Physical parameters of the soil of slope applied to slope stability analysis.
\r\n\tEqually important are the consequences deriving from the extraordinary nature of the present times. The COVID-19 pandemic and the restrictive measures to contain the infection (lockdown and "physical distancing" in primis) have revolutionized the lives, and a distortion/modification of habits, rhythms, arrangements will continue to be necessary.
\r\n\tGovernments have implemented a series of actions to mitigate the spread of infections and alleviate the consequent pressure on the hospital system. On the other hand, the Covid-19 pandemic has caused a series of other cascading effects that will probably be much more difficult to mitigate and which expose to complex consequences. The past two years have brought many challenges, particularly for healthcare professionals, students, family members of COVID-19 patients, people with mental disorders, the frail, the elderly, and more generally those in disadvantaged socio-economic conditions, and workers whose livelihoods have been threatened. Indeed, the substantial economic impact of the pandemic may hinder progress towards economic growth as well as progress towards social inclusion and mental well-being.
\r\n\t
\r\n\tAlthough in all countries the knowledge on the impact of the pandemic on mental health is still limited and mostly derived from experiences only partially comparable to the current epidemic, such as those referring to the SARS or Ebola epidemics, it is likely that the demand for intervention it will increase significantly in the coming months and years. The extraordinary growth of scientific research in the field of neuroscience now offers the possibility of a new perspective on the relationship between mind and brain and generates new scenarios in understanding the long wave of the pandemic and in the prospects for treatment. Moreover, the pandemic also has led to opportunities to implement remote monitoring and management interventions.
\r\n\t
\r\n\tOverall this volume will address the complex relationship existing between COVID-19, mental health, acquired knowledge, and possible interventions taking a highly multidisciplinary approach; from physiological and psychobiological mechanisms, and neuromodulation through medical treatment, psychosocial interventions, and self-management.
Recently, there have been many natural disasters due to climate change. In particular, slope failure in urban areas has caused loss of lives and of property [1]. The causes of slope failures around the world are intense rainfall, rapid snowmelt, water level changes in rivers or lakes at the foot of slopes, volcanic eruptions, and earthquakes [2]. In the type of slope failure, Soil slope mainly was occurred a deep circular failure and a shallow plane failure. The failure of the rock slope is caused by activity, overturning, and rockfall. In addition, there is debris flow and creep in soft ground [3].
The types of slope failure are determined by the composting materials and exterior conditions of slope. The shear strength of slope soil is decreased as time goes by, especially time-dependent deterioration of cut-slope would greatly happen after excavation. These cut-slopes are degraded in strength by time-deterioration phenomenon, and progressive slope failure is caused.
A time-dependent deterioration of soil owing to external environmental change causes progressive slope failure and the traditional analysis of limit equilibrium stability has limitations for an appropriate analysis of the stability [4]. The analysis of progressive slope failure requires finite element analysis that is capable of analyzing the creation and progression of shearing zone [5, 6, 7]. The behavior of progressive slope failure can be evaluated through the finite element analysis. Besides, for the analysis of the slope stability, the calculation of safety factor is needed. Zeinkiewicz, et al. [8] have proposed the strength reduction method to calculate the safety factor through finite element analysis and the proposition was followed by many subsequent studies conducted by many researchers [9, 10, 11]. Recently, there has been many studies unsaturated slope stability analysis induced by rainfall infiltration [12, 13, 14, 15, 16]. In general, rainfall-induced slope failures are caused by increased pore pressure and seepage force during periods of intense rainfall [17, 18]. The factor of safety on the slope is calculated by the equilibrium equation of the force of the failure surface. The pore pressure acting as an active force on the failure surface is increased by seepage of rainfall, and the slope is collapsed when it is larger than the resistance force.
The slope behaviors and exterior environment should be measured continuously to maintain slope. The slope behavior is measured by inclinometer, electro-optical wave distance measuring instrument, groundwater level meter etc., also, the exterior environments, rainfall and temperature are measured by the weather station. The various management criteria of the sensors are developed based on mathematical or statistical methods; the slope reinforcement be done if the management criteria [19]. However, the developments of perfect safety factors and management criteria are very difficult from the analysis of measured data in slope.
In Korea, a lot of researches were done for cut-slope management near roadway [20, 21, 22]. The displacements of cut-slope were measured by tension wire, and the data were analyzed by the statistical process control (SPC) method. However, it confirm only the abnormal behaviors of slopes, the factor of safety (FOS) of slope cannot be calculated, therefore, the application of slope reinforcement methods are determined according to extra slope stability analysis.
Also, many studies had also been carried out to predict the time of the failure of slope through displacement velocity [1, 23, 24, 25, 26, 27, 28]. The researchers have used the inverse-velocity obtained from measurements to predict the time of the slope failure and verified respective applications of the inverse-velocity through actual cases of the slope failure and experiments. However, in cases of slopes, the prediction of the time of the slope failure by using the inverse-velocity curve derived from such measurement is quite difficult because the behavioral aspects of such slope are diverse and the failure surface has to be assumed. So far, the slope stability analysis methods only estimate the FOS of slope and, maintenance methods based on the measured data do not provide clear management criteria. For these reasons, efficient maintenance and prevention of slope failure in urban areas have not been achieved. To solve this problem, the integrated analysis methods of slope stability analysis and maintenance for progressive slope failure due to time-dependent deterioration should be developed.
This study developed an integrated analysis method for stability analysis and maintenance of cut-slopes in urban. The integrated analysis method for this research treated cut-slope and the failure-inducing factor was considered the shear strength decrease (SRF) by time-dependent deterioration was considered as inducing factor of slope failure. The strength variation of soil slope happens continuously from the variation of weather conditions and infiltration of rainfall. Also, measuring the slope displacements is easier then sensing the capillary force and water content of slope. Therefore, for this research, the slope displacements to progressive failure were calculated, then they were analyzed and applied to criteria of displacements sensing.
To link the slope stability analysis with the maintenance method based on the measured data, the displacement until the slope failure to the finite element model was analyzed and applied to the maintenance method. A flowchart of the integrated analysis method was presented and a case study was conducted. The slope stability analysis was performed by generating a finite element model and, the time-dependent deterioration of slope was quantified by applying the SRF to the strength parameter of the soil. The FOS was calculated by the stress analysis method (SAM) of the finite element model, and the behavior up until slope failure was analyzed by nonlinear static analysis with
The limit equilibrium method (LEM), a deterministic method, compares the shear stress and shear strength applied to assumed the failure surface of slope to present the FOS. However, because the limit equilibrium analysis provides only the minimum of FOS as the analytic result, it cannot present appropriate safety factor applicable to the analysis of progressive slope failure attributable to concurrent continuous displacement induced by a time-dependent deterioration of soil.
The finite element method can provide the measurement system for the maintenance of slope with proper analytic results. It also is an appropriate method to analyze the behavior of progressive slope failure [29]. The progressive slope failure has been examined through the finite element method. Zeinkiewicz, Humpheson and Lewis [8] had presented the strength reduction method that employed the SRF by which the safety factor was calculated as in the case of limit equilibrium analysis. Thereafter, Griffiths [10] had applied the strength reduction method to his analysis of progressive behavior of slope according to diverse soil conditions and geometries and verified the analytical method through comparative analyses with the chart (s) presented by Bishop and Morgenstern [30].
The SAM is a combination of the advantages of simple limit equilibrium method (LEM) and of finite element method (FEM), the advanced method. The stress state in slope is analyzed through finite element analysis, and the FOS of virtual active surfaces of the limit equilibrium analysis are calculated. Thereafter, the minimum of FOS and critical section among active surfaces in the limit equilibrium analysis are calculated. In the finite element analysis, the model of the material constituting the soil will use the Mohr-coulomb yield criteria identical to the failure criteria used in the limit equilibrium analysis.
The FOS of the slope to be determined by the stress analysis method is as expressed in the following Eq. (1).
Here,
The FEM can analyze the slope behavior until failure, and if the SRF is applied, it also can quantify the time-dependent deterioration of slope. However, until now the FEM is not used for analyzing and comparing to the measured displacement data of slope.
The representative method used for the domestic maintenance of slope is the statistical process control (SPC) method broadly employed in manufacturing industries to reduce the level of defects of commercial products. The population for the SPC for the maintenance of slope is a set of measurements of the displacement of slope. The values of the mean and standard deviation of the population is used to judge the stability of slope statistically according to respective values plotted on the region beyond or within the control limit determined by the control chart. By using the control chart, the anomaly in the stability of slope can be found easily.
The method above uses the
The control limit and centerline of the
Where, the constant
The control limit and centerline of the
Where, the constants
KICT [20] applied the measured data of real slope to SPC method. After that, Yoo [22] proposed a statistical decision algorithm for maintenance of the slope based on the measured data. Therefore, it is necessary to calculate the management criteria of statistical process control method by integrating it with the finite element analysis which can simulate the failure of the slope.
To predict the time of the slope failure, diverse models employed the correlation between the time and the displacement varying according to the creep behavior of bedrock have been proposed [25, 31]. Since such models were difficult to apply to the prediction of the slope failure as a generalized model, Fukuzono [1] proposed the model of inverse-velocity expressing the changing characteristics of ground displacement as the relationship between time and inverse-velocity. The proposed inverse-velocity model was derived by using the measurements of varying acceleration obtained from the large-scaled actual experiment simulated an artificial landslide. Fukuzono [1] proposed the time of the slope failure as expressed in the following Eq. (4) by taking the trend line of inverse-velocity approaching 0 in accordance with the increasing velocity of displacement into account.
Here,
To exploit the advantage of the value of inverse-velocity becoming 0 at the time of the slope failure, the relevance between time and inverse-velocity has been widely used [32, 33]. Petley, Bulmer and Murphy [32] have analyzed the patterns of trend lines of the cases the slope failure however, since the patterns were analyzed from the measurements of the displacement after the failure of faces of slopes, it would be very difficult to get actual real-time prediction of the time of failure. Therefore, an analysis on the pattern of inverse-velocity curve at the design stage is needed to predict the time of the slope failure in the stage of performing maintenance works based on measurements. Thus, in this study, the procedure to analyze the progressive slope failure was presented in a way to link the procedure to the maintenance methods based on actual site measurements.
Figure 1 is an integrated analysis method for stability analysis and maintenance of cut-slopes.
Mesh and boundary conditions of slope stability analysis.
The integrated analysis method presented in this study is divided into 14 steps. It is divided into three sections. In the first section, the geometric of the slope and the finite element model of FEM are generated. And, to consider the time-dependent deterioration, the SRF is applied to the strength parameter of the soil (step 1 ∼ 3). The integrated analysis method proposed in this study is based on the cut-slope and only the strength degradation caused by the time-dependent deterioration is taken into consideration. The proposed method can be used both as soil and rock as a material of cut slope, but the only soil is considered in this study.
In the second section, slope stability analysis is performed using FEM. The FOS is calculated by the SAM and the behavior up to the slope failure is analyzed by the nonlinear static analysis with
In the last section, the results of the slope stability analysis are applied to the maintenance method. A typical sensor used for slope maintenance is an in-site inclinometer, which is applied to SPC using slope stability analysis results at the same point. Next, a mathematical failure model of the slope was predicted using a cumulative displacement curve. And the time of the slope failure was predicted using an inverse-velocity curve and, compared the formulation of Fukuzono [1]. Finally, the collapse behavior of Selborne in the United Kingdom and Kunini Slope in Japan, as reported by Petley [34], was compared.
Figure 2 in this study improves the problem of the slope stability analysis method that only estimates the FOS and, the problem of maintenance method that fails to evaluate clear management criteria and failure behavior of slope. It also combines the advantages of slope stability analysis and maintenance method based on measured data [35, 36]. Slope stability analysis is used to determine the failure behavior and FOS of the slope. And, it can be applied to the maintenance method to predict the management criteria of statistical process control method, a mathematical failure model of slope, and the time of slope failure.
A flowchart on integrated analysis methods of slope stability analysis and maintenance of the slope.
In the maintenance of the slope, the surface displacement is usually tension wire, and the ground displacement is the inclinometer. Because the displacement of the entire slope is analyzed using the FEM, that can be applied to the management criteria of the displacement measuring instrument installed on the slope. In particular, the displacement at the crown of the slope is very important, which can be measured both by tension wire and inclinometer. There are two maintenance methods presented in this study. First, the failure model is calculated by the cumulative displacement curve of the slope. And the displacement according to the depth is applied to the SPC method to judge the occurrence of abnormal behavior of the slope. If only tension wire is applied to the maintenance of the slope, the formation of the failure surface cannot be confirmed because only the surface displacement of the slope can be measured. Because the inclinometer measures the displacement of the whole underground, it has an advantage that it can easily judge the failure surface. Therefore, the inclinometer was applied to the slope instrument in this study. Please refer to KICT [20] for the advantages and disadvantages of both measurement devices.
In this section, detailed description is given for each step according to the flowchart shown in Figure 2. The details are as follows:
Step 1: This is the step of generating the geometry and mesh of the slope. And the load and boundary conditions acting on the slope. In general, only self-weight is considered. Please refer to the literature on FEM [10, 11, 29].
Step 2: In the FEM, the soil uses the Mohr-coulomb model. The soil investigation is performed to calculate the cohesive and internal friction angle, which are the strength parameters of the soil.
Step 3: The strength parameters of soil are to be decreased according to the SRF, and the cohesion of soil at the point of failure and the internal friction angle are as expressed in Eqs. (5) and (6), respectively. In the case where the SRF is used, the value of initial strength reduction factor (SRF) and the value of increment should be determined. The values of 1.0 and 0.05 of the strength factor and increment are frequently applied to the method of general strength reduction. The final strength reduction coefficient will be a value at the stage failed to converge in the nonlinear static analysis.
where,
Step 4: To conduct the finite element analysis, the calculation of initial underground stress of slope is important and, the value is calculated under the
Step 5: Based on the calculated initial underground stress of the slope, the FOS is calculated through the SAM [37]. In this case, the decrease in the value of safety factor is identified through an iterative analysis to be conducted according to the reduced strength parameter, and the failure surface will be applied to it as in the case of limit equilibrium analysis.
Step 6: The nonlinear static analysis will be conducted to analyze the behaviors of progressive slope failure. The iterative analysis should be continued until the value fails to converge (=until the occurrence of failure) according to the stages of each strength reduction factor.
Step 7: The displacement resulted from the progressive slope failure is identified through the iterative analysis conducted according to the strength reduction.
Step 8: After completing the calculation of cumulative displacement curve of the points of maximum displacement on slope through following the process in Step 7 above, the obtained results should be linked to the plan of the measurement of slope.
Step 9: The failure model of slope is created by using the velocity curve made from the analytic results and then it will be compared with the cumulative displacement curve made from the measurements collected through the stages of maintenance of the slope.
Step 10: In this step, plot an inverse-velocity curve for predict the time of slope failure.
Step 11: From this stage, the results of the slope stability analysis are applied to the maintenance method. In step 11, the displacement calculated at the point where the in-place inclinometer is installed is applied to the statistical process control method. And judges whether the management criteria is exceeded by depth of slope. Finally, determine whether the slope failure behavior is occurring and the location of the failure surface.
Step 12: In this step, we calculate the mathematical failure model of the slope. The calculated mathematical failure model is used as a reference for the displacement results measured by the in-place inclination.
Step 13: In this step, first order linear equation is calculated by regression analysis of velocity curve of the slope. It is difficult to derive a clear engineering meaning like the accumulated displacement curve of step 12 and the inverse-velocity curve of step 14. Therefore, if the slope failure happens, the measured displacement velocity curve changes into the 1st-degree polynomials. It means the slope displacement velocity turns into invariable velocity, and it is estimated that the slope failure happens. Therefore it could be important criterion for slope maintenance.
Step 14: This stage predicts the time of slope failure in slope maintenance. Curve fitting is performed by regression analysis of the inverse-velocity curve by slope stability analysis. According to the existing literature, slopes with ductile behaviors are a third polynomial equation and slopes with brittle behavior are a linear equation. Regression analysis results are also compared with Fukuzono [1]‘s slope failure prediction formula.
In the first section, the geometric of the slope and the finite element model of FEM are generated. And, to consider the time-dependent deterioration, the SRF is applied to the strength parameter of the soil (step 1 ∼ 3).
For the slope stability analysis of the progressive behavior of slope, the geometry and meshes of the finite slope of 10.0 m in height and 1: 1.2 of standard slope were created (Figure 1). For this research, the cut-slope modeling is obliged the standard height and incline suggested by the design manuals [19, 38]. The displacements until progressive failure analyzed FEM are compared to the measured data, the criteria come from the inclinometer data.
The boundary condition of left and right side is dx = 0 and same as roller. The boundary condition of the floor is dz. = 0, which is the same as the hinge. The load applied only its own gravity. In the finite element model, the element at the point where the in-place inclinometer is installed should be identified.
The Mohr-coulomb model was selected for the FEM for which the internal friction angle
Parameter | Case 1 | Case 2 |
---|---|---|
19.0 | 19.0 | |
E (kPa) | 40,000 | 40,000 |
0.28 | 0.28 | |
30.0 | 40.0 | |
10.0 | 0.0 | |
0.0 | 0.0 |
Physical parameters of the soil of slope applied to slope stability analysis.
The soil slope behaviors are largely divided into two categories; firstly, ductible behavior in case of small particle soils, at second, brittle behavior in case of coarse particle soils. Mohr-coulomb model is used to analyze those two cases, which is the elastic-perfect plastic model. The case 1 is for the ductile behavior of slope, whose cohesion value is applied as 10 kPa to show the behavior small soil particles. The case 2 is for the brittle behavior of slope, whose cohesion value is 0 kPa to show the brittle slope behavior of coarse soil particles.
The soil of Case 1 has a cohesive of 10 kPa and an internal friction angle of 30 degrees. The soil of Case 2 has a cohesive of 0 kPa and an internal friction angle of 40 degrees. The slope of Case 1 shows the ductility behavior due to the cohesive of soil, and the slope of Case 2 shows the brittle behavior because the soil has no cohesive and the internal friction angle is large. The analytical results are compared according to the material characteristics of these slopes.
In step 3, the time-dependent deterioration of slope was quantified by applying the SRF to the strength parameter of the soil. The strength parameters of the slope shown in Table 1 were reduced according to the SRF as shown in Figure 3. The slope stability analysis is performed with the reduced strength parameters, and iterative analysis is performed until it is not converged. If it does not converge, the slope has collapsed in the finite element analysis. Until now, the modeling is identical to that of the usual strength reduction factor (SRF) method of slope stability analysis. [8, 39, 40].
Variation of the strength parameters of slope according to strength reduction factor.
In the second section, and slope stability analysis using finite element model. The FOS is calculated by the stress analysis method (SAM) and the behavior up to the slope failure is analyzed by the nonlinear static analysis with
In this step, slope stability analysis is performed using the finite element model generated in the first section. In slope stability analysis using FEM, it is very important to estimate the stress distribution in the slope. In Step 5, the initial stress distribution of slope is estimated at
The results of slope stability analysis in the slope of case 1; (a) factor of safety, (b) SRC vs. displacement curve, (c) SRC vs. velocity curve, (d) SRC vs. inverse velocity curve.
The results of slope stability analysis in the slope of case 2; (a) factor of safety, (b) SRC vs. displacement curve, (c) SRC vs. velocity curve, (d) SRC vs. inverse velocity curve.
Figure 6 is the distribution of displacement and shear strain by finite element analysis under slope failure condition in the slope of case 1. The legend in Figure 6(a) shows the amount of displacement, and in Figure 6(b) shows the effective shear strain. When the slope stability analysis is performed by the proposed method, the behavior up to the progressive failure of the slope can be analyzed. The distribution of shear strain can predict the failure surface of the slope. One of the greatest advantages is that the failure surface can be estimated by the finite element analysis in the slope consist of the continuous soil. Step 7 is the same as the general procedure for slope stability analysis using finite element analysis. In this study, only 2D finite element analysis was performed. Three-dimensional analysis is also possible. For finite element analysis using the SRF, see the paper by Wei, et al. [40].
Distribution of displacement and shear strain by finite element analysis under slope failure condition (case 1).
In the third stage, the displacements until the slope failure analyzed using the slope stability analysis plot the cumulative displacement curve, velocity curve, and inverse velocity curve and, applied to the maintenance methods of the slope. In the finite element analysis, the displacements of all nodes are calculated in the finite element model of the slope. Here, only the displacement of the node at the point where the displacement meter such as an inclinometer or a tension wire is installed is used. In particular, the displacement at the crown of the slope is most important. Therefore, in this stage, a graph was created by displacement at the crown of the slope.
Figure 4 shows the result of slope stability analysis in the slope of case 1. Above all, the FOS was calculated by using the stress analysis method and then, the cumulative displacement curve, the displacement velocity curve, and the displacement inverse-velocity curve was plotted to illustrate the displacement of the upper part of the slope. Figure 4(a) Represents the reduction in safety factor resulted from the stress analysis. The FOS was 1.0 when the SRF was 1.0 and the FOS reached 1.0 when the SRF was 1.5. The calculated displacement at each stage of reduced strength is as illustrated in Figure 4(b)–(d). In the cumulative displacement curve plotted in Figure 4(b), the rapid progression of displacement, initiated at the stage of 1.6 of strength reduction factor and then evolved rapidly after the stage of 2.0 of SRF, is illustrated. The failure model of the slope was calculated as in the following 3rd order polynomial equation:
Figure 5 shows the result of slope stability analysis in the slope of case 2. Figure 5(a) shows the change of FOS according to SRF. Compared with case 1, the decreasing slope was more moderate. When SRF was 1.0, FOS was 1.27, which was smaller than case 1. When SRF was 1.5, FOS reached 1.0 and was the same as case 1. In the cumulative displacement curve plotted in Figure 5(b), compared to that in the case 1 (Figure 4(b)), the displacement proceeded continuously from the initial stage and the displacement increased rapidly after the stage of 1.6 of the strength reduction factor. The failure model of the slope was calculated as in the following 3rd order polynomial equation:
In the last section, the results of the slope stability analysis are applied to the maintenance method. For the maintenance of the slope, the displacement of the slope is measured by tension wire or inclinometer. However, no technique has been proposed to determine management criteria. The typical sensor used for slope maintenance is an in-site inclinometer, which is applied to statistical process control using slope stability analysis results at the same point. The displacement at each depth measured in the inclinometer can be calculated by applying the SPC method to the upper and lower control limits (UCL, LCL). If the displacement exceeds this management criterion, an abnormal behavior has occurred. Next, a mathematical failure model of the slope was predicted using a cumulative displacement curve. The cumulative displacement data of the slope measured over time are compared with the behavior up to the failure estimated by the finite element analysis. This can qualitatively determine whether the slope is causing the failure behavior. And the time of the slope failure was predicted using an inverse velocity curve and, compared the formulation of Fukuzono [1].
The inverse-velocity curve is a method of predicting the time of failure of the slope. If the measured inverse-velocity curve shows this pattern, it can be predicted the time of slope failure. Finally, the collapse behavior of Selborne in the United Kingdom and Kunini Slope in Japan, as reported by Petley [34], was compared.
In step 11, the displacement calculated at the point where the in-place inclinometer is installed is applied to the statistical process control method. In the finite element analysis, the displacement of the entire slope is estimated. Depending on the SRF, the displacement at the point where the inclinometer is installed can be estimated. The SPC method determines the abnormal behavior at the point where the inclinometer is installed, as described in Section 2.2. This abnormal region appears when a failure surface is formed due to the progressive behavior of the slope. SPC method can be statistically evaluated and have the advantage of setting upper and lower control limits. Finally, determine whether the slope failure behavior is occurring and the location of the failure surface.
The in-place inclinometer measures the displacement of the ground at intervals of 1.0 m. From the results of the slope stability analysis, the displacements at each depth were analyzed at intervals of 1.0 m as shown in Figure 1. The calculated displacement is applied to the statistical process control method as shown in Figure 7. The depth of the horizontal axis shows the depth from the ground surface. The vertical axis shows the displacement of the slope. Figure 7(a) shows that when the strength reduction factor is 1.6, Figure 7(b) is 1.7, Figure 7(c) is 1.8, Figure 7(d) is 1.9, Figure 7(e) is 2.0 and Figure 7(f) is 2.075. Figure 7(a) shows the case where the strength reduction factor is 1.6, and the displacement at all depths does not exceed the management criteria of upper control limit. Figure 7(d) shows that the strength reduction factor is 1.9 and exceeds the management criteria of upper control limit. From this time, a failure surface of the slope was formed. By applying the SPC method, it is possible to judge the failure behavior of the slope and the generation of the failure surface.
In this Step 12, a mathematical model of slope failure is predicted by the displacement result of the slope stability analysis. As shown in Step 11, the displacement up to the slope failure at the point where the in-place inclinometer is installed is used.
Figure 8 shows the mathematical failure model using the cumulative displacement curves for each depth. The largest displacement occurs on the ground surface, and the displacement is hardly generated below the failure surface of the slope. The location of the failure surface can be determined in step 4 through the slope stability analysis, as shown in Figure 6(b). As shown in Figure 8(f), little displacement occurred at the 5.0 m depth, because it exists below the failure surface of the slope.
The mathematical failure model using the cumulative displacement curves for each depth (case 1).
The cumulative displacement curve through slope stability analysis can be applied as a management criterion for the measured data of the in-place inclinometer.
This stage predicts the time of slope failure in slope maintenance. Curve fitting is performed by regression analysis of the inverse-velocity curve by slope stability analysis. According to the existing literature, slopes with ductile behaviors are a third polynomial equation and slopes with brittle behavior are a linear equation. Regression analysis results are also compared with Fukuzono [1]‘s slope failure prediction formula.
Fukuzono [1] intended to predict the time of slope failure resulted from progressive behavior with the inverse-velocity curve. The resulted inverse-velocity curves are as illustrated in Figures 9 and 10. In the case of the soil strength parameters of the cohesion (
Results of ductile slope (case 1); (a) displacement-inverse velocity curve, (b) failure case of Kunini slope movement.
Results of brittle slope (case 2); (a) inverse displacement velocity curve, (b) failure case of Selborne cut-slope experiment.
And in the case of the soil strength parameters of the cohesion (
This study developed an integrated analysis method for stability analysis and maintenance of cut-slopes in urban. To link the slope stability analysis with the maintenance method based on the measured data, the displacement until the slope failure to the finite element model was analyzed and applied to the maintenance method. The integrated analysis method proposed in this study is based on the cut-slope and only the strength degradation caused by the time-dependent deterioration is taken into consideration. The proposed method can be used both as soil and rock as a material of cut slope, but the only soil is considered in this study.
The integrated analysis method in this study can complement the disadvantages of the slope stability analysis and integrate it with the maintenance method based on the measured data of slope. The slope stability analysis can be used to quantify the displacement until slope failure as the cumulative displacement curve, velocity curve, and inverse velocity curve. The results of slope stability analysis could be used as management criteria for statistical process control method, mathematical model and the time of slope failure applied to maintenance. Then, the failure behavior of the slope and the generation of the failure surface were confirmed. The displacement of the slope analyzed by the finite element analysis should be the same as the position of the displacement meter installed on the slope.
By the comparison of this model with the failure model based on measured data, the obtained failure model was concluded as a 3rd order polynomial failure model equivalent to that of the site of ‘Neureupjae’ presented by Han and Chang [41]. Figure 4(c) represents the velocity curve. It also shows the rapid progression of displacement velocity at the point of 2.0 of SRF. The corresponding displacement inverse-velocity curve is illustrated in Figure 4(d). The inverse-velocity was generated by the following 3rd order equation,
The behavior of the slope appeared almost identical with that in the Case 1 and, the 3rd order polynomial equation similar to that of the site of ‘Neureupjae’ presented by Han and Chang [41] was also derived. The equation appeared in 3rd order polynomial equation:
The slope stability analysis conducted with conditions defined in the Case 1 rendered following results of the changes in initial soil strength (cohesion) and internal friction varied from
The results obtained from the analysis of the Case 2 showed that the failure resulted from the initial soil cohesion of 0 kPa with the internal friction varied from 40° to 21.5°. The resulted failure model corresponded to this cumulative displacement curve was reduced to the 3rd order polynomial equation,
When the road is constructed by the development of the urban, it is essential to cut-slope. However, the slope has gradually degraded the strength of the soil due to the time-dependent deterioration, and progressive slope failure is induced. This study developed an integrated analysis method for stability analysis and maintenance of cut-slopes in urban. The slope stability analysis was performed using the finite element model, and the progressive slope failure by time-dependent deterioration was quantified by using the strength parameters of soil applying the SRF. The displacements until the slope failure by slope stability analysis were quantified by cumulative displacement curve, velocity curve, and inverse velocity curve and, applied to the slope maintenance method. The inverse-velocity curve applied to the prediction of the time of slope failure was regressed to the 1st linear equation in the brittle material and the 3rd polynomial equation in the ductile material. This is consistent with the proposed formula of Fukuzono [1] and also shows similar behavior to the existing failure case.
Recently, sensors and communication technologies for measuring the behavior of slopes have been dramatically developed. However, there is no technique or management method to interpret it. This study aims to solve these problems.
The proposed method integrates the existing slope stability analysis and maintenance techniques. It is difficult to obtain the measurement data of the collapsed slope, but the proposed technique should be verified through the failure of the model slope. And the behavior of ductile and brittle behavior appeared depending on the characteristics of the materials constituting the slope. Research on this part is also necessary. In the future, integrated analysis method should be improved through additional research. And it should be applied to cut-slope of urban to prevent disasters.
In this study, the proposed method was carried out only on homogeneous slopes consist of soil. In the future, research on the slope with the heterogeneous and anisotropic is needed. Also, the proposed method should be verified by applying it to the 3D rock slope which causes collapse along the joint of rock.
This work was supported by Seoul Institute of Technology (SIT) [(2020-AA-007) Development and Application Plan on Smart GNSS Technology for Monitoring Displacement of Urban Infrastructure] The content of this chapter is the rewriting of Dr. Park Min-cheol’s doctoral dissertation [36] and a paper [35] already published in Korea.
Violence has become an issue of public health, responsible for deaths and illnesses, leaving in its wake consequences for all age groups in the population. Intentionality is one of the more complex elements in the concept of violence, however, the World Health Organization (WHO) explains that any act causing implications for an individual’s health is considered a violent act, even when sustained by the culture or when there was an intention to use force without the intention to cause harm [1].
As far as the typology is concerned, violence is divided into three types: self-inflicted, interpersonal, and collective. Self-inflicted violence is subdivided into suicidal behavior and self-abuse; collective violence, into social, political, and economic; lastly, interpersonal, divided into two subcategories: violence within the family or by a close partner, which mostly occurs between family members, and community violence, which takes place among people who are unrelated [2].
With regard to the nature of violent acts, these may be classified as physical, sexual, psychological, deprivation or abandonment. The four types of violent act occur in each of the main categories and subcategories, except for self-inflicted violence. Violence towards children, committed inside the home, for example, may include physical, sexual, or psychological abuse, as well as negligence or abandonment [3].
Specifically, with regard to children and adolescents, violent acts (physical, sexual, psychological, negligent) are called maltreatment and refer to various forms of violence, in the majority of cases with events being repeated and committed by someone close or the guardian of the child or adolescent [4].
Studies into violence, conducted by Finkelhor et al. [5], assert that living with or experiencing situations of violence, with the particular potential to cause trauma, is called victimization. Studies into victimization describe five types of violence: victimization through conventional crime, victimization through maltreatment, victimization by peers, sexual victimization and indirect, witnessed victimization.
Victimization through conventional crime is commonly identified by the police authorities as, for example, assault, theft, vandalism, and prejudice. As for violence through maltreatment, this is detected through living with situations of violence directly related to the family or to guardians. This type of victimization also includes negligence, physical and psychological abuse, in the form of depriving children and/or adolescents of basic necessities like food and hygiene. Victimization by peers is characterized by the aggression that occurs by individuals within the same age group, normally among students. In this respect, aggression through the practice of bullying is also taken into account as well as attacks by groups and physical and psychological violence. Sexual victimization relates to aggression related to issues of sexuality. For Finkelhor et al. [5], sexual victimization is more than just penetration, it also includes lewd acts without the consent of the individual or even with consent where the children are not old enough to be responsible for their choices; this also encompasses sexual aggression by an adult, by peers, sexual harassment, rape or attempted rape and sexually-related verbal harassment. Lastly, indirect victimization refers to the witnessing of violence suffered by others, and this also covers issues such as witnessing domestic violence, seeing parents attack siblings or their spouses, witnessing attacks, robberies, homicides, shootings, terrorism, and exposure to ethnic conflict.
In epidemiological terms, studies show that approximately 40 million children in the world, under the age of 15, have suffered abuse and negligence [1] and, in the USA, between 25% and 66% of children and adolescents are exposed to traumatic events during childhood [6, 7]. As far as Brazil is concerned, a survey by the Brazilian Center for Latin American Studies, based on the Ministry of Health’s Mortality Information System (SIM), shows that the number of homicides of teenagers, between 1980 and 2010, rose 346%.
Brazilian researcher that investigates violence directed against children and adolescents point to alarming data. According to the National Human Rights Ombudsman, 58.9% of the complaints received via channels such as Dial 100 refer to some type of violence against children and adolescents. The main types of violence reported are mistreatment: negligence (61,416), psychological violence (39,561), and physical violence (33,105). In 2017 alone, there were 84,049 reports of physical violence and, in the previous year, there were 76,171. In this sense, the data indicate that 68% of Brazilian children and adolescents aged up to 14 years, which is equivalent to 30.3 million children and adolescents, have already suffered corporal violence at home [8].
An exploratory/descriptive desk study conducted by Júnior et al. [9], analyzed the characterization of cases of domestic violence against children and adolescents in the Brazilian city of Volta Redonda, situated in the state of Rio de Janeiro. The investigation was carried out based on an analysis of the patient records of registered children and adolescents cared for as victims of maltreatment by parents, relatives, and/or guardians in the city’s Specialized Social Welfare Reference Center (CREAS). The results indicated that, of the 210 patient records analyzed, 29% were victims of physical violence, 29% sexual violence, 29% were linked to negligence and 13% were cases of psychological violence. Although this study cannot be generalized as it makes use of a convenience sample, some important points were deliberated. The prevalence of the identification of physical violence, as it leaves marks on the body, and sexual violence, as it causes significant harm to the victims’ health, is capable of mobilizing more the child protection institutions and society in general, which probably explains the higher volumes of identification. As for negligence, though difficult to identify, as it involves the economic and social aspects of each family or social group, detection is possible when there is already contact between the social institutions and the families in situations of risk and vulnerability. On the other hand, psychological violence, which accounted for the smallest percentage of identification, requires children’s welfare professionals to redouble their attention because the indicators of its manifestation are not so straightforward, however, the consequences are equally serious for the victims’ mental health.
One study conducted by Lin et al. [10] investigate the link between serious child abuse and cerebral activation based on Magnetic Resonance Imaging examinations during a sustained attentional task. A total of 70 individuals (13 to 20 years old) took part, divided into three groups: history of abuse before 12 years old; psychiatric control group (no maltreatment but with psychiatric disorders); control group (no maltreatment, no psychological disorders). The results indicated that the participants exposed to child abuse exhibited results that show that the longer the youngster suffered abuse, the worse the performance in capacity to maintain sustained attention.
Another important piece of data indicates that, according to the Ministry of Women, Family and Human Rights (MMFDH), of the accusations received via Helpline 100 in 2018, over 17,000 were related to sexual abuse and sexual exploitation involving children and adolescents. Thus, based on the data presented and seeking protective measures for children and adolescents, in Brazil, the Child and Adolescent Statute (ECA) is regarded as one of the most advanced pieces of legislation in the world in terms of child protection [11]. Among the general clauses, the law establishes full protection for children and adolescents, considering that children, for the purposes of the law, are those aged under 12 while adolescents are those aged between 12 and 18 years. In terms of protection against violence, article 5 of the ECA states that no child or adolescent shall be the object of any form of negligence, discrimination, exploitation, violence, cruelty, or oppression and that any attempt, through commission or omission, against their fundamental rights must be punished in accordance with the law. Despite the ECA and the penalties it imposes on people who commit violence against children and adolescents, the percentage of victims within this age group is still significant.
Despite the ECA being a statute that provides for severe infractions for those who are aggressors, the number of victimizations is still significant. The aim of the ECA, therefore, is the full protection of children and adolescents, seeking to guarantee their cognitive, psychosocial, and physical development. The dividing line between child and adolescent is important, mainly as it considers that significant, important differences exist during each period of their lives [12].
Development in childhood is characterized by constant processes of development in terms of cognitive function and social skills. In the third stage of childhood, between six and 11 years of age, cognitive development is seen as an increase in cognitive skills that permits an improvement in the ability to learn as well as preparation for academic performance. In terms of psychosocial development, relationships between peers, schoolmates, and others take on fundamental importance. In adolescence, interest in peer relationships remains strong, however, with a greater concern to belong to a group, which may exert positive or negative influences. Cognitive development is characterized by the ability to think in abstract terms, but immature thinking persists in some attitudes and conduct, with more impulsive behavior [12]. Situations of violence may adversely affect this important period of development, causing impairment of cognitive, social, emotional skills and, consequently, may compromise the quality of life of victimized subjects.
With regard to the damage to quality of life, for victimized children, a study by Matos, Pinto, and Stelko-Pereira [13], which aimed to investigate the existence of a possible connection between exposure to sexual abuse in childhood and inferior quality of life in university students, noted that childhood sexual abuse is negatively associated with quality of life in adults. The results of another study, conducted by Dias [14], although investigating a different age group, specifically relating to the impact of violence on the quality of life of adult females, showed that violence exerts a negative impact on the quality of life of victims and also generates physical trauma, posttraumatic stress disorder, stress, and depression.
Studies into the relationship of experience of violence in childhood and adolescence have increased as a result of the recognition of the dimensions of the phenomenon as a serious public health problem, on account of the high index and the consequences they have for the physical, psychological and cognitive health of people who suffer violence [15]. In order to identify victimization, for the most part, studies look to institutions that protect victimized children, as well as instruments (questionnaires and/or scales) that can be answered by the parents/guardians or by the child or adolescent him/herself. The instruments most frequently employed are the Child Maltreatment Questionnaire, Child Trauma Questionnaire, and Juvenile Victimization Questionnaire [4, 10, 16, 17]. The last two instruments in this list include validity studies in the national context conducted by Grassi-Oliveira et al. [18] and Faria and Zanini [19], respectively, and are not instruments restricted to the use of psychologists.
Despite the variety in the way victimization is identified, studies have shown impairment to cognitive functions in this age group [4, 10, 20]. However, there are still very few studies available that have sought to investigate the impact of violence specifically on executive functions.
Executive function (EF) refers to the processes called upon whenever it is necessary to focus attention, manage and control behavior or action towards a goal, evaluate the efficiency of this behavior, and readjust strategy when required. Thus it is possible to assert that the human capacity to adapt to different situations is heavily associated with good executive function [21, 22, 23, 24].
In spite of the agreement between the theoretical models that EF is important for good brain function, insofar as it relates to its definition and component structure, there seems to be a divergence in ideas [14, 25, 26, 27]. Thus, several different EF models have been developed and studied.
One of the more influential theories about EF proposes the association between the frontal lobes, their principal connections, and the Supervisory Attentional System (SAS). SAS is a model developed by Norman and Shallice [28] and describes EF as a specific system in the processing of information, which takes place based on two processes. An automatic process is the ability to automatically select responses based on information in an existing repertoire. The controlled process is identified as the modification or even the construction of new responses, including decision-making, mental flexibility, inhibitory control, and planning [28, 29]. In this regard, there are some studies about the relationship of violence with EF [10, 30] which used attention as a component of EF.
One widely accepted model is that of Miyaki et al. [31], for whom EF is composed of three basic components or nuclear EFs, namely: working memory (WM), cognitive flexibility (CF), and inhibitory control (IC). Subsequently, Diamond [21] carried out a new study corroborating the idea that three nuclear EFs exist, but that they are the basis for the development of more complex components such as planning, deductive reasoning, and problem resolution, subsequently designated complex executive functions. For a better understanding of the model, it is necessary to define each of these components.
IC involves the ability to control the behaviors of attention, thoughts, and emotions, inhibiting an automatic behavior or a distraction and, instead of generating said behavior, do what is most appropriate or necessary [22]. WM is defined as the ability to keep information in one’s mind and deal with it over a short period of time, enabling understanding, learning, and reasoning, as well as problem resolution [32]. CF involves the capacity to change perspectives, alternate attentional focus, favoring the ability to adapt to the environment, enabling the individual to evaluate his/her performance in a particular situation, seeking to comply with rules, and problem resolution [22, 33]. With regard to complex EFs, planning involves the ability, based around an initial starting point, to set an objective, define the best ways to achieve it, organize the necessary steps to this end, analyze the efficacy and, if necessary, adjust the execution [22]. Problem resolution involves the ability to create and test solutions for conflicts, through mental representation, in the planning and implementation of strategies and monitoring [34].
Another skill developed from the three nuclear components is decision-making, crucial for day-to-day functioning because it involves a process of choice of one among many alternatives in situations that include uncertainty, generally guided by an emotional or motivational component. During decision-making, other EF components are involved like operational memory, cognitive flexibility, inhibitory control, and planning [23, 34].
Regarding the development of EF in the early years of life, it is considered a unitary construct, that is to say, in this phase it is not possible to distinguish between each component, however, it is already possible to identify an improvement in the performance of the components in the first year of life [35].
From school age, the development of operational memory and cognitive flexibility is relatively linear; in this period, the EF components appear in sequence: firstly working memory, then inhibitory control. The two components in combination permit the development of cognitive flexibility [23, 36].
Adolescence is characterized by an increase in impulsiveness and, consequently, by a pattern of immediatist choices, changes in the course of action without making a conscience judgment, unintended behaviors, and a tendency to act without planning. All these aspects lead to risk-taking behavior without evaluating the consequences, suggesting a lesser capacity for self-regulation and inhibitory control [23].
WM is an essential ability in learning, both in childhood and in adolescence and, although there are a series of abilities required for learning, there is evidence that working memory is one of the best predictors of performance at school [37, 38]. In this regard, it is important to stress that the development of EF is directly related to the ability of children and adolescents in the learning processes, as well as the ability to adapt to new situations.
As EF is important for the learning processes, the evaluation of this function must investigate, in minute detail, if each of the components is developing as expected. There are specific batteries for its evaluation, such as the Behavioral Assessment of the Dysexecutive Syndrome (BADS) and the Delis Kaplan Executive Function System (D-KEFS). These batteries perform an overall evaluation of EF and serve a population ranging in age from eight to 87 years.
There are several favorable psychological tests, which evaluate EF, as well as instruments validated for use. The Wisconsin Card Test, for example, is used to evaluate EF, specifically cognitive flexibility, as well as Trail Making Test and the Five Digit Test (FDT). To evaluate WM, the WISC-IV subtests are used, such as digit span and numbers and letters sequencing and, to evaluate inhibitory control, FDT, Stroop Test, and the Hayling Test are used. On the one hand, the wide variety of tests to evaluate EF permits a full investigation based on the collection of data from all the components, however, with regard to the comparison of data in studies, it may make analysis difficult as the studies use different instruments and tests.
Despite the diversity, in the way, the data is collected, either for identifying violence or evaluating EF, international studies point out the consequences of victimization for children and adolescents. Some studies have investigated the consequences of short- and long-term violence with victims who presented with a condition indicative of posttraumatic stress disorder, psychiatric disorders, or the use of illicit substances such as alcohol and drugs [39, 40, 41, 42, 43]. Other studies have shown that victimization as a result of maltreatment, as well as sexual victimization, may impair the development of EF in terms of the components of working memory, cognitive flexibility, and inhibitory control [39, 41, 44, 45].
So, based on the data presented, the present study aimed to perform a literature review of the literature concerning studies that investigated the relationship between living with violence and the development of EF in children and adolescents, over the last 10 years. It also intends to demonstrate how these impairments can affect the quality of life of these children and adolescents.
Articles in scientific reviews, published within the last 10 years, which sought to assess the relationship between living with violence and executive function in children and adolescents aged between six and 16, located in the following databases: PsycINFO, Pubmed/Medline, BVS, Lilacs, Web of Science, Scopus and Gale.
In order to carry out this literature review, the following databases were used: PsycINFO, Pubmed/Medline, BVS, Lilacs, Web of Science, Scopus, and Gale, with articles, published up to October 2019. In these databases, the potentially relevant documents were selected using the following descriptors: executive functions, violence, child, children, adolescent, and adolescence, inserting the
Studies between 2009 and October 2019 were accepted, reviewed by peers, and published in the English, Spanish and Portuguese languages. Initially, 486 articles were located, of which 200 were repeated articles. After a reading of the titles and abstracts of the remaining 286 articles, 221 were excluded, in accordance with the following criteria: articles that were not available in their entirety (16), that had no connection with the proposed topic (172), comprising longitudinal studies (7), with a target demographic of subjects over 16 years of age (10), with a target demographic of subjects under 6 years of age (11), related to the use of illicit drugs (5). A total of 65 articles remained, selected for a full-text reading, to be subsequently included or excluded in accordance with the following criteria:
Inclusion criteria: (1) articles that investigated the relationship between violence and EF, (2) articles with a target demographic between six and 16 years of age, (3) studies with a control group. Exclusion criteria: duplicated articles (2), articles not available in full, (3) articles with a target demographic under 6 years of age, (4) articles that did not indicate the instruments used to evaluate EF. Based on the final analysis of the selection, the studies were characterized by author and year of publication, objective, age range of target demographic, type/nature of violence, instruments used, evaluated EF components and results. Figure 1 represents the detailed flowchart of the study selection process.
Flowchart of studies selected for review.
Figure 1 indicates that the initial search of the databases identified 486 files. After applying inclusion and exclusion criteria, 65 articles remained for full-text reading. After the reading, the following studies were excluded: outside the studied age range (n = 25), those that did not have a control group (n = 23), those without instruments to measure EF (n = 13), and those which were literature or systematic reviews (n = 4), leaving a total of eight articles.
There follow a series of tables with the results obtained in this review study. Table 1 describes the eight articles selected according to the inclusion criteria, identifying the authors, number of participants, age group, and study objectives.
De Bellis et al. [30] | Children (7 and 8 years old) | To investigate impairment in cognitive functions in neglected and sexually abused children. The children were divided into three groups: neglected and with symptoms of PTSD; neglected but no PTSD, children neither neglected nor PTSD (control group). The following cognitive domains were investigated: IQ, reading, math, fine-motor coordination, speech, visuospatial perception, memory, attention/ executive function. |
Nooner et al. [45] | 202 children (11 and 12 years old). | To investigate the impact of maltreatment on cognitive functions, comparing boy and girl victims. The cognitive functions investigated were: attention, speech, memory, intelligence, EF, and academic performance (reading, writing). The children were divided into 4 groups: boys with and without maltreatment; girls with and without maltreatment. |
Spann et al. [16] | 30 adolescents (12 to 17 years old). | To investigate the relationship between maltreatment and EF, specifically cognitive flexibility in adolescents without psychiatric disorders. The adolescents, divided into two groups: with and without a history of maltreatment. |
Borges and Dell’Aglio [39] | 26 children and adolescents (8 to 13 years old) | To identify the manifestation of symptoms of PTSD and impairment of attention, verbal memory, cognitive flexibility/executive function in girls that suffered sexual abuse. Divided into 2 groups: girls who were victims of sexual abuse and girls without a history of sexual abuse. |
Smith et al. [46] | 80 adolescents (11 to 18 years old) | To investigate if adolescents who suffered maltreatment exhibited worse performance in EF than the group which did not suffer maltreatment. Divided into 2 groups; with and without maltreatment. |
Tran et al. [17] | 1851 children and adolescents (12 to 17 years old) | Cross-sectional study investigating associations between different forms of maltreatment and emotional function, cognitive function, physical health, as well as the effects of the moderation of ethnicity and gender. Divided into 2 groups, with and without maltreatment. |
Lim et al. [10] | 70 adolescents (13 to 20 years old) | To investigate the link between serious child abuse and cerebral activation based on Magnetic Resonance Imaging examinations during a sustained attentional task. History of abuse before 12 years old; psychiatric control group (no maltreatment but with psychiatric disorders); control group (no maltreatment, no psychological disorders). |
Vasilevski and Tucker [47] | 82 children and adolescents (12 to 16 years of age) | To investigate to what extent maltreatment impacts cognitive performance, including the EF of adolescents who suffered maltreatment. Divided into two groups: the first composed of adolescents who suffered severe maltreatment and the second, adolescents who did not suffer any maltreatment. |
Authors, Participants, and Objective of the study.
The results displayed in Table 1 show that the number of participants ranged from 26 to 1851. As far as the age range is concerned, just one study analyzed only children [30], three investigated both children and adolescents [39, 45, 46] and four studies investigated adolescents [10, 16, 17, 47]. With regard to the objectives of the studies, it was possible to observe that all the articles included studies related to maltreatment. Two studies sought to identify a correlation between maltreatment, cognitive/executive functions, and Post Traumatic Stress Syndrome (PTSD) [30, 39], and one sought to identify the difference in the impact of maltreatment in adolescents with psychiatric disorders [10].
Table 2 shows that the most studied form of violence is interpersonal based on an investigation into maltreatment, however, several articles investigated specific types of maltreatment, namely negligence, physical abuse, sexual abuse, emotional abuse, and witnessed violence. Five articles investigated negligence ([30]; Nooner et al. [45]; [16, 17, 46]); four studies investigated physical abuse [16, 17, 45, 46]; four, sexual abuse [17, 39, 45, 46]; two, emotional abuse [45, 46]; two, domestic violence [45, 46]; and one article investigated maltreatment, without specifying the nature thereof [47].
De Bellis et al. [30] | Negligence (excludes sexual abuse). | |
Nooner et al. [45] | Maltreatment, negligence, physical abuse, sexual abuse, witnessing interpersonal violence at home, and emotional abuse. | |
Borges and Dell’Aglio [39] | Sexual abuse | Reference services for sexually abused children. |
Spann et al. [16] | Physical abuse, emotional abuse, and negligence. | |
Smith et al. [46] | Physical, sexual, or emotional abuse, negligence, and domestic violence. | Collection of records from teachers and tutors. |
Lim et al. [10] | Severe child abuse. | |
Tran et al. [17] | Physical abuse, sexual abuse, and negligence. | |
Vasilevski and Tucker [47] | Maltreatment |
Authors, types of violence, and instruments employed.
As for the way to identify violence, five studies recruited children or adolescents from institutions or agencies responsible for caring for victimized children and/or adolescents [30, 39, 45, 46, 47], two studies used the Child Trauma Questionnaire [10, 16] and one the Child Maltreatment Questionnaire [17]. Both instruments are self-report inventories composed of items to identify emotional, physical, or sexual abuse, and negligence in children and adolescents.
The results observed in Table 3 show that the components of EF evaluated in six of the eight studies agree to the Miyake et al. [31] model that considers cognitive flexibility, working memory, and inhibitory control as the basic components for the evaluation of EF, but only one study evaluated the three components in conjunction [46]. Two studies evaluated two components: working memory and cognitive flexibility [39, 47]; a further two studies only analyzed cognitive flexibility [16, 45]; and one study only evaluated WM [17]. Two studies [10, 30] considered the EF model of Norman and Shallice [28], who describe EF as a unique system of cognitive functions, named the Supervisory Attentional System (SAS).
De Bellis et al. [30] | Sustained attention. | Neglected children demonstrated a significantly worse performance in sustained attention, memory, planning and problem resolution. |
Nooner et al. [45] | Cognitive flexibility. | Boys who suffered maltreatment demonstrated worse EF performance than girls who suffered maltreatment and boys in the control group. |
Borges & Dell’Aglio [39] | WISC-III digit span forward and backward; Working memory and cognitive flexibility. | No differences were found between the groups in terms of working memory and cognitive flexibility. |
Spann et al. [16] | Cognitive flexibility. | Adolescents who suffered physical abuse and negligence showed worse performance in cognitive performance. |
Smith et al. [46] | Working memory, inhibitory control, and cognitive flexibility. | Adolescents who suffered maltreatment demonstrated worse performance in working memory, fluency, and inhibition, however, cognitive flexibility was not affected in comparison with the control group. |
Lim et al. [10] | Sustained attention. | Participants exposed to child abuse exhibited results that show that the longer the youngster suffered abuse, the worse the performance in capacity to maintain sustained attention. |
Tran et al. [17] | Operational memory. | The experience of sexual abuse and negligence throughout their lives were related to worse performance with operational memory. |
Vasilevski and Tucker [47] | WISC-IV. Working memory, cognitive flexibility, and executive function. | The results showed that the group of adolescents that suffered maltreatment demonstrated impaired EF, attention, and working memory. |
Authors, Instruments, and Results.
As far as the EF measurement instruments are concerned, it was possible to identify diversity. For the evaluation of CF, the following tests were employed:
As for the results of the articles, only one of the studies was unable to find significant correlations between maltreatment, specifically, sexual abuse and EF [39]. The remaining seven studies [16, 17, 45, 46, 47] noted impairment with EF based on the components evaluated, namely: WM, CF, and IC, as well as in attention [10, 30], in children and adolescents suffering maltreatment.
The present study, the aim of which is to carry out a literature review of the literature in respect of the impact of violence on the executive functions of children and adolescents, outlines the picture of the last 10 years’ studies on the topic, in both the domestic and international arenas.
The first issue to mention is that all the studies located investigated victimization through maltreatment; some of them specified the types (negligence, physical abuse, sexual abuse, emotional abuse, and the witnessing of interpersonal violence at home), while others considered maltreatment in a general sense. The prevalence of studies on the topic may be connected with the fact that epidemiological data indicate growing victimization through maltreatment in childhood and adolescence, as noted in Ending Violence in Childhood: Global Report [48]. Another aspect that should be considered is the typical development of the components of EF in this period between childhood and adolescence, extremely important for the processes of learning [36, 37, 38]. Thus, it has become important to investigate the situations which could interfere with this process, as is the case of violence.
The fact that there are four types of maltreatment might also explain the number of studies on this topic, as the specific studies consider sexual abuse and even physical abuse as maltreatment, including them in a single group. On the other hand, for Finkelhor et al. [5], sexual victimization is a form to be evaluated separately because sexual abuse includes lewd acts without the consent of the individual or even with the consent of children at an age when they cannot be responsible for their choices, including sexual aggression by an adult, by peers and sexually related verbal harassment. So, considering the study of victimization from Finkelhor et al. [5], sexual abuse would be in distinct study groups.
In this study, no articles were found concerning the impact of victimization through conventional crimes, violence by peers, and indirect or witnessed violence, which points to the scarcity of studies that evaluate other forms of victimization. In relation to indirect or witnessed violence, one study evaluates the impact of witnessing interpersonal violence, however, it does not include the witnessing of other forms of violence such as robberies, street attacks, and aggression between colleagues. In this sense, the results of the study conducted by Brancalhone et al. [49] indicate impairment of EF in the group of children victimized by bullying and also in those who witness it. They also pointed out that the impact of indirect violence or violence witnessed by children is evident in the course of their development, causing symptoms of depression and a drop in school performance.
As far as the evaluation of EF is concerned, only two studies [10, 30] used the model of Norman and Shallice [28], who describe EF as the Supervisory Attentional System (SAS) and, based on this, they considered sustained attention as a component of EF. The others used the model proposed by Miyake et al. [31], corroborating the literature that regards this as the model most used in both empirical and theoretical studies into EF. Just one study considered all three components, while the others used one or two components, considered responsible for the evaluation of EF. The result corroborates the literature, which is quite diverse in terms of the structure of the components [14, 26, 27], which results in complexity with the process of evaluating EF.
Despite the theoretical diversity, studies have shown that, for the most part, components of EF were impaired in children and adolescents who suffered maltreatment and only two of them presented different results. In the study by Borges & Dell’Aglio [39], girls aged between eight and 13 who suffered sexual abuse had no impairment of working memory and, in Smith et al. [46], adolescents who suffered maltreatment showed no CF impairment, but no studies were found with results that corroborate these data.
Working memory was the most studied component, appearing in four of the eight articles studied; of these four, three identified impairment with WM in children and adolescents victimized through maltreatment. Working memory is an ability essential to learning [37, 38, 50], so, the interest in investigating the impact of violence in this EF component can be justified. Studies have shown that maltreatment can impair WM in both childhood and adolescence and, consequently, the processes of learning, as well as academic performance.
As regards the instruments for EF evaluation, these are diverse, which could influence the comparison of the results found. To evaluate WM, the subtests
For the evaluation of CF, the following tests were used:
Studies show that children and adolescents are part of a vulnerable age group and, as a result, they are more subject to experiencing violence in its various forms. Self-report instruments that seek to identify the different types of violence, that is to say, those to which the children or adolescents themselves respond, are capable of analyzing the perception of living with violence in a more sensitive way or one that better approximates the extent to which this child or adolescent could be affected, and are thus considered to be more effective instruments, as they identify the perception of living with violence. In this regard, adolescents, the group with the largest number of studies, have greater capacity to identify this experience as their cognitive and emotional repertoire is better developed in terms of perception.
From childhood to adolescence, living with violence impairs the nuclear components of EF, namely working memory, cognitive flexibility, and inhibitory control, which are the basis for the development of the following complex components: planning, problem resolution, and decision-making. These components may be impaired, not to mention the processes of learning, of adaptation to situations in both cognitive and social aspects, which are characteristic of this age group, leading to difficulties that will be omnipresent in diverse situations throughout their lives.
Apart from the impairment of executive functions that the processes of victimization may cause in children and adolescents, these impairments may adversely affect the quality of life in this important age group. In this sense, a study conducted by the Center on the Developing Child, at Harvard [51], indicated that typical development in executive function skills help children to remember and follow instructions with various stages, to avoid distractions, control precipitous responses, adjust when the rules change, persist with the solution of problems and control long-term obligations which are directly associated with quality of life. Moreover, Matos et al. [13] noted that child sex abuse is negatively associated with quality of life in adulthood.
In short, the study notes the scarcity, mainly in the domestic setting, of studies investigating the relationship between living with violence and the development of EF. However, the studies that were found point out, for the most part, the impairments that living with violence may bring to the development of EF and with the processes of learning. It has become important than that future studies investigate not only experience of maltreatment but also that of other types of violence, justifying on scientific basis the need for investment in public policies that can avert living with violence, as well as in intervention policies and care for children and adolescents who are victims of violence.
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\\n\\nThe University of Massachusetts, Amherst is pledging funds via the Knowledge Unlatched program to ensure academics can publish Open Access content more easily.
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\\n\\nThe University of Surrey is pledging funds via the Knowledge Unlatched program to ensure academics can publish Open Access content more easily.
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\n\nCorresponding authors will receive a 15% discount on their Open Access Publication Fees (OAPF) for Open Access book chapters or monograph publications. To use the discount you will need to verify your institutional email address. These discounts are valid from 2020 to 2022.
\n\nThe University of Massachusetts, Amherst is pledging funds via the Knowledge Unlatched program to ensure academics can publish Open Access content more easily.
\n\nCorresponding authors will receive a 10% discount on their Open Access Publication Fees (OAPF) for Open Access book chapters or monograph publications. To use the discount you will need to verify your institutional email address. These discounts are valid from 2020 to 2022.
\n\nThe University of Surrey is pledging funds via the Knowledge Unlatched program to ensure academics can publish Open Access content more easily.
\n\nCorresponding authors will receive a 10% discount on their Open Access Publication Fees (OAPF) for Open Access book chapters or monograph publications. To use the discount you will need to verify your institutional email address. These discounts are valid from 2020 to 2022.
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