Counsellor behaviours and patient language during brief motivational interventions: a sequential analysis of speech

AIMS: To investigate empirically the hypothesized relationship between counsellor motivational interviewing (MI) skills and patient change talk (CT) by analysing the articulation between counsellor behaviours and patient language during brief motivational interventions (BMI) addressing at-risk alcohol consumption. DESIGN: Sequential analysis of psycholinguistic codes obtained by two independent raters using the Motivational Interviewing Skill Code (MISC), version 2.0. SETTING: Secondary analysis of data from a randomized controlled trial evaluating the effectiveness of BMI in an emergency department. PARTICIPANTS: A total of 97 patients tape-recorded when receiving BMI. MEASUREMENTS: MISC variables were categorized into three counsellor behaviours (MI-consistent, MI-inconsistent and 'other') and three kinds of patient language (CT, counter-CT (CCT) and utterances not linked with the alcohol topic). Observed transition frequencies, conditional probabilities and significance levels based on odds ratios were computed using sequential analysis software. FINDINGS: MI-consistent behaviours were the only counsellor behaviours that were significantly more likely to be followed by patient CT. Those behaviours were significantly more likely to be followed by patient change exploration (CT and CCT) while MI-inconsistent behaviours and 'other' counsellor behaviours were significantly more likely to be followed by utterances not linked with the alcohol topic and significantly less likely to be followed by CT. MI-consistent behaviours were more likely after change exploration, whereas 'other' counsellor behaviours were more likely only after utterances not linked with the alcohol topic. CONCLUSIONS: Findings lend support to the hypothesized relationship between MI-consistent behaviours and CT, highlight the importance of patient influence on counsellor behaviour and emphasize the usefulness of MI techniques and spirit during brief interventions targeting change enhancement.

Increased audiovisual integration in cochlear-implanted deaf patients: independent components analysis of longitudinal positron emission tomography data.

It has been demonstrated in earlier studies that patients with a cochlear implant have increased abilities for audio-visual integration because the crude information transmitted by the cochlear implant requires the persistent use of the complementary speech information from the visual channel. The brain network for these abilities needs to be clarified. We used an independent components analysis (ICA) of the activation (H2 (15) O) positron emission tomography data to explore occipito-temporal brain activity in post-lingually deaf patients with unilaterally implanted cochlear implants at several months post-implantation (T1), shortly after implantation (T0) and in normal hearing controls. In between-group analysis, patients at T1 had greater blood flow in the left middle temporal cortex as compared with T0 and normal hearing controls. In within-group analysis, patients at T0 had a task-related ICA component in the visual cortex, and patients at T1 had one task-related ICA component in the left middle temporal cortex and the other in the visual cortex. The time courses of temporal and visual activities during the positron emission tomography examination at T1 were highly correlated, meaning that synchronized integrative activity occurred. The greater involvement of the visual cortex and its close coupling with the temporal cortex at T1 confirm the importance of audio-visual integration in more experienced cochlear implant subjects at the cortical level.

Intégration de méthodes de data mining dans le renseignement criminel : analyse par des structures issues de la théorie des graphes dans le profilage des stupéfiants

Data mining can be defined as the extraction of previously unknown and potentially useful information from large datasets. The main principle is to devise computer programs that run through databases and automatically seek deterministic patterns. It is applied in different fields of application, e.g., remote sensing, biometry, speech recognition, but has seldom been applied to forensic case data. The intrinsic difficulty related to the use of such data lies in its heterogeneity, which comes from the many different sources of information. The aim of this study is to highlight potential uses of pattern recognition that would provide relevant results from a criminal intelligence point of view. The role of data mining within a global crime analysis methodology is to detect all types of structures in a dataset. Once filtered and interpreted, those structures can point to previously unseen criminal activities. The interpretation of patterns for intelligence purposes is the final stage of the process. It allows the researcher to validate the whole methodology and to refine each step if necessary. An application to cutting agents found in illicit drug seizures was performed. A combinatorial approach was done, using the presence and the absence of products. Methods coming from the graph theory field were used to extract patterns in data constituted by links between products and place and date of seizure. A data mining process completed using graphing techniques is called ``graph mining''. Patterns were detected that had to be interpreted and compared with preliminary knowledge to establish their relevancy. The illicit drug profiling process is actually an intelligence process that uses preliminary illicit drug classes to classify new samples. Methods proposed in this study could be used \textit{a priori} to compare structures from preliminary and post-detection patterns. This new knowledge of a repeated structure may provide valuable complementary information to profiling and become a source of intelligence.

Mapping of Environmental Data Using Kernel-Based Methods

Recently, kernel-based Machine Learning methods have gained great popularity in many data analysis and data mining fields: pattern recognition, biocomputing, speech and vision, engineering, remote sensing etc. The paper describes the use of kernel methods to approach the processing of large datasets from environmental monitoring networks. Several typical problems of the environmental sciences and their solutions provided by kernel-based methods are considered: classification of categorical data (soil type classification), mapping of environmental and pollution continuous information (pollution of soil by radionuclides), mapping with auxiliary information (climatic data from Aral Sea region). The promising developments, such as automatic emergency hot spot detection and monitoring network optimization are discussed as well.

Influenza surveillance using data from a telemedicine centre.

OBJECTIVES: This study aimed at investigating whether data from medical teleconsultations may contribute to influenza surveillance. METHODS: International Classification of Primary Care 2nd Edition (ICPC-2) codes were used to analyse the proportion of teleconsultations due to influenza-related symptoms. Results were compared with the weekly Swiss Sentinel reports. RESULTS: When using the ICPC-2 code for fever we could reproduce the seasonal influenza peaks of the winter seasons 07/08, 08/09 and 09/10 as depicted by the Sentinel data. For the pandemic influenza 09/10, we detected a much higher first peak in summer 2009 which correlated with a potential underreporting in the Sentinel system. CONCLUSIONS: ICPC-2 data from medical teleconsultations allows influenza surveillance in real time and correlates very well with the Swiss Sentinel system.

Example of Data Telemetry for Biomedical Applications: An In Vivo Experiment

This letter describes a data telemetry biomedical experiment. An implant, consisting of a biometric data sensor, electronics, an antenna, and a biocompatible capsule, is described. All the elements were co-designed in order to maximize the transmission distance. The device was implanted in a pig for an in vivo experiment of temperature monitoring.

Toward interoperable bioscience data.

To make full use of research data, the bioscience community needs to adopt technologies and reward mechanisms that support interoperability and promote the growth of an open 'data commoning' culture. Here we describe the prerequisites for data commoning and present an established and growing ecosystem of solutions using the shared 'Investigation-Study-Assay' framework to support that vision.

Linking Global Youth Tobacco Survey (GYTS) data to the WHO Framework Convention on Tobacco Control (FCTC): the case for the Seychelles

Tobacco control has been recognized as a main public health concern in Seychelles for the past two decades. Tobacco advertising, sponsoring and promotion has been banned for years, tobacco products are submitted to high taxes, high-profile awareness programs are organized regularly, and several other control measures have been implemented. The Republic of Seychelles was the first country to ratify the WHO Framework Convention on Tobacco Control (FCTC) in the African region. Three population-based surveys have been conducted in adults in Seychelles and results showed a substantial decrease in the prevalence of smoking among adults between 1989 and 2004. A first survey in adolescents was conducted in Seychelles in 2002 (the Global Youth Tobacco Survey, GYTS) in a representative sample of 1321 girls and boys aged 13-15 years. The results show that approximately half of students had tried smoking and a quarter of both boys and girls had smoked at least one cigarette during the past 30 days. Although "current smoking" is defined differently in adolescents (>or=1 cigarette during the past 30 days) and in adults (>or=1 cigarette per day), which precludes direct comparison, the high smoking prevalence in youth in Seychelles likely predicts an increasing prevalence of tobacco use in the next adult generation, particularly in women. GYTS 2002 also provides important data on a wide range of specific individual and societal factors influencing tobacco use. Hence, GYTS can be a powerful tool for monitoring the situation of tobacco use in adolescents, for highlighting the need for new policy and programs, and for evaluating the impact of current and future programs.

Handheld-assisted field data collection for occupational risk assessment.

A computerized handheld procedure is presented in this paper. It is intended as a database complementary tool, to enhance prospective risk analysis in the field of occupational health. The Pendragon forms software (version 3.2) has been used to implement acquisition procedures on Personal Digital Assistants (PDAs) and to transfer data to a computer in an MS-Access format. The data acquisition strategy proposed relies on the risk assessment method practiced at the Institute of Occupational Health Sciences (IST). It involves the use of a systematic hazard list and semi-quantitative risk assessment scales. A set of 7 modular forms has been developed to cover the basic need of field audits. Despite the minor drawbacks observed, the results obtained so far show that handhelds are adequate to support field risk assessment and follow-up activities. Further improvements must still be made in order to increase the tool effectiveness and field adequacy.

Hydrogeophysical data integration at larger scales: Application of Bayesian sequential simulation for the characterization of heterogeneous alluvial aquifers

Knowledge of the spatial distribution of hydraulic conductivity (K) within an aquifer is critical for reliable predictions of solute transport and the development of effective groundwater management and/or remediation strategies. While core analyses and hydraulic logging can provide highly detailed information, such information is inherently localized around boreholes that tend to be sparsely distributed throughout the aquifer volume. Conversely, larger-scale hydraulic experiments like pumping and tracer tests provide relatively low-resolution estimates of K in the investigated subsurface region. As a result, traditional hydrogeological measurement techniques contain a gap in terms of spatial resolution and coverage, and they are often alone inadequate for characterizing heterogeneous aquifers. Geophysical methods have the potential to bridge this gap. The recent increased interest in the application of geophysical methods to hydrogeological problems is clearly evidenced by the formation and rapid growth of the domain of hydrogeophysics over the past decade (e.g., Rubin and Hubbard, 2005).

Are there two species of Pygmy Shrews (Sorex)? Revisiting the question using DNA sequence data

Pygmy Shrews in North America have variously been considered to be one species (Sorex hoyi) or two species (S. hoyi and S. thompsoni). Currently, only S. hoyi is recognized. In this study, we examine mitochondrial DNA sequence data for the cytochrome b gene to evaluate the level of differentiation and phylogeographic relationships among eleven samples of Pygmy Shrews from across Canada. Pygmy Shrews from eastern Canada (i.e., Ontario, Quebec, New Brunswick, Nova Scotia, and Prince Edward Island) are distinct from Pygmy Shrews from western Canada (Alberta, Yukon) and Alaska. The average level of sequence divergence between these clades (3.3%) falls within the range of values for other recognized pairs of sister species of shrews. A molecular clock based on third position transversion substitutions suggests that these two lineages diverged between 0.44 and 1.67 million years ago. These molecular phylogenetic data. combined with a reinterpretation of previously published morphological data, are suggestive of separate species status for S. hoyi and S. thompsoni as has been previously argued by others. Further analysis of specimens from geographically intermediate areas (e.g., Manitoba. northern Ontario) is required to determine if there is secondary contact and/or introgression between these two putative species.

Body mass index, cigarette smoking, and alcohol consumption and cancers of the oral cavity, pharynx, and larynx: modeling odds ratios in pooled case-control data.

Odds ratios for head and neck cancer increase with greater cigarette and alcohol use and lower body mass index (BMI; weight (kg)/height(2) (m(2))). Using data from the International Head and Neck Cancer Epidemiology Consortium, the authors conducted a formal analysis of BMI as a modifier of smoking- and alcohol-related effects. Analysis of never and current smokers included 6,333 cases, while analysis of never drinkers and consumers of < or =10 drinks/day included 8,452 cases. There were 8,000 or more controls, depending on the analysis. Odds ratios for all sites increased with lower BMI, greater smoking, and greater drinking. In polytomous regression, odds ratios for BMI (P = 0.65), smoking (P = 0.52), and drinking (P = 0.73) were homogeneous for oral cavity and pharyngeal cancers. Odds ratios for BMI and drinking were greater for oral cavity/pharyngeal cancer (P < 0.01), while smoking odds ratios were greater for laryngeal cancer (P < 0.01). Lower BMI enhanced smoking- and drinking-related odds ratios for oral cavity/pharyngeal cancer (P < 0.01), while BMI did not modify smoking and drinking odds ratios for laryngeal cancer. The increased odds ratios for all sites with low BMI may suggest related carcinogenic mechanisms; however, BMI modification of smoking and drinking odds ratios for cancer of the oral cavity/pharynx but not larynx cancer suggests additional factors specific to oral cavity/pharynx cancer.