Students identified as having special educational needs (SEN) in secondary school showed significantly poorer social-behavioural outcomes. This is similar to findings for this sample at younger ages (Taggart et al., 2006; Anders et al., 2010). It is worth noting that the link between behaviour problems and learning difficulties is often reciprocal. An additional strong predictor was the experience of multiple disadvantage from a young age 2 . For instance, students who had experienced several disadvantages in the early years continued to show poorer ‘self-regulation’ and ‘pro-social’ behaviour and increased scores for ‘hyperactivity and ‘anti-social’ behaviour in adolescence at the end of KS3.
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A methodological complication was that for some schools (e.g., independent schools) no CVA scores were calculated by the DfE or Ofsted inspection judgments were unavailable while others fall outside Ofsted’s jurisdiction. Such data are said to be structurally missing (as opposed to missing due to e.g., attrition) and the recommended practice among methodologists is to exclude affected variables from the multiple imputation process for substantive rationales. Given these limitations, the estimates produced on the multiply imputed data are based on a reduced sample size as data for students where there was no valid CVA scores or Ofsted inspection judgements was available were excluded from the analyses. Despite these difficulties analyses revealed significant secondary school influences on students’ social-behavioural outcomes in KS3, as well as consistent evidence of a cross-level interplay between these influences and individual student background factors. Measure of secondary school academic effectiveness (the four-year school average CVA score) did not predict students’ social-behavioural outcomes in Year 9 to any significant extent. This measure only relates to academic attainment in GSCE subjects, so it may not have a straightforward bearing on social-behavioural development. Similarly, the school-level aggregate social composition as measured by the percent students who are FSM recipients, the percent students identified as SEN, and the percent students of White British heritage, was not significantly related to social-behavioural assessments by Year 9 teachers. This is in contrast to the findings on EPPSE students’ academic outcomes (Sammons et al, 2011a) which were predicted by these factors.
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The level of neighbourhood disadvantage 3 predicted social-behavioural outcomes after controlling for other characteristics although relationships were weak. Higher levels of disadvantage in the EPPSE sample predicted poorer ‘self-regulation’, higher levels of ‘hyperactivity’ and increased ‘anti-social’ behaviour. Higher levels of criminality in neighbourhoods also predicted poorer outcomes in all four social-behavioural domains (e.g. ES=0.14 for ‘hyperactivity’). Higher levels of unemployment in the area predicted higher levels of ‘hyperactivity’ in 14 year olds but did not influence other social-behavioural outcomes. Finally, a higher incidence of limiting long-term illness in the neighbourhood predicted lower scores for ‘self- regulation’. All these relationships were identified after controlling for the influence of individual, family and HLE characteristics. Although neighbourhood influences were small they were statistically significant (in contrast to findings for this group at younger ages) and are similar to the effects on academic outcomes.
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172 The purpose of the current article is to consider whether variation in the endorsement of criminal stereotypes helps explain variation in affective, behavioural and attitudinal responses to crime. Importantly, this is the first time that the Stereotype Content Model (SCM) (Fiske et al., 2002) has been applied to public attitudes toward the punishment of criminals. Two studies test an integrative theoretical account of stereotyping on an important socio-political phenomenon of our time. Public discourse about crime and punishment is fraught with language that suggests that criminals are ‘evil’ ‘cruel’ ‘monsters’ and ‘bad’, that we should adopt ‘harsher’ or ‘stiffer’ laws and sentences, and that society and its institutions should engage in a ‘war’ or ‘get tough’ on crime. Two studies link perceptions and responses to the ‘Big Two’ dimensions of social perception – warmth and competence – to punitive attitudes. The studies apply Fiske and colleagues’ (2002) SCM as well as Cuddy and colleagues’ (2007) Behavior from Intergroup Affect and Stereotypes (BIAS) map. The studies depart from the ways in which the SCM and BIAS map are typically employed by looking at heterogeneous perceptions of a single social group (i.e., criminals) and differences in attitudinal responses to these perceptions.
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Early identification of autistic features, or indeed socio-communicative difficulties, may facilitate early recognition of symptoms in order for support to be provided for families. Screening in early adolescence has been shown to have good diagnostic utility and a number of studies have found that infant developmental test scores and abnormal ratings on the CBCL, particularly the withdrawn scale, are associated with ASD features in infancy and childhood.[42, 48] A recent study has also suggested that NICU graduates with ASD may display a unique behavioural profile including the persistence of abnormal neonatal neurobehaviours and a declining developmental trajectory in infancy. However, this was a heterogeneous sample of babies admitted for neonatal intensive care and the significance and predictive utility of such markers requires investigation in a purely preterm population.
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challenges for children in specific circumstances and how these relate to different outcomes. For example, where children are living with a number of siblings, they may benefit from additional support to realize their potential; and where they are living with a depressed or lone parent, they may benefit from specific support in terms of their behavioural outcomes. Support for financial literacy may also have direct pay-offs in reducing stress within the home and helping to bring about more favourable outcomes for children. Receipt of benefits and being behind on bills, as well as receiving financial help from grandparents, were associated with worse outcomes, even taking poverty into account. This suggests that, beyond income itself, the source and management of that income may be related to children’s outcomes. The analysis also showed that even those factors which have a significant relationship with children’s outcomes only ‘explain’ a small part (up to a quarter) of the differences in
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Table 5.1 summarises the findings from value added multilevel analyses testing the predictive power of Year 2 pupils’ self-perception factors in multilevel models of children’s cognitive and social/behavioural outcomes. The findings suggest that relative to the other two self-perception factors, pupils’ earlier ‘Behavioural self-image’ has the strongest predictive power and indicates that the children who had a more positive ‘Behavioural self-image’ in Year 2 made more all round improvements in social/behavioural development and greater progress in Reading between Year 1 and Year 5. In addition, the effect sizes for social/behavioural outcomes are higher than for cognitive outcomes, which one would expect since perceptions of pupils’ own social behaviour are more likely to predict later social/behavioural outcomes than later cognitive outcomes. Interestingly, out of all three pupils’ self-perception factors, only ‘Enjoyment of school’ was statistically significant in the final value added model for Mathematics. This suggests that ‘Enjoyment of school’ measured in Year 2 had a stronger impact on progress in Mathematics than other pupils’ self-perception factors.
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Findings from multilevel analyses showed that pupils’ ‘Behavioural self-image’ is an important predictor and indicate that pupils who had higher ‘Behavioural self-image’ in Year 2 (age 7) had all round better social/behavioural development and higher cognitive attainment and made better progress by Year 5 (age 10). In addition, the associations of ‘Behavioural self-image’ with social/behavioural outcomes are higher than for cognitive outcomes, which we expected since perceptions of pupils’ own social behaviour are more likely to predict later social/behavioural outcomes than later cognitive outcomes. The factors ‘Enjoyment of school’ and ‘Academic self- image’ did not show strong relationships with the outcomes after controlling for other influences. Nevertheless, they were significant when used separately from other pupils’ self-perception factors. In general, higher levels of ‘Academic self-image’ were related to higher Mathematics scores, better ‘Self-regulation’ and ‘Pro-social’ behaviour, and lower ‘Hyperactivity’. Medium and high levels of ‘Enjoyment of school’ were related to higher Mathematics scores, and better ‘Self- regulation’ and ‘Pro-social’ behaviour, whereas medium levels of ‘Enjoyment of school’ were related to higher Reading scores and lower ‘Hyperactivity’. The findings were broadly similar to the results of Year 5 pupils’ perceptions even though there are some apparent differences, particularly in the effect of ‘Academic self-image’. 6
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One problem with looking at behavioural outcomes alone when evaluating public health initiatives is that it ignores the possibility that there might be other, perhaps harmful, effects that should be set against the benefit of behaviour change. Even in the case of smoking and lung cancer there may be risks or harms as well as benefits from health education initiatives deemed successful in behavioural terms. To illustrate this point we draw on our recent research identifying factors that contribute to a delay in lung cancer diagnosis (Tod et al 2008). This examined the pathway of people from first symptom to lung cancer diagnosis and identified a number of issues that helped and hindered people in reporting their symptoms to a health professional. The data identified examples of how health education regarding smoking cessation can have unanticipated harmful effects as well as the anticipated benefit of encouraging people to stop smoking. Let us turn to these harmful effects.
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Type of norms and behavioural outcomes From all 27 included studies, 20 studies investi- gated the relationship between subjective norm and risky driving behaviour, three studies investi- gated on the relationship between group norm and risky driving behaviour, seven studies inves- tigated the relationship between moral norm and risky driving behaviour, six studies investigated the relationship between injunctive norm and risky driving behavior and finally, nine studies investigated the relationship between descriptive norm and risky driving behaviour. The behav- ioural outcomes of risky driving behavior in this review are speeding, dangerous overtake, used of mobile phone while driving, drink-drive, tailgat- ing, disobey road sign, run over red light and ne- glect the helmet usage.
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Data show that pan-London simulation training under the London Stroke Model has positive outcomes for staff in terms of their emotional reactions and self-reported behavioural outcomes, both in terms of skills and motiv- ation. These effects persist to a certain extent in practice, where staff can recall training episodes and change engen- dered. Simulation ‘debriefing’ after live video recorded scenarios offers many possibilities for tailored behaviour change techniques; trainers should be clear about a) target behaviours/learning objectives, and b) specific mecha- nisms of change. Simulation training was effective in help- ing achieve HASU-specific learning outcomes and the project demonstrated that a carefully designed simulation programme congruent with clinical practice can provide valuable training opportunities that support patient care.
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In one area, however, there are differences. An extended time in pre-school (associated with a younger starting age - e.g. at age 2 years or below - at entry to the target pre-school often associated with Local Authority and Private Day nurseries) is linked with poorer outcomes for ‘Anti-social / Worried’ behaviour both at age 3 years plus (the start of the pre-school study) and at rising five years (start of primary school). For cognitive outcomes, however, an earlier start is associated with better progress and higher attainment at entry to primary school. This pattern of poorer antisocial behaviour, yet higher cognitive attainment, associated with an early start in group care, has also been found in the major American study of child care (NICHD, 2002). Quality of pre-school provision (as measured by the total observational schedule ECERS-R) was positively related to better child outcomes in ‘Co-operation & Conformity’. The results of analyses of the ECERS-R subscales suggest that two specific aspects of quality measured by this instrument (language and reasoning and social interaction) are associated with better social behavioural outcomes at primary school entry. In addition, other observational measures of adult child interactions (the Arnett Caregiver Interaction Scale), are related to three of the social behavioural outcomes. These findings indicate that high quality of pre-school is associated with more positive impacts on social behavioural developmental gains. These results are supported by other studies (e.g. NICHD, 2002) finding positive effects for quality of child care upon social development. Howes & Olencik (1986) found that higher quality child care was associated with increased co-operation for children and both Lamb et al. (1992) and Vandell et al. (1988) report better social adjustment for children was associated with higher quality child care.
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MDFT is often regarded as a substance abuse treat- ment programme, for historic reasons (funding sources and initial research interests) and achieved outcomes, but the approach is also valuable for treating adolescent externalising symptoms and delinquency. In teens, sub- stance use frequently occurs along with a constellation of other problems [35,36]. In earlier trials [18-20] and the present one, MDFT reduced the rate of externalising symptoms, more so than active comparison treatments. Lowering the level of externalising symptoms may help a youth to refrain from criminal offenses [35,36]. The effect of treatment on externalising symptoms merits further study in relation to the distal goal of reducing criminal offenses.
to texts because it actually takes a painstaking effort to do so, especially when typing, we however encourage our scholars and teachers to take the pain because it is a worthy one. If we fail to do this, the teaching of this language would not be done effectively; the learning outcomes would also continue to be unproductive; and both meaning and correct pronunciation of certain lexical items in the language would as well continue to be adversely affected. One the other hand, in teaching English at the primary level of education, the teacher is duty-bound to define or make known to the learner what parts of speech are. And they are usually defined thus “A noun is a naming word” “A determiner is a word which is used at the beginning of a noun group to indicate which thing one is referring to, or whether one is referring to one thing or several”. “A verb is a doing or an action word” “A pronoun is a word used instead of a noun to avoid unnecessary repetition” “An adverb is a word which modifies, completes or adds to the meaning of the verb, adjective and another adverb” “An adjective is a word which qualifies or describes a noun or pronoun” “A preposition is a word which shows relationship between two entities or things” “A conjunction is a word used in joining or connecting words, a group of words or clauses together” etc. Defining parts of speech this way has already become part of the learner from this level, even to the secondary level of education. From our dealings with both pupils and students over the years, when asked to define any of these parts of speech, they usually do so with ease but when a teacher makes a sentence and asks them to show which one is an adjective, an adverb, or a verb, etc., they either start guessing or stare at the teacher
Figure 1 presents the variation in 10-year CVD risk, which was separately attributable to fixed and modi- fiable risk factors, among the 20 primary care clinics. The embedded pie chart details the proportion of attrib- utable risk associated with each of the 4 behavioural factors for 1 selected clinic. As presented, a substan- tial amount of variability existed among the clinics in terms of both overall CVD risk and attributable risk. The multivariable analysis examining individual patient behaviour revealed that patients who reported good management of their diets and adherence to prescribed medication regimens improved their mean risk of any cardiovascular event by 44% and 39%, respectively (P < .03). Self-report of regular exercise had no significant effect on overall CVD risk in this study.
A total of 117 children had been placed in one of The Orchards’ eight houses since it opened (in June 1991) and had left by the time the fieldwork for this research started (in January 2007) (Table 1). The target sample was restricted to former residents who were at least 16 years of age and who had finished their final year of compulsory education (n=77). These inclusion criteria were chosen for two main reasons: first, to ensure that we had some established measures of educational achievement that would enable us to assess our respondents’ outcomes in this area and compare these with those of their peers in the literature; and secondly, to minimise the risk of the research having any adverse effect upon the care or education which potential participants might have been receiving.
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CR in the SUD population. Another difficulty of the lit- erature is that studies often exclude participants with common comorbidities such as traumatic brain injury and psychiatric comorbidities. This ultimately affects the generalisability of results. In addition, many studies have relied on performance-based measures of EF rather than more ecologically valid EF measures, which have been shown to be better predictors of real-world functioning and treatment success . Finally, previous SUD literature has not followed-up the long-term effects of compensatory CR, such as treatment retention and recovery. Given findings of its success in improving functional outcomes in other cognitively impaired groups, we propose that compensatory CR aimed at improving EF is likely to be a beneficial adjunctive intervention to boost AOD treatment efficacy and long-term outcomes.
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As stated earlier the learning process itself leads to increased ability to carry out those same sub processes. That is, by remembering, understanding, etc. a situation or situations, one’s ability to do the same will be affected. Thus one finds the same sub-processes used in the Post-Informal Knowledge construct. Specifically, they are used to measure the cognitive learning dimension. The other dimension is the behavioural learning. This is the application of learning in the work place and can be seen as the main benefit of the research for practitioners. Behavioural learning is measured with the constructs previously used by Gullberg and Pelser (2006) to examine knowledge transfer in a high technology company: decision making skills, technical/functional skills, negotiation skills, and supervisory skills. This process may involve the use of communication media. In this study this is restricted to Information and Communication Technology (ICT) - a key enabler in the KM paradigm and is measured using two dimensions - Communication ICT and Knowledge Repository Based ICT. This differentiates between a person actively engaging in communicating with another human being (i.e. communication technology) and gaining information from a captured and codified source (i.e. a knowledge repository).
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program with the aim to guide evaluation of an intervention (Rogers et al. 2000). Logic model development is the centrepiece of rebuilding program theory, which intends to link investments in projects’ inputs with observed or intended outputs, outcomes and impacts. PT usually develops an ex-ante causal model to identify how research and development projects are likely to and should occur. In other words, an innovation pathway is developed and established before the research program is implemented. Is the researcher fully responsible for rebuilding the theory (the innovation pathway), or only a facilitator within the setting of participatory impact evaluations, whose interest is to enhance responsiveness during evaluation process in empowering stakeholders for mobilising changes as well as increasing the plausibility that results will be used (Weiss 1998; Cousins and Whitmore 1998). Greene (1987, 1988) even demonstrated that the participation level was correlated with political, emotional and intellectual implications, but Alkin advocated for the non- necessity to please all stakeholders at once as they are not necessarily the primary users of the evaluation (Alkin 1991). In this paper, the intervention evaluation is conducted in an ex- post manner, which needs innovative methodological developments.
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It is feasible to reliably assess the ﬁ delity of behaviour change interventions in clinical practice . However, there is limited evidence regarding methods for quantifying ﬁ delity within complex behaviour change interventions . A method to measure ﬁ delity to BS delivery requires capturing what is delivered: both its content- and interaction-based activities [13,16] and quantifying how these are delivered [24,25]. These can be conceptualized as compositional/structural features forming items of the index and functional/process features forming the anchors to quantify each item. While studies have previously devel- oped methods to characterize the content of BS using the behaviour change techniques (BCTs) taxonomies [26–29] and BCT associations with outcomes , these limit rat- ings to the delivery process and their predictive value for outcomes. The extent to which ﬁ delity of delivery of a BS in- tervention in ﬂ uences smoking cessation outcomes remains unclear.
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