5 resultados para INCLUSION BEHAVIOR
em Deakin Research Online - Australia
Resumo:
Background
Study design and methods
A cross-section of 425 members of African CALD communities was surveyed face to face using bilingual workers, ensuring inclusion across literacy levels within the CALD community. Constructs used within the survey were drawn from the TPB blood donation literature (i.e., attitudes, social norms, and self-efficacy). A new measure of blood donation knowledge was included.
Results
Structural equation modeling found that the Basic TPB model did not hold for African CALD communities in Australia. The Basic TPB model was modified and within this Adapted TPB model attitudes were found not to impact intentions directly, but had a mediating effect through self-efficacy. An Extended TPB model including overall knowledge was then tested and improved the model fit statistics, explaining 59.8% variation in intentions. Overall knowledge was found to indirectly impact intentions, through self-efficacy, social norms, and attitudes.
Conclusion
The TPB applies differently when examining African CALD communities' blood donation intentions in Australia. Knowledge is an important mediating component of the Extended TPB model rather than directly affecting intentions. Addressing CALD communities' psychographic characteristics may assist blood services in developing targeted strategies to increase donations within these communities.
Resumo:
Objective: Evidence on the effectiveness of walking and cycling interventions is mixed. This may be partly attributable to differences in intervention content, such as the cognitive and behavioral techniques (BCTs) used. Adopting a taxonomy of BCTs, this systematic review addressed two questions: (a) What are the behavior change techniques used in walking and cycling interventions targeted at adults? (b) What characterizes interventions that appear to be associated with changes in walking and cycling in adults?
Method: Previous systematic reviews and updated database searches were used to identify controlled studies of individual-level walking and cycling interventions involving adults. Characteristics of intervention design, context, and methods were extracted in addition to outcomes. Intervention content was independently coded according to a 26-item taxonomy of BCTs.
Results: Studies of 46 interventions met the inclusion criteria. Twenty-one reported a statistically significant effect on walking and cycling outcomes. Analysis revealed substantial heterogeneity in the vocabulary used to describe intervention content and the number of BCTs coded. “Prompt self-monitoring of behavior” and “prompt intention formation” were the most frequently coded BCTs.
Conclusion: Future walking and cycling intervention studies should ensure that all aspects of the intervention are reported in detail. The findings lend support to the inclusion of self-monitoring and intention formation techniques in future walking and cycling intervention design, although further exploration of these and other BCTs is required. Further investigation of the interaction between BCTs and study design characteristics would also be desirable.
Resumo:
The present work introduces a double inclusion elasto-plastic self-consistent (DI-EPSC) scheme for topologies in which crystals can contain subdomains (i.e. twins, etc.). The approach yields a direct coupling between the mechanical response of grains and their subdomains via a concentration relationship on mean fields derived from both the Eshelby and the Tanaka-Mori properties. The latent effect caused by twinning on the mechanical response is observed on both initially extruded and non-textured Mg alloys. For twinned grains, it is shown that deformation system activities and plastic strain distributions within twins drastically depend on the interaction with parent domains. Moreover, a quantitative study on the coupled influence of secondary slip activities on the material response is proposed. © 2014 Published by Elsevier Ltd.
Resumo:
Sedentary behavior has negative health outcomes, evident even in young children. Identifying the prevalence of sedentary behavior in children <2years is important for determining the necessity for intervention strategies. The aim of this systematic review was to determine the prevalence of sedentary behavior in children <2years. Medline, PsycINFO, SPORTDiscus, and Education Research Complete electronic databases were searched, as were reference lists of included articles and the authors' own collections. Inclusion criteria were: published in a peer-reviewed English language journal; mean age of children <2years; and a reported measure of the prevalence of sedentary behavior. Twenty-four studies met the inclusion criteria. Most studies used parent-reported screen time as the sedentary behavior measure; only one study reported time spent restrained (i.e., kept inactive) and no studies reported objectively assessed sedentary time. Estimates of young children's screen time ranged from 36.6 to 330.9min/day. The proportion of children meeting the zero screen time recommendation ranged from 2.3% to 83.0%. In conclusion, very little is known about sedentary behaviors other than screen time in this age group. Although highly variable, findings suggest that children are already engaging in high levels of screen time by age 2 and the majority exceed current recommendations.
Resumo:
BACKGROUND: Independent of physical activity levels, youth sedentary behaviors (SB) have negative health outcomes. SB prevalence estimates during discretionary periods of the day (e.g., after-school), inform the need for targeted period-specific interventions. This systematic review aimed to determine children's and adolescents' SB prevalence during the after-school period.
METHODS: A computerized search was conducted in October 2015 (analysed November 2015). Inclusion criteria were: published in a peer-reviewed English journal; participants aged 5-18 years; measured overall after-school sedentary time (ST) objectively, and/or specific after-school SBs (e.g., TV viewing) objectively or subjectively; and provided the percentage of the after-school period spent in ST/SB or duration of behavior and period to calculate this. Where possible, findings were analyzed by location (e.g., after-school care/'other' locations). The PRISMA guidelines were followed.
RESULTS: Twenty-nine studies were included: 24 included children (≤12 years), four assessed adolescents (>12 years) and one included both; 20 assessed ST and nine assessed SB. On average, children spent 41% and 51% of the after-school period in ST when at after-school care and other locations respectively. Adolescents spent 57% of the after-school period in ST. SBs that children and adolescents perform include: TV viewing (20% of the period), non-screen based SB (including homework; 20%), screen-based SB (including TV viewing; 18%), homework/academics (13%), motorised transport (12%), social SB (9%), and screen-based SB (excluding TV viewing; 6%).
CONCLUSION: Children spent up to half of the after-school period in ST and this is higher among adolescents. A variety of screen- and non-screen based SBs are performed after school, providing key targets for interventions.
