Sd 38 Introduction To K3000 For Mac
Introduction deadlines: Generally, bills and resolutions must be introduced within 2 legislative days after delivery. JR 40-50, H40-10. “General bills” is used to denote all bills, except appropriation or revenue bills, and all joint resolutions. Notes: Deadline dates are determined according to legislative days.
Results The results revealed that aggressive behaviour measured one year predicted decreases in prosocial behaviour in the following year. Conversely, prosocial behaviour did not predict changes in aggressive behaviour in the subsequent year.
Furthermore, peer difficulties were examined and found to be an important mediator of the link between aggressive and prosocial behaviour. Specifically, peer difficulties mediated the links between aggressive behaviour and prosocial behaviour one year later, particularly during the first three years of school attendance. Aggressive behaviour predicts subsequent prosocial behaviour Other developmental scientists have argued that aggressive behaviour may be linked to subsequent reductions in prosocial behaviour, particularly if children form friendships with aggressive peers (e.g., Bowker et al.
Empirical findings suggest that aggressive children tend to form friendships with each other (Dishion and Tipsord; Logis et al. ), they lose their social reputation, and experience peer rejection.
When they attack and inflict harm on others, aggressive children may be seen as a threat to both victims and bystanders, who may therefore avoid interactions with them. In this way, children who engage in aggressive behaviour may isolate themselves from and/or become isolated by their socially competent peers from whom they could learn to engage in prosocial behaviours.
In addition, aggressive behaviour, especially when it is part of a sustained pattern of conduct problems, is likely to reinforce social information-processing biases (Arsenio and Lemerise ). Hence, children who engage in aggressive behaviour may subsequently not perceive prosocial behaviours as response options and/or they may not evaluate them as strategies that are associated with internal or external gratifications. Aggressive behaviour and prosocial behaviour reciprocally relate to each other over time The third possibility is that aggressive behaviour and prosocial behaviour reciprocally relate to or predict each other over time. Zimmer-Gembeck et al. examined but did not find reciprocal links between prosocial behaviour and relational or physical aggression and vice versa between Grades 3 and 6.
They did, however, find that social preference, a measure of likability and acceptance by peers, predicted both aggressive behaviours as well as prosocial behaviour three years later. To our knowledge only one study thus far has examined the possibility of reciprocal links between these two behaviours at more than only two time points and across a longer period of time.
Specifically, Chen et al. , tested the cross-lagged reciprocal relations between aggressive behaviour, academic achievement and social competence, a construct related to prosocial behaviour, over time in a sample of 1140 Chinese children from Grades 2 to 5 based on peer nominations and teacher reports. Combining information from the two informants, aggression in Grades 2, 3, and 4 was significantly negatively related to subsequent social competence (peer-assessed sociability, social preference, teacher-rated social competence, and leadership), while this was not the case in Grade 5.
In contrast, levels of social competence were not related to aggressive behaviour one year later. These findings hence support the hypothesis of a unidirectional effect from aggression to later social competence, which includes aspects of prosocial behaviour, but not from social competence to aggression. The authors argue that earlier aggressive behaviour may elicit negative social evaluations of others, which may in turn lead to lower levels of social competence and fewer opportunities to develop a healthy self-confidence. Parent and teacher ratings of aggressive and prosocial behaviour For the parent and teacher ratings, the Social Behaviour Questionnaire (SBQ; Tremblay et al. ) was utilised.
The SBQ is a 55-item paper and pencil questionnaire rated on a 5-point Likert scale from never = ‘0’ to very often = ‘5’. It is used to rate children’s psychosocial functioning across ten subscales contributing to five higher order scales. This study utilised two scales of the SBQ: mean scores of the overt Aggressive Behaviour and Prosocial Behaviour scales. The overt Aggressive Behaviour scale included eleven items in total, tapping into pro-active aggression (four items; e.g. ”The child encourages others to pick on a particular child”), reactive aggression (three items; e.g.
“The child is aggressive when he/she is contradicted.”), and physical aggression (four items; e.g. “The child kicks, bites and hits”).
Cronbach’s alphas ranged from.77 to.81 with mean alpha.79 for parents and from.93 to.94 with mean alpha.93 for teachers. The Prosocial Behaviour scale consisted of ten items and tapped into behaviours related to helping and empathic behaviour, for example “The child helps someone who is hurt” or “The child listens to others’ point of view”; respectively. Cronbach's alphas ranged from.76 to.80 with mean alpha.78 for parents and from.91 to.92 with mean alpha.91 for teachers. Child rating of aggressive and prosocial behaviour Children completed the “Tom & Tina” – Adapted Social Behaviour Questionnaire (T & T). The T&T adaptation was developed by the research team with the purpose of measuring self-reported aggressive and prosocial behaviour amongst primary-school children parallel to the reports of teachers and parents. It is an adapted computer-based multimedia version of the SBQ that consists of a series of 54 drawings displaying specific behaviours of a child called “Tom” or “Tina” based on the child’s sex.
For each drawing the child is asked by a voice recorded on the computer whether he/she happens to do what is shown on the drawing and responds by pressing the “Yes” or “No” button at the bottom of each screen. The administration was adapted from the “Dominic Interactif” (Scott et al. ) measure with a demonstrated moderate to excellent reliability and validity for young children (Campbell et al.
The computer-based version of the T & T was administered to children at W1 to W3 and its parallel paper and pencil version was administered at W4. We utilised the prosocial and overt aggressive behaviour subscales comprised of parallel items to the SBQ scales described above. Cronbach's alphas ranged from.55 to.62 with mean alpha.60 for prosocial behaviour and from.72 to.79 with mean alpha.76 for aggressive behaviour.
The means in Table represent the means for the number of items they responded with “Yes”. Boys Girls Informant Variable (age) M SD M SD min max p d Teacher Prosocial (7) 1.939.836 2.412.737 0 4.00. Teacher rating of peer difficulties At each wave of data collection, teachers answered three questions to rate the degree to which each child is “popular”, “victimised” and/or “isolated” by peers on a 5-point Likert scale from ‘does not apply at all’ to ‘applies very much’. The three items were combined into composite scores, with being popular reverse-scored. The scores for W2 to 4, which yielded Cronbach’s alphas.75,.78,.80, respectively, were utilised in the analyses. This scale was specifically developed for the purposes of this study based on a review of literature related to peer rejection and negative peer experiences. At the time this longitudinal project was launched (in 2004/2005) peer rejection was most commonly measured via peer nomination sociometric tools (Lev-Wiesel et al.
These were deemed not sufficient or feasible for the then six-year old participants of the current study. For consistency of measurement over time, the same measure was utilised during subsequent data collection points. Autoregressive cross-lagged model of the association between prosocial behaviour and aggressive behaviour. Note: Autoregressive pathways are displayed as the pathways within constructs over time (e.g., prosocial behaviour at W1 to prosocial behaviour at W2). Cross-lagged pathways are displayed as the pathways between constructs over time (e.g., prosocial behaviour at W1 to aggressive behaviour at W2).
Control variables – exposure to Triple P and/or Paths – were regressed on the relevant waves. Due to its implementation at W2, Triple P was regressed on aggressive and prosocial behaviour at Ws 2, 3, and 4. Due to its implementation one year later at W3, exposure to Paths was regressed only on aggressive and prosocial behaviour at Ws 3 and 4. Not displayed are residual correlations, which were estimated as described in the data analytic plan.
First-order autoregressive and cross-lagged pathways of association were simultaneously evaluated. In a first-order autoregressive model, variables are represented as causes of themselves over time.
Therefore, autoregressive pathways estimate the association between prosocial behaviour at time t n with prosocial behaviour at time t n+1 as well as the association between aggressive behaviour at time t n and aggressive behaviour at time t n+1. The autoregressive pathways were allowed to vary across time to allow for the changes in the level of influence that behaviours at time t n have on the same behaviours at time t n+1 as children grow older. Aggressive and prosocial behaviours will be modelled in this way as extensive previous literature suggests that past behaviour is often the best predictor of current behaviour (e.g., Crick; Eivers et al.
Cross-lagged models (e.g., Kenny and Harackiewicz ) have been widely used in developmental research to assess bi-directional time-lagged relations (e.g., Defoe et al. The cross-lagged associations represent relations between prosocial behaviour at time t n and aggressive behaviour at time t n+1 as well as the reciprocal association between aggressive behaviour at time t n and prosocial behaviour at time t n+1. These effects were allowed to vary across time to examine change in the reciprocal association between aggressive and prosocial behaviour from age 7 to age 11. Concurrent residual correlations between aggressive and prosocial behaviour at the same time of assessment were estimated and allowed to vary over time as were the residuals within construct variances.
The intervention conditions (attendance/engagement in the intervention) were included in the models as covariates to account for possible effects on behaviour; Triple P at Ws 2, 3, and 4 as it was implemented when the children were in Grade 2 and Paths at Ws 3 and 4 as it was implemented when the children were in Grade 3. The autoregressive models were set up as multiple-group analyses to examine the association between aggressive and prosocial behaviour by sex. Within this framework, structural models with the associations between aggressive and prosocial behaviour over time were assessed independently in three separate models; one based on each type of informant (child, parent, teacher). The research question of whether sex moderates the associations between aggressive and prosocial behaviour was assessed in each of the models. A series of nested models were fit to the data in which each of the cross-lagged parameters were constrained to be equal across sexes.
Finally, nested mediation models were tested to assess the influence of peer difficulties on the association between prosocial and aggressive behaviour at each cross-lag (see Figure ). Specifically, a model in which the paths from and to peer difficulties were restrained (no mediation) was compared to a model, in which these paths were free to vary (or account for variance). These final models were only tested utilising the teacher reported data for several reasons. First, the reports about peer difficulties were provided by the teachers based on their observation of the children in the classroom, based on which they also rated their engagement in aggressive and prosocial behaviours. Furthermore, some research suggests that teacher reports of behaviour at school are more reliable than those of children (e.g., Ladd and Profilet ). Autoregressive cross-lagged model of the association between prosocial behaviour and aggressive behaviour, including mediation by peer difficulties.
Note: Not displayed are pathways controlling for the effects of treatment as pictured in Figure 1 and residual correlations. All of these were estimated as described in the data analytic plan. The dotted lines represent the influences by peer difficulties; paths a1, a2, and a3 represent the influence of aggression at time t on peer difficulties at time t+1; paths b1, b2, and b3 represent the influence of peer difficulties at time t on prosocial behaviour at time t.
Paths c1, c2, and c3 represent the direct influence of aggressive behaviour at time t on prosocial behaviour at time t+1. Missing data Prior to conducting the final data analysis, missing data patterns were examined.
The number of missing values over the four time periods was 4% for teacher reported measures, 8.5% for parent reported measures, and 7% for child reported measures. As missing data for each type of informant were not related to any of the demographic variables collected at W1 (age of parent and child, ethnicity, SES, education, single parenthood), they were handled through the use of Full Information Maximum Likelihood Estimation, which produce valid estimates under the assumption that the missing data are missing at random (MAR; Rubin ). Descriptive statistics Descriptive statistics and paired-samples t-tests revealed significant differences in the mean levels of boys’ versus girls’ aggressive and prosocial behaviours at each wave of data collection for all informants (see Table ).
At each wave, boys rated themselves lower and were rated lower by both their parents and teachers on prosocial behaviour and higher on aggressive behaviour. Effect sizes for sex differences in prosocial behaviours ranged from small to medium, with largest effect sizes observed based on teacher reports. The effect sizes for differences in aggressive behaviour remained in the small range (maximum 0.44 according to teacher reported aggression at age 11; see also Nivette et al. There were, however, no significant mean differences in the rate of peer difficulties experienced by boys and girls as reported by their teachers. The inter-correlations between the study variables are displayed in Table.
The within-informant correlations between the ratings of the child’s aggressive and prosocial behaviour were small to medium, but negative and significant at each wave. The correlations between teacher reported aggressive behavior and peer difficulties were positive and medium in size. On the other hand, the correlations between prosocial behaviours and peer difficulties were negative and small. Structural equation models All SEM models were evaluated using recommended fit indices, including root mean square error of approximation (RMSEA), where values.90 indicate acceptable fit and values.95 indicate good fit (McDonald and Ho ).
Because the χ 2 becomes increasingly sensitive with growing sample size (Marsh et al. ), it was not considered for evaluation of model fit. Instead, we used practical fit indexes to test for sex invariance. According to Little , model invariance can be assumed (a) if the overall model fit is acceptable, as indicated by relative fit indexes (e.g., if the CFI is approximately.90 or greater; Marsh et al.,; and if the RMSEA is less than.05; Browne and Cudeck ); (b) if the difference in model fit is negligible (e.g., ≤.05 for the fit indices) after introduction of the equality constraints; and (c) if the justification for the accepted model is substantively more meaningful and the interpretation is more parsimonious than the alternative model. In addition, we followed recommendations by MacCallum et al.
and used the 95% confidence interval (CI) around the RMSEA to evaluate model fit and for nested model comparisons. Specifically, if the upper bound of the CI is equal to or lower than.05, a close fit of the model to the data can be assumed. Moreover, if the CIs of subsequent nested models overlap with those of preceding, less constrained models, the more parsimonious model is deemed acceptable. Sex Invariance In the first step of the analyses, we examined whether invariance across boys and girls can be assumed. Model invariance across the sexes was assumed to be more parsimonious and was tested in the model for each type of informant by comparing the fit indices of nested models: A model where all the regression weights were free to vary across boys and girls, and a model in which these regression weights were constrained to be equal (see Table ). Comparison of fit indices supported sex invariance (no significant sex differences) in the predicted paths between aggressive and prosocial behaviour over four points of data collection, from 7 to 10 years of age. This was the case for each of the models (see Table ); teacher reported (NFI =.939, CFI =.940, RMSEA =.050), parent reported (NFI =.922, CFI =.921, RMSEA =.060) and child self-reported (NFI =.907, CFI =.904, RMSEA =.038).
Chi-square difference tests were also carried out for each informant and provided further support for sex invariance (critical value 12.59 observed difference of 5.89, 4.66 and 10.74 for the teacher, parent and child model, respectively; p. Cross-lagged relations between prosocial behaviour and aggressive behaviour Next, we examined the cross-lagged effects between aggressive and prosocial behaviour. Based on both the teacher- and parent-reported models, increases in aggressive behaviour at time t n consistently and significantly predicted decreases in prosocial behaviour at time t n+1 across each of the waves. However, based on both the teacher- and parent-reported models increases in prosocial behaviour at time t n did not predict decreases in aggressive behaviours at time t n+1. A similar pattern of negative paths from aggressive behaviour to prosocial behaviour was observed in the model based on children’s self-reports. However, only the paths from aggressive behaviour at age 7 to prosocial behaviour at age 8 reached statistical significance (see Table for all model coefficients).
Mediation by peer difficulties Next we tested a model (see Figure ), in which peer difficulties at t n+1 was included as a mediator of the links between aggressive and prosocial behaviours one year later (at t n+1). This model yielded a significant goodness of fit for the overall model, χ 2 (126) = 386.907; p.
Discussion Both, aggressive behaviour and prosocial behaviour, have been identified as crucial in children’s social development (Eisenberg; Eisenberg et al.,; Eisner and Malti ). While both behaviours have been studied extensively independently, less is known about the way they relate to each other throughout development. The current study contributed to this understanding by examining the bidirectional cross-lagged links between aggressive and prosocial behaviours in a large-scale sample of boys and girls from age 7 to 11. The relations were examined on the basis of teacher, parent and child self-reports. Aggressive behaviour and prosocial behaviour Our first main finding was that both, aggressive behaviour and prosocial behaviour one year prior, were strong predictors of the same behaviour one year later, thus suggesting considerable stability in both behaviours.
There is evidence in support of stability of aggressive behaviour across normative and high-risk samples from early childhood (Crick et al. ) through adolescence (Piquero et al. Much less is known about the stability or change in prosocial behaviour over time (Hay and Cook ).
The handful of studies which have explored these trends suggest a modest continuity in prosocial behaviours according to teacher reports, but not peer nominations measured at two time points, from age 9 to 12 (Zimmer-Gembeck et al. ) and from age 5 to 6 (Eivers et al.
The current study provides support for the continuity of both aggressive and prosocial behaviours by demonstrating these relations across four time points, from age 7 to 11 in a large sample. Importantly, the level of stability was similarly high for prosocial behaviour as it was for aggressive behaviour. We also found evidence for the one-directional prediction of aggressive behaviour on prosocial behaviour one year later but not vice versa. Children’s elevated levels of aggressive behaviour at time t n predicted a decreased level of their engagement in prosocial behaviour at t n+1 after controlling for their propensity to engage in prosocial behaviour at t n.
In contrast, no evidence in support of the effects in the opposite direction was found. Our results suggest that this pattern of findings holds equally for boys and girls and was evident in the parent and the teacher reports. Findings for the child reports were in the same direction, but were not significant, with the exception of the effects of aggressive behaviour at t 1 predicting decreased prosocial behaviour at t 2.
The lower consistency in the results for the child self-reports can be due to the fact that the child data have lower reliability, resulting in attenuated observed measures of existing relationships. Nevertheless, it is important to note that teacher, parent and child reports were all positively correlated across all time points with respect to both types of behaviours. Given that the pattern of findings is consistent across informants, we believe that our findings provide evidence of the one-directional pattern of effects of levels of aggressive behaviour on levels of prosocial behaviour but not vice versa. Taken together, these findings are consistent with the findings of Chen et al. based on a similar design in a similar sample of children in China. The authors found that aggressive behaviour at t n was related to social competence at t n+1, but that social competence did not predict later aggressive behaviour.
Although social competence as measured by Chen and colleagues and prosocial behaviour as measured in this study are not the same construct, they are closely related. The consistency of findings in two different cultures suggests that they may reflect universal rather than culturally specific dynamics. Conceptually, there are several possibilities of how one type of behaviour can influence subsequent behaviour patterns within the same individual.
In this paper we expanded previous research by examining the role of peers and specifically peer difficulties on facilitating this link. Our findings suggest that aggressive behaviour is related to children’s subsequent experiences of peer difficulties, which in turn is related to decreases in prosocial behaviours.
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These findings are consistent with a transactional model developed by Sameroff , which proposes that an individual’s behaviour has effects on the social environment, which in turn triggers change in another behaviour domain. In other words, our findings suggest that children who engage in aggressive behaviour may elicit negative social evaluations by others, which are associated with peer difficulties and in turn may lead to fewer opportunities to practice and further develop social competencies. However, as prosocial behaviour and peer difficulties are measured at the same time, it is also possible that increases in aggression lead to decreases in prosocial behaviour, and this in turn results in increases in peer difficulties. This possibility warrants further examination. In line with our findings and our proposed primary interpretation, some research suggests that children’s social reputation among peers significantly decreases when they continuously behave overtly aggressively (e.g., Card et al. These children are often rejected by prosocial peers and continue to be rejected by peers overall even one year later (Lansford et al.
Also, aggressive children may not readily express moral emotions based on respect, reciprocity and cooperation, and hence lower the readiness of more socially competent children to engage in interactions with them (Gasser and Malti ). Thus, aggressive behaviour is likely to be linked to peer difficulties because victims of aggressive behaviour may avoid subsequent contact with the aggressors due to a fear of further victimisation (Rubin et al. Some research suggests that based on their experiences of difficulties with prosocial peers and acceptance by aggressive peers, children develop negative views of themselves (Rudolph and Clark ), which may lead to lowered motivation to act in a prosocial way. Others (e.g., Volk et al.
) suggest that aggressive behaviour in children and adolescents has strategic and evolutionary roots. Following this argument, children who successfully aggress against others may have fewer incentives to engage in cooperative behaviour. Notably, peer difficulties were a significant mediator between aggressive behaviour and prosocial behaviour up until age 9. However, it was no longer significant in linking aggressive behaviour at age 9 to prosocial behaviour at age 11. Possibly, aggressive behaviour in younger children exerts a greater influence on future peer difficulties than in older children, where the pattern of peer difficulties may already be set, aggression becomes more valued (or less disliked) and/or children transfer into different classrooms/schools as it was the case in this study.
Both of these hypotheses warrant further inquiry to further elucidate the role of peer difficulties in the development of these behaviours from childhood to pre-adolescence. The current study utilised a new measure of peer difficulties and as such these findings are not directly comparable with other studies exploring the role of peer rejection and victimisation specifically. Future research needs to extend our study and investigate the moderating and mediating role of various other dimensions of peer relationships (e.g., friendship quality, characteristics of friends and peers, etc.) and other processes, unexplored in the current study, that may also contribute to the link between aggressive and prosocial behaviour.
For example, there is ample evidence suggesting that aggressive children tend to develop friendships with other aggressive children (e.g., Bowker et al. Children who are surrounded by aggressive peers may also be under peer pressure and at first opt to not engage in prosocial behaviours so as to appear tough, avoid ridicule, or feel accepted as part of the peer group (e.g., Pepler et al. Through these associations, children may be exposed to fewer opportunities to practice previously acquired, or to acquire new, social skills, which would allow them to engage in more prosocial behaviours.
Each of the above explanations adopts the more common interpretation in linking higher levels of aggression to decreased levels of prosocial behaviour later. However, the opposite is possible as well. Specifically, it is plausible that children’s low levels of aggressive behaviour predicted an increased level of their engagement in prosocial behaviour later after controlling for their propensity to engage in prosocial behaviour. In the current study we did not examine the specificity of these links, but this question represents another important future direction for research in this area. Interestingly, prosocial behaviour in the previous year did not negatively predict aggressive behaviour in the following year according to any of the informants.
In other words, engaging in more prosocial behaviour in one year did not predict decreases in aggressive behaviour the next year. This may imply that children’s engagement in more helpful and considerate behaviours is not directly linked to their engagement in less aggressive behaviours. Given the low level of aggressive behaviour overall among the children in this sample, it is possible that children with relatively high levels of prosocial behaviour do not engage or engage in only low levels of aggressive behaviour.
However, this would not explain why increases in aggressive behaviour one year would predict decreases in prosocial behaviour the next year. Variation in aggressive behaviour over and above the individual propensity might be driven by factors other than other-oriented, prosocial behaviour, for example emotion recognition, empathy, and emotion regulation. Here we did not examine various additional other-oriented social-emotional skills, such as identifying and managing emotions, understanding others’ emotions, and how they may be related to both types of behaviours, and cross-lagged relations on each other over time (see Fraser et al. Given the importance that is placed on the development of other-oriented, prosocial skills with the goal to decrease aggressive behaviours and increase prosocial behaviours, the examination of these links is a crucial next step in understanding the processes through which positive behavioural outcomes are expected to occur. Consistent with past research, our results also revealed sex differences in the mean levels of aggressive and prosocial behaviour (Ostrov and Keating ). However, the developmental relations between aggressive behaviour and prosocial behaviour were not dependent on the sex of the child. This finding provides further evidence suggesting that the processes through which these two behaviours are related may not be gender-specific.
Furthermore, our results suggested that boys and girls experienced similar levels of peer difficulties from age 7 to 11. Similarly, the effects of peer difficulties did not differ in linking aggressive and prosocial behaviours in boys versus girls.
These findings are consistent with reports from previous studies (e.g., Crick and Dodge ), which found no sex differences in the links between peer rejection and reactive and proactive aggression. Further supporting previous findings but extending research by documenting these links over a five-year period, peer difficulties were consistently concurrently related to increased aggressive behaviours and decreased prosocial behaviour. Thus, this finding further documents the harmful effects of peer difficulties on child development across two behavioural domains.
While the multi-informant measurement of prosocial and aggressive behaviour in a large sample of children over five years constitutes a strength of this study, several limitations should be noted. First, we focused only on direct/overt aggressive behaviour and overt prosocial behaviour, which included helping, sharing, and comforting behaviours. As we pointed out earlier, this approach has its advantages. However, recent evidence suggests that different types of aggressive behaviour, such as relational and physical aggression, may have different developmental links with later prosocial behaviour (Carlo et al. In the present study, we focused on overt direct aggression, amongst others because indirect aggression is much more difficult to assess by raters such as teachers or parents. Future research is needed to examine the developmental causal pathways between sub-domains of aggressive and prosocial behaviour.
For example, future studies should examine the pattern of these relations with respect to relational aggression as it is possible that these will differ for girls versus boys. Furthermore, the aggression and prosocial variables in this study were skewed, as is to be expected in a normative sample. This could have influenced the estimates, however, according to Satorra non-normality in structural equation models is not a problem with large samples (over 1000 as is the case in this study) and results are robust. Second, our assessment of peer difficulties was based on teacher reports.
While peer difficulties are most commonly observed in the school context and teachers provide solid ratings of peer difficulties, future studies that combine teacher reports and peer nominations may elucidate similarities and differences of these ratings in relation to aggression and prosocial behaviour. Third, while the parent and teacher scales of aggressive and prosocial behaviour were directly adapted from a well-established instrument (SBQ; Tremblay et al. ), the parallel child measure involved a greater adaptation due to its computer-administration and dichotomous response style. These adaptations were implemented in order to provide children a more accessible response alternative.
The internal reliability of the child scales was relatively low, in particular with respect to prosocial behaviour, hence the results related to the child-reported behaviours should be interpreted with caution and warrant replication. Conclusions Despite some limitations, the current study offers insights into the effects aggressive and prosocial behaviours have on each other with a one to two year lag, and has as such implications for the design of interventions that aim to reduce aggression.
Specifically, our findings highlight that prosocial behaviour may not necessarily be seen as a main proximal target of intervention strategies. Our study provides further support for the role of peer difficulties as an important mechanism linking aggressive behaviour and subsequent decreases in prosocial behaviour. Together these findings suggest that promoting positive peer relationship may be an important component of interventions with young people exhibiting behaviour problems. Endnotes aFrom here on we will use the term ‘parent’ to refer to the primary caregiver. The vast majority of primary caregivers (97%) were biological mothers. BModel invariance by immigration status (yes/no) was tested and compared to the unconstrained model was not significantly different than the constrained (invariant) model, suggesting that immigration status did not make a difference in model fit.
CThe presented coefficients are unstandardised estimates recommended by Kline to be used when reporting results in AMOS, as only those (and not the standardised estimates) are influenced by identification constraints. The authors would firstly like to thank the children, parents and teachers who participated in the study as well as the numerous research assistants who were instrumental in collecting this data. The authors would also like to acknowledge the generosity of the Jacobs Foundation (Grant 2010–888), the Swiss National Science Foundation (Grants 129 & 124), and the Swiss Federal Office of Public Health (Grant 8.000665) each of which provided continued financial support for this project.
Competing interests The authors declare that they have no competing interests. Authors’ contributions IO has made a substantial contribution to the analysis and interpretation of data, drafting, revising and finalising the manuscript.
ME has made a substantial contribution to the acquisition of data, contributed to the drafting of the manuscript, and interpretation of data. TM has made a substantial contribution to the drafting of the manuscript and contributed to the interpretation of data. DR has made a substantial contribution to the acquisition of data. All authors read and approved the final manuscript.
Note: If you are new to the K2000 or are new to deploying images to Macs, I strongly suggest you also viewing Corey Serrins article related to imaging for both Windows and Mac systems. There is a 33 minute video session containing both environments. The Mac capture and deploy process described in the below steps are provided on the walk through video, showing you every step of the process which will help set you at ease for the task at hand. Here is the link to Corey's article: Prior to starting the process of capturing a Mac image from a system, please make sure you are on the latest version of the Mac OS X for the system and also have the latest Macintosh CD. Only version 3.4 on the KBOX supports Lion (Mac OS X 10.7) so if this is the version you plan on capturing, please make sure the K2000 is on version 3.4. If you plan on using the captured image on different platforms of Mac, then it is also recommended to run a clean up script on the machine you plan on capturing the image from that will remove the cached KEXT files associated to the Mac OS X and its current system. To view an example of this type of clean up script.
When the image is ready, follow these steps:. Log in to the K2000 appliance. Click LibraryDownload Manager. Click Download for Mac OS X.
Insert the Mac OS X installation CD, but close out the installation pop up window. Then next process is to build a Netboot environment.
To do this, follow these steps:. Log in as admin to the Mac OS X system you plan on capturing the image from. The Mac OS X system must be on the same subnet as the K2000. Open the Media Manager you just installed.
Click the Create Netboot Image tab. In the K2000 Host Name field, enter the host name or IP address of the appliance. Browse to and select the Mac OS X installation disc. In the NetBoot Password field, enter the VNC-Remote Control Application password.
Confirm password. Click Start Build. When this completes, the NetBoot environment can be found on the Source Media and Boot Environments page. To enable and configure the K2000 appliance NetBoot server, follow these steps:. Log in to the K2000 admin console. Navigate to Settings & MaintenanceControl PanelNetwork Settings. Click Edit.
Click the Enable NetBoot Server (for Mac OS X client) check box. After making this selection, two BSDP field boxes will appear. Set the BSDP settings. (The settings used in the above screenshot are examples).
Save. The next step requires working with both Pre/Post install tasks. By default, there are some canned Pre/Post install tasks provided within the K2000 in relation to Macs. However, custom Pre/Post install tasks can be created if a canned version is not available for the task you need to be performed during the image process.
To setup the Pre/Post install tasks, follow these steps:. Log in to the K2000 admin console. Navigate to DeploymentsSystem Images. Your newly created system image will appear here.
A System Image Detail page will appear. Drag and drop your Pre and Post installation tasks from the right columns to the left columns in the order of which you want the tasks to take place.
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If you are only planning on using the default Preinstallation Tasks given, the order must be:. Save. (optional) If you plan on creating custom Pre/Post installation tasks, follow these steps prior to adding them to the order on the System Image Detail page:. Log in to the K2000 console. Navigate to Library and select either the Preinstallation Tasks tab or the Post Installation Tasks tab. Select Choose ActionAdd New Shell Script. Based on the tab chosen either a Preinstallation or Post Installation Task Detail page will appear.
Glance over to the right side of the page (often overlooked). Information in creating a custom pre/post installation task is not found in the manual but is found in this section. The right side discusses where to find documentation related to creating a custom task. By default, your shell script must begin with #!/bin/bash. Build the rest of your custom script based on the tutorial content found from the link provided for. Whe finished with the shell script, save it.
Then switch back over to your System Image Detail page to find your custom task. Below is an example of a Custom Post Installation task for changing the computer name after they system has been imaged. NOTE: Custom Pre/Post installation tasks are normally not a supported feature provided by KACE Support. KACE Support will attempt best effort in trying to resolve an issue with a custom designed Pre/Post installation task, however if you want KACE Support to create one for you then this type of service request would be handled by Dell KACE Pro-Services. Now you are able to NetBoot and image a Mac system. If you would like to view the image process from start to finish, press CMD and V (verbose mode)on the Mac in question. To view other articles related to the above information and troubleshooting NetBoot/Imaging issues.
To capture the image, NetBoot the Mac unit you plan on taking the image from. It will bring you to what would look like a very basic user interface with a very small number of choices on a Dock.
Click on the K2000 Image Utility App in the Dock to launch the application and the utility will appear. Select the Capture Image tab in the utility. Select the appropriate volume to capture (most often Macintosh HD) and select Start Capture in the bottom right corner. When complete, the image is now ready to deploy. To deploy the image, NetBoot the Mac unit(s) you would like to deploy to. Access the same utility only select the Deploy Image tab. NOTE: Not all Mac systems can be upgraded to Lion (10.7.X) if you are in fact trying to image an older Mac computer with Lion.
Make sure the Mac system meets the requirements found in this article that Apple has made available on their website.