Which outcome expectancies are important in determining young adults intentions to use condoms with casual sexual partners?: A cross-sectional study

Background: The prevalence of unwanted pregnancy and sexually transmitted infection amongst young adults represents an important public health problem in the UK. Individuals attitude towards the use of condoms has been identified as an important determinant of behavioural intentions and action. The Theory of Planned Behaviour has been widely used to explain and predict health behaviour. This posits that the degree to which an individual positively or negatively values a behaviour (termed direct attitude) is based upon consideration of the likelihood of a number of outcomes occurring (outcome expectancy) weighted by the perceived desirability of those outcomes (outcome evaluation). Outcome expectancy and outcome evaluation when multiplied form indirect attitude. The study aimed to assess whether positive outcome expectancies of unprotected sex were more important for young adults with lower safe sex intentions, than those with safer sex intentions, and to isolate optimal outcomes for targeting through health promotion campaigns. Methods: A cross-sectional survey design was used. Data was collected from 1051 school and university students aged 16-24 years. Measures of intention, direct attitude and indirect attitude were taken. Participants were asked to select outcome expectancies which were most important in determining whether they would use condoms with casual sexual partners. Results: People with lower safe sex intentions were more likely than those with safer sex intentions to select all positive outcome expectancies for unprotected sex as salient, and less likely to select all negative outcome expectancies as salient. Outcome expectancies for which the greatest proportion of participants in the less safe sex group held an unfavourable position were: showing that I am a caring person, making sexual experiences less enjoyable, and protecting against pregnancy. Conclusions: The findings point to ways in which the attitudes of those with less safe sex intentions could be altered in order to motivate positive behavioural change. They suggest that it would be advantageous to highlight the potential for condom use to demonstrate a caring attitude, to challenge the potential for protected sex to reduce sexual pleasure, and to target young adults risk appraisals for pregnancy as a consequence of unprotected sex with casual sexual partners

Object matching using boundary descriptors

The problem of object recognition is of immense practical importance and potential, and the last decade has witnessed a number of breakthroughs in the state of the art. Most of the past object recognition work focuses on textured objects and local appearance descriptors extracted around salient points in an image. These methods fail in the matching of smooth, untextured objects for which salient point detection does not produce robust results. The recently proposed bag of boundaries (BoB) method is the first to directly address this problem. Since the texture of smooth objects is largely uninformative, BoB focuses on describing and matching objects based on their post-segmentation boundaries. Herein we address three major weaknesses of this work. The first of these is the uniform treatment of all boundary segments. Instead, we describe a method for detecting the locations and scales of salient boundary segments. Secondly, while the BoB method uses an image based elementary descriptor (HoGs + occupancy matrix), we propose a more compact descriptor based on the local profile of boundary normals’ directions. Lastly, we conduct a far more systematic evaluation, both of the bag of boundaries method and the method proposed here. Using a large public database, we demonstrate that our method exhibits greater robustness while at the same time achieving a major computational saving – object representation is extracted from an image in only 6% of the time needed to extract a bag of boundaries, and the storage requirement is similarly reduced to less than 8%

Quantitative Analysis of Saliency Models

Previous saliency detection research required the reader to evaluate performance qualitatively, based on renderings of saliency maps on a few shapes. This qualitative approach meant it was unclear which saliency models were better, or how well they compared to human perception. This paper provides a quantitative evaluation framework that addresses this issue. In the first quantitative analysis of 3D computational saliency models, we evaluate four computational saliency models and two baseline models against ground-truth saliency collected in previous work.Comment: 10 page

Rapid Online Analysis of Local Feature Detectors and Their Complementarity

A vision system that can assess its own performance and take appropriate actions online to maximize its effectiveness would be a step towards achieving the long-cherished goal of imitating humans. This paper proposes a method for performing an online performance analysis of local feature detectors, the primary stage of many practical vision systems. It advocates the spatial distribution of local image features as a good performance indicator and presents a metric that can be calculated rapidly, concurs with human visual assessments and is complementary to existing offline measures such as repeatability. The metric is shown to provide a measure of complementarity for combinations of detectors, correctly reflecting the underlying principles of individual detectors. Qualitative results on well-established datasets for several state-of-the-art detectors are presented based on the proposed measure. Using a hypothesis testing approach and a newly-acquired, larger image database, statistically-significant performance differences are identified. Different detector pairs and triplets are examined quantitatively and the results provide a useful guideline for combining detectors in applications that require a reasonable spatial distribution of image features. A principled framework for combining feature detectors in these applications is also presented. Timing results reveal the potential of the metric for online applications. © 2013 by the authors; licensee MDPI, Basel, Switzerland