Implementing mentor mothers in family practice to support abused mothers: Study protocol

Contains fulltext : 97988.pdf (postprint version ) (Open Access)ABSTRACT: BACKGROUND: Intimate partner violence is highly prevalent and mostly affects women with negative consequences for their physical and mental health. Children often witness the violence which has negative consequences for their well-being too. Care offered by family physicians is often rejected because abused women experience a too high threshold. Mentor mother support, a low threshold intervention for abused mothers in family practice, proved to be feasible and effective in Rotterdam, the Netherlands. The primary aim of this study is to investigate which factors facilitate or hinder the implementation of mentor mother support in family practice. Besides we evaluate the effect of mentor mother support in a different region. METHODS/DESIGN: An observational study with pre- and posttests will be performed. Mothers with home living children or pregnant women who are victims of intimate partner violence will be offered mentor mother support by the participating family physicians. The implementation process evaluation consists of focus groups, interviews and questionnaires. In the effect evaluation intimate partner violence, the general health of the abused mother, the mother-child relationship, social support, and acceptance of professional help will be measured twice (t = 0 and t = 6 months) by questionnaires, reporting forms, medical records and interviews with the abused mothers. Qualitative coding will be used to analyze the data from the reporting forms, medical records, focus groups, interviews, and questionnaires. Quantitative data will be analyzed with descriptive statistics, chi square test and t-test matched pairs. DISCUSSION: While other intervention studies only evaluate the feasibility and effectiveness of the intervention, our primary aim is to evaluate the implementation process and thereby investigate which factors facilitate or hinder implementation of mentor mother support in family practice.6 p

Do People Taking Flu Vaccines Need Them the Most?

Background: A well targeted flu vaccine strategy can ensure that vaccines go to those who are at the highest risk of getting infected if unvaccinated. However, prior research has not explicitly examined the association between the risk of flu infection and vaccination rates. Purpose: This study examines the relationship between the risk of flu infection and the probability of getting vaccinated. Methods: Nationally representative data from the US and multivariate regression models were used to estimate what individual characteristics are associated with (1) the risk of flu infection when unvaccinated and (2) flu vaccination rates. These results were used to estimate the correlation between the probability of infection and the probability of getting vaccinated. Separate analyses were performed for the general population and the high priority population that is at increased risk of flu related complications. Results: We find that the high priority population was more likely to get vaccinated compared to the general population. However, within both the high priority and general populations the risk of flu infection when unvaccinated was negatively correlated with vaccination rates (r = 20.067, p,0.01). This negative association between the risk of infection when unvaccinated and the probability of vaccination was stronger for the high priority population (r = 20.361, p,0.01). Conclusions: There is a poor match between those who get flu vaccines and those who have a high risk of flu infectio

Modeling causes of death: an integrated approach using CODEm

Background: Data on causes of death by age and sex are a critical input into health decision-making. Priority setting in public health should be informed not only by the current magnitude of health problems but by trends in them. However, cause of death data are often not available or are subject to substantial problems of comparability. We propose five general principles for cause of death model development, validation, and reporting.Methods: We detail a specific implementation of these principles that is embodied in an analytical tool - the Cause of Death Ensemble model (CODEm) - which explores a large variety of possible models to estimate trends in causes of death. Possible models are identified using a covariate selection algorithm that yields many plausible combinations of covariates, which are then run through four model classes. The model classes include mixed effects linear models and spatial-temporal Gaussian Process Regression models for cause fractions and death rates. All models for each cause of death are then assessed using out-of-sample predictive validity and combined into an ensemble with optimal out-of-sample predictive performance.Results: Ensemble models for cause of death estimation outperform any single component model in tests of root mean square error, frequency of predicting correct temporal trends, and achieving 95% coverage of the prediction interval. We present detailed results for CODEm applied to maternal mortality and summary results for several other causes of death, including cardiovascular disease and several cancers.Conclusions: CODEm produces better estimates of cause of death trends than previous methods and is less susceptible to bias in model specification. We demonstrate the utility of CODEm for the estimation of several major causes of death

Rate-invariant analysis of covariance trajectories

Statistical analysis of dynamic systems, such as videos and dynamic functional connectivity, is often translated into a problem of analyzing trajectories of relevant features, particularly covariance matrices. As an example, in video-based action recognition, a natural mathematical representation of activity videos is as parameterized trajectories on the set of symmetric, positive-definite matrices (SPDMs). The variable execution-rates of actions, implying arbitrary parameterizations of trajectories, complicates their analysis and classification. To handle this challenge, we represent covariance trajectories using transported square-root vector fields (TSRVFs), constructed by parallel translating scaled-velocity vectors of trajectories to their starting points. The space of such representations forms a vector bundle on the SPDM manifold. Using a natural Riemannian metric on this vector bundle, we approximate geodesic paths and geodesic distances between trajectories in the quotient space of this vector bundle. This metric is invariant to the action of the reparameterization group, and leads to a rate-invariant analysis of trajectories. In the process, we remove the parameterization variability and temporally register trajectories during analysis. We demonstrate this framework in multiple contexts, using both generative statistical models and discriminative data analysis. The latter is illustrated using several applications involving video-based action recognition and dynamic functional connectivity analysis

Self-medication of migraine and tension-type headache: summary of the evidence-based recommendations of the Deutsche Migräne und Kopfschmerzgesellschaft (DMKG), the Deutsche Gesellschaft für Neurologie (DGN), the Österreichische Kopfschmerzgesellschaft (ÖKSG) and the Schweizerische Kopfwehgesellschaft (SKG)

The current evidence-based guideline on self-medication in migraine and tension-type headache of the German, Austrian and Swiss headache societies and the German Society of Neurology is addressed to physicians engaged in primary care as well as pharmacists and patients. The guideline is especially concerned with the description of the methodology used, the selection process of the literature used and which evidence the recommendations are based upon. The following recommendations about self-medication in migraine attacks can be made: The efficacy of the fixed-dose combination of acetaminophen, acetylsalicylic acid and caffeine and the monotherapies with ibuprofen or naratriptan or acetaminophen or phenazone are scientifically proven and recommended as first-line therapy. None of the substances used in self-medication in migraine prophylaxis can be seen as effective. Concerning the self-medication in tension-type headache, the following therapies can be recommended as first-line therapy: the fixed-dose combination of acetaminophen, acetylsalicylic acid and caffeine as well as the fixed combination of acetaminophen and caffeine as well as the monotherapies with ibuprofen or acetylsalicylic acid or diclofenac. The four scientific societies hope that this guideline will help to improve the treatment of headaches which largely is initiated by the patients themselves without any consultation with their physicians