Prediction of successful labor induction in persons with a low Bishop score using machine learning: Secondary analysis of two randomized controlled trials.

BACKGROUND: The objective of this paper was to identify predictors of a vaginal birth in individuals with singleton pregnancies and a Bishop Score <4, following Induction of Labor (IoL) using dinoprostone vaginal insert (DVI). Secondarily, we sought to understand the association between oxytocin use for labor augmentation and IoL outcomes. METHODS: We developed and internally validated a multivariate prediction model using machine learning (ML) applied to data from two Phase-III randomized controlled double-blind trials (NCT01127581, NCT00308711). The model was internally validated using 10-fold cross-validation. RESULTS: This study included 1107 participants. Despite unfavorable cervical status and inclusion of high-risk pregnancies, 72% of participants had vaginal births. The model's area under receiver operating characteristic curve was 0.73. The following factors increased the chance of vaginal birth: being parous; being between 37 and 41 weeks of gestation; having a lower Body Mass Index; having a lower maternal age; having fewer maternal comorbidities; and having a higher Bishop score. Parity alone correctly predicted the outcome in ~50% of cases, at a ~10% false-negative rate. Participants whose labors progressed without requiring oxytocin had a higher probability of vaginal birth than those requiring oxytocin for either induction or augmentation (81% vs 70% vs 77%, respectively). DISCUSSION: Even in high-risk pregnancies and with low Bishop scores, the use of DVI results in a high chance of vaginal birth. Parity is a critical predictor of success. The judicious use of oxytocin for labor induction or augmentation can increase the chance of vaginal birth. Our study validates the use of ML and predictive modeling for treatment response prediction when considering IoL.

Identification of potentially undiagnosed patients with nontuberculous mycobacterial lung disease using machine learning applied to primary care data in the UK.

Nontuberculous mycobacterial lung disease (NTMLD) is a rare lung disease often missed due to a low index of suspicion and unspecific clinical presentation. This retrospective study was designed to characterise the prediagnosis features of NTMLD patients in primary care and to assess the feasibility of using machine learning to identify undiagnosed NTMLD patients.IQVIA Medical Research Data (incorporating THIN, a Cegedim Database), a UK electronic medical records primary care database was used. NTMLD patients were identified between 2003 and 2017 by diagnosis in primary or secondary care or record of NTMLD treatment regimen. Risk factors and treatments were extracted in the prediagnosis period, guided by literature and expert clinical opinion. The control population was enriched to have at least one of these features.741 NTMLD and 112 784 control patients were selected. Annual prevalence rates of NTMLD from 2006 to 2016 increased from 2.7 to 5.1 per 100 000. The most common pre-existing diagnoses and treatments for NTMLD patients were COPD and asthma and penicillin, macrolides and inhaled corticosteroids. Compared to random testing, machine learning improved detection of patients with NTMLD by almost a thousand-fold with AUC of 0.94. The total prevalence of diagnosed and undiagnosed cases of NTMLD in 2016 was estimated to range between 9 and 16 per 100 000.This study supports the feasibility of machine learning applied to primary care data to screen for undiagnosed NTMLD patients, with results indicating that there may be a substantial number of undiagnosed cases of NTMLD in the UK.

CNVs conferring risk of autism or schizophrenia affect cognition in controls.

In a small fraction of patients with schizophrenia or autism, alleles of copy-number variants (CNVs) in their genomes are probably the strongest factors contributing to the pathogenesis of the disease. These CNVs may provide an entry point for investigations into the mechanisms of brain function and dysfunction alike. They are not fully penetrant and offer an opportunity to study their effects separate from that of manifest disease. Here we show in an Icelandic sample that a few of the CNVs clearly alter fecundity (measured as the number of children by age 45). Furthermore, we use various tests of cognitive function to demonstrate that control subjects carrying the CNVs perform at a level that is between that of schizophrenia patients and population controls. The CNVs do not all affect the same cognitive domains, hence the cognitive deficits that drive or accompany the pathogenesis vary from one CNV to another. Controls carrying the chromosome 15q11.2 deletion between breakpoints 1 and 2 (15q11.2(BP1-BP2) deletion) have a history of dyslexia and dyscalculia, even after adjusting for IQ in the analysis, and the CNV only confers modest effects on other cognitive traits. The 15q11.2(BP1-BP2) deletion affects brain structure in a pattern consistent with both that observed during first-episode psychosis in schizophrenia and that of structural correlates in dyslexia.

Does maternal attachment to her infant mediate the link between perceptions of infant crying at 6 months and parenting stress at 24 months? A structural equation modelling approach.

BACKGROUND: Parenting stress is influenced by many factors including maternal attachment and excessive infant crying, yet the nature of these relationships is not well understood. For example, excessive infant crying despite maternal soothing may impact maternal attachment to the child, leading to higher stress. This paper explored whether maternal perception of excessive infant crying at 6 months was associated with higher maternal parenting stress at 24 months, and whether maternal attachment mediated this relationship. METHODS: All families, present at 24 months in a randomized controlled trial of a 5-year early intervention programme targeting school readiness skills in disadvantaged area of Ireland, were included. At 6 months, infant crying was assessed using a maternal reported measure of duration of infant crying, and maternal attachment to the infant was assessed using the Condon Maternal Attachment Scale. Parenting stress was assessed at 24 months using the childrearing stress subscale from the Parenting Stress Index. Structural equation modelling was used to explore the direct and indirect effects of maternal perceptions of excessive infant crying on parenting stress, controlling for infant, maternal, and environmental characteristics, and focusing on the mediating role of maternal attachment. RESULTS: Reporting excessive infant crying at 6 months was associated with lower maternal attachment at 6 months, which led to higher parenting stress at 24 months. In addition, vulnerable adult attachment style, previous maternal mental health difficulties, low paternal education, paternal involvement with the child, and not being married were associated with higher parenting stress. CONCLUSION: Findings suggest that the association between maternal perceptions of excessive crying at 6 months and later parenting stress may be mediated through maternal attachment to the infant. Interventions based on improving maternal attachment could be investigated to determine the effectiveness of supporting mothers with low attachment.

Breastfeeding and externalising problems: a quasi-experimental design with a national cohort.

Evidence from correlational studies supporting the benefits of breastfeeding on children's externalising problems is mixed. Quasi-experimental approaches can help in better understanding possible 'effects'. We aimed to investigate the longitudinal impact of breastfeeding on externalising problems from childhood into adolescence. Participants included ~ 5000 full-term children, from the Growing Up in Ireland Child Cohort. Externalising problems (conduct problems and hyperactivity) were assessed using both the parent and teacher versions of the Strengths and Difficulties Questionnaire when children were age 9 and 13. Maternal reports were used to collect retrospective information on breastfeeding. Propensity score matching, and adjusting for multiple testing were used to compare the average treatment effects for children who were breastfed. Post matching results revealed statistically significant reductions in hyperactivity at age nine, using both maternal and teacher reports (difference score - 0.48, 95% CI - 0.85, - 0.11; and - 0.51, 95% CI - 0.90, - 0.12, respectively), for children who were breastfed between 6 and 12 months, but not thereafter. These effects were not maintained at age 13. Moreover, no effects of breastfeeding on conduct problems were found at any age, regardless of duration, using either maternal or teacher report. While some benefits of breastfeeding were found, compatible with a temporary modest reduction in hyperactivity, related to being breastfed for 26-50 weeks, these results must be viewed in the context of reliance of propensity score matching on observable characteristics. Additionally, our results are suggestive of a potential non-linear dose-response of breastfeeding on hyperactivity.

Population-Based System of Parenting Support to Reduce the Prevalence of Child Social, Emotional, and Behavioural Problems: Difference-In-Differences Study.

The quality of parenting is recognised as an important determinant of children's mental health. Parenting interventions typically target high-risk families rather than adopting a universal approach. This study examined the population impact of the Triple P Positive Parenting Programme on the prevalence of children's social, emotional, and behavioural problems. A propensity score matching difference-in-differences method was used to compare intervention and comparison regions matched on socio-demographic characteristics in midlands Ireland. The pre-intervention sample included 1501 and 1495 parents of children aged 4-8 years in the intervention and comparison regions respectively. The post-intervention sample included 1521 and 1544 parents respectively. The primary outcome measure was parental reports on the Strengths and Difficulties Questionnaire. There were some significant reductions in the prevalence rates of social, emotional, and behavioural problems in the intervention regions compared to the comparison regions. Children in the intervention sample experienced lower total difficulties, emotional symptoms, and conduct problems than children in the comparison sample, and they were less at risk of scoring within the borderline/abnormal range for total difficulties, conduct problems, and hyperactivity. The programme reduced the proportion of children scoring within the borderline/abnormal range by 4.7% for total difficulties, 4.4% for conduct problems, and 4.5% for hyperactivity in the total population. This study demonstrated that a universal parenting programme implemented at multiple levels using a partnership approach may be an effective population health approach to targeting child mental health.

Parsing the Roles of the Frontal Lobes and Basal Ganglia in Task Control Using Multivoxel Pattern Analysis.

Cognitive control has traditionally been associated with pFC based on observations of deficits in patients with frontal lesions. However, evidence from patients with Parkinson disease indicates that subcortical regions also contribute to control under certain conditions. We scanned 17 healthy volunteers while they performed a task-switching paradigm that previously dissociated performance deficits arising from frontal lesions in comparison with Parkinson disease, as a function of the abstraction of the rules that are switched. From a multivoxel pattern analysis by Gaussian Process Classification, we then estimated the forward (generative) model to infer regional patterns of activity that predict Switch/Repeat behavior between rule conditions. At 1000 permutations, Switch/Repeat classification accuracy for concrete rules was significant in the BG, but at chance in the frontal lobe. The inverse pattern was obtained for abstract rules, whereby the conditions were successfully discriminated in the frontal lobe but not in the BG. This double dissociation highlights the difference between cortical and subcortical contributions to cognitive control and demonstrates the utility of multivariate approaches in investigations of functions that rely on distributed and overlapping neural substrates.

Effects of early intervention on dietary intake and its mediating role on cognitive functioning: a randomised controlled trial.

OBJECTIVE: To investigate the impact of an early intervention programme, Preparing for Life, on dietary intake between 12 and 36 months of age, and the mediating role played by diet on cognitive functioning. DESIGN: A randomised controlled trial evaluation of a community-based home visiting programme. The intervention involved biweekly visits from mentors from pregnancy until age 5 years and parent training at age 2 years. Dietary intake was assessed at 12, 18, 24 and 36 months using an FFQ to calculate the proportion meeting dietary recommendations. Cognitive functioning was measured at 24 and 36 months. Treatment effects were estimated using conventional χ 2 tests, permutation testing, inverse probability weighting and the stepdown procedure. Mediation analysis examined the indirect effect of the intervention on cognitive functioning via its effect on dietary intake. SETTING: Socio-economically disadvantaged communities in Dublin, Republic of Ireland. SUBJECTS: Pregnant women (n 233) were assigned to the intervention (n 115) or control (n 118) group using an unconditional probability randomisation strategy. RESULTS: Positive treatment effects were observed for meeting dietary recommendations for protein foods at 24 (OR=2·52) and 36 (OR=2·42) months, and all food groups at 24 (OR=3·92) months. There were no effects on grain, dairy, fruit and vegetable, or fatty/sugary food recommendations in most models. The conventional and more novel methods yielded similar results. Mediation analysis indicated that 13 % of the intervention's effect on cognitive functioning was mediated by 36-month protein food consumption. CONCLUSIONS: The study demonstrates some potential to alter early childhood dietary patterns through community-based intervention programmes.

Maternal warmth and toddler development: support for transactional models in disadvantaged families.

Studies support cognitive and social domains of development as entwined in childhood, however, there is a paucity of investigation into the nature of the mother-child relationship within an interdependence framework. Furthermore, the focus on these processes within families from impoverished communities using frequent assessments in early childhood has been limited. Our objectives were to identify (1) the directional associations between toddler's communication ability and social competence, (2) to establish whether the association between toddler's communication ability and social competence is mediated by maternal warmth, and (3) to establish support for transactional models between toddlers' outcomes and maternal warmth in disadvantaged communities in Ireland. Participants included 173 toddlers and their families enrolled in a prenatally commencing prevention programme. Toddler's communication and social competence were assessed at 12, 18, 24 and 36 months and maternal warmth at 6 and 24 months. Cross-lagged models were estimated examining multiple paths of associations simultaneously. Direct and indirect paths of maternal warmth were also examined. Bi-directional associations were found between communication ability and social competence from 12 to 24 months but not thereafter. Maternal warmth did not significantly mediate these associations, however, support of a transactional model was found with social competence. The results support early positive associations between better communication ability and social competence in the first 2 years, however, they suggest that these associations are no longer present by the third year. The role of maternal warmth in fostering social competencies is important for toddlers and equally important is toddler's level of social competence in eliciting increased maternal warmth.

"Bursting" to Go and Other Experiences.

Children's use of the toilet at school, although rarely explored, is an important facet of school experience with consequences for physical and psychological health. A mixed methods study investigated views of 25 children (4-5 years) regarding potential stressors in the first school year, including views of toileting, in Dublin, Ireland. Despite very positive responses to school, most responses to toileting (15 of 25) were mixed or negative. Although some liked to go, or noted the toilets were clean, most indicated delayed toilet use ("bursting" to go) and ambivalent or negative experiences such as fear of not identifying the right toilet, fear of being alone, lack of privacy, and potential bullying. Many children did not expect to receive help from the teacher. As delaying toilet use can have lasting health consequences, teacher-nurse collaboration could be used to develop whole-school policies to support children's early adjustment in this sensitive area of functioning.

Bayesian multi-task learning for decoding multi-subject neuroimaging data.

Decoding models based on pattern recognition (PR) are becoming increasingly important tools for neuroimaging data analysis. In contrast to alternative (mass-univariate) encoding approaches that use hierarchical models to capture inter-subject variability, inter-subject differences are not typically handled efficiently in PR. In this work, we propose to overcome this problem by recasting the decoding problem in a multi-task learning (MTL) framework. In MTL, a single PR model is used to learn different but related "tasks" simultaneously. The primary advantage of MTL is that it makes more efficient use of the data available and leads to more accurate models by making use of the relationships between tasks. In this work, we construct MTL models where each subject is modelled by a separate task. We use a flexible covariance structure to model the relationships between tasks and induce coupling between them using Gaussian process priors. We present an MTL method for classification problems and demonstrate a novel mapping method suitable for PR models. We apply these MTL approaches to classifying many different contrasts in a publicly available fMRI dataset and show that the proposed MTL methods produce higher decoding accuracy and more consistent discriminative activity patterns than currently used techniques. Our results demonstrate that MTL provides a promising method for multi-subject decoding studies by focusing on the commonalities between a group of subjects rather than the idiosyncratic properties of different subjects.

Child care in infancy and cognitive performance until middle childhood in the millennium cohort study.

This study used a British cohort (n = âˆ¼13,000) to investigate the association between child care during infancy and later cognition while controlling for social selection and missing data. It was found that attending child care (informal or center based) at 9 months was positively associated with cognitive outcomes at age 3 years, but only for children of mothers with low education. These effects did not persist to ages 5 or 7 years. Early center-based care was associated with better cognitive outcomes than informal care at ages 3 and 5 years, but not at 7 years. Effect sizes were larger among children whose mother had low education. Propensity score matching and multiple imputation revealed significant findings undetected using regression and complete-case approaches.

Economics of childbirth.

BACKGROUND: Increasing birth rates have raised questions for policy makers and hospital management about the economic costs of childbirth. OBJECTIVE: The purpose of this article is to identify and review all existing scientific studies in relation to the economic costs of alternative modes of childbirth delivery and to highlight deficiencies in the existing scientific research. METHOD: We searched Cochrane, Centre for Reviews and Dissemination, EconLit, the Excerpta Medica Database, the Health Economic Evaluations Database, MEDLINE and PubMed. RESULTS: Thirty articles are included in this review. The main findings suggest that there is no internationally acceptable childbirth cost and clinical outcome classification system that allows for comparisons across different delivery modes. CONCLUSION: This review demonstrates that a better understanding and classification of the costs and associated clinical outcomes of childbirth is required to allow for valid comparisons between maternity units, and to inform policy makers and hospital management.

The economic impact of living with a rare disease for children and their families: a scoping review protocol.

Background: Rare diseases are an often chronic, progressive and life-limiting group of conditions affecting more than 30 million people in Europe. These diseases are associated with significant direct and indirect costs to a spectrum of stakeholders, ranging from individuals and their families to society overall. Further quantitative research on the economic cost for children and their families living with a rare disease is required as there is little known on this topic. This scoping review aims to document the extent and type of evidence on the economic impacts of living with a rare disease for children and their families. Methods: This scoping review will follow the PRISMA-ScR and Joanna Briggs Institute guidelines and follow the six-stage methodology for scoping reviews: (1) identifying the research question, (2) identifying relevant studies, (3) study selection, (4) charting the data, (5) collating, summarising and reporting results and (6) knowledge user consultation. Key inclusion criteria have been developed according to the Population-Concept-Context (PCC) framework. The databases EconLit, ABI/Inform, MEDLINE, PubMed, CINAHL, and Scopus will be searched for possible articles for inclusion. Two independent reviewers will screen titles and abstracts of potential articles using a dual review process to ensure all relevant studies are included. All included articles will be assessed using a validated quality appraisal tool. A panel of patient and public involvement representatives experiencing rare diseases and knowledge users will validate the review results. Conclusions: This scoping review will map the current literature on the economic impact of paediatric rare diseases to understand how these impacts affect children living with rare diseases and their families. This evidence has the potential to influence policy and future research in this area and will support further research on the economic impact of rare diseases on families.

Finding undiagnosed patients with hepatitis C virus: an application of machine learning to US ambulatory electronic medical records.

AIMS: To develop and validate a machine learning (ML) algorithm to identify undiagnosed hepatitis C virus (HCV) patients, in order to facilitate prioritisation of patients for targeted HCV screening. METHODS: This retrospective study used ambulatory electronic medical records (EMR) from January 2015 to February 2020. A Gradient Boosting Trees algorithm was trained using patient records to predict initial HCV diagnosis and was validated on a temporally independent held-out cross-section of the data. The fold improvement in precision (proportion of patients identified by the algorithm who are HCV positive) over universal screening was examined and compared with risk-based screening. RESULTS: 21 508 positive (HCV diagnosed) and 28.2M unlabelled (lacking evidence of HCV diagnosis) patients met the inclusion criteria for the study. After down-sampling unlabelled patients to aid the algorithm's learning process, 16.2M unlabelled patients entered the analysis. Performance of the algorithm was compared with universal screening on the held-out cross-section, which had an incidence of HCV diagnoses of 0.02%. The algorithm achieved a 101.0 ×, 18.0 × and 5.1 × fold improvement in precision over universal screening at 5%, 20% and 50% levels of recall. When compared with risk-based screening, the algorithm required fewer patients to be screened and improved precision. CONCLUSIONS: This study presents strong evidence towards the use of ML on EMR data for the prioritisation of patients for targeted HCV testing with potential to improve efficiency of resource utilisation, thereby reducing the workload for clinicians and saving healthcare costs. A prospective interventional study would allow for further validation before use in a clinical setting.

Worker Stress, Burnout, and Wellbeing Before and During the COVID-19 Restrictions in the United Kingdom.

COVID-19 created a transformational shift in the working environment for much of the labour force, yet its impact on workers is unclear. This study uses longitudinal data to examine the wellbeing of 621 full-time workers assessed before (November 2019-February 2020) and during (May-June 2020) the first lockdown in the United Kingdom. We employ fixed effects analyses to investigate the impact of the restrictions and mandatory homeworking on cognitive, emotional, and psychological wellbeing. Within the sample, the rate of full-time homeworking increased from 2 to 74% between waves. We identify significant changes in 9 of the 15 measures assessed, with a general pattern of improvements in wellbeing during lockdown. Overall levels of stress, self-rated mental health, positive emotions and life and job satisfaction are not adversely affected by the restrictions. There is a reduction in the burnout symptoms of disengagement (-0.13 sd) and exhaustion (-0.20 sd) and in the frequency with which negative emotions are experienced at work (-0.15 sd). Workers feel more autonomous (+0.09 sd), closer to their co-workers (+0.10 sd), and more attached to their organisations (+0.19 sd). However, homelife satisfaction declines (-0.11 sd). These findings highlight the possibility that the COVID-19 pandemic and large-scale transition to homeworking was associated with unchanged or improved worker wellbeing. This study has important implications for governments and employers regarding a global shift to homeworking.

Machine learning using longitudinal prescription and medical claims for the detection of non-alcoholic steatohepatitis (NASH).

OBJECTIVES: To develop and evaluate machine learning models to detect patients with suspected undiagnosed non-alcoholic steatohepatitis (NASH) for diagnostic screening and clinical management. METHODS: In this retrospective observational non-interventional study using administrative medical claims data from 1 463 089 patients, gradient-boosted decision trees were trained to detect patients with likely NASH from an at-risk patient population with a history of obesity, type 2 diabetes mellitus, metabolic disorder or non-alcoholic fatty liver (NAFL). Models were trained to detect likely NASH in all at-risk patients or in the subset without a prior NAFL diagnosis (at-risk non-NAFL patients). Models were trained and validated using retrospective medical claims data and assessed using area under precision recall curves and receiver operating characteristic curves (AUPRCs and AUROCs). RESULTS: The 6-month incidences of NASH in claims data were 1 per 1437 at-risk patients and 1 per 2127 at-risk non-NAFL patients . The model trained to detect NASH in all at-risk patients had an AUPRC of 0.0107 (95% CI 0.0104 to 0.0110) and an AUROC of 0.84. At 10% recall, model precision was 4.3%, which is 60× above NASH incidence. The model trained to detect NASH in the non-NAFL cohort had an AUPRC of 0.0030 (95% CI 0.0029 to 0.0031) and an AUROC of 0.78. At 10% recall, model precision was 1%, which is 20× above NASH incidence. CONCLUSION: The low incidence of NASH in medical claims data corroborates the pattern of NASH underdiagnosis in clinical practice. Claims-based machine learning could facilitate the detection of patients with probable NASH for diagnostic testing and disease management.

A Demonstration Study of the Quiet Time Transcendental Meditation Program.

This manuscript presents a demonstration study of Quiet Time (QT), a classroom-based Transcendental Meditation intervention. The aim of the study is to assess the feasibility of implementing and evaluating QT in two pilot settings in the United Kingdom and Ireland. This study contributes to the field by targeting middle childhood, testing efficiency in two settings operating under different educational systems, and including a large array of measures. First, teacher and pupil engagement with QT was assessed. Second, the feasibility of using a quasi-experimental design and a wide range of instruments to measure changes in pupil outcomes before and after the intervention was assessed. This allows us to obtain information about which instruments might be feasible to administer and most sensitive to change. The first setting included 89 students from a primary school in the United Kingdom: those in sixth grade received the QT intervention, while those in fifth grade practiced meditation using the Headspace application. The second setting included 100 fifth- and sixth-grade students from two schools in Ireland: one received the QT intervention, the other served as a control. Recruitment and retention rates were high in both settings, and the intervention was feasible and accepted by students, parents and teachers. Implementation fidelity was lower in the United Kingdom setting where delivery started later in the school year and the practice was affected by preparation for the Standard Assessment Tests. These results show that QT may be feasibly delivered in school settings, and suggest the use of a compact battery of tests to measure impact. We find suggestive evidence that the intervention affected executive function as children who practiced QT showed improved working memory in both settings. In the Irish setting, pupils in the QT group had improved ability to control responses. These results have implications for future studies by a) demonstrating that implementation fidelity is highly context dependent and b) providing suggestive evidence of the malleability of children's skills in middle childhood. The results of this demonstration study will be used to inform a larger RCT of the QT intervention.

Application of machine learning methods to bridge the gap between non-interventional studies and randomized controlled trials in ophthalmic patients with neovascular age-related macular degeneration.

PURPOSE: The effectiveness of intravitreal anti-vascular endothelial growth factor agents is usually lower in real world settings compared with randomized clinical trials (RCTs), often limiting the use of real-world evidence (RWE) in regulatory and healthcare decisions. The current analysis aimed to develop and validate an algorithm to explain the difference in outcomes between RWE studies and RCTs in patients with neovascular age-related macular degeneration. METHODS: The algorithm was developed using ranibizumab real world data (RWD) from the US and validated on Australian and UK RWD. A decision model was developed using machine learning principles, in which the model learns how to partition the most influential factors (out of 59 variables) so that they maximally relate to the change in visual acuity (VA) over 12 months. RESULTS: The algorithm identified baseline VA <73 Early Treatment Diabetic Retinopathy Study letters, presence of baseline subretinal fluid, and administration of three loading doses by Day 90 from drug initiation as the characteristics with the greatest impact on VA at month 12. When applying the different criteria, RWE outcomes became similar to those obtained in known RCTs. CONCLUSION: Machine learning techniques can be used to classify real world cohorts and identify subsets of patients who benefit to the same extent as that reported in RCTs. This methodology may support the translation of clinical trial findings to treatment performance in the clinical practice setting.

The effect of local unemployment on health: A longitudinal study of Irish mothers 2001-2011.

The relationship between economic conditions and health is mixed, with some evidence from the most recent financial crisis finding a positive effect of periods of unemployment on heath behaviours. This study uses longitudinal data spanning the periods before, during and after the Irish crisis of 2007, to test the impact of economic expansion and contraction on mothers physical and mental health and health behaviours. Three waves of data from the Irish Lifeways Cohort Study for the period 2001-2011, and local area employment rates from the Irish Census, are used to capture the impact of a period of increased unemployment on health before, during and after the Irish recession, independent of individual employment status. The results from fixed effect linear probability models demonstrate that an additional unit of local area unemployment increases the probability of reporting poor self-rated health by 1-1.8 percentage points and of reporting poor mental well-being by 1.4 and 2.7 percentage points depending on the instrument used. There are decreases in the probability of consuming cigarettes by 3.3 percentage points, self-describing as a regular smoker by 2.9 percentage points and obesity by 0.9 percentage points. The probability of engaging in at least 20 minutes of strenuous or moderate exercise per week declines by 7.8 and 8.7 percentage points respectively, while the probability of engaging in at least 20 minutes of mild exercise rises by 10 percentage points. These results are largely consistent with the US literature, which is predominantly based on working men, thus demonstrating the universal impact of economic vulnerability on health.