Patients satisfaction in an academic walk-in centre : a new model of residents training achieved by family doctors

Introduction Walk-in centers may improve access to healthcare for some patients, due to their convenient location and extensive opening hours, with no need for appointment. Herein we describe and assess a new model of walk-in centre, characterized by care provided by residents and supervision achieved by experienced family doctors. Main aim of the study was to assess patients satisfaction about the care they received from residents and the supervision by family doctors. Secondary aim was to describe walk-in patients demographic characteristics and to identify potential associations with satisfaction. Methods The study was conducted in the walk-in centre of Lausanne. Patients who consulted between in April 2011 were automatically included and received a questionnaire in French. We used a five-point Likert scale, from "not at all satisfied" to "very satisfied", converted from 1 to 5. We focused on the satisfaction regarding residents care and supervision by a family doctor. The former was divided in three categories: "Skills", "Treatment" and "Behaviour". Mean satisfaction was calculated for each category and a multivariable logistic model was applied in order to identify associations among patients demographics. Results Response rate was 47% [184/395], Walk-in patients were more likely to be women, young, with a high education level. Patients were very satisfied with residents care, with median satisfaction between 4.5 and 5, for each category. Over than 90% of patients were "satisfied" or "very satisfied" that a family doctor was involved in the consultation. Age showed the major association of satisfaction. Discussion Patients were highly satisfied with care provided by residents and with involvement of a family doctor in the consultation. Older age showed the major association with satisfaction with a positive impact. The high satisfaction reported by walk-in patients supports this new model of walk-in centre.

An empirical hierarchical Bayesian unification of occupational exposure assessment methods.

In occupational exposure assessment of airborne contaminants, exposure levels can either be estimated through repeated measurements of the pollutant concentration in air, expert judgment or through exposure models that use information on the conditions of exposure as input. In this report, we propose an empirical hierarchical Bayesian model to unify these approaches. Prior to any measurement, the hygienist conducts an assessment to generate prior distributions of exposure determinants. Monte-Carlo samples from these distributions feed two level-2 models: a physical, two-compartment model, and a non-parametric, neural network model trained with existing exposure data. The outputs of these two models are weighted according to the expert's assessment of their relevance to yield predictive distributions of the long-term geometric mean and geometric standard deviation of the worker's exposure profile (level-1 model). Bayesian inferences are then drawn iteratively from subsequent measurements of worker exposure. Any traditional decision strategy based on a comparison with occupational exposure limits (e.g. mean exposure, exceedance strategies) can then be applied. Data on 82 workers exposed to 18 contaminants in 14 companies were used to validate the model with cross-validation techniques. A user-friendly program running the model is available upon request.

Predictors of onset of cannabis and other drug use in male young adults: results from a longitudinal study.

BACKGROUND: The use of cannabis and other illegal drugs is particularly prevalent in male young adults and is associated with severe health problems. This longitudinal study explored variables associated with the onset of cannabis use and the onset of illegal drug use other than cannabis separately in male young adults, including demographics, religion and religiosity, health, social context, substance use, and personality. Furthermore, we explored how far the gateway hypothesis and the common liability to addiction model are in line with the resulting prediction models. METHODS: The data were gathered within the Cohort Study on Substance Use Risk Factors (C-SURF). Young men aged around 20 years provided demographic, social, health, substance use, and personality-related data at baseline. Onset of cannabis and other drug use were assessed at 15-months follow-up. Samples of 2,774 and 4,254 individuals who indicated at baseline that they have not used cannabis and other drugs, respectively, in their life and who provided follow-up data were used for the prediction models. Hierarchical logistic stepwise regressions were conducted, in order to identify predictors of the late onset of cannabis and other drug use separately. RESULTS: Not providing for oneself, having siblings, depressiveness, parental divorce, lower parental knowledge of peers and the whereabouts, peer pressure, very low nicotine dependence, and sensation seeking were positively associated with the onset of cannabis use. Practising religion was negatively associated with the onset of cannabis use. Onset of drug use other than cannabis showed a positive association with depressiveness, antisocial personality disorder, lower parental knowledge of peers and the whereabouts, psychiatric problems of peers, problematic cannabis use, and sensation seeking. CONCLUSIONS: Consideration of the predictor variables identified within this study may help to identify young male adults for whom preventive measures for cannabis or other drug use are most appropriate. The results provide evidence for both the gateway hypothesis and the common liability to addiction model and point to further variables like depressiveness or practising of religion that might influence the onset of drug use.

Patients satisfaction in an academic walk-in centre: a new model of residents training achieved by family doctors.

BACKGROUND: Walk-in centres may improve access to healthcare for some patients, due to their convenient location and extensive opening hours, with no need for an appointment. Herein, we describe and assess a new model of walk-in centre, characterised by care provided by residents and supervision achieved by experienced family doctors. The main aim of the study was to assess patients' satisfaction about the care they received from residents and their supervision by family doctors. The secondary aim was to describe walk-in patients' demographic characteristics and to identify potential associations with satisfaction. METHODS: The study was conducted in the walk-in centre of Lausanne. Patients who consulted between 11th and 31st April were automatically included and received a questionnaire in French. We used a five-point Likert scale, ranging from "not at all satisfied" to "very satisfied", converted from values of 1 to 5. We focused on the satisfaction regarding residents' care and supervision by a family doctor. The former was divided in three categories: "Skills", "Treatment" and "Behaviour". A mean satisfaction score was calculated for each category and a multivariable logistic model was applied in order to identify associations with patients' demographics. RESULTS: The overall response rate was 47% [184/395]. Walk-in patients were more likely to be women (62%), young (median age 31), with a high education level (40% of University degree or equivalent). Patients were "very satisfied" with residents' care, with a median satisfaction score between 4.5 and 5, for each category. Over 90% of patients were "satisfied" or "very satisfied" that a family doctor was involved in the consultation. Age showed the greatest association with satisfaction. CONCLUSION: Patients were highly satisfied with care provided by residents and with the involvement of a family doctor in the consultation. Older age showed the greatest positive association with satisfaction with a positive impact. The high level satisfaction reported by walk-in patients supports this new model of walk-in centre.

Good genes and good luck: Ammonoid diversity and the end-Permian mass extinction

The end-Permian mass extinction removed more than 80% of marine genera. Ammonoid cephalopods were among the organisms most affected by this crisis. The analysis of a global diversity data set of ammonoid genera covering about 106 million years centered on the Permian-Triassic boundary (PTB) shows that Triassic ammonoids actually reached levels of diversity higher than in the Permian less than 2 million years after the PTB. The data favor a hierarchical rather than logistic model of diversification coupled with a niche incumbency hypothesis. This explosive and nondelayed diversification contrasts with the slow and delayed character of the Triassic biotic recovery as currently illustrated for other, mainly benthic groups such as bivalves and gastropods.

Surgical safety and hospital volume across a wide range of interventions

OBJECTIVES:: For certain major operations, inpatient mortality risk is lower in high-volume hospitals than those in low-volume hospitals. Extending the analysis to a broader range of interventions and outcomes is necessary before adopting policies based on minimum volume thresholds. METHODS:: Using the United States 2004 Nationwide Inpatient Sample, we assessed the effect of intervention-specific and overall hospital volume on surgical complications, potentially avoidable reoperations, and deaths across 1.4 million interventions in 353 hospitals. Outcome variations across hospitals were analyzed through a 3-level hierarchical logistic regression model (patients, surgical interventions, and hospitals), which took into account interventions on multiple organs, 144 intervention categories, and structural hospital characteristics. Discriminative performance and calibration were good. RESULTS:: Hospitals with more experience in a given intervention had similar reoperation rates but lower mortality and complication rates: odds ratio per volume deciles 0.93 and 0.97. However, the benefit was limited to heart surgery and a small number of other operations. Risks were higher for hospitals that performed more interventions overall: odds ratio per 1000 for each event was approximately 1.02. Even after adjustment for specific volume, mortality varied substantially across both high- and low-volume hospitals. CONCLUSION:: Although the link between specific volume and certain inpatient outcomes suggests that specialization might help improve surgical safety, the variable magnitude of this link and the heterogeneity of hospital effect do not support the systematic use of volume-based referrals. It may be more efficient to monitor risk-adjusted postoperative outcomes and to investigate facilities with worse than expected outcomes.

A dynamic assessment of medication-taking behavior during pregnancy and postpartum: should cART adherence be reinforced during postpartum?

This study compared adherence (persistence and execution) during pregnancy and postpartum in HIV-positive women having taken part in the adherence-enhancing program of the Community Pharmacy of the Department of Ambulatory Care and Community Medicine in Lausanne between 2004 and 2012. This interdisciplinary program combined electronic drug monitoring and semi-structured, repeated motivational interviews. This was a retrospective, observational study. Observation period spread over from first adherence visit after last menstruation until 6 months after childbirth. Medication-taking was recorded by electronic drug monitoring. Socio-demographic and delivery data were collected from Swiss HIV Cohort database. Adherence data, barriers and facilitators were collected from pharmacy database. Electronic data were reconciled with pill-count and interview notes in order to include reported pocket-doses. Execution was analyzed over 3-day periods by a mixed effect logistic model, separating time before and after childbirth. This model allowed us to estimate different time slopes for both periods and to show a sudden fall associated with childbirth. Twenty-five pregnant women were included. Median age was 29 (IQR: 26.5, 32.0), women were in majority black (n_17,68%) and took a cART combining protease and nucleoside reverse transcriptase inhibitors (n_24,96%). Eleven women (44%) were ART-naı¨ve at the beginning of pregnancy. Twenty women (80%) were included in the program because of pregnancy. Women were included at all stages of pregnancy. Six women (24%) stopped the program during pregnancy, 3 (12%) at delivery, 4 (16%) during postpartum and 12 (48%) stayed in program at the end of observation time. Median number of visits was 4 (3.0, 6.3) during pregnancy and 3 (0.8, 6.0) during postpartum. Execution was continuously high during pregnancy, low at beginning of postpartum and increased gradually during the 6 months of postpartum. Major barriers to adherence were medication adverse events and difficulties in daily routine. Facilitators were motivation for promoting child-health and social support. The dramatic drop and very slow increase in cART adherence during postpartum might result in viral rebound and drug resistance. Although much attention is devoted to pregnant women, interdisciplinary care should also be provided to women in the community during first trimester of postpartum to support them in sustaining cART adherence.

Quantitative genetic modeling and inference in the presence of nonignorable missing data.

Natural selection is typically exerted at some specific life stages. If natural selection takes place before a trait can be measured, using conventional models can cause wrong inference about population parameters. When the missing data process relates to the trait of interest, a valid inference requires explicit modeling of the missing process. We propose a joint modeling approach, a shared parameter model, to account for nonrandom missing data. It consists of an animal model for the phenotypic data and a logistic model for the missing process, linked by the additive genetic effects. A Bayesian approach is taken and inference is made using integrated nested Laplace approximations. From a simulation study we find that wrongly assuming that missing data are missing at random can result in severely biased estimates of additive genetic variance. Using real data from a wild population of Swiss barn owls Tyto alba, our model indicates that the missing individuals would display large black spots; and we conclude that genes affecting this trait are already under selection before it is expressed. Our model is a tool to correctly estimate the magnitude of both natural selection and additive genetic variance.

Population density and offspring size in the cladoceran Simocephalus vetulus (Müller)

r/K theory classically predicts that offspring size should increase under density-dependent selection. However, this is questionable, being based on implicit rather than explicit assumption (the logistic model does not include offsring size as a parameter). From recent models of optimal offspring size (Sibly & Calow, 1983; Taylor & Williams, 1984) it can be shown that density should select for larger offspring if density-dependence in the per capita rate of increase is mainly due to a reduction of the juvenile growth rate or survivorship. In contrast, density should select for smaller offspring if such density-dependence is mainly due to a reduction of adult fecundity or survivorship. Therfore, the outcome of selection cannot be predicted without precise knowledge of the density-dependence of age-specific reproduction and mortality rates. To test the above models, genetically identical individuals of Simocephalus vetulus (Müller) were reared in a density gradient; density-dependence in the per capita rate of increase was shown to be mainly due to a reduction of the juvenile growth rate, thereby selecting for larger offspring; offspring size at birth appeared to be phenotypically plastic and to increase with density. Models were therefore qualitatively supported. However, a discrepancy occurred in quantitative predictions; offspring were produced larger than predicted. Field and laboratory studies are suggested to address this.

Further insights on the French WISC-IV factor structure through Bayesian structural equation modeling

The interpretation of the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) is based on a 4-factor model, which is only partially compatible with the mainstream Cattell-Horn-Carroll (CHC) model of intelligence measurement. The structure of cognitive batteries is frequently analyzed via exploratory factor analysis and/or confirmatory factor analysis. With classical confirmatory factor analysis, almost all crossloadings between latent variables and measures are fixed to zero in order to allow the model to be identified. However, inappropriate zero cross-loadings can contribute to poor model fit, distorted factors, and biased factor correlations; most important, they do not necessarily faithfully reflect theory. To deal with these methodological and theoretical limitations, we used a new statistical approach, Bayesian structural equation modeling (BSEM), among a sample of 249 French-speaking Swiss children (8-12 years). With BSEM, zero-fixed cross-loadings between latent variables and measures are replaced by approximate zeros, based on informative, small-variance priors. Results indicated that a direct hierarchical CHC-based model with 5 factors plus a general intelligence factor better represented the structure of the WISC-IV than did the 4-factor structure and the higher order models. Because a direct hierarchical CHC model was more adequate, it was concluded that the general factor should be considered as a breadth rather than a superordinate factor. Because it was possible for us to estimate the influence of each of the latent variables on the 15 subtest scores, BSEM allowed improvement of the understanding of the structure of intelligence tests and the clinical interpretation of the subtest scores.

Which is the optimal sampling strategy for habitat suitability modelling

Designing an efficient sampling strategy is of crucial importance for habitat suitability modelling. This paper compares four such strategies, namely, 'random', 'regular', 'proportional-stratified' and 'equal -stratified'- to investigate (1) how they affect prediction accuracy and (2) how sensitive they are to sample size. In order to compare them, a virtual species approach (Ecol. Model. 145 (2001) 111) in a real landscape, based on reliable data, was chosen. The distribution of the virtual species was sampled 300 times using each of the four strategies in four sample sizes. The sampled data were then fed into a GLM to make two types of prediction: (1) habitat suitability and (2) presence/ absence. Comparing the predictions to the known distribution of the virtual species allows model accuracy to be assessed. Habitat suitability predictions were assessed by Pearson's correlation coefficient and presence/absence predictions by Cohen's K agreement coefficient. The results show the 'regular' and 'equal-stratified' sampling strategies to be the most accurate and most robust. We propose the following characteristics to improve sample design: (1) increase sample size, (2) prefer systematic to random sampling and (3) include environmental information in the design'

Diagnostic value of vestibulo-ocular reflex parameters in the detection and characterization of labyrinthine lesions.

OBJECTIVE: To evaluate the power of various parameters of the vestibulo-ocular reflex (VOR) in detecting unilateral peripheral vestibular dysfunction and in characterizing certain inner ear pathologies. STUDY DESIGN: Prospective study of consecutive ambulatory patients presenting with acute onset of peripheral vertigo and spontaneous nystagmus. SETTING: Tertiary referral center. PATIENTS: Seventy-four patients (40 females, 34 males) and 22 normal subjects (11 females, 11 males) were included in the study. Patients were classified in three main diagnoses: vestibular neuritis: 40; viral labyrinthitis: 22; Meniere's disease: 12. METHODS: The VOR function was evaluated by standard caloric and impulse rotary tests (velocity step). A mathematical model of vestibular function was used to characterize the VOR response to rotational stimulation. The diagnostic value of the different VOR parameters was assessed by uni- and multivariable logistic regression. RESULTS: In univariable analysis, caloric asymmetry emerged as the most powerful VOR parameter in identifying unilateral vestibular deficit, with a boundary limit set at 20%. In multivariable analysis, the combination of caloric asymmetry and rotational time constant asymmetry significantly improved the discriminatory power over caloric alone (p<0.0001) and produced a detection score with a correct classification of 92.4%. In discriminating labyrinthine diseases, different combinations of the VOR parameters were obtained for each diagnosis (p<0.003) supporting that the VOR characteristics differ between the three inner ear disorders. However, the clinical usefulness of these characteristics in separating the pathologies was limited. CONCLUSION: We propose a powerful logistic model combining the indices of caloric and time constant asymmetries to detect a peripheral vestibular loss, with an accuracy of 92.4%. Based on vestibular data only, the discrimination between the different inner ear diseases is statistically possible, which supports different pathophysiologic changes in labyrinthine pathologies.

Population density and optimal body size.

The population density of an organism is one of the main aspects of its environment, and shoud therefore strongly influence its adaptive strategy. The r/K theory, based on the logistic model, was developed to formalize this influence. K-selectioon is classically thought to favour large body sizes. This prediction, however, cannot be directly derived from the logistic model: some auxiliary hypotheses are therefor implicit. These are to be made explicit if the theory is to be tested. An alternative approach, based on the Euler-Lotka equation, shows that density itself is irrelevant, but that the relative effect of density on adult and juvenile features is crucial. For instance, increasing population will select for a smaller body size if the density affects mainly juvenile growth and/or survival. In this case, density shoud indeed favour large body sizes. The theory appears nevertheless inconsistent, since a probable consequence of increasing body size will be a decrease in the carrying capacity

Scale-specific sex-biased dispersal in the Valais shrew unveiled by genetic variation on the Y chromosome, autosomes, and mitochondrial DNA.

We investigated sex specificities in the evolutionary processes shaping Y chromosome, autosomes, and mitochondrial DNA patterns of genetic structure in the Valais shrew (Sorex antinorii), a mountain dwelling species with a hierarchical distribution. Both hierarchical analyses of variance and isolation-by-distance analyses revealed patterns of population structure that were not consistent across maternal, paternal, and biparentally inherited markers. Differentiation on a Y microsatellite was lower than expected from the comparison with autosomal microsatellites and mtDNA, and it was mostly due to genetic variance among populations within valleys, whereas the opposite was observed on other markers. In addition, there was no pattern of isolation by distance for the Y, whereas there was strong isolation by distance on mtDNA and autosomes. We use a hierarchical island model of coancestry dynamics to discuss the relative roles of the microevolutionary forces that may induce such patterns. We conclude that sex-biased dispersal is the most important driver of the observed genetic structure, but with an intriguing twist: it seems that dispersal is strongly male biased at large spatial scale, whereas it is mildly biased in favor of females at local scale. These results add to recent reports of scale-specific sex-biased dispersal patterns, and emphasize the usefulness of the Y chromosome in conjunction with mtDNA and autosomes to infer sex specificities.

Improvement in gross motor performance between 3 and 5 years of age.

This study examined gross motor performance of 101 typically developing children between 3 and 5 years of age (48 boys, 53 girls, M age = 3.9 yr., SD = 0.5). All children performed 7 different gross motor tasks which were rated on a 5-point scale. Age and sex were assessed by an ordinal-logistic model, and odds ratios were calculated for each task using age and sex as covariates. For standing on one leg, walking on a beam, hopping on one leg, running, and taking stairs, statistically significant age differences were found, while for rising and jumping down, none were apparent. Mean motor performance did not differ between boys and girls on the tasks. The older the children were, the better they performed on the tasks.