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Our objective was to describe, for the first time in an English-speaking Caribbean country, the contribution of ultra-processed foods (UPFs) to nutrients linked to non-communicable disease. Using a cross-sectional study design, dietary data were collected from two non-consecutive 24-h dietary recalls. Recorded food items were then classified according to their degree of processing by the NOVA system. The present study took place in Barbados (2012–13). A representative population-based sample of 364 adult Barbadians (161 males and 203 females) aged 25–64 years participated in the study. UPFs represented 40⋅5 % (838 kcal/d; 95 % CI 791, 885) of mean energy intake. Sugar-sweetened beverages made the largest contribution to energy within the UPF category. Younger persons (25–44 years) consumed a significantly higher proportion of calories from UPF (NOVA group 4) compared with older persons (45–64 years). The mean energy shares of UPF ranged from 22⋅0 to 58⋅9 % for those in the lowest tertile to highest tertile. Within each tertile, the energy contribution was significantly higher in the younger age group (25–44 years) compared with the older (45–64 years). One-quarter of persons consume ≥50 % of their daily calories from UPF, this being significantly higher in younger persons. The ultra-processed diet fraction contained about six times the mean of free sugars and about 0⋅8 times the dietary fibre of the non-ultra-processed fraction (NOVA groups 1–3). Targeted interventions to decrease the consumption of UPF especially in younger persons is thus of high priority to improve the diet quality of Barbadians.
The development of maternal representations of the child during pregnancy guides a mother’s thoughts, feelings, and behavior toward her child. The association between prenatal representations, particularly those that are disrupted, and toddler social-emotional functioning is not well understood. The present study examined associations between disrupted prenatal representations and toddler social-emotional functioning and to test disrupted maternal behavior as a mediator of this association. Data were drawn from 109 women from a larger prospective longitudinal study (N=120) of women and their young children. Prenatal disrupted maternal representations were assessed using the Working Model of the Child Interview disrupted coding scheme, while disrupted maternal behavior was coded 12-months postpartum from mother-infant interactions. Mother-reported toddler social-emotional functioning was assessed at ages 12 and 24 months. Disrupted prenatal representations significantly predicted poorer toddler social-emotional functioning at 24 months, controlling for functioning at 12 months. Further, disrupted maternal behavior mediated the relation between disrupted prenatal representations and toddler social-emotional problems. Screening for disrupted representations during pregnancy is needed to facilitate referrals to early intervention and decrease the likelihood of toddler social-emotional problems.
This SHEA white paper identifies knowledge gaps and challenges in healthcare epidemiology research related to COVID-19 with a focus on core principles of healthcare epidemiology. These gaps, revealed during the worst phases of the COVID-19 pandemic, are described in 10 sections: epidemiology, outbreak investigation, surveillance, isolation precaution practices, personal protective equipment (PPE), environmental contamination and disinfection, drug and supply shortages, antimicrobial stewardship, healthcare personnel (HCP) occupational safety, and return to work policies. Each section highlights three critical healthcare epidemiology research questions with detailed description provided in supplemental materials. This research agenda calls for translational studies from laboratory-based basic science research to well-designed, large-scale studies and health outcomes research. Research gaps and challenges related to nursing homes and social disparities are included. Collaborations across various disciplines, expertise and across diverse geographic locations will be critical.
Toddler milk (i.e. a nutrient-fortified milk-based drink marketed for children 12–36 months old) is increasingly being marketed in the USA despite not being recommended for young children. There is evidence of targeted toddler milk marketing to Latinos in the USA. This study aimed to explore toddler milk perceptions and behaviours among Latino and non-Latino parents.
An online survey assessed toddler milk perceptions, behaviours and interpretations of nutrition-related claims. Multivariable logistic and linear regression explored socio-demographic correlates of parent reported past purchases and perceived healthfulness.
National convenience sample of 1078 US parents of children aged 2–12 years (48 % Latino).
About half of parents (51 %) had previously purchased toddler milk and few (11 %) perceived toddler milk as unhealthy. Latino parents were more likely to have purchased toddler milk than non-Latino parents (P < 0·001), but there were no differences in perceived product healthfulness (P = 0·47). Compared to parents born in the USA, parents living in the USA 10 years or less were more likely to have purchased toddler milk (P < 0·001) and perceive toddler milk as healthier (P = 0·002). Open-ended interpretations of claims were primarily positive, suggesting ‘health halo’ effects.
Common misperceptions about toddler milk healthfulness suggest stronger labelling regulations are needed. Greater reported purchases by Latino parents and recent immigrants warrant further investigation.
The first demonstration of laser action in ruby was made in 1960 by T. H. Maiman of Hughes Research Laboratories, USA. Many laboratories worldwide began the search for lasers using different materials, operating at different wavelengths. In the UK, academia, industry and the central laboratories took up the challenge from the earliest days to develop these systems for a broad range of applications. This historical review looks at the contribution the UK has made to the advancement of the technology, the development of systems and components and their exploitation over the last 60 years.
The Clinical and Translational Science Awards (CTSA) Consortium, a network of academic health care institutions with CTSA hubs, is charged with improving the national clinical and translational research enterprise. The CTSA Consortium and the NIH National Center for Advancing Translational Sciences implemented the Common Metrics Initiative comprised of standardized metrics and a shared performance improvement framework. This article summarizes hubs’ perspectives on its value during the initial implementation.
The value was assessed across 58 hubs. Survey items assessed change in perceived ability to manage performance and advance clinical and translational science. Semi-structured interviews elicited hubs’ perspectives on meaningfulness and value-added of the Common Metrics Initiative and hubs’ recommendations.
Hubs considered their abilities to manage performance to have improved, but there was no change in perceived ability to advance clinical and translational science. The initiative added value by providing a formal structured process, enabling strategic conversations, facilitating improvements in processes, providing an external impetus for improvement, and providing justification for funds invested. Hubs were concerned about the usefulness of the metrics chosen and whether the value-added was sufficient relative to the effort required. Hubs recommended useful benchmarking, disseminating best practices and promoting peer-to-peer learning, and expanding the use of data to inform the initiative.
Implementing Common Metrics and a performance improvement framework yielded concrete short-term benefits, but concerns about usefulness remained, particularly considering the effort required. The Common Metrics Initiative should focus on facilitating cross-hub collaboration around metrics that address high-priority impact areas for individual hubs and the Consortium.
Congenital heart disease (CHD) is the most common birth defect for infants born in the United States, with approximately 36,000 affected infants born annually. While mortality rates for children with CHD have significantly declined, there is a growing population of individuals with CHD living into adulthood prompting the need to optimise long-term development and quality of life. For infants with CHD, pre- and post-surgery, there is an increased risk of developmental challenges and feeding difficulties. Feeding challenges carry profound implications for the quality of life for individuals with CHD and their families as they impact short- and long-term neurodevelopment related to growth and nutrition, sensory regulation, and social-emotional bonding with parents and other caregivers. Oral feeding challenges in children with CHD are often the result of medical complications, delayed transition to oral feeding, reduced stamina, oral feeding refusal, developmental delay, and consequences of the overwhelming intensive care unit (ICU) environment. This article aims to characterise the disruptions in feeding development for infants with CHD and describe neurodevelopmental factors that may contribute to short- and long-term oral feeding difficulties.
Impairment in reciprocal social behavior (RSB), an essential component of early social competence, clinically defines autism spectrum disorder (ASD). However, the behavioral and genetic architecture of RSB in toddlerhood, when ASD first emerges, has not been fully characterized. We analyzed data from a quantitative video-referenced rating of RSB (vrRSB) in two toddler samples: a community-based volunteer research registry (n = 1,563) and an ethnically diverse, longitudinal twin sample ascertained from two state birth registries (n = 714). Variation in RSB was continuously distributed, temporally stable, significantly associated with ASD risk at age 18 months, and only modestly explained by sociodemographic and medical factors (r2 = 9.4%). Five latent RSB factors were identified and corresponded to aspects of social communication or restricted repetitive behaviors, the two core ASD symptom domains. Quantitative genetic analyses indicated substantial heritability for all factors at age 24 months (h2 ≥ .61). Genetic influences strongly overlapped across all factors, with a social motivation factor showing evidence of newly-emerging genetic influences between the ages of 18 and 24 months. RSB constitutes a heritable, trait-like competency whose factorial and genetic structure is generalized across diverse populations, demonstrating its role as an early, enduring dimension of inherited variation in human social behavior. Substantially overlapping RSB domains, measurable when core ASD features arise and consolidate, may serve as markers of specific pathways to autism and anchors to inform determinants of autism's heterogeneity.
The Common Metrics Initiative aims to develop and field metrics to improve research processes within the national Clinical and Translational Science Award (CTSA) Consortium. A Median Accrual Ratio (MAR) common metric was developed to assess the results of efforts to increase subject accrual into a set of clinical trials within the expected time period. A pilot test of the MAR was undertaken at Tufts Clinical and Translational Science Institute (CTSI) with eight CTSA Consortium hubs. Post-pilot interviews were conducted with 9 CTSA Principal Investigators (PIs) and 23 pilot team members. Over three-quarters (78%) of respondents reported that the MAR could be useful for performance improvement, but also described limitations or concerns. The most commonly cited barrier to MAR use for performance improvement was difficulty in interpreting the single value that is produced. Most respondents were interested in using the MAR to assess recruitment at an individual trial level. Majority of respondents (63%) had mixed opinions about aggregating metric results across the CTSA Consortium for comparison or benchmarking. Collecting data about additional contextual factors, and comparing accrual between subgroups, were cited as potentially helping address concerns about aggregation. Significant challenges remain in ensuring that the MAR can be sufficiently useful for collaborative process improvement. We offer recommendations to potentially improve metric usefulness.
Lack of participation in clinical trials (CTs) is a major barrier for the evaluation of new pharmaceuticals and devices. Here we report the results of the analysis of a dataset from ResearchMatch, an online clinical registry, using supervised machine learning approaches and a deep learning approach to discover characteristics of individuals more likely to show an interest in participating in CTs.
We trained six supervised machine learning classifiers (Logistic Regression (LR), Decision Tree (DT), Gaussian Naïve Bayes (GNB), K-Nearest Neighbor Classifier (KNC), Adaboost Classifier (ABC) and a Random Forest Classifier (RFC)), as well as a deep learning method, Convolutional Neural Network (CNN), using a dataset of 841,377 instances and 20 features, including demographic data, geographic constraints, medical conditions and ResearchMatch visit history. Our outcome variable consisted of responses showing specific participant interest when presented with specific clinical trial opportunity invitations (‘yes’ or ‘no’). Furthermore, we created four subsets from this dataset based on top self-reported medical conditions and gender, which were separately analysed.
The deep learning model outperformed the machine learning classifiers, achieving an area under the curve (AUC) of 0.8105.
The results show sufficient evidence that there are meaningful correlations amongst predictor variables and outcome variable in the datasets analysed using the supervised machine learning classifiers. These approaches show promise in identifying individuals who may be more likely to participate when offered an opportunity for a clinical trial.
Irrespective of our life paths, the ability to initiate and sustain effective interactions with others is a key determinant of success and fulfillment. Conflicts occur on a regular basis, hence a level of personal insight is vital. As physicians and healthcare professionals, we can help our patients by better understanding the components of emotional intelligence (EQ) and suggesting how they can incorporate the best attitudes and behaviors into their lives. We can be far more effective in this mission if we model the desired traits in our professional and personal actions. This standard is a challenge, given the often-demanding nature of our clinical responsibilities and the need to achieve balance with family and friends. Yet, it is vital if we are to maintain fulfillment throughout our lives.
The Clinical and Translational Science Awards (CTSA) Consortium, about 60 National Institutes of Health (NIH)-supported CTSA hubs at academic health care institutions nationwide, is charged with improving the clinical and translational research enterprise. Together with the NIH National Center for Advancing Translational Sciences (NCATS), the Consortium implemented Common Metrics and a shared performance improvement framework.
Initial implementation across hubs was assessed using quantitative and qualitative methods over a 19-month period. The primary outcome was implementation of three Common Metrics and the performance improvement framework. Challenges and facilitators were elicited.
Among 59 hubs with data, all began implementing Common Metrics, but about one-third had completed all activities for three metrics within the study period. The vast majority of hubs computed metric results and undertook activities to understand performance. Differences in completion appeared in developing and carrying out performance improvement plans. Seven key factors affected progress: hub size and resources, hub prior experience with performance management, alignment of local context with needs of the Common Metrics implementation, hub authority in the local institutional structure, hub engagement (including CTSA Principal Investigator involvement), stakeholder engagement, and attending training and coaching.
Implementing Common Metrics and performance improvement in a large network of research-focused organizations proved feasible but required substantial time and resources. Considerable heterogeneity across hubs in data systems, existing processes and personnel, organizational structures, and local priorities of home institutions created disparate experiences across hubs. Future metric-based performance management initiatives across heterogeneous local contexts should anticipate and account for these types of differences.
Variations of circadian activity profiles and sleep patterns are altered in various neurospsychiatric disorders. In this context, changes in heart rate (HR), -variability (HRV) and related parameters have been reported, too. However, data situation is presently heterogeneous and nonstandard-ized. As long-term evaluation may provide more valuable information, applicability and data us-ability of a new data acquisition system was tested in patients with major depression.
The course of a depressive episode in inpatients was assessed by standard psychometric in-struments. ECG and motor activity were recorded continuously with a new wearable sensor sys-tem (EP04106001.3) consisting of a textile with three electrodes for 1-lead ECG recordings, and an electronic module (2D-accelerometer, microcontroller, memory, rechargeable batteries, Bluetooth unit) to be attached to the waistband of standard underpants.
ECG signal quality highly depended on physical activity, but sufficient data quality was obtained during sleep. From the accelerometer signal, time in bed and movement time were identifiable. Preliminary data of patients (n=15) versus healthy controls (n=9) showed a reduction of HRV in several time domain parameters, high frequency (HF) power, and daytime activity (24h/day, mean 8 weeks).
This first pilot study demonstrates alterations of physiological parameters potentially relevant for depression, with continuous monitoring of inpatient treatment period. Facing long-term monitoring the device proved to be robust and safe and might provide a psychobiological profile of the clini-cal course of depression, useful for evaluation of disorder and therapy.
This work is part of the European research project ‘MyHeart’ (6th framework, IST 507816).
The updated common rule, for human subjects research, requires that consents “begin with a ‘concise and focused’ presentation of the key information that will most likely help someone make a decision about whether to participate in a study” (Menikoff, Kaneshiro, Pritchard. The New England Journal of Medicine. 2017; 376(7): 613–615.). We utilized a community-engaged technology development approach to inform feature options within the REDCap software platform centered around collection and storage of electronic consent (eConsent) to address issues of transparency, clinical trial efficiency, and regulatory compliance for informed consent (Harris, et al. Journal of Biomedical Informatics 2009; 42(2): 377–381.). eConsent may also improve recruitment and retention in clinical research studies by addressing: (1) barriers for accessing rural populations by facilitating remote consent and (2) cultural and literacy barriers by including optional explanatory material (e.g., defining terms by hovering over them with the cursor) or the choice of displaying different videos/images based on participant’s race, ethnicity, or educational level (Phillippi, et al. Journal of Obstetric, Gynecologic, & Neonatal Nursing. 2018; 47(4): 529–534.).
We developed and pilot tested our eConsent framework to provide a personalized consent experience whereby users are guided through a consent document that utilizes avatars, contextual glossary information supplements, and videos, to facilitate communication of information.
The eConsent framework includes a portfolio of eight features, reviewed by community stakeholders, and tested at two academic medical centers.
Early adoption and utilization of this eConsent framework have demonstrated acceptability. Next steps will emphasize testing efficacy of features to improve participant engagement with the consent process.
Cognitive impairment associated with lifetime major depressive disorder (MDD) is well-supported by meta-analytic studies, but population-based estimates remain scarce. Previous UK Biobank studies have only shown limited evidence of cognitive differences related to probable MDD. Using updated cognitive and clinical assessments in UK Biobank, this study investigated population-level differences in cognitive functioning associated with lifetime MDD.
Associations between lifetime MDD and cognition (performance on six tasks and general cognitive functioning [g-factor]) were investigated in UK Biobank (N-range 7,457–14,836, age 45–81 years, 52% female), adjusting for demographics, education, and lifestyle. Lifetime MDD classifications were based on the Composite International Diagnostic Interview. Within the lifetime MDD group, we additionally investigated relationships between cognition and (a) recurrence, (b) current symptoms, (c) severity of psychosocial impairment (while symptomatic), and (d) concurrent psychotropic medication use.
Lifetime MDD was robustly associated with a lower g-factor (β = −0.10, PFDR = 4.7 × 10−5), with impairments in attention, processing speed, and executive functioning (β ≥ 0.06). Clinical characteristics revealed differential profiles of cognitive impairment among case individuals; those who reported severe psychosocial impairment and use of psychotropic medication performed worse on cognitive tests. Severe psychosocial impairment and reasoning showed the strongest association (β = −0.18, PFDR = 7.5 × 10−5).
Findings describe small but robust associations between lifetime MDD and lower cognitive performance within a population-based sample. Overall effects were of modest effect size, suggesting limited clinical relevance. However, deficits within specific cognitive domains were more pronounced in relation to clinical characteristics, particularly severe psychosocial impairment.
Shared patient–clinician decision-making is central to choosing between medical treatments. Decision support tools can have an important role to play in these decisions. We developed a decision support tool for deciding between nonsurgical treatment and surgical total knee replacement for patients with severe knee osteoarthritis. The tool aims to provide likely outcomes of alternative treatments based on predictive models using patient-specific characteristics. To make those models relevant to patients with knee osteoarthritis and their clinicians, we involved patients, family members, patient advocates, clinicians, and researchers as stakeholders in creating the models.
Stakeholders were recruited through local arthritis research, advocacy, and clinical organizations. After being provided with brief methodological education sessions, stakeholder views were solicited through quarterly patient or clinician stakeholder panel meetings and incorporated into all aspects of the project.
Participating in each aspect of the research from determining the outcomes of interest to providing input on the design of the user interface displaying outcome predications, 86% (12/14) of stakeholders remained engaged throughout the project. Stakeholder engagement ensured that the prediction models that form the basis of the Knee Osteoarthritis Mathematical Equipoise Tool and its user interface were relevant for patient–clinician shared decision-making.
Methodological research has the opportunity to benefit from stakeholder engagement by ensuring that the perspectives of those most impacted by the results are involved in study design and conduct. While additional planning and investments in maintaining stakeholder knowledge and trust may be needed, they are offset by the valuable insights gained.
To determine sociodemographic factors associated with occupational, recreational and firearm-related noise exposure.
This nationally representative, multistage, stratified, cluster cross-sectional study sampled eligible National Health and Nutrition Examination Survey participants aged 20–69 years (n = 4675) about exposure to occupational and recreational noise and recurrent firearm usage, using a weighted multivariate logistic regression analysis.
Thirty-four per cent of participants had exposure to occupational noise and 12 per cent to recreational noise, and 13 per cent repeatedly used firearms. Males were more likely than females to have exposure to all three noise types (adjusted odds ratio range = 2.63–14.09). Hispanics and Asians were less likely to have exposure to the three noise types than Whites. Blacks were less likely than Whites to have occupational and recurrent firearm noise exposure. Those with insurance were 26 per cent less likely to have exposure to occupational noise than those without insurance (adjusted odds ratio = 0.74, 95 per cent confidence interval = 0.60–0.93).
Whites, males and uninsured people are more likely to have exposure to potentially hazardous loud noise.
Scientific quality and feasibility are part of ethics review by Institutional Review Boards (IRBs). Scientific Review Committees (SRCs) were proposed to facilitate this assessment by the Clinical and Translational Science Award (CTSA) SRC Consensus Group. This study assessed SRC feasibility and impact at CTSA-affiliated academic health centers (AHCs).
SRC implementation at 10 AHCs was assessed pre/post-intervention using quantitative and qualitative methods. Pre-intervention, four AHCs had no SRC, and six had at least one SRC needing modifications to better align with Consensus Group recommendations.
Facilitators of successful SRC implementation included broad-based communication, an external motivator, senior-level support, and committed SRC reviewers. Barriers included limited resources and staffing, variable local mandates, limited SRC authority, lack of anticipated benefit, and operational challenges. Research protocol quality did not differ significantly between study periods, but respondents suggested positive effects. During intervention, median total review duration did not lengthen for the 40% of protocols approved within 3 weeks. For the 60% under review after 3 weeks, review was lengthened primarily due to longer IRB review for SRC-reviewed protocols. Site interviews recommended designing locally effective SRC processes, building buy-in by communication or by mandate, allowing time for planning and sharing best practices, and connecting SRC and IRB procedures.
The CTSA SRC Consensus Group recommendations appear feasible. Although not conclusive in this relatively short initial implementation, sites perceived positive impact by SRCs on study quality. Optimal benefit will require local or federal mandate for implementation, adapting processes to local contexts, and employing SRC stipulations.
Epidemiological studies indicate that individuals with one type of mental disorder have an increased risk of subsequently developing other types of mental disorders. This study aimed to undertake a comprehensive analysis of pair-wise lifetime comorbidity across a range of common mental disorders based on a diverse range of population-based surveys.
The WHO World Mental Health (WMH) surveys assessed 145 990 adult respondents from 27 countries. Based on retrospectively-reported age-of-onset for 24 DSM-IV mental disorders, associations were examined between all 548 logically possible temporally-ordered disorder pairs. Overall and time-dependent hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using Cox proportional hazards models. Absolute risks were estimated using the product-limit method. Estimates were generated separately for men and women.
Each prior lifetime mental disorder was associated with an increased risk of subsequent first onset of each other disorder. The median HR was 12.1 (mean = 14.4; range 5.2–110.8, interquartile range = 6.0–19.4). The HRs were most prominent between closely-related mental disorder types and in the first 1–2 years after the onset of the prior disorder. Although HRs declined with time since prior disorder, significantly elevated risk of subsequent comorbidity persisted for at least 15 years. Appreciable absolute risks of secondary disorders were found over time for many pairs.
Survey data from a range of sites confirms that comorbidity between mental disorders is common. Understanding the risks of temporally secondary disorders may help design practical programs for primary prevention of secondary disorders.
This paper summarizes a multi-state, multi-year study assessing the potential for local agriculture in northern New England. While largely rural, this region's agricultural sector differs greatly from the rest of the United States, and demand for locally produced food has been increasing. To assess this unique economic landscape, researchers and Cooperative Extension at the Universities of Maine, New Hampshire, and Vermont investigated four key areas: (1) local food capacities, (2) constraints to agricultural expansion, (3) consumer preferences for local and organic produce, and (4) the role of intermediaries as alternative local food outlets. The project included input from local farmers, Extension members, restaurants, and the general public. We present the four research areas in a sequential, overlapping fashion. The timing of our research was such that each step in the process informed the next and can be used as a template for assessing a region's potential for local agricultural production.