Continuing professional education of Iranian healthcare professionals in shared decision-making: lessons learned.

BACKGROUND: In this study, we sought to assess healthcare professionals' acceptance of and satisfaction with a shared decision making (SDM) educational workshop, its impact on their intention to use SDM, and their perceived facilitators and barriers to the implementation of SDM in clinical settings in Iran. METHODS: We conducted an observational quantitative study that involved measurements before, during, and immediately after the educational intervention at stake. We invited healthcare professionals affiliated with Tabriz University of Medical Sciences, East Azerbaijan, Iran, to attend a half-day workshop on SDM in December 2016. Decisions about prenatal screening and knee replacement surgery was used as clinical vignettes. We provided a patient decision aid on prenatal screening that complied with the International Patient Decision Aids Standards and used illustrate videos. Participants completed a sociodemographic questionnaire and a questionnaire to assess their familiarity with SDM, a questionnaire based on theoretical domains framework to assess their intention to implement SDM, a questionnaire about their perceived facilitators and barriers of implementing SDM in their clinical practice, continuous professional development reaction questionnaire, and workshop evaluation. Quantitative data was analyzed descriptively and with multiple linear regression. RESULTS: Among the 60 healthcare professionals invited, 41 participated (68%). Twenty-three were female (57%), 18 were specialized in family and emergency medicine, or community and preventive medicine (43%), nine were surgeons (22%), and 14 (35%) were other types of specialists. Participants' mean age was 37.51 ± 8.64 years with 8.09 ± 7.8 years of clinical experience. Prior to the workshop, their familiarity with SDM was 3.10 ± 2.82 out of 9. After the workshop, their belief that practicing SDM would be beneficial and useful (beliefs about consequences) (beta = 0.67, 95% CI 0.27, 1.06) and beliefs about capability of using SDM (beta = 0.32, 95% CI -0.08, 0.72) had the strongest influence on their intention of practicing SDM. Participants perceived the main facilitator and barrier to perform SDM were training and high patient load, respectively. CONCLUSIONS: Participants thought the workshop was a good way to learn SDM and that they would be able to use what they had learned in their clinical practice. Future studies need to study the level of intention of participants in longer term and evaluate the impact of cultural differences on practicing SDM and its implementation in both western and non-western countries.

Behavioral and Psychological Symptoms that Predict Cognitive Decline or Impairment in Cognitively Normal Middle-Aged or Older Adults: a Meta-Analysis.

Epidemiological studies have revealed that behavioral and psychological (or non-cognitive) symptoms are risk factors for cognitive decline in older adults. This study aimed to systematically review the literature and determine which behavioral and psychological symptoms are most predictive of future cognitive decline among individuals with no pre-existing cognitive impairments. The selected studies included middle-aged or older adults without cognitive impairments. The predictors were assessed using behavioral and psychological questionnaires, or diagnostic interviews, to identify non-cognitive symptoms or psychiatric clinical conditions. The follow-up period was at least one year, and the design of the selected studies was either retrospective or prospective. This study compared individuals with and without non-cognitive manifestations and resulted in one of three outcomes: (a) a score change on a cognitive measure, (b) a diagnosis of mild cognitive impairment, or (c) a diagnosis of Alzheimer's disease or dementia. Four online databases were searched for eligible studies from the database inception to January 17, 2017: MEDLINE (PubMed), Embase (OVID), PsycINFO, and Web of Science. Pooled effect sizes were estimated using a random-effect model. Higgins I2, the Q statistic, and tau-squared were used to quantify the observed heterogeneity between the studies. Results indicate that depression and sleep duration (long and short) were the most consistent associations between behavioral or psychological symptoms and cognitive decline. This meta-analysis supports the need to assess behavioral and psychological symptoms in cognitively intact older adults to identify those who are at risk for cognitive decline.

Correction to: Time to move? Factors associated with burden of care among informal caregivers of cognitively impaired older people facing housing decisions: secondary analysis of a cluster randomized trial.

Following publication of the original article [1], we have been notified that one of the authors' given name and last names are reversed and misspelled and thus not reflected correctly (given name now is Painchaud-Guérard and it should be Geneviève and last name now is Geneviève and it should be Painchaud Guérard).

Time to move? Factors associated with burden of care among informal caregivers of cognitively impaired older people facing housing decisions: secondary analysis of a cluster randomized trial.

BACKGROUND: Making health-related decisions about loved ones with cognitive impairment may contribute to caregiver burden of care. We sought to explore factors associated with burden of care among informal caregivers who had made housing decisions on behalf of a cognitively impaired older person. METHODS: We conducted a secondary analysis within a cluster randomized trial (cRT) conducted in 16 publicly-funded home care service points across the Province of Quebec. The cRT assessed the impact of training home care teams in interprofessional shared decision making (IP-SDM). We assessed burden of care with the Zarit Burden Interview (ZBI) scale. We adapted Pallett's framework to inform our data analysis. This framework posits that factors influencing burden of care among caregivers fall within four domains: (a) characteristics of the caregiver, (b) characteristics of the cognitively impaired older person, (c) characteristics of the relationship between the caregiver and the cognitively impaired older person, and (d) the caregiver's perception of their social support resources. We computed the ZBI score and performed multilevel linear regression modelling. RESULTS: Among 296 caregivers included in the dataset, the mean ZBI score was 29.8 (SD = 17.5) out of 88. The typical participant was 62.6 years old (SD = 11.7), female (74.7%), and caring for a mother or father (61.2%). Using multivariate analysis, factors significantly associated with caregiver burden mapped onto: caregiver characteristics (caregivers with higher burden were female, experienced higher decision regret and decisional conflict, preferred that their loved one move into the caregiver's home, into a private nursing home or a mixed private-public nursing home, and had made the decision more recently); relationship characteristics (spouses and children experienced higher burden); and caregiver's perception of social support resources (caregivers who perceived that a joint decision making process had occurred had higher burden). CONCLUSION: In line with the proposed framework used, we found that caregiver characteristics, relationship characteristics and caregiver's perception of social support resources were associated with burden of care. Our results will help design interventions to prevent and/or reduce caregivers' burden of care. TRIAL REGISTRATION: NCT02244359 . Date of registration: September 18, 2014.

Polyunphased: an extension to polytomous outcomes of the Unphased package for family-based genetic association analysis.

Polytomous phenotypes arise when a disease has multiple subtypes or when two dichotomous phenotypes are analyzed simultaneously. Few software programs offer the option to analyze such phenotypes in family studies, and none implements conditional polytomous logistic regression for within-family analysis robust to population stratification. We introduce Polyunphased, an extension to polytomous phenotypes of the Unphased package, a flexible software tool for genetic association analysis in nuclear families. Like Unphased, Polyunphased is written in C++ and runs from the command line or from a Java graphical user interface. Most Unphased options remain available in Polyunphased, including those handling missing parental genotypes while preserving robustness to population stratification, and the modelling options. Simulation studies confirmed the expected statistical behaviour of the maximum likelihood estimates of the association parameters of the conditional logistic regression model when the corresponding association parameters in the parental term of the likelihood function are set to 0, but revealed convergence problems when estimating these parental association parameters separately. The former approach is thus recommended with polytomous phenotypes.

Psychosocial Factors of Health Professionals' Intention to Use a Decision Aid for Down Syndrome Screening: Cross-Sectional Quantitative Study.

BACKGROUND: Decisions about prenatal screening for Down syndrome are difficult for women, as they entail risk, potential loss, and regret. Shared decision making increases women's knowledge of their choices and better aligns decisions with their values. Patient decision aids foster shared decision making but are rarely used in this context. OBJECTIVE: One of the most promising strategies for implementing shared decision making is distribution of decision aids by health professionals. We aimed to identify factors influencing their intention to use a DA during prenatal visit for decisions about Down syndrome screening. METHODS: We conducted a cross-sectional quantitative study. Using a Web panel, we conducted a theory-based survey of health professionals in Quebec province (Canada). Eligibility criteria were as follows: (1) family physicians, midwives, obstetrician-gynecologists, or trainees in these professions; (2) involved in prenatal care; and (3) working in Quebec province. Participants watched a video depicting a health professional using a decision aid during a prenatal consultation with a woman and her partner, and then answered a questionnaire based on an extended version of the theory of planned behavior, including some of the constructs of the theoretical domains framework. The questionnaire assessed 8 psychosocial constructs (attitude, anticipated regret, subjective norm, self-identity, moral norm, descriptive norm, self-efficacy, and perceived control), 7 related sets of behavioral beliefs (advantages, disadvantages, emotions, sources of encouragement or discouragement, incentives, facilitators, and barriers), and sociodemographic data. We performed descriptive, bivariate, and multiple linear regression analyses to identify factors influencing health professionals' intention to use a decision aid. RESULTS: Among 330 health professionals who completed the survey, 310 met the inclusion criteria: family physicians, 55.2% (171/310); obstetrician-gynecologists, 33.8% (105/310); and midwives, 11.0% (34/310). Of these, 80.9% were female (251/310). Mean age was 39.6 (SD 11.5) years. Less than half were aware of any decision aids at all. In decreasing order of importance, factors influencing their intention to use a decision aid for Down syndrome prenatal screening were as follows: self-identity (beta=.325, P<.001), attitude (beta=.297, P<.001), moral norm (beta=.288, P<.001), descriptive norm (beta=.166, P<.001), and anticipated regret (beta=.099, P=.003). Underlying behavioral beliefs significantly related to intention were that the use of a decision aid would promote decision making (beta=.117, 95% CI 0.043-0.190), would reassure health professionals (beta=.100, 95% CI 0.024-0.175), and might require more time than planned for the consultation (beta=-.077, 95% CI -0.124 to -0.031). CONCLUSIONS: We identified psychosocial factors that could influence health professionals' intention to use a decision aid about Down syndrome screening. Strategies should remind them of the following: (1) using a decision aid for this purpose should be a common practice, (2) it would be expected of someone in their societal role, (3) the experience of using it will be satisfying and reassuring, and (4) it is likely to be compatible with their moral values.

Neuropsychological Measures that Predict Progression from Mild Cognitive Impairment to Alzheimer's type dementia in Older Adults: a Systematic Review and Meta-Analysis.

This study aimed to determine the extent to which cognitive measures can predict progression from mild cognitive impairment (MCI) to Alzheimer's type dementia (AD), assess the predictive accuracy of different cognitive domain categories, and determine whether accuracy varies as a function of age and length of follow-up. We systematically reviewed and meta-analyzed data from longitudinal studies reporting sensitivity and specificity values for neuropsychological tests to identify individuals with MCI who will develop AD. We searched articles in Medline, Cochrane, EMBASE, PsycINFO, and the Web of Science. Methodological quality was assessed using the STARDem and QUADAS standards. Twenty-eight studies met the eligibility criteria (2365 participants) and reported predictive values from 61 neuropsychological tests with a 31-month mean follow-up. Values were pooled to provide combined accuracy for 14 cognitive domains. Many domains showed very good predictive accuracy with high sensitivity and specificity values (≥ 0.7). Verbal memory measures and many language tests yielded very high predictive accuracy. Other domains (e.g., executive functions, visual memory) showed better specificity than sensitivity. Predictive accuracy was highest when combining memory measures with a small set of other domains or when relying on broad cognitive batteries. Cognitive tests are excellent at predicting MCI individuals who will progress to dementia and should be a critical component of any toolkit intended to identify AD at the pre-dementia stage. Some tasks are remarkable as early indicators, whereas others might be used to suggest imminent progression.

When Is an Endophenotype Useful to Detect Association to a Disease? Exploring the Relationships between Disease Status, Endophenotype and Genetic Polymorphisms.

OBJECTIVES: To investigate the conditions and analysis strategies required so that endophenotypes related to a disease help discover genetic variants involved in the disease. METHODS: The association with disease susceptibility variants is examined as a function of the relationships between disease status, endophenotype values and the genotype at another disease or endophenotype susceptibility locus assumed to be previously known, using approximate linear models of allele frequencies as a function of these variables and simulations in the context of family studies when the endophenotype is dichotomous. RESULTS: Under genetic mechanisms where the risk allele of the tested locus has an effect exclusively in subjects with the endophenotype, the risk allele frequency differences between affected and unaffected subjects are much greater in the subset of subjects with an endophenotype impairment than in those without such an impairment, and power gains are obtained when testing the association under a joint disease-endophenotype model, both with two-locus or single-locus tests. However, with moderate main effect on the risk of disease or endophenotype impairment, testing directly the association between risk allele and disease or endophenotype is more powerful than testing under a joint disease-endophenotype model. CONCLUSIONS: Joint modeling of disease and endophenotype should be used only in parallel with standard disease association testing.

Detection of phenotype modifier genes using two-locus linkage analysis in complex disorders such as major psychosis.

OBJECTIVE: To increase power to detect modifier loci conferring susceptibility to specific phenotypes such as disease diagnoses which are part of a broader disorder spectrum by jointly modeling a modifier and a broad susceptibility gene and to identify modifier loci conferring specific susceptibility to schizophrenia (SZ) or to bipolar disorder (BP) using the approach. METHODS: We implemented a two-locus linkage analysis model where a gene 1 genotype increases the risk of a broad phenotype and a gene 2 genotype modifies the expression of gene 1 by conferring susceptibility to a specific phenotype. RESULTS: Compared to a single-locus analysis within the broad phenotype, the proposed approach had greater power to detect the modifier gene 2 (0.96 vs. 0.54 under a simulation scenario including heterogeneity). In a sample of 12 mixed SZ and BP Eastern Quebec kindreds, D8S1110 at 8p22 showed the strongest evidence of linkage to a gene determining a specific phenotype (SZ or BP) among subjects susceptible to major psychosis because of putative genes at 10p13 (D10S245, conditional maximized LOD (cMOD) = 4.20, p = 0.0003) and 3q21-q23 (D3S2418, cMOD = 4.09, p = 0.0005). CONCLUSION: The proposed strategy is useful to detect modifier loci conferring susceptibility to a specific phenotype within a broader phenotype.

Latent class model with familial dependence to address heterogeneity in complex diseases: adapting the approach to family-based association studies.

Clinical diagnoses of complex diseases may often encompass multiple genetically heterogeneous disorders. One way of dissecting this heterogeneity is to apply latent class (LC) analysis to measurements related to the diagnosis, such as detailed symptoms, to define more homogeneous disease sub-types, influenced by a smaller number of genes that will thus be more easily detectable. We have previously developed a LC model allowing dependence between the latent disease class status of relatives within families. We have also proposed a strategy to incorporate the posterior probability of class membership of each subject in parametric linkage analysis, which is not directly transferable to genetic association methods. Under the framework of family-based association tests (FBAT), we now propose to make the contribution of an affected subject to the FBAT statistic proportional to his or her posterior class membership probability. Simulations showed a modest but robust power advantage compared to simply assigning each subject to his or her most probable class, and important power gains over the analysis of the disease diagnosis without LC modeling under certain scenarios. The use of LC analysis with FBAT is illustrated using autism spectrum disorder (ASD) symptoms on families from the Autism Genetics Research Exchange, where we examined eight regions previously associated to autism in this sample. The analysis using the posterior probability of membership to an LC detected an association in the JARID2 gene as significant as that for ASD (P = 3 × 10(-5)) but with a larger effect size (odds ratio = 2.17 vs. 1.55).

Global gene expression profiling of the polyamine system in suicide completers.

In recent years, gene expression, genetic association, and metabolic studies have implicated the polyamine system in psychiatric conditions, including suicide. Given the extensive regulation of genes involved in polyamine metabolism, as well as their interconnections with the metabolism of other amino acids, we were interested in further investigating the expression of polyamine-related genes across the brain in order to obtain a more comprehensive view of the dysregulation of this system in suicide. To this end, we examined the expression of genes related to polyamine metabolism across 22 brain regions in a sample of 29 mood-disordered suicide completers and 16 controls, and identified 14 genes displaying differential expression. Among these, altered expression of spermidine/spermine N1-acetyltransferase, spermine oxidase, and spermine synthase, has previously been observed in brains of suicide completers, while the remainder of the genes represent novel findings. In addition to genes with direct involvement in polyamine metabolism, including S-adenosylmethionine decarboxylase, ornithine decarboxylase antizymes 1 and 2, and arginase II, we identified altered expression of several more distally related genes, including aldehyde dehydrogenase 3 family, member A2, brain creatine kinase, mitochondrial creatine kinase 1, glycine amidinotransferase, glutamic-oxaloacetic transaminase 1, and arginyl-tRNA synthetase-like. Many of these genes displayed altered expression across several brain regions, strongly implying that dysregulated polyamine metabolism is a widespread phenomenon in the brains of suicide completers. This study provides a broader view of the nature and extent of the dysregulation of the polyamine system in suicide, and highlights the importance of this system in the neurobiology of suicide.

A new strategy for linkage analysis under epistasis taking into account genetic heterogeneity.

BACKGROUND/AIMS: Epistasis, the biological interaction of multiple genes modulating their individual effects, is likely omnipresent in complex diseases, and modelling epistasis in linkage studies can help detect loci with little marginal effect and detect epistatic effects themselves. We propose a complete three-step strategy for parametric linkage analysis under epistasis and heterogeneity in extended pedigrees. METHODS: (1) Loci most likely involved in epistatic interactions are pre-screened using two-locus one-marker analyses. (2) Among selected loci, linkage to each locus is evaluated conditionally on linkage information at another locus under two-locus epistatic models. Linkage statistics are maximized over a space of epistatic models to avoid misspecification of model parameters. (3) Families linked to the conditioning locus are selected to deal with heterogeneity between pairs of epistatically interacting loci and other unlinked loci. Properties of conditional linkage statistics prevent the introduction of bias. RESULTS: Simulations reveal important gains in power to detect a locus with weak marginal effect involved in epistatic interaction. Application of our methods to schizophrenia and bipolar disorder in Eastern Quebec kindreds suggests epistasis between three locus pairs for bipolar disorder: 8p11-16p13, 15q11-16p13 and 18q12-15q11. CONCLUSION: These results suggest that the proposed strategy is powerful for tackling complex phenotypes involving epistasis and heterogeneity.

A multimodal attempt to follow-up linkage regions using RNA expression, SNPs and CpG methylation in schizophrenia and bipolar disorder kindreds.

The complexity of schizophrenia (SZ) and bipolar disorder (BD) has slowed down progress in understanding their genetic roots. Alternative genomic approaches are needed to bypass these difficulties. We attempted a multimodal approach to follow-up on reported linkage findings in SZ and BD from the Eastern Quebec kindreds in chromosomes 3q21, 4p34, 6p22, 8p21, 8p11, 13q11-q14, 15q13, 16p12, and 18q21. First, in 498 subjects, we measured RNA expression (47 K Illumina chips) in SZ and BD patients that we compared with their non-affected relatives (NARs) to identify, for each chromosomal region, genes showing the most significant differences in expression. Second, we performed SNP genotyping (700 K Illumina chips) and cis-eQTN analysis. Third, we measured DNA methylation on genes with RNA expression differences or eQTNs. We found a significant overexpression of the gene ITGB5 at 3q25 in SZ and BD after multiple testing p value adjustment. SPCS3 gene at 4q34, and FZD3 gene at 8p21, contained significant eQTNs after multiple testing corrections, while ITGB5 provided suggestive results. Methylation in associated genes did not explain the expression differences between patients and NARs. Our multimodal approach involving RNA expression, dense SNP genotyping and eQTN analyses, restricted to chromosomal regions having shown linkage, lowered the multiple testing burden and allowed for a deeper examination of candidate genes in SZ or BD.

Engaging Caregivers in Health-Related Housing Decisions for Older Adults With Cognitive Impairment: A Cluster Randomized Trial.

BACKGROUND AND OBJECTIVES: Informal caregivers are rarely as involved as they want to be in the housing decisions of cognitively impaired older adults. Lack of awareness of available options and their benefits and risks may lead to decisions that do not reflect older adults' preferences, and to guilt and regret. We assessed the effect of training home care teams in interprofessional shared decision-making (SDM) on the proportion of caregivers who report being active in this decision. RESEARCH DESIGN AND METHODS: In a two-arm pragmatic cluster randomized trial with home care teams working in health centers in the Province of Quebec, we randomized health centers to receive training in interprofessional SDM (intervention) or not (control). Eligible caregivers had made a housing decision for a cognitively impaired adult aged 65 years or older who was receiving services from a home care team. The primary outcome was the proportion of caregivers reporting an active role in decision making. We performed intention-to-treat multilevel analysis. RESULTS: We consecutively enrolled a random group of 16 health centers and recruited 309 caregivers, among whom 296 were included in the analysis. In the intervention arm, the proportion of caregivers reporting an active role in decision making increased by 12% (95% CI -2% to 27%; p = .10). After removal of an influential cluster outlier, the proportion increased to 18% (95% CI: 7%-29%; p < .01). DISCUSSION AND IMPLICATIONS: Training home care teams in interprofessional SDM increased caregiver involvement in health-related housing decisions for cognitively impaired older adults.

Using disease symptoms to improve detection of linkage under genetic heterogeneity.

A major reason for the slow progress in identifying susceptibility genes for complex diseases may be that the clinical diagnoses used as phenotypes are genetically heterogeneous. This has led researchers to collect various phenotypes related to the diagnosis, such as detailed symptoms, in the hope that these measurements define more homogeneous disease sub-types, influenced by a smaller number of genes that will thus be more easily detectable. Latent class analysis can be used to define disease sub-types from multivariate symptoms under the assumption that the subjects are independent, an assumption that does not hold between members of the same family. We have recently developed a latent class model allowing dependence between the latent disease class status of relatives within nuclear families. In this paper, we propose approaches to use the resulting latent class probabilities in linkage analysis. We present results from a simulation study showing that the latent class approach can provide a substantial gain in power to detect disease genes over the standard heterogeneity approach of Smith and identity-by-descent sharing methods applied to the disease diagnosis. Taking into account familial dependence in the latent class model generally provides greater power than assuming independence. In an analysis of autism symptoms in families from the Autism Genetics Research Exchange, linkage signals obtained with latent class-derived phenotypes were stronger than those obtained using the original autism spectrum disorder diagnosis.

Shared decision-making experienced by Canadians facing health care decisions: a Web-based survey.

BACKGROUND: Despite health policy that promotes shared decision-making, it is not yet the norm in clinical practice. We aimed to assess how much shared decision-making Canadians experienced in health-related decisions in 2017. METHODS: We conducted a cross-sectional online survey in January 2018 with a Web-based panel of Canadians representing all 10 provinces. We assessed their involvement in health-related decisions made with a health care professional over the previous year by asking about 1) discussion of choice of treatment or care plan, 2) presentation of advantages and disadvantages, 3) exploration of ideas and preferences, 4) discussion of preferred option and 5) match between preferred and actual level of participation. We computed an average shared decision-making score (range 1 [never] to 5 [always]). We presented characteristics of participants and responses using descriptive statistics and explored variations across sociodemographic factors, jurisdictions, geographical areas and care settings (home care or not) using multivariate weighted regressions. RESULTS: Of the 1591 participants surveyed, 1010 (63.5%) reported receiving health care in the previous 12 months. The mean of the average shared decision-making score was 2.25/5 (standard deviation [SD] 1.16). After weighting, 42.8% of respondents reported that their health care professional often or always mentioned that they had a choice of treatment or care plan, 45.4% reported that advantages and disadvantages were often or always presented, 38.8% reported that they were often or always asked for their ideas or preferences, 40.2% reported that they were often or always asked about their preferred option, and 54.1% stated that their level of participation in decision-making often or always matched their preferred level of participation. Increasing age, rural setting, living in the province of Quebec and not being white significantly decreased the level of shared decision-making experienced. Older respondents (age ≥ 65 yr) receiving home care reported the least shared decision-making (mean score 1.7 [SD 0.5]). INTERPRETATION: Canadians in all 10 provinces experienced a low degree of shared decision-making in 2017, with variations across sociodemographic factors, jurisdictions, care settings and geographical areas. Further efforts to foster implementation of shared decision-making are needed and should take these variations into account.

Implementation Research on Shared Decision Making in Primary Care: Inventory of Intracluster Correlation Coefficients.

Background. Cluster randomized trials are important sources of information on evidence-based practices in primary care. However, there are few sources of intracluster correlation coefficients (ICCs) for designing such trials. We inventoried ICC estimates for shared decision-making (SDM) measures in primary care. Methods. Data sources were studies led by the Canada Research Chair in Shared Decision Making and Knowledge Transition. Eligible studies were conducted in primary care, included at least 2 hierarchical levels, included SDM measures for individual units nested under any type of cluster (area, clinic, or provider), and were approved by an ethics committee. We classified measures into decision antecedents, decision processes, and decision outcomes. We used Bayesian random-effect models to estimate mode ICCs and the 95% highest probability density interval (HPDI). We summarized estimates by calculating median and interquartile range (IQR). Results. Six of 14 studies were included. There were 97 ICC estimates for 17 measures. ICC estimates ranged from 0 to 0.5 (median, 0.03; IRQ, 0-0.07). They were higher for process measures (median, 0.03; IQR, 0-0.07) than for antecedent measures (0.02; 0-0.07) or outcome measures (0.02; 0-0.06), for which, respectively, "decisional conflict" (mode, 0.48; 95% HPDI, 0.39-0.57), "reluctance to disclose uncertainty to patients" (0.5; 0.11-0.89), and "quality of the decision" (0.45; 0.14-0.84) had the highest ICCs. ICCs for provider-level clustering (median, 0.06; IQR, 0-0.13) were higher than for other levels. Limitations. This convenience sample of studies may not reflect all potential ICC ranges for primary care SDM measures. Conclusions. Our inventory of ICC estimates for SDM measures in primary care will improve the ease and accuracy of power calculations in cluster randomized trials and inspire its further expansion in SDM contexts.

Physical activity during pregnancy and infant's birth weight: results from the 3D Birth Cohort.

AIM: To evaluate the association between maternal physical activity and infant's birth weight or risk of inappropriate weight for gestational age (GA), and whether this association differs by infant's sex, maternal body mass index (BMI) or pregnancy complications in a prospective cohort study. METHODS: 1913 pregnant women from the 3D Birth Cohort (Québec, Canada) completed the Pregnancy Physical Activity Questionnaire at each trimester. Energy expenditure (metabolic equivalent of task (MET)*hours/week) for total activity, sports and exercise and vigorous intensity activities was calculated. The associations with birth weight and risk of inappropriate weight for GA were evaluated by regression modelling. Interactions were tested with infant's sex, maternal prepregnancy BMI, gestational diabetes, hypertensive disorders and prematurity. RESULTS: Each 1 MET/hours/week increase in sports and exercise in the first trimester was associated with a 2.5 g reduction in infant's birth weight (95% CI -4.8 to -0.3) but was not associated with the risk of small weight for GA. In contrast, although not significant, a 17% reduction in the risk of large weight for GA was observed with increasing sports and exercise. Furthermore, in women with subsequent pre-eclampsia (but not normotensive or hypertensive women), each 1 MET/hours/week increment spent in any vigorous exercise in the first trimester reduced the infant's birth weight by 19.8 g (95% CI -35.2 to -4.3). CONCLUSIONS: Pregnant women with higher sports and exercise levels in the first trimester delivered infants with a lower birth weight. The risk of reducing infant's birth weight with vigorous exercise in women who develop pre-eclampsia later in pregnancy requires evaluation.

Estimating genetic effect sizes under joint disease-endophenotype models in presence of gene-environment interactions.

Effects of genetic variants on the risk of complex diseases estimated from association studies are typically small. Nonetheless, variants may have important effects in presence of specific levels of environmental exposures, and when a trait related to the disease (endophenotype) is either normal or impaired. We propose polytomous and transition models to represent the relationship between disease, endophenotype, genotype and environmental exposure in family studies. Model coefficients were estimated using generalized estimating equations and were used to derive gene-environment interaction effects and genotype effects at specific levels of exposure. In a simulation study, estimates of the effect of a genetic variant were substantially higher when both an endophenotype and an environmental exposure modifying the variant effect were taken into account, particularly under transition models, compared to the alternative of ignoring the endophenotype. Illustration of the proposed modeling with the metabolic syndrome, abdominal obesity, physical activity and polymorphisms in the NOX3 gene in the Quebec Family Study revealed that the positive association of the A allele of rs1375713 with the metabolic syndrome at high levels of physical activity was only detectable in subjects without abdominal obesity, illustrating the importance of taking into account the abdominal obesity endophenotype in this analysis.