A systematic review of interventions in primary care to improve health literacy for chronic disease behavioral risk factors

Background: To evaluate the effectiveness of interventions used in primary care to improve health literacy for change in smoking, nutrition, alcohol, physical activity and weight (SNAPW). Methods: A systematic review of intervention studies that included outcomes for health literacy and SNAPW behavioral risk behaviors implemented in primary care settings. We searched the Cochrane Library, Johanna Briggs Institute, Medline, Embase, CINAHL, Psychinfo, Web of Science, Scopus, APAIS, Australasian Medical Index, Google Scholar, Community of Science and four targeted journals (Patient Education and Counseling, Health Education and Behaviour, American Journal of Preventive Medicine and Preventive Medicine). Study inclusion criteria: Adults over 18 years; undertaken in a primary care setting within an Organisation for Economic Co-operation and Development (OECD) country; interventions with at least one measure of health literacy and promoting positive change in smoking, nutrition, alcohol, physical activity and/or weight; measure at least one outcome associated with health literacy and report a SNAPW outcome; and experimental and quasi-experimental studies, cohort, observational and controlled and non-controlled before and after studies. Papers were assessed and screened by two researchers (JT, AW) and uncertain or excluded studies were reviewed by a third researcher (MH). Data were extracted from the included studies by two researchers (JT, AW). Effectiveness studies were quality assessed. A typology of interventions was thematically derived from the studies by grouping the SNAPW interventions into six broad categories: individual motivational interviewing and counseling; group education; multiple interventions (combination of interventions); written materials; telephone coaching or counseling; and computer or web based interventions. Interventions were classified by intensity of contact with the subjects (High ≥ 8 points of contact/hours; Moderate \u3e3 and \u3c8; Low ≤ 3 points of contact hours) and setting (primary health, community or other). Studies were analyzed by intervention category and whether significant positive changes in SNAPW and health literacy outcomes were reported. Results: 52 studies were included. Many different intervention types and settings were associated with change in health literacy (73% of all studies) and change in SNAPW (75% of studies). More low intensity interventions reported significant positive outcomes for SNAPW (43% of studies) compared with high intensity interventions (33% of studies). More interventions in primary health care than the community were effective in supporting smoking cessation whereas the reverse was true for diet and physical activity interventions. Conclusion: Group and individual interventions of varying intensity in primary health care and community settings are useful in supporting sustained change in health literacy for change in behavioral risk factors. Certain aspects of risk behavior may be better handled in clinical settings while others more effectively in the community. Our findings have implications for the design of programs

A new approach to generating research-quality data through citizen science: The USA National Phenology Monitoring System

Phenology is one of the most sensitive biological responses to climate change, and recent changes in phenology have the potential to shake up ecosystems. In some cases, it appears they already are. Thus, for ecological reasons it is critical that we improve our understanding of species’ phenologies and how these phenologies are responding to recent, rapid climate change. Phenological events like flowering and bird migrations are easy to observe, culturally important, and, at a fundamental level, naturally inspire human curiosity— thus providing an excellent opportunity to engage citizen scientists. The USA National Phenology Network has recently initiated a national effort to encourage people at different levels of expertise—from backyard naturalists to professional scientists—to observe phenological events and contribute to a national database that will be used to greatly improve our understanding of spatio-temporal variation in phenology and associated phenological responses to climate change.

Traditional phenological observation protocols identify specific dates at which individual phenological events are observed. The scientific usefulness of long-term phenological observations could be improved with a more carefully structured protocol. At the USA-NPN we have developed a new approach that directs observers to record each day that they observe an individual plant, and to assess and report the state of specific life stages (or phenophases) as occurring or not occurring on that plant for each observation date. Evaluation is phrased in terms of simple, easy-to-understand, questions (e.g. “Do you see open flowers?”), which makes it very appropriate for a citizen science audience. From this method, a rich dataset of phenological metrics can be extracted, including the duration of a phenophase (e.g. open flowers), the beginning and end points of a phenophase (e.g. traditional phenological events such as first flower and last flower), multiple distinct occurrences of phenophases within a single growing season (e.g multiple flowering events, common in drought-prone regions), as well as quantification of sampling frequency and observational uncertainties. These features greatly enhance the utility of the resulting data for statistical analyses addressing questions such as how phenological events vary in time and space, and in response to global change. This new protocol is an important step forward, and its widespread adoption will increase the scientific value of data collected by citizen scientists.
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Statistical Modeling of the Default Mode Brain Network Reveals a Segregated Highway Structure

We investigate the functional organization of the Default Mode Network (DMN) - an important subnetwork within the brain associated with a wide range of higher-order cognitive functions. While past work has shown the whole-brain network of functional connectivity follows small-world organizational principles, subnetwork structure is less well understood. Current statistical tools, however, are not suited to quantifying the operating characteristics of functional networks as they often require threshold censoring of information and do not allow for inferential testing of the role that local processes play in determining network structure. Here, we develop the correlation Generalized Exponential Random Graph Model (cGERGM) - a statistical network model that uses local processes to capture the emergent structural properties of correlation networks without loss of information. Examining the DMN with the cGERGM, we show that, rather than demonstrating small-world properties, the DMN appears to be organized according to principles of a segregated highway - suggesting it is optimized for function-specific coordination between brain regions as opposed to information integration across the DMN. We further validate our findings through assessing the power and accuracy of the cGERGM on a testbed of simulated networks representing various commonly observed brain architectures

Statistical Modeling of the Default Mode Brain Network Reveals a Segregated Highway Structure

We investigate the functional organization of the Default Mode Network (DMN) – an important subnetwork within the brain associated with a wide range of higher-order cognitive functions. While past work has shown the whole-brain network of functional connectivity follows small-world organizational principles, subnetwork structure is less well understood. Current statistical tools, however, are not suited to quantifying the operating characteristics of functional networks as they often require threshold censoring of information and do not allow for inferential testing of the role that local processes play in determining network structure. Here, we develop the correlation Generalized Exponential Random Graph Model (cGERGM) – a statistical network model that uses local processes to capture the emergent structural properties of correlation networks without loss of information. Examining the DMN with the cGERGM, we show that, rather than demonstrating small-world properties, the DMN appears to be organized according to principles of a segregated highway – suggesting it is optimized for function-specific coordination between brain regions as opposed to information integration across the DMN. We further validate our findings through assessing the power and accuracy of the cGERGM on a testbed of simulated networks representing various commonly observed brain architectures

Linking Microscopic Spatial Patterns of Tissue Destruction in Emphysema to Macroscopic Decline in Stiffness Using a 3D Computational Model

Pulmonary emphysema is a connective tissue disease characterized by the progressive destruction of alveolar walls leading to airspace enlargement and decreased elastic recoil of the lung. However, the relationship between microscopic tissue structure and decline in stiffness of the lung is not well understood. In this study, we developed a 3D computational model of lung tissue in which a pre-strained cuboidal block of tissue was represented by a tessellation of space filling polyhedra, with each polyhedral unit-cell representing an alveolus. Destruction of alveolar walls was mimicked by eliminating faces that separate two polyhedral either randomly or in a spatially correlated manner, in which the highest force bearing walls were removed at each step. Simulations were carried out to establish a link between the geometries that emerged and the rate of decline in bulk modulus of the tissue block. The spatially correlated process set up by the force-based destruction lead to a significantly faster rate of decline in bulk modulus accompanied by highly heterogeneous structures than the random destruction pattern. Using the Karhunen-Loève transformation, an estimator of the change in bulk modulus from the first four moments of airspace cell volumes was setup. Simulations were then obtained for tissue destruction with different idealized alveolar geometry, levels of pre-strain, linear and nonlinear elasticity assumptions for alveolar walls and also mixed destruction patterns where both random and force-based destruction occurs simultaneously. In all these cases, the change in bulk modulus from cell volumes was accurately estimated. We conclude that microscopic structural changes in emphysema and the associated decline in tissue stiffness are linked by the spatial pattern of the destruction process

Soft-bottom fishes and spatial protection: findings from a temperate marine protected area

Numerous studies over the last decades have focused on marine protected areas (MPAs) and their effects on fish communities. However, there is a knowledge gap regarding how species that live associated with soft-substrates (e.g., sand, mud) respond to spatial protection. We analyzed abundance, biomass and total lengths of the soft-bottom fishes in a multiple-use MPA in the north-eastern Atlantic, the Luiz Saldanha Marine Park (Portugal), during and after the implementation of its management plan. Data were collected by experimental fishing in areas with three different levels of protection, during the implementation period and for three years after full implementation of the MPA. Univariate analysis detected significant biomass increases between the two periods. Fish assemblages were mainly structured by depth and substrate, followed by protection level. Community composition analyses revealed significant differences between protection levels and between the two periods. Species exhibited a broad variation in their response to protection, and we hypothesize that factors such as species habitat preferences, body size and late maturity might be underlying determinants. Overall, this study provides some evidence of protection effectiveness in soft-bottom fish communities, supported by the significant increase in biomass in the protected areas and the positive trends of some species.project LIFE-BIOMARES [LIFE06 NAT/P/000192]; project BUFFER (ERA-Net BiodivERsA); company SECIL-Companhia Geral de Cal e Cimento S.A.; FCT-Foundation for Science and Technology [CCMAR/Multi/04326/2013, SFRH/BD/80771/2011]; Foundation for Science and Technology [SFRH/BD/80771/2011]; 2012 Sesimbra Scientific Priz

Prioritising cat-owner behaviours for a campaign to reduce wildlife depredation

Behavior prioritisation is underutilised but critical to the success of conservation campaigns. It provides an understanding of the target audience’s values to transcend conflict and informs the design of achievable and effective advocacy campaigns. Depredation by domestic cats may depress wildlife populations, leading to conflict between cat owners and conservationists. We surveyed veterinarians and cat owners at veterinary clinics to prioritise a list of nine cat-management behaviours. Cat-owner behaviours were ranked by their (i) likelihood of implementation and (ii) current adoption rate by cat owners, (iii) perceived effectiveness at reducing predation on wildlife, and (iv) veterinarians’ opinions about their impact on cat welfare. Bringing cats in at night, from before dusk until after dawn, was revealed to be the behaviour most suited to a campaign to reduce cats’ hunting. Behaviours ranked as more effective for conservation (e.g., 24-hour cat confinement) were unlikely to be adopted by cat owners or not supported by veterinarians, whose expert and normative support may be critical to a campaign. Although more conservation-effective behaviours received a lower priority, we discuss the repeated use of behaviour prioritisation to achieve incremental reductions in cat depredation by engaging with cat owners

Genetic association study of QT interval highlights role for calcium signaling pathways in myocardial repolarization.

The QT interval, an electrocardiographic measure reflecting myocardial repolarization, is a heritable trait. QT prolongation is a risk factor for ventricular arrhythmias and sudden cardiac death (SCD) and could indicate the presence of the potentially lethal mendelian long-QT syndrome (LQTS). Using a genome-wide association and replication study in up to 100,000 individuals, we identified 35 common variant loci associated with QT interval that collectively explain ∼8-10% of QT-interval variation and highlight the importance of calcium regulation in myocardial repolarization. Rare variant analysis of 6 new QT interval-associated loci in 298 unrelated probands with LQTS identified coding variants not found in controls but of uncertain causality and therefore requiring validation. Several newly identified loci encode proteins that physically interact with other recognized repolarization proteins. Our integration of common variant association, expression and orthogonal protein-protein interaction screens provides new insights into cardiac electrophysiology and identifies new candidate genes for ventricular arrhythmias, LQTS and SCD

Research Directions in the Clinical Implementation of Pharmacogenomics: An Overview of US Programs and Projects

Response to a drug often differs widely among individual patients. This variability is frequently observed not only with respect to effective responses but also with adverse drug reactions. Matching patients to the drugs that are most likely to be effective and least likely to cause harm is the goal of effective therapeutics. Pharmacogenomics (PGx) holds the promise of precision medicine through elucidating the genetic determinants responsible for pharmacological outcomes and using them to guide drug selection and dosing. Here we survey the US landscape of research programs in PGx implementation, review current advances and clinical applications of PGx, summarize the obstacles that have hindered PGx implementation, and identify the critical knowledge gaps and possible studies needed to help to address them

Association of Mild Anemia with Cognitive, Functional, Mood and Quality of Life Outcomes in the Elderly: The “Health and Anemia” Study

BACKGROUND: In the elderly persons, hemoglobin concentrations slightly below the lower limit of normal are common, but scant evidence is available on their relationship with significant health indicators. The objective of the present study was to cross-sectionally investigate the association of mild grade anemia with cognitive, functional, mood, and quality of life (QoL) variables in community-dwelling elderly persons. METHODS: Among the 4,068 eligible individuals aged 65-84 years, all persons with mild anemia (n = 170) and a randomly selected sample of non-anemic controls (n = 547) were included in the study. Anemia was defined according to World Health Organization (WHO) criteria and mild grade anemia was defined as a hemoglobin concentration between 10.0 and 11.9 g/dL in women and between 10.0 and 12.9 g/dL in men. Cognition and functional status were assessed using measures of selective attention, episodic memory, cognitive flexibility and instrumental and basic activities of daily living. Mood and QoL were evaluated by means of the Geriatric Depression Scale-10, the Short-Form health survey (SF-12), and the Functional Assessment of Cancer Therapy-Anemia. RESULTS: In univariate analyses, mild anemic elderly persons had significantly worse results on almost all cognitive, functional, mood, and QoL measures. In multivariable logistic regressions, after adjustment for a large number of demographic and clinical confounders, mild anemia remained significantly associated with measures of selective attention and disease-specific QoL (all fully adjusted p<.046). When the lower limit of normal hemoglobin concentration according to WHO criteria was raised to define anemia (+0.2 g/dL), differences between mild anemic and non anemic elderly persons tended to increase on almost every variable. CONCLUSIONS: Cross-sectionally, mild grade anemia was independently associated with worse selective attention performance and disease-specific QoL ratings