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These books synthesize perspectives of renowned scientists from the world’s most prestigious institutions - from Fukushima Renewable Energy Institute in Japan to Stanford University in the United States, including Columbia University (US), University of Sidney (AU), University of Miami (USA), Cardiff University (UK), and many others.
\\n\\nThis collaboration embodied the true essence of Open Access by simplifying the approach to OA publishing for Academic editors and authors who contributed their research and allowed the new research to be made available free and open to anyone anywhere in the world.
\\n\\nTo celebrate the 50 books published, we have gathered them at one location - just one click away, so that you can easily browse the subjects of your interest, download the content directly, share it or read online.
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IntechOpen and Knowledge Unlatched formed a partnership to support researchers working in engineering sciences by enabling an easier approach to publishing Open Access content. Using the Knowledge Unlatched crowdfunding model to raise the publishing costs through libraries around the world, Open Access Publishing Fee (OAPF) was not required from the authors.
\n\nInitially, the partnership supported engineering research, but it soon grew to include physical and life sciences, attracting more researchers to the advantages of Open Access publishing.
\n\n\n\nThese books synthesize perspectives of renowned scientists from the world’s most prestigious institutions - from Fukushima Renewable Energy Institute in Japan to Stanford University in the United States, including Columbia University (US), University of Sidney (AU), University of Miami (USA), Cardiff University (UK), and many others.
\n\nThis collaboration embodied the true essence of Open Access by simplifying the approach to OA publishing for Academic editors and authors who contributed their research and allowed the new research to be made available free and open to anyone anywhere in the world.
\n\nTo celebrate the 50 books published, we have gathered them at one location - just one click away, so that you can easily browse the subjects of your interest, download the content directly, share it or read online.
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The impact severe mental disorders (SMDs) have on a student acquires great relevance in the adolescent’s life. This is because of the repercussion it has on academic performance and the construction of a personal project while hindered by the disorder [1]. We emphasize the importance of this study, given that it aims to make it known that these students with mental disorders, in order for them to remain in the educational system, must receive adequate attention that meets their needs. It is a vulnerable population that presents greater risks of early school dropout than the general population [2]. It is pertinent to study in-depth lines of work that respond to such a specific need [3].
Before going any further, we would like to delimit the concept of SMD, so we can understand the profile of the studied population and some of the elements that make this population a homogeneous observation group. The severe mental disorders would be those disorders that “due to their severity, seriously compromise evolution, learning, personal development and the social and labor insertion of those children or adolescents who suffer from it. ….. that mental disorder of long duration and involving a variable degree of disability and social dysfunction” [4].
We found different perspectives [5], but they all could be synthesized in the idea that a serious mental disorder is that whose symptomatology affects very severely on different areas of the person and for a long time.
It is estimated that 20% of adolescents suffer from some type of mental disorder [6]. We know mental health problems account for 16% of total adolescent health problems. Also, half of mental health problems begin at the age of 14 years, and most of them go undetected or untreated. The same authors point out that suicide is the third cause of death between ages 15 and 19 years, as a consequence of not addressing mental health problems during the transition from adolescence to adulthood [7]. This limits the opportunities to develop a fulfilling life as an adult. This population segment is at a disadvantage regarding their participation, permanence, and promotion in the educational field. Adopting support measures that respond to their educational needs should compensate this situation.
According to the United Nations Children’s Fund [8], children who suffer from mental health problems are among the most vulnerable population groups. For an adolescent with a SMD, academic success is central and structural for the construction of their personal project, both from an academic and therapeutic point of view. Maintaining the relationship and staying in school allow students with SMD to have a reference of fundamental normality, so as to make improvements in other areas of their lives.
Some publications suggest that students with externalizing disorders are more likely to obtain poor academic results. This same publication points out that the economic factors, the age of onset of the mental disorder, academic performance, and family support are among some of the factors that are present in students with severe mental disorders [9]. Other studies indicate that groups of students with higher levels of emotional strength and low levels of distress obtain higher grades, have a greater prosocial contribution to the community, and show greater satisfaction with life [10].
The relationship between mental health and psychosocial factors seems clear [11]. Psychosocial factors play an important role in the adherence to interventions of the population with severe mental disorders. They could also play it on their academic results. Knowing the psychosocial factors of students with severe mental disorders could help us to personalize interventions [12].
We understand that, in order to develop educational practices appropriate to the needs of students with a SMD [13], understanding and knowing the psychosocial characteristics of this class of students is mandatory. This is how the European Education Information Network of the European Union warned in 2017 that one in eight children has a diagnosed mental disorder [14]. These same authors argue that 50% of mental health problems in adulthood begin to take effect before the age of 15 years, in adolescence. From this reality, it is necessary to deepen the development of educational practices that respond to many adolescents who are in a situation of greater vulnerability.
Based on the results obtained in a previous research carried out by us [15], and on the research in the scientific literature, we have used 18 variables to analyze the observed reality. We want to show the meanings attributed to each variable, since they will serve to interpret and help us make decisions in the factor analysis adjustment that we explain in the following section.
Thus, when we have observed the family accompaniment, we understand the fundamental role the family has both in the genesis and the treatment of the disorder [16]. So, depending on how the family support developed, the family will therefore be either a protective or a risk factor for students in a situation of SMD. When we talk about a family providing positive support, we refer to those families that understand their children’s clinical situation and, therefore, make good use of training guidelines favoring a healthy upbringing. We could differentiate between those families that play an abandonment and negligent role, not very favorable to the children’s rehabilitation process. At the other extreme, we would find families with an excessively care role and whose accompaniment is overprotective. In either case, we would be referring to families with difficulties in establishing a healthy parental-filial relationship.
When we analyzed the type of linkage with the school, we considered that it was a good linkage when maintaining the relationship and staying in school allow students with severe mental disorders to maintain a reference of fundamental normality that propitiates improvements in other areas of their lives. A proper bond with the school describes not only permanence and regular assistance – elements that are closely related –, but the grade the student feels and perceives the context with [3]. Failure to establish stable and healthy links with teachers, the educational center and the classmates are directly related with low self-esteem and could have a direct impact in the student’s academic performance [17]. We cannot forget that the perception that the rest of the educational community has and perceives of students with SMD would be included in the relationship with the educational center. This is how some research indicates that young people have negative attitudes toward their peers with mental health difficulties [18].
With the definition of this variable, we talk about lack of conflicts and a good relationship with teachers and peers. All this defines a contextual framework that allows students to express themselves with emotional tranquility. This is fundamental for their emotional wellness and the avoidance of subclinical or clinical symptoms. So is some authors see the inability to bond as a determining risk factor in obtaining mental health [19].
When analyzing academic success, we cannot forget that the children with mental health problems obtain worse academic results [20]. We also know there is an association between mental health problems and persistent truancy. This relationship is greater in those students who showed externalizing symptoms, since they obtain worse academic results [21]. So, when talking about academic success, we are referring to obtaining good academic results. It is mandatory to pass all subjects, except two, to be promoted to the next course. When a child makes through, we considered they have achieved academic success. When a student fails more than two subjects, we consider they are not in a situation of academic success. Academic success can be interpreted in multiple ways. It depends on where the light is pointing. We have not wanted to establish references in the scientific literature. We wanted to define what the concept means to us. That has been our way of observing and looking for the data in the consulted reports.
On the other hand, we also wanted to analyze the degree of academic promotion of the population analyzed. In this sense, some research shows the negative relationship between academic performance and psychiatric disorders, whether externalizing or internalizing ones [22]. Therefore, the possibility of repeating an academic year seems to be a conditioning element for the population studied. We have taken as a unit of temporal analysis the moment of the analytical work of the present investigation. This circumstance could have happened more times. Anyway, we understand that when a member of the sample repeated a school year at last once prior to hospitalization, the variable is marked as positive.
Regarding the continuity of learning processes and school attendance of these students, we found data indicating that the degree of truancy in students with mental disorders is higher than in the rest of the population [23]. Many factors define the situation of an absconding student. However, we would like to stress how important the degree of connection between the child and their school is. When a child feels a high-level bond with the school, it is because they also feel understood and included. So, for us, the degrade of truancy is a consequence of the engagement level with the educative center. Moreover, we think an avoidant behavior is an indication that something is not working as it should.
We have considered that the previous academic history of students with severe mental disorders also becomes a conditioning element for the improvement of these students. Thus, when we have considered this variable, we want to highlight one element that could be present in a student with a SMD [15]. Thus, there is a high chance they have bad previous academic records. This circumstance is present specially in externalizing disorders [9].
We also know that curricular backwardness affects many students with a SMD [24]. This variable defines the level of educative competence of a student in relation to their age. When a student has at least 1 year of curricular lag, we believed it pertinent to conceptualize the variable as positive.
Among the risk factors that predispose a student toward an early school dropout, there is the motivation toward study [25]. This is important for clinical improvement, as school expectations are a fundamental protective factor for mental health [26]. We considered this as a qualitative dichotomous variable.
It is also common for students with SMD to have poor study habits. This is because the disorder interrupts any process. Thus, when the student gets in a dire situation, they find it very difficult to maintain a routine in any activity [27].
In relation to limited conceptual and procedural power and/or cognitive difficulties, we can observe that this obstacle to participate in classroom dynamics predisposes students with SMD toward greater vulnerability in the educational context. This is because they lack the necessary skills to function adaptively in the methodological dynamics of a mainstream classroom [9].
We would also like to highlight the attentional difficulties of these pupils. In this regard, we will not only refer to the disorder with the highest level of attention impairment, as is the attention-deficit hyperactivity disorder. Attention difficulties are a circumstance present in many SMDs. This is because, whether the disorder is an externalizing or internalizing one, the moment of the disorder onset marks the difference [28]. Being in a severe moment could provoke attention difficulties due to circumstances such as problems arising from the disorder and medication, among others.
On the other hand, it seems relevant to us to differentiate between internalizing and externalizing disorders, since the way they are represented in the educational context is different. Thus, internalizing disorders collide less with interpersonal relationships, since they do not contribute to the distortion of coexistence in the educative center. On the other hand, externalizing disorders clash frontally with the school life in an educational center [9, 15]. As these disorders generate more disruption in the classroom, the student’s struggle with this type of disorder challenges more people and is more evident. So, we could say that internalizing disorders can go unnoticed and externalizing disorders become apparent more easily. Finally, we will point out that internalizing disorders, despite going unnoticed in most cases, are sometimes expressed with greater implosion on social networks. Hence, a minor who goes unnoticed in the educational center might be sharing on social sites such material that could compromise them before the educational community even more than an externalizing disorder. In our research when we found one of these cases, we conceptualized it as a problem of coexistence.
We also found it interesting to focus on relational style, as the learner may be more or less inhibited in the way he/she relates to others. It is common to find a greater degree of uninhibited in behavioral disorders. On the other hand, internalizing disorders do not always manifest themselves in a little visible way [29]. Because of this, the inhibited-uninhibited categorization could help to clarify how the mental disorder is represented in the educational center.
In the scientific literature, we also find data that leads us to consider the moment at which the disorder was detected, since when detection is early the prognosis may improve. In this sense, it is known that the prodrome symptoms of SMD begin to present themselves during adolescence [21]. For this reason, early detection could be an element that helps reduce the impact of the disorder on the child’s vital development.
From here, we could analyze when educational problems start. Some studies show vulnerability to clinical symptoms already in the early school years [30]. We also know mental disorders in early childhood are three times as likely in children who present misconduct at the age of 5 years, and around seven times as likely in children with special educational needs [31]. That is, the moment of detection could determine if the disorder occurs one way or the other, as early detection allows intervening in more preventive and less palliative terms [32].
Having analyzed the conceptual elements on which we have decided to focus our research, we set ourselves the following aim, to define psychosocial factors of students aged 12–18 years who have been diagnosed with a severe mental disorders.
For the selection of the sample, we have used an intentional sampling criterion [33]. One hundred and nine cases of students with SMD in the educational field have been analyzed. We have analyzed both internalizing and externalizing serious mental disorders. They range in age from 12 to 17 years old. The mean and mode is 15 years of age. Forty-five percent of them are female and 55% are male.
As inclusion criteria, we note that all cases have been treated for an average of 11 months in a Day Hospital for adolescents with subacute symptomatology. In this Day Hospital, they have received both clinical care and formal educational care. It is therefore a specialized center in which the patients are also students and fulfill this dual role. To be admitted to this Day Hospital, a public Mental Health Centre under DSM-5 and ICD-10 criteria must previously diagnose all patients. All patients have a diagnosis considered a serious mental disorder due to its repercussion and durability. All patients were between 12 and 17 years of age. All of them were in school and doing their studies. Those cases that, despite meeting the criteria indicated, have not been able to access all the information necessary for their analysis because it is not included in their file have been excluded.
The time of the investigative analysis has been retrospective. Therefore, it is a longitudinal study in time that we have analyzed in the present with data from the past. We have analyzed the evolution of the student throughout his academic history until the moment in which he/she is hospitalized in serious condition. We have not taken into account the time after hospitalization. We have performed the analysis with the data collected up to the time of the onset of hospitalization. The analysis of the sample was carried out during the 2018–2019 school year in the Madrid Regional Authority.
We have taken into account, at all times, ethical principles consistent with scientific honesty and the protection of privacy in the cases analyzed [34]. The cases analysis was conducted by reviewing educational records opened for students hospitalized in a day care hospital working with adolescents with a SMD. In our research, we used secondary documents, not the real persons. We kept the anonymity of the cases throughout the whole research and did not ever use any real names. All cases were assigned a code so as to preserve anonymity. The educational director of the specialized center where the students are hospitalized authorized access to secondary reports. The reports were anonymized prior to submission for further analysis. We evaluated the data using a working matrix of a data sheet, which was the basis for analysis with SPSS. In this work matrix, we have added the data obtained from the reading of educational reports.
To conclude this section, we would like to point out, in relation to the conflict of interest, that the data collection was carried out by a member of the educational team working in the Day Hospital specialized in the care of students with SMD where the fieldwork was conducted. We consider that this element provided analytical depth and global vision to the development of the work.
In order to further develop our study, we drew upon a previous research. In that research, carried out under qualitative methodology, we inferred the main characteristics that define students with a SMD. This research used triangulation of in-depth interviews, questionnaires, and case analysis. More information can be found in [15]. This was the first step, but we could feel this investigation as the beginning of something that needed more depth of analysis. We also saw the need to use a larger sample with which to obtain greater rigor and statistical value. With this previous research, we verified that the model obtained was pertinent to the cases analyzed via a qualitative methodology. So, based on the data objected to in this previous research, we understand the present research have construct validity. It is also reliable, since it measures the relationship between variables that it claims to measure with statistical rigor – we explain this element in the next section. Once the sample is shaped, the next step was to define the variables to be used. Then, we have constructed a meaning for the variables, and we have established an observation map for completing the work matrix needed to develop this research. In the following section, we have read the educational reports of the selected students. The analyzed information was recorded in said files. With the reading of these reports, we have completed an ad hoc matrix. This statistical matrix synthesizes the description of the 109 cases observed, allowing us to reduce the complexity of the cases in qualitative terms to measurable and observable units. The records are made up of psycho-pedagogical reports and educational longitudinal information. This information provides data related to the evolution of the student throughout their educational career so far. Then, in relation to reliability, we affirm that we were able to access all the indicated information. Regarding the reliability of the coding of the observed variables, we have been looking for each variable in the report of each student. In the work matrix used, we marked whether it was met or not. Therefore, all the variables have been dichotomous, except for variable 14 – age – and variable 17 – when did the academic problems begin?. When the report did not provide the information needed, the case was dismissed.
Finally, the variables used and their statuses were as follows: (Table 1).
V1. | Accompanying family. We conceptualized this as a qualitative dichotomous variable: Family that accompanies positively in the therapeutic process of the child versus family that does not accompany positively. |
---|---|
V2. | Good bonding with the educational center. We conceptualized this as a qualitative dichotomous variable: has good school bonding versus poor school bonding. |
V3. | Academic success. The educational norm tells us that it is necessary to pass all but two subjects in order to move on to the next year. When the child is in this situation, we understand that he/she has achieved academic success. When the student has failed more than two subjects, we consider that he/she was not in a situation of academic success. We conceptualized this as a qualitative dichotomous variable. |
V4. | Sex. We have differentiated between female and male students. We conceptualized this as a qualitative dichotomous variable. |
V5. | They repeated some grade. We conceptualized this as a qualitative dichotomous variable: Repitieron algún grado frente a no repetir. |
V6. | Truancy/irregular assistance. We conceptualized this as a qualitative dichotomous variable: in the case of a student whose class attendance is not continued. |
V7. | Bad previous academic history. We conceptualized this as a qualitative dichotomous variable: bad previous school history versus good previous school history. |
V8. | Curricular lag. We considered this as a qualitative dichotomous variable: we have used the curricular lag as a variable that defines the level of educative competence that the student has in relation to their age. If the student has at least 1 year of curricular lag at least, we have understood that was pertinent to conceptualize the variable like positive. |
V9. | Good motivation toward study. We considered this as a qualitative dichotomous variable: has good study motivation versus does not have good study motivation |
V10. | Study habits. We considered this as a qualitative dichotomous variable: has study habits versus does not have study habits. |
V11. | Limited conceptual and procedural power/cognitive difficulties. Students with less procedural and conceptual skills have more difficulties and accumulated negative experiences in the educational context. This incidence in basic elements to participate in the dynamics of classroom-class predisposes students with serious mental disorders to have greater vulnerability in the educational context. This is because they do not meet the necessary skills to function in the methodological dynamics of a classroom. We considered this as a qualitative dichotomous variable. |
V12. | Attention difficulties. The attention difficulties are a circumstance present in many severe mental disorders. It is because, whether the disorder is externalizing or internalizing, the moment of the disorder marks the different. Being in a severe moment could involve having difficulties with attention due to circumstances such as problems arising from the disorder and medication, among others. We considered this as a qualitative dichotomous variable. |
V13. | Coexistence issues. We considered this as a qualitative dichotomous variable: presents coexistence problems versus does not present coexistence problems. |
V14. | Age. We considered this as a quantitative scale variable. |
V15. | Relational style (inhibited/uninhibited). We considered this as a qualitative dichotomous variable. |
V16. | Early detection. Early detection is a fundamental element to be able to conduct a good prognosis and minimize the impact of the disease on adulthood. We considered this as a qualitative dichotomous variable: has an early detection record versus does not have an early detection record. |
V17. | Onset of the educational issues. We considered this as a qualitative polychotomous variable. The ranges used were primary education, 1st year of secondary education, 2nd year of secondary education, 3rd year of secondary education, and 4th year of secondary education. |
V18. | Disorder typology. We conceptualized this as a qualitative dichotomous variable: externalizing versus internalizing. |
Variable.
A descriptive analysis of the quantitative variables yields the following data:
After collecting all the information on the work matrix, and identifying the items that apply to each participant in the sample, we used the exploratory factor analysis to conduct our research (Table 2). As this is a multivariate method that allows for reducing the dimensionality of a problem in a set of underlying variables, we considered it adequate for obtaining factors as a set of variables that allow us to understand the relationships between the variables previously described. Therefore, we looked for those factors that explain most of the common variance.
Statistics | |||
---|---|---|---|
Age | Academic problems begin | ||
N | Valid | 109 | 109 |
Missing | 0 | 0 | |
Mean | 14,69 | 1,05 | |
Std. deviation | 1296 | ,937 |
Academic problems begin.
We used an exploratory factor analysis with SPSS Statistics Mac software (v.20.0.0). For this analysis, we used all the variables that make up the study. After analyzing the correlation matrix, we decided on removing variables V4-Sex, V12-Difficulties of attention, and V16-Early detection. We noticed that, by removing them, we obtained a more adequate model, regardless of the values obtained from correlation, the level of Kaiser-Meyer-Olkin sample adequacy, and the significance of the Bartlett sphericity test. To make this decision, we have factored the analysis of communalities and the total value of the variance explained. Regardless of the variables used, we obtained communities close to and greater than .6, as well as better values for total variance. Also, we found greater explanatory coherence according to the theoretical model used, since our intention has been to reach the greatest possible objectivity through a reflective process in which, sometimes, the researcher has to distance himself/herself from the reality constructed by himself/herself [35]. We have ruled out that the variables can cause problems with collinearity because there are no values equal to or greater than 0.9 in the correlation matrix [36]. Finally, after dispensing with the variables indicated, we obtained a Kaiser-Meyer-Olkin sample adequacy result of .776 and significance in the Bartlett test p < .001. Since the Kaiser-Meyer-Olkin test is greater than 0.7, we can count this as a good value [37]. Bartlett’s sphericity test is <.05 and therefore significant. It indicates there are sufficient correlations between the variables to proceed. Given this data, we could say the factor analysis is relevant (Table 3).
Kaiser-Meyer-Olkin measure of sampling adequacy | .776 | |
---|---|---|
Bartlett’s test of sphericity | Approx. Chi-square | 721.333 |
df | 105 | |
Sig. | .000 |
Kaiser-Meyer-Olkin measure of sampling adequacy and Bartlett\'s test of sphericity.
Analysis of the anti-image correlation matrix through the sample adequacy measure shows that, once said variables are eliminated and we work with the chosen model, all the variables show high correlation. We have used the anti-image correlation matrix analysis because it is the most suitable for principal component analysis, and this is the method we have used. This method gives us a representation of variance for each variable explained by the factors. The data obtained in the table of communalities offer adequate extraction values, since they are close to or above 0.6 (Tables 4 and 5) [38].
V1 | V2 | V3 | V5 | V6 | V7 | V8 | V9 | V10 | V11 | V13 | V14 | V15 | V17 | V18 | ||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
V1 | .615 | −.164 | −.032 | −.018 | −.041 | −.107 | .090 | −.161 | .048 | −.115 | −.026 | .096 | .015 | .130 | −.065 | |
V2 | −.164 | .549 | −.109 | −.017 | .189 | .048 | −.019 | .072 | −.063 | .068 | .064 | .041 | −.078 | −.063 | .032 | |
V3 | −.032 | −.109 | .429 | .081 | .018 | .083 | −.044 | −.068 | −.094 | .025 | −.036 | .013 | .000 | .045 | −.067 | |
V5 | −.018 | −.017 | .081 | .540 | .007 | −.091 | −.025 | .031 | .037 | .000 | −.005 | .146 | −.052 | −.086 | −.066 | |
V6 | −.041 | .189 | .018 | .007 | .742 | −.061 | −.027 | −.038 | .042 | .071 | −.008 | .031 | −.061 | .041 | .115 | |
V7 | −.107 | .048 | .083 | −.091 | −.061 | .289 | −.155 | .060 | −.033 | .026 | .022 | .012 | .032 | −.105 | .003 | |
V8 | .090 | −.019 | −.044 | −.025 | −.027 | −.155 | .324 | −.003 | .048 | −.211 | .010 | −.057 | −.001 | .055 | −.007 | |
V9 | −.161 | .072 | −.068 | .031 | −.038 | .060 | −.003 | .397 | −.186 | .077 | .037 | .039 | −.048 | −.091 | −.010 | |
V10 | .048 | −.063 | −.094 | .037 | .042 | −.033 | .048 | −.186 | .418 | −.105 | −.015 | .001 | −.004 | .063 | .081 | |
V11 | −.115 | .068 | .025 | .000 −005 | .071 | .026 | −.211 | .077 | −.105 | .487 | .015 | .054 | −.078 | −.084 | .009 | |
V13 | −.026 | .064 | −.036 | −.005 | −.008 | .022 | .010 | .037 | −.015 | .015 | .353 | .023 | .161 | −.146 | −.162 | |
V14 | .096 | .041 | .013 | .146 | .031 | .012 | −.057 | .039 | .001 | .054 | .023 | .698 | .003 | −.191 | −.043 | |
V15 | .015 | −.078 | .000 | −.052 | −.061 | .032 | −.001 | −.048 | −.004 | −.078 | .161 | .003 | .447 | −.036 | .094 | |
V17 | .130 | −.063 | .045 | −.086 | .041 | −.105 | .055 | −.091 | .063 | −.084 | −.146 | −.191 | −.036 | .468 | .037 | |
V18 | −.065 | .032 | −.067 | −.066 | .115 | .003 | −.007 | −.010 | .081 | .009 | −.162 | −.043 | .094 | .037 | .436 | |
V1 | .632a | −.283 | −.062 | −.032 | −.061 | −.253 | .201 | −.327 | .094 | −.210 | −.057 | .147 | .029 | .243 | −.125 | |
V2 | −.283 | .795a | −.224 | −.031 | .296 | .120 | −.045 | .155 | −.132 | .132 | .145 | .067 | −.157 | −.124 | .065 | |
V3 | −.062 | −.224 | .882a | .168 | .032 | .234 | −.117 | −.164 | −.223 | .055 | −.092 | .024 | −.001 | .100 | −.155 | |
V5 | −.032 | −.031 | .168 | .878a | .011 | −.230 | −.060 | .066 | .079 | .000 | −.012 | .238 | −.107 | −.171 | −.137 | |
V6 | −.061 | .296 | .032 | .011 | .672a | −.131 | −.055 | −.070 | .075 | .118 | −.015 | .044 | −.106 | .069 | .203 | |
V7 | −.253 | .120 | .234 | −.230 | −.131 | .799a | −.507 | .178 | −.096 | .071 | .069 | .026 | .089 | −.286 | .008 | |
V8 | .201 | −.045 | −.117 | −.060 | −.055 | −.507 | .741a | −.009 | .131 | −.532 | .031 | −.120 | −.002 | .141 | −.020 | |
V9 | −.327 | .155 | −.164 | .066 | −.070 | .178 | −.009 | .799a | −.458 | .174 | .100 | .075 | −.115 | −.210 | −.024 | |
V10 | .094 | −.132 | −.223 | .079 | .075 | −.096 | .131 | −.458 | .820a | −.233 | −.040 | .002 | −.010 | .142 | .189 | |
V11 | −.210 | .132 | .055 | .000 | .118 | .071 | −.532 | .174 | −.233 | .646a | .037 | .092 | −.168 | −.176 | .019 | |
V13 | −.057 | .145 | −.092 | −.012 | −.015 | .069 | .031 | .100 | −.040 | .037 | .742a | .046 | .405 | −.358 | −.413 | |
V14 | .147 | .067 | .024 | .238 | .044 | .026 | −.120 | .075 | .002 | .092 | .046 | .748a | .005 | −.335 | −.078 | |
V15 | .029 | −.157 | −.001 | −.107 | −.106 | .089 | −.002 | −.115 | −.010 | −.168 | .405 | .005 | .803a | −.079 | .212 | |
V17 | .243 | −.124 | .100 | −.171 | .069 | −.286 | .141 | −.210 | .142 | −.176 | −.358 | −.335 | −.079 | .735a | .081 | |
V18 | −.125 | .065 | −.155 | −.137 | .203 | .008 | −.020 | −.024 | .189 | .019 | −.413 | −.078 | .212 | .081 | .762a | |
Measures of sampling adequacy (MSA) |
Matrix of anti-image correlations.
Initial | Extraction | |
---|---|---|
Accompanying family | 1.000 | .672 |
Good bonding with the educational center | 1.000 | .583 |
Academic success | 1.000 | .659 |
They have repeated some grade | 1.000 | .588 |
Truancy/irregular assistance | 1.000 | .657 |
Bad previous academic history | 1.000 | .771 |
Curricular lag | 1.000 | .730 |
Good motivation toward study | 1.000 | .570 |
Study habits | 1.000 | .614 |
Reduced conceptual and procedural power/cognitive difficulties | 1.000 | .692 |
Coexistence problems | 1.000 | .769 |
Age | 1.000 | .661 |
Relational style | 1.000 | .717 |
Disorder typology | 1.000 | .761 |
Onset of the educational issues | 1.000 | .570 |
Commonalities obtained through principal component analysis.
Extraction method: principal component analysis.
To determine the number of factors extracted, we took into account the initial self-values, the total of the explained variance, and the theoretical model. Looking at Table 6, we find that all four factors selected are above 1. Therefore, we have performed the factor analysis extracting four factors. Although with other models we obtained a higher percentage of the total variance explained, we consider the chosen model does a better job at explaining its representation from a theoretical point of view.
Initial autovalues | Extraction sums of squared loadings | Rotation sums of squared loadings | |||||||
---|---|---|---|---|---|---|---|---|---|
Component | Total | % of variance | Cumulative% | Total | % of variance | Cumulative % | Total | % of variance | Cumulative % |
1 | 4.880 | 32.536 | 32.536 | 4.880 | 32.536 | 32.536 | 3.238 | 21.584 | 21.584 |
2 | 2.607 | 17.381 | 49.916 | 2.607 | 17.381 | 49.916 | 2.827 | 18.846 | 40.429 |
3 | 1.355 | 9.034 | 58.950 | 1.355 | 9.034 | 58.950 | 1.997 | 13.315 | 53.745 |
4 | 1.172 | 7.813 | 66.763 | 1.172 | 7.813 | 66.763 | 1.953 | 13.019 | 66.763 |
5 | .911 | 6.073 | 72.836 | ||||||
6 | .764 | 5.096 | 77.932 | ||||||
7 | .627 | 4.181 | 82.113 | ||||||
8 | .506 | 3.372 | 85.485 | ||||||
9 | .445 | 2.964 | 88.449 | ||||||
10 | .433 | 2.885 | 91.333 | ||||||
11 | .343 | 2.289 | 93.622 | ||||||
12 | .300 | 2.001 | 95.623 | ||||||
13 | .270 | 1.799 | 97.422 | ||||||
14 | .231 | 1.540 | 98.962 | ||||||
15 | .156 | 1.038 | 100.000 |
Total variance explained with the first four factors.
Extraction method: principal component analysis.
In other words, we weighted the part of the common variance that enables us to explain these factors with greater theoretical sense. We therefore seek an interpretation that combines parsimony and plausibility [38].
The total accumulated variance value is 66.763%, which, together with the criteria described earlier, allows us to think about the model’s adequacy. As the value obtained is above .60%, we consider it appropriate [37] (Table 6).
The extraction method is the principal component analysis, while rotation type is orthogonal with the varimax method. We see each factor is represented by three or more variables; therefore, we consider that the model obtained meets moderate conditions for interpretation (Tables 7 and 8) [38].
Component | ||||
---|---|---|---|---|
1 | 2 | 3 | 4 | |
Accompanying family | −.439 | .011 | .652 | −.233 |
Good bonding with the educational center | −.624 | .090 | .263 | .341 |
Academic success | −.736 | −.262 | .146 | .166 |
They repeated some grade | .641 | .198 | .351 | −.119 |
Truancy/irregular assistance | .201 | .400 | −.268 | −.620 |
Previous academic history | .777 | .331 | .238 | −.034 |
Curricular lag | .650 | .462 | .248 | .181 |
Motivation toward study | −.751 | .016 | .075 | .001 |
Study habits | −.734 | .161 | .092 | .202 |
Reduced conceptual and procedural power/cognitive difficulties | .365 | .555 | .388 | .316 |
Coexistence problems | .434 | −.739 | .184 | −.017 |
Age | .411 | −.178 | −.452 | .506 |
Relational style | −.376 | .737 | −.113 | .138 |
Disorder typology | .327 | −.738 | .331 | −.016 |
Onset of the educational issues | .662 | −.084 | −.034 | .353 |
Matrix of main components.
Extraction method: principal component analysis. a. Four components extracted.
Component | ||||
---|---|---|---|---|
1 | 2 | 3 | 4 | |
Accompanying family | −.005 | .044 | .275 | |
Good bonding with the educational center | −.167 | −.276 | .262 | |
Academic success | −.509 | −.037 | .287 | |
They have repeated some grade | .205 | −.274 | .061 | |
Truancy/irregular assistance | .051 | −.286 | .135 | |
Bad previous academic history | .101 | −.334 | −.108 | |
Curricular lag | −.079 | −.125 | −.155 | |
Good motivation toward study | −.288 | .369 | .373 | |
Study habits | −.327 | −.420 | .279 | |
Reduced conceptual and procedural power/cognitive difficulties | −.241 | .152 | −.003 | |
Coexistence problems | .033 | −.023 | −.137 | |
Age | .069 | .125 | .056 | |
Relational style | .069 | .121 | .092 | |
Disorder typology | .038 | .085 | .009 | |
Onset of the educational issues | .467 | .289 | −.025 |
Rotated component matrix.
Extraction method: principal component analysis. Rotation method: varimax with Kaiser normalization. a. Rotation converged in six iterations.
We will focus our analysis on the rotated components matrix and not on the main components matrix. In this way, we obtain what is called the simple structure principle, achieving a better scientific interpretation of the obtained factors, since we give more importance to the variables that obtain greater weight in the obtained factors [39].
Analyzing the matrix of rotated components, we can see factor number 1 is formed by these variables:
V5. They have repeated some course.
V7. Bad previous school history.
V8. Curricular lag.
V9. Motivation toward study.
V11. Reduced conceptual and procedural power/cognitive difficulties.
We called this factor
Factor number 2, which we will call the
V18. Type of disorder.
V15. Relational style.
V13. Coexistence problems.
We can observe that, in all three cases, the weight of the variables in the factor is higher than 0.8, so we consider that their contribution is relevant.
Factor number 3, which we will call
V2. Good bonding with the educational center.
V3. Academic success.
V6. Truancy. Irregular assistance.
V10. Study habits.
Of the four variables that make up the factor, the best representations are V6 and V2. We can see the other variables have a lesser weight.
Finally, factor number 4 will consist of these variables:
V1. Accompanying family.
V14. Age.
V17. Onset of the academic issues.
We called this factor
Study limitations | Symptomatology representation | ||
---|---|---|---|
They have repeated some course Bad previous school history Curricular lag Motivation toward study Reduced conceptual and procedural power/cognitive difficulties | Type of disorder Relational style Coexistence problems | Good bonding with the educational center Academic success Truancy. Irregular assistance Study habits. | Accompanying family Age Onset of the academic issues |
Factors.
Beyond the mental disorder and knowing how it is represented, we have tried to understand how it is present in the educational environment. We believe that knowing how MSD is represented in the 109 cases analyzed can help us to deepen the understanding and establishment of compensation mechanisms in preventive terms [3]. Only by understanding and knowing the elements that define a reality in contextual terms, we can develop and implement educational measures that are empathetic [40].
Therefore, we wanted to look at the common elements the students with mental disorders show when in a severe condition. We used 18 variables to test them using the quantitative methodology. In the interpretation of the exploratory factor analysis that we have carried out, we have decided to dispense with the variables V4-Sex, V12-Attention Difficulties, and V16-Early Detection. Using these three variables, the factorial models obtained were less statistically consistent. Therefore, in making the decision not to include the three variables we have dispensed with in the proposed factor analysis, we have taken into account both the statistical data obtained and the theoretical framework. We put theory and data together to make a decision. In this way, we were able to obtain a more consistent factor model.
We observed that the variable V12 expresses a symptomatic value that mainly affects externalizing disorders. We were also able to observe that without this variable in the factor analysis, we obtained better statistical results. So given that its contribution to the model generated many doubts from a statistical point of view, and after reviewing the theoretical framework, we decided to eliminate this variable.
Regarding variable V16, we can see it defines a time frame from the clinical perspective. The analysis we are doing focuses on the educational field. In this sense, it must be said we already had another variable covering the moment in which the disorder visibly affects the educational environment, and that is variable V17 – when academic problems start. Thus, given the little representativeness obtained for the model by incorporating variable V16 and the weight of the interpretation carried out under the theoretical framework, we decided to continue without it.
Therefore we find that, when in a serious situation, students with mental disorders show a profile that could be defined by the following factors:
Study Limitations
Symptomatology Representation
Study Facilitators
Other Limitations.
The four factors obtained explain 66.763% of the total variance. Thus, we can affirm that the reduction to four factors gives us a satisfactory result.
With this research, we want to gain an in-depth understanding of the way in which mental disorder is represented in the educational environment through the 18 variables used in the population analyzed. We understand that, when implementing educational practices that serve students with severe mental disorders, we should think about working along four different lines. These intervention lines cannot be understood without the others; therefore, the practices to be implemented should involve specific actions in each of the indicated factors.
In this regard, we observe that the factor
Regarding the
The
With the factor
We consider this research as a descriptive approach that brings us closer to the object studied. In statistical terms, the exploratory factor analysis has been statistically relevant, since we obtained a Kaiser-Meyer-Olkin sample adequacy result of .776 and significance in the Bartlett test p < .001. In conceptual terms, we have been able to understand which are the factorial groups that condition the educational reality of a student with a serious mental disorder. These factors indicate the elements to work to help this population achieve academic success. On the other hand, they also point out the main risk factors that a student with a mental disorder could have. This would allow for preventive pedagogical practices. Therefore, we consider factor analysis to be informative for the data set.
Finally, we could have investigated in relation to the variables that predict school results in this population. We could also have analyzed the differences between students with externalizing disorders versus internalizing. Likewise, to know with certainty the adequacy of the information from the factor analysis for the data set, it is necessary to perform a confirmatory factor analysis. We are indicated these elements as limitations of the present investigation. We will investigate future research in relation to these elements.
Intro
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She is now a lecturer at the University of Witwatersrand, South Africa, and a principal researcher at the Health Economics and Epidemiology Research Office (HE2RO), South Africa. Dr. Moolla holds a Ph.D. in Psychology with her research being focused on mental health and resilience. In her professional work capacity, her research has further expanded into the fields of early childhood development, mental health, the HIV and TB care cascades, as well as COVID. She is also a UNESCO-trained International Bioethics Facilitator.",institutionString:"University of the Witwatersrand",institution:{name:"University of the Witwatersrand",country:{name:"South Africa"}}},{id:"419588",title:"Ph.D.",name:"Sergio",middleName:"Alexandre",surname:"Gehrke",slug:"sergio-gehrke",fullName:"Sergio Gehrke",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000038WgMKQA0/Profile_Picture_2022-06-02T11:44:20.jpg",biography:"Dr. Sergio Alexandre Gehrke is a doctorate holder in two fields. The first is a Ph.D. in Cellular and Molecular Biology from the Pontificia Catholic University, Porto Alegre, Brazil, in 2010 and the other is an International Ph.D. in Bioengineering from the Universidad Miguel Hernandez, Elche/Alicante, Spain, obtained in 2020. In 2018, he completed a postdoctoral fellowship in Materials Engineering in the NUCLEMAT of the Pontificia Catholic University, Porto Alegre, Brazil. He is currently the Director of the Postgraduate Program in Implantology of the Bioface/UCAM/PgO (Montevideo, Uruguay), Director of the Cathedra of Biotechnology of the Catholic University of Murcia (Murcia, Spain), an Extraordinary Full Professor of the Catholic University of Murcia (Murcia, Spain) as well as the Director of the private center of research Biotecnos – Technology and Science (Montevideo, Uruguay). Applied biomaterials, cellular and molecular biology, and dental implants are among his research interests. He has published several original papers in renowned journals. In addition, he is also a Collaborating Professor in several Postgraduate programs at different universities all over the world.",institutionString:null,institution:{name:"Universidad Católica San Antonio de Murcia",country:{name:"Spain"}}},{id:"342152",title:"Dr.",name:"Santo",middleName:null,surname:"Grace Umesh",slug:"santo-grace-umesh",fullName:"Santo Grace Umesh",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/342152/images/16311_n.jpg",biography:null,institutionString:null,institution:{name:"SRM Dental College",country:{name:"India"}}},{id:"333647",title:"Dr.",name:"Shreya",middleName:null,surname:"Kishore",slug:"shreya-kishore",fullName:"Shreya Kishore",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/333647/images/14701_n.jpg",biography:"Dr. Shreya Kishore completed her Bachelor in Dental Surgery in Chettinad Dental College and Research Institute, Chennai, and her Master of Dental Surgery (Orthodontics) in Saveetha Dental College, Chennai. She is also Invisalign certified. She’s working as a Senior Lecturer in the Department of Orthodontics, SRM Dental College since November 2019. She is actively involved in teaching orthodontics to the undergraduates and the postgraduates. Her clinical research topics include new orthodontic brackets, fixed appliances and TADs. She’s published 4 articles in well renowned indexed journals and has a published patency of her own. Her private practice is currently limited to orthodontics and works as a consultant in various clinics.",institutionString:null,institution:{name:"SRM Dental College",country:{name:"India"}}},{id:"323731",title:"Prof.",name:"Deepak M.",middleName:"Macchindra",surname:"Vikhe",slug:"deepak-m.-vikhe",fullName:"Deepak M. Vikhe",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/323731/images/13613_n.jpg",biography:"Dr Deepak M.Vikhe .\n\n\t\n\tDr Deepak M.Vikhe , completed his Masters & PhD in Prosthodontics from Rural Dental College, Loni securing third rank in the Pravara Institute of Medical Sciences Deemed University. He was awarded Dr.G.C.DAS Memorial Award for Research on Implants at 39th IPS conference Dubai (U A E).He has two patents under his name. He has received Dr.Saraswati medal award for best research for implant study in 2017.He has received Fully funded scholarship to Spain ,university of Santiago de Compostela. He has completed fellowship in Implantlogy from Noble Biocare. \nHe has attended various conferences and CDE programmes and has national publications to his credit. His field of interest is in Implant supported prosthesis. Presently he is working as a associate professor in the Dept of Prosthodontics, Rural Dental College, Loni and maintains a successful private practice specialising in Implantology at Rahata.\n\nEmail: drdeepak_mvikhe@yahoo.com..................",institutionString:null,institution:{name:"Pravara Institute of Medical Sciences",country:{name:"India"}}},{id:"204110",title:"Dr.",name:"Ahmed A.",middleName:null,surname:"Madfa",slug:"ahmed-a.-madfa",fullName:"Ahmed A. Madfa",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/204110/images/system/204110.jpg",biography:"Dr. Madfa is currently Associate Professor of Endodontics at Thamar University and a visiting lecturer at Sana'a University and University of Sciences and Technology. He has more than 6 years of experience in teaching. His research interests include root canal morphology, functionally graded concept, dental biomaterials, epidemiology and dental education, biomimetic restoration, finite element analysis and endodontic regeneration. Dr. Madfa has numerous international publications, full articles, two patents, a book and a book chapter. Furthermore, he won 14 international scientific awards. Furthermore, he is involved in many academic activities ranging from editorial board member, reviewer for many international journals and postgraduate students' supervisor. Besides, I deliver many courses and training workshops at various scientific events. Dr. Madfa also regularly attends international conferences and holds administrative positions (Deputy Dean of the Faculty for Students’ & Academic Affairs and Deputy Head of Research Unit).",institutionString:"Thamar University",institution:null},{id:"210472",title:"Dr.",name:"Nermin",middleName:"Mohammed Ahmed",surname:"Yussif",slug:"nermin-yussif",fullName:"Nermin Yussif",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/210472/images/system/210472.jpg",biography:"Dr. Nermin Mohammed Ahmed Yussif is working at the Faculty of dentistry, University for October university for modern sciences and arts (MSA). Her areas of expertise include: periodontology, dental laserology, oral implantology, periodontal plastic surgeries, oral mesotherapy, nutrition, dental pharmacology. She is an editor and reviewer in numerous international journals.",institutionString:"MSA University",institution:null},{id:"204606",title:"Dr.",name:"Serdar",middleName:null,surname:"Gözler",slug:"serdar-gozler",fullName:"Serdar Gözler",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/204606/images/system/204606.jpeg",biography:"Dr. Serdar Gözler has completed his undergraduate studies at the Marmara University Faculty of Dentistry in 1978, followed by an assistantship in the Prosthesis Department of Dicle University Faculty of Dentistry. Starting his PhD work on non-resilient overdentures with Assoc. Prof. Hüsnü Yavuzyılmaz, he continued his studies with Prof. Dr. Gürbüz Öztürk of Istanbul University Faculty of Dentistry Department of Prosthodontics, this time on Gnatology. He attended training programs on occlusion, neurology, neurophysiology, EMG, radiology and biostatistics. In 1982, he presented his PhD thesis \\Gerber and Lauritzen Occlusion Analysis Techniques: Diagnosis Values,\\ at Istanbul University School of Dentistry, Department of Prosthodontics. As he was also working with Prof. Senih Çalıkkocaoğlu on The Physiology of Chewing at the same time, Gözler has written a chapter in Çalıkkocaoğlu\\'s book \\Complete Prostheses\\ entitled \\The Place of Neuromuscular Mechanism in Prosthetic Dentistry.\\ The book was published five times since by the Istanbul University Publications. Having presented in various conferences about occlusion analysis until 1998, Dr. Gözler has also decided to use the T-Scan II occlusion analysis method. Having been personally trained by Dr. Robert Kerstein on this method, Dr. Gözler has been lecturing on the T-Scan Occlusion Analysis Method in conferences both in Turkey and abroad. Dr. Gözler has various articles and presentations on Digital Occlusion Analysis methods. He is now Head of the TMD Clinic at Prosthodontic Department of Faculty of Dentistry , Istanbul Aydın University , Turkey.",institutionString:"Istanbul Aydin University",institution:{name:"Istanbul Aydın University",country:{name:"Turkey"}}},{id:"256417",title:"Associate Prof.",name:"Sanaz",middleName:null,surname:"Sadry",slug:"sanaz-sadry",fullName:"Sanaz Sadry",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/256417/images/8106_n.jpg",biography:null,institutionString:null,institution:{name:"Istanbul Aydın University",country:{name:"Turkey"}}},{id:"240870",title:"Ph.D.",name:"Alaa Eddin Omar",middleName:null,surname:"Al Ostwani",slug:"alaa-eddin-omar-al-ostwani",fullName:"Alaa Eddin Omar Al Ostwani",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/240870/images/system/240870.jpeg",biography:"Dr. Al Ostwani Alaa Eddin Omar received his Master in dentistry from Damascus University in 2010, and his Ph.D. in Pediatric Dentistry from Damascus University in 2014. Dr. Al Ostwani is an assistant professor and faculty member at IUST University since 2014. \nDuring his academic experience, he has received several awards including the scientific research award from the Union of Arab Universities, the Syrian gold medal and the international gold medal for invention and creativity. Dr. Al Ostwani is a Member of the International Association of Dental Traumatology and the Syrian Society for Research and Preventive Dentistry since 2017. He is also a Member of the Reviewer Board of International Journal of Dental Medicine (IJDM), and the Indian Journal of Conservative and Endodontics since 2016.",institutionString:"International University for Science and Technology.",institution:{name:"Islamic University of Science and Technology",country:{name:"India"}}},{id:"42847",title:"Dr.",name:"Belma",middleName:null,surname:"Işik Aslan",slug:"belma-isik-aslan",fullName:"Belma Işik Aslan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/42847/images/system/42847.jpg",biography:"Dr. Belma IşIk Aslan was born in 1976 in Ankara-TURKEY. After graduating from TED Ankara College in 1994, she attended to Gazi University, Faculty of Dentistry in Ankara. She completed her PhD in orthodontic education at Gazi University between 1999-2005. Dr. Işık Aslan stayed at the Providence Hospital Craniofacial Institude and Reconstructive Surgery in Michigan, USA for three months as an observer. She worked as a specialist doctor at Gazi University, Dentistry Faculty, Department of Orthodontics between 2005-2014. She was appointed as associate professor in January, 2014 and as professor in 2021. Dr. Işık Aslan still works as an instructor at the same faculty. She has published a total of 35 articles, 10 book chapters, 39 conference proceedings both internationally and nationally. Also she was the academic editor of the international book 'Current Advances in Orthodontics'. She is a member of the Turkish Orthodontic Society and Turkish Cleft Lip and Palate Society. She is married and has 2 children. Her knowledge of English is at an advanced level.",institutionString:"Gazi University Dentistry Faculty Department of Orthodontics",institution:null},{id:"202198",title:"Dr.",name:"Buket",middleName:null,surname:"Aybar",slug:"buket-aybar",fullName:"Buket Aybar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/202198/images/6955_n.jpg",biography:"Buket Aybar, DDS, PhD, was born in 1971. She graduated from Istanbul University, Faculty of Dentistry, in 1992 and completed her PhD degree on Oral and Maxillofacial Surgery in Istanbul University in 1997.\r\nDr. Aybar is currently a full-time professor in Istanbul University, Faculty of Dentistry Department of Oral and Maxillofacial Surgery. She has teaching responsibilities in graduate and postgraduate programs. Her clinical practice includes mainly dentoalveolar surgery.\r\nHer topics of interest are biomaterials science and cell culture studies. She has many articles in international and national scientific journals and chapters in books; she also has participated in several scientific projects supported by Istanbul University Research fund.",institutionString:null,institution:{name:"Marmara University",country:{name:"Turkey"}}},{id:"178412",title:"Associate Prof.",name:"Guhan",middleName:null,surname:"Dergin",slug:"guhan-dergin",fullName:"Guhan Dergin",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/178412/images/6954_n.jpg",biography:"Assoc. Prof. Dr. Gühan Dergin was born in 1973 in Izmit. He graduated from Marmara University Faculty of Dentistry in 1999. He completed his specialty of OMFS surgery in Marmara University Faculty of Dentistry and obtained his PhD degree in 2006. In 2005, he was invited as a visiting doctor in the Oral and Maxillofacial Surgery Department of the University of North Carolina, USA, where he went on a scholarship. Dr. Dergin still continues his academic career as an associate professor in Marmara University Faculty of Dentistry. He has many articles in international and national scientific journals and chapters in books.",institutionString:null,institution:{name:"Marmara University",country:{name:"Turkey"}}},{id:"178414",title:"Prof.",name:"Yusuf",middleName:null,surname:"Emes",slug:"yusuf-emes",fullName:"Yusuf Emes",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/178414/images/6953_n.jpg",biography:"Born in Istanbul in 1974, Dr. Emes graduated from Istanbul University Faculty of Dentistry in 1997 and completed his PhD degree in Istanbul University faculty of Dentistry Department of Oral and Maxillofacial Surgery in 2005. He has papers published in international and national scientific journals, including research articles on implantology, oroantral fistulas, odontogenic cysts, and temporomandibular disorders. Dr. Emes is currently working as a full-time academic staff in Istanbul University faculty of Dentistry Department of Oral and Maxillofacial Surgery.",institutionString:null,institution:{name:"Istanbul University",country:{name:"Turkey"}}},{id:"192229",title:"Ph.D.",name:"Ana Luiza",middleName:null,surname:"De Carvalho Felippini",slug:"ana-luiza-de-carvalho-felippini",fullName:"Ana Luiza De Carvalho Felippini",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/192229/images/system/192229.jpg",biography:null,institutionString:"University of São Paulo",institution:{name:"University of Sao Paulo",country:{name:"Brazil"}}},{id:"256851",title:"Prof.",name:"Ayşe",middleName:null,surname:"Gülşen",slug:"ayse-gulsen",fullName:"Ayşe Gülşen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/256851/images/9696_n.jpg",biography:"Dr. Ayşe Gülşen graduated in 1990 from Faculty of Dentistry, University of Ankara and did a postgraduate program at University of Gazi. \nShe worked as an observer and research assistant in Craniofacial Surgery Departments in New York, Providence Hospital in Michigan and Chang Gung Memorial Hospital in Taiwan. \nShe works as Craniofacial Orthodontist in Department of Aesthetic, Plastic and Reconstructive Surgery, Faculty of Medicine, University of Gazi, Ankara Turkey since 2004.",institutionString:"Orthodontist, Assoc Prof in the Department of Aesthetic, Plastic and Reconstructive Surgery, Faculty of Medicine, University of Gazi",institution:null},{id:"255366",title:"Prof.",name:"Tosun",middleName:null,surname:"Tosun",slug:"tosun-tosun",fullName:"Tosun Tosun",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/255366/images/7347_n.jpg",biography:"Graduated at the Faculty of Dentistry, University of Istanbul, Turkey in 1989;\nVisitor Assistant at the University of Padua, Italy and Branemark Osseointegration Center of Treviso, Italy between 1993-94;\nPhD thesis on oral implantology in University of Istanbul and was awarded the academic title “Dr.med.dent.”, 1997;\nHe was awarded the academic title “Doç.Dr.” (Associated Professor) in 2003;\nProficiency in Botulinum Toxin Applications, Reading-UK in 2009;\nMastership, RWTH Certificate in Laser Therapy in Dentistry, AALZ-Aachen University, Germany 2009-11;\nMaster of Science (MSc) in Laser Dentistry, University of Genoa, Italy 2013-14.\n\nDr.Tosun worked as Research Assistant in the Department of Oral Implantology, Faculty of Dentistry, University of Istanbul between 1990-2002. \nHe worked part-time as Consultant surgeon in Harvard Medical International Hospitals and John Hopkins Medicine, Istanbul between years 2007-09.\u2028He was contract Professor in the Department of Surgical and Diagnostic Sciences (DI.S.C.), Medical School, University of Genova, Italy between years 2011-16. \nSince 2015 he is visiting Professor at Medical School, University of Plovdiv, Bulgaria. \nCurrently he is Associated Prof.Dr. at the Dental School, Oral Surgery Dept., Istanbul Aydin University and since 2003 he works in his own private clinic in Istanbul, Turkey.\u2028\nDr.Tosun is reviewer in journal ‘Laser in Medical Sciences’, reviewer in journal ‘Folia Medica\\', a Fellow of the International Team for Implantology, Clinical Lecturer of DGZI German Association of Oral Implantology, Expert Lecturer of Laser&Health Academy, Country Representative of World Federation for Laser Dentistry, member of European Federation of Periodontology, member of Academy of Laser Dentistry. Dr.Tosun presents papers in international and national congresses and has scientific publications in international and national journals. He speaks english, spanish, italian and french.",institutionString:null,institution:{name:"Istanbul Aydın University",country:{name:"Turkey"}}},{id:"260116",title:"Dr.",name:"Mehmet",middleName:null,surname:"Yaltirik",slug:"mehmet-yaltirik",fullName:"Mehmet Yaltirik",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/260116/images/7413_n.jpg",biography:"Birth Date 25.09.1965\r\nBirth Place Adana- Turkey\r\nSex Male\r\nMarrial Status Bachelor\r\nDriving License Acquired\r\nMother Tongue Turkish\r\n\r\nAddress:\r\nWork:University of Istanbul,Faculty of Dentistry, Department of Oral Surgery and Oral Medicine 34093 Capa,Istanbul- TURKIYE",institutionString:null,institution:{name:"Istanbul University",country:{name:"Turkey"}}},{id:"171887",title:"Prof.",name:"Zühre",middleName:null,surname:"Akarslan",slug:"zuhre-akarslan",fullName:"Zühre Akarslan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/171887/images/system/171887.jpg",biography:"Zühre Akarslan was born in 1977 in Cyprus. She graduated from Gazi University Faculty of Dentistry, Ankara, Turkey in 2000. \r\nLater she received her Ph.D. degree from the Oral Diagnosis and Radiology Department; which was recently renamed as Oral and Dentomaxillofacial Radiology, from the same university. \r\nShe is working as a full-time Associate Professor and is a lecturer and an academic researcher. \r\nHer expertise areas are dental caries, cancer, dental fear and anxiety, gag reflex in dentistry, oral medicine, and dentomaxillofacial radiology.",institutionString:"Gazi University",institution:{name:"Gazi University",country:{name:"Turkey"}}},{id:"272237",title:"Dr.",name:"Pinar",middleName:"Kiymet",surname:"Karataban",slug:"pinar-karataban",fullName:"Pinar Karataban",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/272237/images/8911_n.png",biography:"Assist.Prof.Dr.Pınar Kıymet Karataban, DDS PhD \n\nDr.Pınar Kıymet Karataban was born in Istanbul in 1975. After her graduation from Marmara University Faculty of Dentistry in 1998 she started her PhD in Paediatric Dentistry focused on children with special needs; mainly children with Cerebral Palsy. She finished her pHD thesis entitled \\'Investigation of occlusion via cast analysis and evaluation of dental caries prevalance, periodontal status and muscle dysfunctions in children with cerebral palsy” in 2008. She got her Assist. Proffessor degree in Istanbul Aydın University Paediatric Dentistry Department in 2015-2018. ın 2019 she started her new career in Bahcesehir University, Istanbul as Head of Department of Pediatric Dentistry. In 2020 she was accepted to BAU International University, Batumi as Professor of Pediatric Dentistry. She’s a lecturer in the same university meanwhile working part-time in private practice in Ege Dental Studio (https://www.egedisklinigi.com/) a multidisciplinary dental clinic in Istanbul. Her main interests are paleodontology, ancient and contemporary dentistry, oral microbiology, cerebral palsy and special care dentistry. She has national and international publications, scientific reports and is a member of IAPO (International Association for Paleodontology), IADH (International Association of Disability and Oral Health) and EAPD (European Association of Pediatric Dentistry).",institutionString:null,institution:null},{id:"172009",title:"Dr.",name:"Fatma Deniz",middleName:null,surname:"Uzuner",slug:"fatma-deniz-uzuner",fullName:"Fatma Deniz Uzuner",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/172009/images/7122_n.jpg",biography:"Dr. Deniz Uzuner was born in 1969 in Kocaeli-TURKEY. After graduating from TED Ankara College in 1986, she attended the Hacettepe University, Faculty of Dentistry in Ankara. \nIn 1993 she attended the Gazi University, Faculty of Dentistry, Department of Orthodontics for her PhD education. After finishing the PhD education, she worked as orthodontist in Ankara Dental Hospital under the Turkish Government, Ministry of Health and in a special Orthodontic Clinic till 2011. Between 2011 and 2016, Dr. Deniz Uzuner worked as a specialist in the Department of Orthodontics, Faculty of Dentistry, Gazi University in Ankara/Turkey. In 2016, she was appointed associate professor. Dr. Deniz Uzuner has authored 23 Journal Papers, 3 Book Chapters and has had 39 oral/poster presentations. She is a member of the Turkish Orthodontic Society. Her knowledge of English is at an advanced level.",institutionString:null,institution:null},{id:"332914",title:"Dr.",name:"Muhammad Saad",middleName:null,surname:"Shaikh",slug:"muhammad-saad-shaikh",fullName:"Muhammad Saad Shaikh",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Jinnah Sindh Medical University",country:{name:"Pakistan"}}},{id:"315775",title:"Dr.",name:"Feng",middleName:null,surname:"Luo",slug:"feng-luo",fullName:"Feng Luo",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Sichuan University",country:{name:"China"}}},{id:"344229",title:"Dr.",name:"Sankeshan",middleName:null,surname:"Padayachee",slug:"sankeshan-padayachee",fullName:"Sankeshan Padayachee",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of the Witwatersrand",country:{name:"South Africa"}}},{id:"315727",title:"Ms.",name:"Kelebogile A.",middleName:null,surname:"Mothupi",slug:"kelebogile-a.-mothupi",fullName:"Kelebogile A. Mothupi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of the Witwatersrand",country:{name:"South Africa"}}},{id:"423519",title:"Dr.",name:"Sizakele",middleName:null,surname:"Ngwenya",slug:"sizakele-ngwenya",fullName:"Sizakele Ngwenya",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of the Witwatersrand",country:{name:"South Africa"}}},{id:"337613",title:"Mrs.",name:"Tshakane",middleName:null,surname:"R.M.D. Ralephenya",slug:"tshakane-r.m.d.-ralephenya",fullName:"Tshakane R.M.D. Ralephenya",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of the Witwatersrand",country:{name:"South Africa"}}},{id:"419270",title:"Dr.",name:"Ann",middleName:null,surname:"Chianchitlert",slug:"ann-chianchitlert",fullName:"Ann Chianchitlert",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Walailak University",country:{name:"Thailand"}}},{id:"419271",title:"Dr.",name:"Diane",middleName:null,surname:"Selvido",slug:"diane-selvido",fullName:"Diane Selvido",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Walailak University",country:{name:"Thailand"}}},{id:"419272",title:"Dr.",name:"Irin",middleName:null,surname:"Sirisoontorn",slug:"irin-sirisoontorn",fullName:"Irin Sirisoontorn",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Walailak University",country:{name:"Thailand"}}}]}},subseries:{item:{id:"40",type:"subseries",title:"Ecosystems and Biodiversity",keywords:"Ecosystems, Biodiversity, Fauna, Taxonomy, Invasive Species, Destruction of Habitats, Overexploitation of Natural Resources, Pollution, Global Warming, Conservation of Natural Spaces, Bioremediation",scope:"