seen in the previous descriptive analysis, the results of Table 4 confirm that there is a great difference between genders in the mental health question. For females, the impact is greater on loneliness (16%) and insomnia (10.7%), being significantly different from that observed for males – 6.4% and 5.7% respectively. In turn, the impact of sexual abuse on the number of friends is higher for males (8.6%) than for females (5%).

Discussion and conclusion

The present study presents a significant sample of the Brazilian young population, where 4% of them suffered sexual abuse. Meta-analysis15,16 estimate that 10-20% of girls, and 5-10% of boys, have already suffered sexual abuse before the age of 18. Predominance varies according to the type of sexual abuse, being higher for sexual abuse without physical contact and lower for abuse with physical contact. The lower predominance found in our study can be explained by the nature of the question used to identify cases of sexual abuse, which is more likely to bring back a memory of physical sexual abuse, underestimating the real predominance from a broader concept of sexual abuse that does not include physical contact. It should also be considered that the problem of measuring predominance may be greater since, according to London17, about two-thirds of the victims never reveal the fact and most cases are not reported to the authorities18. All this contributes to the development of psychological and social problems, making room for discussions of preventive and therapeutic measures for sexual abuse.

As for the profile of the abused person, we noticed that the youngsters who were abused were more likely to have used illicit drugs, alcohol and to have friends who had already done the same. According to the literature19,20 on the subject, addiction to drugs and alcohol is common among victims of sexual violence, a problem that may persist for a long time. In addition, we observed that there is a greater possibility of there being age-grade gap among abused students, as documented in several studies21-23. Our findings also show that sexually abused students seem to be less likely to continue their studies in high school and undergraduate school and are more likely to be already working. Frothingham et al.24 found that individuals who were abused have more trouble learning and Fergusson et al.12 pointed out that they will rely on social welfare programs in the future. All of this shows a greater difficulty of adaptation of the abused person in the school/university and professional environment.

Socioeconomic factors such as low income and having an uneducated mother have been associated with sexual abuse in the literature12,25. In the present study, however, the variables that represent the socioeconomic level, such as ‘Ownership index’ and ‘Educated Mother’, were not significant, unlike the coefficients related to the variable that determines whether the student has ever been hungry due to lack of food at home. This suggests that family income is not as strongly associated with sexual abuse as is the degree of parental monitoring and the functionality of the family environment26. Another trait of the victim’s profile that reinforces this idea, already pointed out by Bezerra and Beltrão27, is that the victim of sexual violence avoids staying home and tries to spend as much time as possible outside the home environment, in order to feel safer. These data are pointed out by the variables that evaluate the greater chance that the individual will practice physical activities (aside from physical education) and not live with his/her mother.

The mental health variables used in the study (insomnia, friends, and solitude) do not involve mental disorders per se, but have a power to suggest psychic suffering. Kendall-Tackett et al.28 observed that abused children displayed more psychological symptoms than non-abused children, with the most common symptoms being nightmares, depression, withdrawal behavior, aggression, regressive behavior and neurotic disorder. Other common symptoms include fear, anxiety and low self-esteem29,30. These findings support the mental health variables used in the present study. Insomnia can be explained by the presence of nightmares, fears and mood disorders such as depression. The lack of friends and loneliness may be linked to aggressive behavior or withdrawal from the creation of new social bonds, as well as being due to characteristics of low self-esteem and bullying.

The impacts found when studying these variables are extremely significant. Descriptive analysis of the data revealed that, on average, abused youngsters frequently report having few friends, insomnia, and feeling lonely. Estimates from a causal impact methodology confirmed how harmful the effects of sexual violence on the mental health of victims are. The fact that the score used in the variables is divided between always/almost always gives an even stronger impression of the intensity of these results, suggesting the suffering and marked presence of psychological stressors in the youngsters, as well as the possibility of developing and maintaining other mental disorders in this study population.

Considering gender differences, the impact of sexual abuse on loneliness and insomnia is greater for females, and the impact on the number of friends is greater for males. Such a result is consistent with the literature that says men have less emotional regulation and therefore cannot cope with the abuse situation without externalizing the trauma. This leads to less empathy and less involvement with others in such a way that the result for the ‘Friends’ variable is larger for this group. Since women have greater emotional regulation, they are able to cope with the problem before people, however, they end up running greater risks of internalizing the adverse effects of trauma, which is portrayed by the results for solitude and insomnia31-34.

It should be emphasized that the impacts already commented on may be even more serious if we consider the fact that psychological disorders can last a lifetime. Fergusson et al.12 found adverse effects on the mental health of individuals between the ages of 18 and 30 who were sexually abused in childhood/adolescence. They have scored higher for depression, anxiety, suicidal ideation, suicide attempts and substance abuse/dependence. In addition, they reported more problems regarding psychological well-being, risky sexual behaviors, and increased need for medical support throughout life. The consequences of these findings are comprehensive within the family and social context, with significant costs for health institutions, social assistance, and the legal system5. Thus, the development of preventive as well as therapeutic approaches that provide the psychological rehabilitation and integration of the individual in society becomes of extreme relevance.

International studies show that cognitive-behavioral therapies offer the best evidence of negative impacts on the psychosocial function of abused individuals. Macdonald et al.35 and Arellano et al.36 show through meta-analysis that the main variables affected by this form of treatment seem to be post-traumatic stress disorder and feeling anxiety. Furthermore, there is evidence that treatment may also reduce symptoms of depression, behavioral and sexual problems, and embarrassment37,38. Some studies, however, cast doubt on the validity of the effects of cognitive-behavioral therapy on this broad set of mental health indicators, especially in relation to the last four. On the other hand, no reports of adverse effects of treatment were found in the analyzed studies35.

Prevention programs are another means of intervention against sexual abuse. The literature indicates that the most widely used method for the prevention of sexual violence consists of school programs that cover primary and secondary school students. Such programs gain relevance if we consider the findings of this article, that the abused youngster lacks family support. In this sense, the school may end up being the only source of care and protection of students who are at risk. There is a wide variety of international program models, ranging from passive styles (films, presentations, readings) to active styles (active participation, protective behaviors, etc)39. Studies show that these programs provide the grasping of concepts of sexual abuse prevention and protective abilities in situations of risk40-43. Other impacts include increased encouragement of case disclosure and less guilt and victimization43,44.

Adult-oriented prevention programs are another way of fighting sexual abuse. Most of these programs are aimed at caregivers who can gain knowledge and skills to deal with possible situations of sexual abuse with their children and thus hold dialogues on the subject between the parties45,46. Because child care providers are often involved in sexual abuse, other non-caregiver adult education programs, including teachers47, child care workers48, and adults in general49, have been developed. Although studies lack evidence of a decreasing predominance of sexual abuse42,43, spreading knowledge on the subject and developing the ability to deal with it may be a first step towards fighting abuse.

In Brazil, there are few studies that evaluate practices and types of treatments specific to abuse situations. The work of Habigzang et al.50 followed a cohort of forty abused children and adolescents during sixteen group therapy sessions. The results point to a significant drop in the symptoms of depression, anxiety, childhood stress and post-traumatic stress disorder. In this context, the concern of the Ministry of Health with the theme has been translated into two booklets about sexual abuse in childhood and adolescence, which give recommendations to health professionals on the need for support and care for the victim’s mental health51,52. However, as shown in Von Hohendorff et al.53, children and teenagers who have been abused but whose psychopathological symptoms are not regarded as severe or persistent do not have access to any mental health service. Thus, there seems to be a gap between existing scientific knowledge on the consequences of sexual violence and national public policies, which do not clearly provide the access of this population to psychotherapy53. With regard to prevention policies, Brazil is even further behind. There are initiatives of different government agencies, but they lack synergy and initiative. It follows that there is currently no concrete guideline for prevention.

The results found in this study indicate that the sexual abuse of children in Brazil, in addition to being related to several socioeconomic factors (drug involvement, early work, etc.), result in significant impacts on the victims’ mental health indicators. Thus, it is recommended that practices evaluated in international studies be internally recognized in order to guide the development of future public policies. Finally, new research also needs to be done to evaluate measures already adopted to expand the horizons for new therapy models, monitoring and prevention.


1. Stoltenborgh M, Van Ijzendoorn MH, Euser EM, Bakermans-Kranenburg MJ.A global perspective on child sexual abuse: meta-analysis of prevalence around the world. Child Maltreat 2011; 16(2):79-101. [ Links ]

2. Brasil. Ministério da Saúde (MS). Viva: sistema de vigilância de violências e acidentes: 2009, 2010 e 2011. Brasília: MS; 2013. [ Links ]

3. Mendonça RNS, Alves JGB, Filho JEC. Gastos hospitalares com crianças e adolescentes vítimas de violência, no Estado de Pernambuco. Cad Saude Publica 2002; 18(6):1577-1581. [ Links ]

4. Barrett A, Kamiya Y, O’Sullivan V.Childhood sexual abuse and later-life economic consequences. Journal of Behavioral and Experimental Economics 2014; 53:10-16. [ Links ]

5. Fang X, Brown DS, Curtis FS, Mercy J.The economic burden of child maltreatment in the United States and implications for prevention.Child Abuse Neglec 2012; 36(2):156-165. [ Links ]

6. Saied-Tessier A. Estimating the costs of child sexual abuse in the UK. London: NSPCC; 2014. [ Links ]

7. United Nations Organization. World report on violence against children. Geneva: United Nations Publishing Services; 2006. [ Links ]

8. Instituto Brasileiro de Geografia e Estatística (IBGE). Pesquisa Nacional de Saúde do Escolar 2015. Rio de Janeiro: IBGE; 2016. [ Links ]

9. Kilpatrick DG, Ruggiero KJ, Acierno R, Saunders BE, Resnick HS, Best, CL.Violence and risk of PTSD, major depression, substance abuse/dependence, and comorbidity: Results from the National Survey of Adolescents. J Consult Clin Psychol 2003; 71(4):692-700. [ Links ]

10. Bridge JA, Goldstein TR, Brent, DA.Adolescent suicide and suicidal behavior. J Child Psychol Psychiatry 2006; 47(3-4):372-394. [ Links ]

11. Shin SH, Edwards EM, Heeren T.Child abuse and neglect: Relations to adolescent binge drinking in the national longitudinal study of Adolescent Health (AddHealth) Study. Addict Behav 2009; 34(3):277-280. [ Links ]

12. Fergusson DM, Mcleod GFH, Horwood LJ.Childhood sexual abuse and adult developmental outcomes: Findings from a 30-year longitudinal study in New Zealand. Child Abuse Neglec2013; 37(9):664-674. [ Links ]

13. Davidson SK, Dowrick CF, Gunn JM.Impact of functional and structural social relationships on two year depression outcomes: A multivariate analysis. J Affect Disord 2016; 193:274-281. [ Links ]

14. Escudero AC, Cardoso APA, Tesser APF, Domingos LR, De Freitas MI. Abuso sexual na Infância. Psicologado Artigos [periódico na internet]. 2013 [acessado 25 fev 2017]. Disponível em: [ Links ]

15. Barth J, Bermetz L, Heim E, Trelle S, Tonia T.The current prevalence of child sexual abuse worldwide: a systematic review and meta-analysis. Int J Public Health 2013; 58(3):469-483. [ Links ]

16. Pereda N, Guilera G, Forns M, Gómez-Benito J.The international epidemiology of child sexual abuse: a continuation of Finkelhor (1994). Child Abuse Neglec 2009; 33(6):331-420. [ Links ]

17. London K, Bruck M, Ceci SJ, Shuman DW.Disclosure of child sexual abuse: what does the research tell us about the ways that children tell? Psychology, Public Policy, and Law 2005; 11(1):194-226. [ Links ]

18. Wyatt GE, Loeb TB, Solis B, Carmona JV.The prevalence and circumstances of child sexual abuse: changes across a decade. Child Abuse Neglec 1999; 23(1):45-60. [ Links ]

19. Nickel MK, Tritt K, Mitterlehner FO, Leiberich NC, Lahmann C, Forthuber P, Rother WK, Loew TH.Sexual abuse in childhood and youth as psychopathologically relevant life occurrence: Cross-sectional survey. Croat Med J2004; 45(4):483-489. [ Links ]

20. Kendler KS, Bulik CM, Silberg J, Hettema JM, Myers J, Prescott CA. Childhood sexual abuse and adult psychiatric and substance abuse disorders in women. Arch Gen Psychiatry 2000; 57(10):953-959. [ Links ]

21. Boden J, Horwood L, Fergusson D.Exposure to childhood sexual and physical abuse and subsequent educational achievement outcomes. Child Abuse Neglec 2007; 31(10):1101-1114. [ Links ]

22. Currie J, Spatz WC.Long-term consequences of child abuse and neglect on adult economic well-being. Child Maltreat 2010; 15(2):111-120. [ Links ]

23. Noll JG, Shenk CE, Yeh MT, Ji J, Putnam FW, Trickett PK.Receptive language and educational attainment for sexually abused females. Pediatrics 2010; 126(3):e615-622. [ Links ]

24. Frothingham TE, Hobbs CJ, Wynne JM, Yee L, Goyal A, Wadsworth DJ.Follow up study 8 years after diagnosis of sexual abuse. Arch Dis Child2000; 83(2):132-134 [ Links ]

25. Hecht DB, Hansen DJ.The environment of child maltreatment: Contextual factors and the development of psychopathology. Aggression and Violent Behavior 2001; 6(5):433-457. [ Links ]

26. Fassler IR, Amodeo M, Griffin ML, Clay CM, Ellis MA.Predicting long-term outcomes for women sexually abused in childhood: Contribution of abuse severity versus family environment. Child Abuse Neglec 2005; 29(3):269-284 [ Links ]

27. Bezerra MMS, Beltrão K. Abuso sexual infantil – criança x abuso sexual. Faculdade Metropolitana da Grande Recife, 2006. [acessado 2012 abr 5]. Disponível em: ]

28. Kendall-Tackett KA, Williams LM, Finkelhor D.Impact of sexual abuse on children: a review and synthesis of recent empirical studies. Psychol Bull 1993; 113(1):164-180. [ Links ]

29. Andrews G, Corry J, Slade T, Issakidis C, Swanston H. Child sexual abuse. Comparative Quantification of Health Risks: Global and Regional Burden of Disease Attributable to Selected Major Risk Factors. Geneva: WHO; 2004. Vol. 2 [ Links ]

30. Gilbert R, Spatz-Widom C, Browne K, Fergusson D, Webb E, Janson S.Burden and consequences of child maltreatment in high-income countries. Lancet 2009; 373(9657):68-81. [ Links ]

31. Bender PK, Reinholdt-Dunne ML, Esbjørn BH, Pons F.Emotion dysregulation and anxiety in children and adolescents: gender differences. Personality and Individual Differences 2012; 53(3):284-288. [ Links ]

32. Kim-Spoon J, Cicchetti D, Rogosch FA.A longitudinal study of emotion regulation, emotion lability-negativity, and internalizing symptomatology in maltreated and nonmaltreated children. Child Develop 2013; 84(2):512-527. [ Links ]

33. Chaplin TM, Aldao A.Gender differences in emotion expression in children: A meta-analytic review. Psychol Bull 2013; 139(4):735-765. [ Links ]

34. Séguin-Lemire A, Hébert M, Cossette L, Langevin R.A longitudinal study of emotion regulation among sexually abused preschoolers. Child Abuse Neglec 2017; 63:307-316. [ Links ]

35. Macdonald G, Higgins JP, Ramchandani P, Valentine JC, Bronger LP, Klein P, O’Daniel R, Pickering M, Rademaker B, Richardson G, Taylor M. Cognitive-behavioural interventions for children who have been sexually abused. Cochrane Database Syst Rev 2012; (5):CD001930. [ Links ]

36. Arellano MAR, Lyman DR, Jobe-Shields L, George P, Dougherty RH, Daniels AS, Delphin-Rittmon ME.Trauma-focused cognitive-behavioral therapy for children and adolescents: Assessing the evidence. Psychiatr Serv 2014; 65(5):591-602. [ Links ]

37. Cohen JA, Deblinger E, Mannarino AP, Steer RA.A multisite, randomized controlled trial for children with sexual abuse-related PTSD symptoms. J Am Acad Child Adolesc Psychiatry2004; 43(4):393-402. [ Links ]

38. Cohen JA, Mannarino, AP, Knudsen K. Treating sexually abused children: 1 year follow-up of a randomized controlled trial. Child Abuse Negl 2005; 29(2):135-145. [ Links ]

39. Zwi KJ, Woolfenden SR, Wheeler DM, O’brien TA, Tait P, Williams KW. School-based education programmes for the prevention of child sexual abuse. Cochrane Database Syst Rev.2007; (3):CD004380. [ Links ]

40. Taal M, Edelaar M.Positive and negative effects of a child sexual abuse prevention program. Child Abuse Negl 1997; 21(4):399-410. [ Links ]

41. Rispens J, Aleman A, Goudena PP.Prevention of child sexual abuse victimization: a meta-analysis of school programs. Child Abuse Negl 1997; 21(10):975-987. [ Links ]

42. MacMillan H, Wathen, CN, Barlow J, Fergusson DM, Lenethal JM, Taussig HN. Interventions to prevent child maltreatment and associated impairment. Lancet 2009; 373(9659):250-266. [ Links ]

43. Walsh K, Zwi K, Woolfenden S, Shlonsky A. School-based education programmes for the prevention of child sexual abuse. Cochrane Database Syst Rev. 2015; (4):CD004380. [ Links ]

44. Ji K, Finkelhor D, Dunne M. Child sexual abuse in China: a meta-analysis of 27 studies. Child Abuse & Neglect 2013; 37(9):613-622. [ Links ]

45. Hébert M, Lavoie F, Parent N.An assessment of outcomes following parents’ participation in a child abuse prevention program. Violence Vict 2002; 17(3):355-372. [ Links ]

46. Kenny MC.Child sexual abuse prevention: psychoeducational groups for preschoolers and their parents. J Spec Group Work 2009; 34(1):24-42. [ Links ]

47. Walsch K, Rassafiani M, Mathews B, Farell A, Butler W. Assessment and prevention: exploratory factor analysis and psychometric evaluation of the teacher reporting attitude scale of child sexual abuse. J Child Sex Abus 2012; 21(5):489-506. [ Links ]

48. Rheingold AA, Zajac K, Chapman JE, Patton M, Arellana, M, Saunders B.Child sexual abuse prevention training for childcare professionals: an independent multi-site randomized controlled trail of Stewards of Children. Prev. Sci2015; 16(3):374-385. [ Links ]

49. Self-Brown S, Rheingold AA, Campbell C, Arellano MA.A media campaign prevention program for child sexual abuse: community members’ perspectives. J Interpers Violence2008; 23(6):728-743. [ Links ]

50. Habigzang LF, Stroeher FH, Hatzenberger R, Cunha RCD, Ramos MDS, Koller SH.Grupoterapia cognitivo-comportamental para crianças e adolescentes vítimas de abuso sexual. Rev Saude Publica2009; 43(1):70-78. [ Links ]

51. Brasil. Ministério da Saúde (MS). Linha de cuidado para a atenção integral à saúde de crianças, adolescentes e suas famílias em situação de violências: orientação para gestores e profissionais de saúde. Brasília: MS; 2010. [ Links ]

52. Brasil. Ministério da Saúde (MS). Prevenção e tratamento dos agravos resultantes da violência sexual contra mulheres e adolescentes: norma técnica. Brasília: MS; 2012. [ Links ]

53. Von Hohendorff J, Koller SH, Habigzang LF.Psicoterapia para crianças e adolescentes vítimas de violência sexual no sistema público: panorama e alternativas de atendimento. Psicologia: Ciência e Profissão 2015; 35(1):182-198. [ Links ]

Received: January 23, 2017; Revised: April 18, 2017; Accepted: May 08, 2017


LFC Fontes, OC Conceição and S Machado participated in the elaboration of the entire article.

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