Impact of finance on growth: Does it vary with development levels or cyclical conditions?

Financial systems are complex and may support economic growth differently at various stages of economic development. This study of 90 countries extends the financial development-economic growth literature by using four proxies of financial development (banking, stock market, bond market and insurance), and considering a country’s level of economic development, on both a full and pre-global crisis sample. As expected financial markets have different effects on growth where the level of economic development vary. Policy makers should find that the insurance sector offers the most benefit for economic growth at all levels of development. Stock markets promote growth for middle income countries. Similarly bond markets promote growth with middle and high income countries. Some bond market and stock market results differed in the pre-crisis sample. Policies which promote trade but limit other areas such as inflation, government consumption and crises, should also support growth.     

Applications of Bayesian statistical methodology to clinical trial design: A case study of a phase 2 trial with an interim futility assessment in patients with knee osteoarthritis

Development of new pharmacological treatments for osteoarthritis that address unmet medical needs in a competitive market place is challenging. Bayesian approaches to trial design offer advantages in defining treatment benefits by addressing clinically relevant magnitude of effects relative to comparators and in optimizing efficiency in analysis. Such advantages are illustrated by a motivating case study, a proof of concept, and dose finding study in patients with osteoarthritis. Patients with osteoarthritis were randomized to receive placebo, celecoxib, or 1 of 4 doses of galcanezumab. Primary outcome measure was change from baseline WOMAC pain after 8 weeks of treatment. Literature review of clinical trials with targeted comparator therapies quantified treatment effects versus placebo. Two success criteria were defined: one to address superiority to placebo with adequate precision and another to ensure a clinically relevant treatment effect. Trial simulations used a Bayesian dose response and longitudinal model. An interim analysis for futility was incorporated. Simulations indicated the study had ≥85% power to detect a 14‐mm improvement and ≤1% risk for a placebo‐like drug to pass. The addition of the second success criterion substantially reduced the risk of an inadequate, weakly efficacious drug proceeding to future development. The study was terminated at the interim analysis due to inadequate analgesic efficacy. A Bayesian approach using probabilistic statements enables clear understanding of success criteria, leading to informed decisions for study conduct. Incorporating an interim analysis can effectively reduce sample size, save resources, and minimize exposure of patients to an inadequate treatment.     

Co‐production in the epidemiological clinic: A decentred analysis of the tensions in community‐based,client‐facing risk work

Public health policies to prevent disease within populations are giving rise to shifting patterns of healthcare delivery in the late modern era. There is an inherent tension in modern medicine between evidence‐based standardisation, on the one hand, and patient‐centred specificity on the other. This tension manifests in recent policy narratives regarding public health risk (which we have characterised in terms of the epidemiological clinic) and co‐production. Drawing on co‐produced data with health trainers (lay health workers tasked with supporting behavioural change in patients at high risk of cardiovascular disease) in a deprived post‐industrial region of England, our decentred analysis focuses on three extended narratives from this data set. Our analysis builds on and develops emerging theories of risk work, informed by Habermas, and we explore the extent to which elite narratives of public health risk are resisted, absorbed, or bracketed off by client‐facing health workers—emphasising the heterogeneity of responses—and locate these responses within the context of the workers' employment conditions, their embodied experiences, and their wider beliefs and traditions. We argue that co‐production—albeit in a highly constrained form—is possible while delivering public health interventions. However, in the context of a community where health is so adversely affected by wider social problems and where task shifting has drawn lower status healthcare workers into these client‐facing roles, workers must find their own ways to negotiate and attempt to reconcile this context with the risk‐framed practices they are required to carry out.     

Associations between Croatian Adolescents’ Use of Sexually Explicit Material and Risky Sexual Behavior: A Latent Growth Curve Modeling Approach

Objectives: The aim of this biobehavioral longitudinal study was to assess the association between sexually explicit material (SEM) use and risky sexual behavior among Croatian adolescents (n?=?577). Methods: The data were collected over the period of 15?months. Conditional dual-domain latent growth modeling was used. Results: Male adolescents’ initial SEM use, but not subsequent growth, was related to changes in sexual risk taking over the observed period. Among female adolescents, SEM use and sexual risk taking were significantly related only at baseline. Conclusions: Our findings point to gender-specific association between adolescents’ SEM use and risky sexual behavior.     

Community engagement in the Aboriginal Families Study: Strategies to promote participation

Background

Aboriginal women and families are under-represented in Australian research on pregnancy and childbirth. The Aboriginal Families Study aimed to investigate the views and experiences of a representative sample of women giving birth to an Aboriginal baby in South Australia between July 2011 and June 2013, using methods designed to respect Aboriginal culture and communities.