Knowledge and Concern about STIs/HIV and Sociodemographic Variables Associated with Getting Tested for HIV Among the General Population in Spain

HIV testing is important in terms of prevention and treatment. However, HIV testing rates in the Spanish general population remains low. Therefore, HIV testing promotion constitutes a key issue. A high level of knowledge about HIV/AIDS is associated with having been tested for HIV. The general aim of this study was to determine the prevalence of people who had ever been tested for HIV in Spain. The sample consisted of 1,106 participants from the general population — 60.0% females and 40.0% males — aged between 17 and 55 years old. The assessment instruments were a questionnaire on sociodemographic data and HIV testing, a scale of knowledge about STIs and HIV/AIDS, and a scale of concern about STIs/HIV. Results showed that greater knowledge about STIs and HIV was associated with a greater likelihood of being tested for HIV (OR = .77; 95.0% CI = .73–.82; p < .05). In addition, higher concern about HIV/AIDS decreased the likelihood of not having been tested for HIV (OR = .87; 95.0% CI = .83–.92; p < .05). In fact, the higher participants concern about STIs was, the lower their likelihood of not having been tested for HIV was (OR = .87; 95.0% CI = .83–.91; p < .05). It is necessary to promote HIV testing in the general population as well as to consider their socio-demographic and psychological characteristics.     

Automated verbal credibility assessment of intentions: The model statement technique and predictive modeling

Recently, verbal credibility assessment has been extended to the detection of deceptive intentions, the use of a model statement, and predictive modeling. The current investigation combines these 3 elements to detect deceptive intentions on a large scale. Participants read a model statement and wrote a truthful or deceptive statement about their planned weekend activities (Experiment 1). With the use of linguistic features for machine learning, more than 80% of the participants were classified correctly. Exploratory analyses suggested that liars included more person and location references than truth‐tellers. Experiment 2 examined whether these findings replicated on independent‐sample data. The classification accuracies remained well above chance level but dropped to 63%. Experiment 2 corroborated the finding that liars' statements are richer in location and person references than truth‐tellers' statements. Together, these findings suggest that liars may over‐prepare their statements. Predictive modeling shows promise as an automated veracity assessment approach but needs validation on independent data.     

The dimensions of deception detection: Self‐reported deception cue use is underpinned by two broad factors

Many perceived cues to deception have been reported in the literature, but little attention has been paid to how they are combined when making deception judgments. The present research used a data‐driven approach to investigate how cues are integrated when evaluating veracity. Two hundred fifteen participants performed a deception detection task before completing a deception cue use questionnaire. A factor analysis of the questionnaire data produced two dimensions, one associated with nonverbal cues to anxiety and the other associated with detail and level of involvement. The present work extends our understanding of deception detection processes and underlines the importance of examining not only the cues that people use but also the way in which they use them.     

Detecting Clusters/Communities in Social Networks

Cohen's κ, a similarity measure for categorical data, has since been applied to problems in the data mining field such as cluster analysis and network link prediction. In this paper, a new application is examined: community detection in networks. A new algorithm is proposed that uses Cohen's κ as a similarity measure for each pair of nodes; subsequently, the κ values are then clustered to detect the communities. This paper defines and tests this method on a variety of simulated and real networks. The results are compared with those from eight other community detection algorithms. Results show this new algorithm is consistently among the top performers in classifying data points both on simulated and real networks. Additionally, this is one of the broadest comparative simulations for comparing community detection algorithms to date.     

Word Detection in Sung and Spoken Sentences in Children With Typical Language Development or With Specific Language Impairment

Background: Previous studies have reported that children score better in language tasks using sung rather than spoken stimuli. We examined word detection ease in sung and spoken sentences that were equated for phoneme duration and pitch variations in children aged 7 to 12 years with typical language development (TLD) as well as in children with specific language impairment (SLI ), and hypothesized that the facilitation effect would vary with language abilities. Method: In Experiment 1, 69 children with TLD (7–10 years old) detected words in sentences that were spoken, sung on pitches extracted from speech, and sung on original scores. In Experiment 2, we added a natural speech rate condition and tested 68 children with TLD (7–12 years old). In Experiment 3, 16 children with SLI and 16 age-matched children with TLD were tested in all four conditions. Results: In both TLD groups, older children scored better than the younger ones. The matched TLD group scored higher than the SLI group who scored at the level of the younger children with TLD . None of the experiments showed a facilitation effect of sung over spoken stimuli. Conclusions: Word detection abilities improved with age in both TLD and SLI groups. Our findings are compatible with the hypothesis of delayed language abilities in children with SLI , and are discussed in light of the role of durational prosodic cues in words detection.     

Mimicry and Investigative Interviewing: Using Deliberate Mimicry to Elicit Information and Cues to Deceit

We examined the effect of deliberate mimicry on eliciting (accurate) information and cues to deceit. Mimicry is considered to facilitate cooperation and compliance in truth tellers, whereas liars are constrained to provide detail. We therefore expected truth tellers to be more detailed than liars, particularly after being mimicked. A total of 165 participants told the truth or lied about a meeting they attended. During the interview, an interviewer mimicked half of the participants. Truth tellers were more detailed than liars, but only in the ‘mimicry present’ condition. Truth tellers also gave more accurate units of information than liars, and the difference was most pronounced in the ‘mimicry present’ condition. Mimicry as a tool for eliciting information and cues to deceit fits well with the emerging ‘interviewing to detect deception’ literature, particularly in the ‘encouraging interviewees to say more’ approach. Copyright © 2015 John Wiley & Sons, Ltd.     

Classroom Climate and Political Learning: Findings from a Swedish Panel Study and Comparative Data

Numerous studies have shown that an open classroom climate for discussion increases students' civic knowledge. However, most previous studies draw on cross‐sectional data and have not been able to show that the effect is causal. This article presents results from a Swedish panel survey following students during the first year in the gymnasium (upper secondary level). Using this study, we are better equipped to evaluate the link between an open classroom climate and political knowledge. Results suggest that the effect is causal. A 10% increase in open classroom climate is associated with about 5 percentage points higher knowledge. The beneficial effect of an open classroom climate is an important insight that should be seriously considered not only by researchers but also by educational policy makers, school managements, and teachers.