106 research outputs found

    Healthcare providers' views on the acceptability of financial incentives for breastfeeding:a qualitative study

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    BACKGROUND: Despite a gradual increase in breastfeeding rates, overall in the UK there are wide variations, with a trend towards breastfeeding rates at 6–8 weeks remaining below 40% in less affluent areas. While financial incentives have been used with varying success to encourage positive health related behaviour change, there is little research on their use in encouraging breastfeeding. In this paper, we report on healthcare providers’ views around whether using financial incentives in areas with low breastfeeding rates would be acceptable in principle. This research was part of a larger project looking at the development and feasibility testing of a financial incentive scheme for breastfeeding in preparation for a cluster randomised controlled trial. METHODS: Fifty–three healthcare providers were interviewed about their views on financial incentives for breastfeeding. Participants were purposively sampled to include a wide range of experience and roles associated with supporting mothers with infant feeding. Semi-structured individual and group interviews were conducted. Data were analysed thematically drawing on the principles of Framework Analysis. RESULTS: The key theme emerging from healthcare providers’ views on the acceptability of financial incentives for breastfeeding was their possible impact on ‘facilitating or impeding relationships’. Within this theme several additional aspects were discussed: the mother’s relationship with her healthcare provider and services, with her baby and her family, and with the wider community. In addition, a key priority for healthcare providers was that an incentive scheme should not impact negatively on their professional integrity and responsibility towards women. CONCLUSION: Healthcare providers believe that financial incentives could have both positive and negative impacts on a mother’s relationship with her family, baby and healthcare provider. When designing a financial incentive scheme we must take care to minimise the potential negative impacts that have been highlighted, while at the same time recognising the potential positive impacts for women in areas where breastfeeding rates are low

    Academic Performance and Behavioral Patterns

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    Identifying the factors that influence academic performance is an essential part of educational research. Previous studies have documented the importance of personality traits, class attendance, and social network structure. Because most of these analyses were based on a single behavioral aspect and/or small sample sizes, there is currently no quantification of the interplay of these factors. Here, we study the academic performance among a cohort of 538 undergraduate students forming a single, densely connected social network. Our work is based on data collected using smartphones, which the students used as their primary phones for two years. The availability of multi-channel data from a single population allows us to directly compare the explanatory power of individual and social characteristics. We find that the most informative indicators of performance are based on social ties and that network indicators result in better model performance than individual characteristics (including both personality and class attendance). We confirm earlier findings that class attendance is the most important predictor among individual characteristics. Finally, our results suggest the presence of strong homophily and/or peer effects among university students

    TRY plant trait database - enhanced coverage and open access

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    Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

    Evaluation of Directed Graph-Mapping in Complex Atrial Tachycardias

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    Objectives: Directed graph-mapping (DGM) is a novel operator-independent automatic tool that can be applied to the identification of the atrial tachycardia (AT) mechanism. In the present study, for the first time, DGM was applied in complex AT cases, and diagnostic accuracy was evaluated. Background: Catheter ablation of ATs still represents a challenge, as the identification of the correct mechanism can be difficult. New algorithms for high-density activation mapping (HDAM) render an easier acquisition of more detailed maps; however, understanding of the mechanism and, thus, identification of the ablation targets, especially in complex cases, remains strongly operator-dependent. Methods: HDAMs acquired with the latest algorithm (COHERENT version 7, Biosense Webster, Irvine, California) were interpreted offline by 4 expert electrophysiologists, and the acquired electrode recordings with corresponding local activation times (LATs) were analyzed by DGM (also offline). Entrainment maneuvers (EM) were performed to understand the correct mechanism, which was then confirmed by successful ablation (13 cases were centrifugal, 10 cases were localized re-entry, 22 cases were macro–re-entry, and 6 were double-loops). In total, 51 ATs were retrospectively analyzed. We compared the diagnoses made by DGM were compared with those of the experts and with additional EM results. Results: In total, 51 ATs were retrospectively analyzed. Experts diagnosed the correct AT mechanism and location in 33 cases versus DGM in 38 cases. Diagnostic accuracy varied according to different AT mechanisms. The 13 centrifugal activation patterns were always correctly identified by both methods; 2 of 10 localized reentries were identified by the experts, whereas DGM diagnosed 7 of 10. For the macro–re-entries, 12 of 22 were correctly identified using HDAM versus 13 of 22 for DGM. Finally, 6 of 6 double-loops were correctly identified by the experts, versus 5 of 6 for DGM. Conclusions: Even in complex cases, DGM provides an automatic, fast, and operator-independent tool to identify the AT mechanism and location and could be a valuable addition to current mapping technologies. © 2021 The Authors.Dr. Lorenzo is an employee of Biosense Webster. Dr. Goedgebeur is funded with a research grant of the Research Foundation Flanders/Fonds voor Wetenschappelijk Onderzoek (FWO). Dr. Strisciuglio is supported by a research grant from the Cardiopath PhD program. Dr. el Haddad is a consultant for Biosense Webster. Dr. Duytschaever is a consultant for Biosense Webster. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose

    Developing consensus-based policy solutions for medicines adherence for Europe: a Delphi study

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    <p>Abstract</p> <p>Background</p> <p>Non-adherence to prescribed medication is a pervasive problem that can incur serious effects on patients’ health outcomes and well-being, and the availability of resources in healthcare systems. This study aimed to develop practical consensus-based policy solutions to address medicines non-adherence for Europe.</p> <p>Methods</p> <p>A four-round Delphi study was conducted. The Delphi Expert Panel comprised 50 participants from 14 countries and was representative of: patient/carers organisations; healthcare providers and professionals; commissioners and policy makers; academics; and industry representatives. Participants engaged in the study remotely, anonymously and electronically. Participants were invited to respond to open questions about the causes, consequences and solutions to medicines non-adherence. Subsequent rounds refined responses, and sought ratings of the relative importance, and operational and political feasibility of each potential solution to medicines non-adherence. Feedback of individual and group responses was provided to participants after each round. Members of the Delphi Expert Panel and members of the research group participated in a consensus meeting upon completion of the Delphi study to discuss and further refine the proposed policy solutions.</p> <p>Results</p> <p>43 separate policy solutions to medication non-adherence were agreed by the Panel. 25 policy solutions were prioritised based on composite scores for importance, and operational and political feasibility. Prioritised policy solutions focused on interventions for patients, training for healthcare professionals, and actions to support partnership between patients and healthcare professionals. Few solutions concerned actions by governments, healthcare commissioners, or interventions at the system level.</p> <p>Conclusions</p> <p>Consensus about practical actions necessary to address non-adherence to medicines has been developed for Europe. These actions are also applicable to other regions. Prioritised policy solutions for medicines non-adherence offer a benefit to policymakers and healthcare providers seeking to address this multifaceted, complex problem.</p

    Multilevel factors are associated with immunosuppressant nonadherence in heart transplant recipients: The international BRIGHT study

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    Factors at the level of family/healthcare worker, organization, and system are neglected in medication nonadherence research in heart transplantation (HTx). The 4-continent, 11-country cross-sectional Building Research Initiative Group: Chronic Illness Management and Adherence in Transplantation (BRIGHT) study used multistaged sampling to examine 36 HTx centers, including 36 HTx directors, 100 clinicians, and 1397 patients. Nonadherence to immunosuppressants\u2014defined as any deviation in taking or timing adherence and/or dose reduction\u2014was assessed using the Basel Assessment of Adherence to Immunosuppressive Medications Scale \ua9 (BAASIS \ua9 ) interview. Guided by the Integrative Model of Behavioral Prediction and Bronfenbrenner's ecological model, we analyzed factors at these multiple levels using sequential logistic regression analysis (6 blocks). The nonadherence prevalence was 34.1%. Six multilevel factors were associated independently (either positively or negatively) with nonadherence: patient level: barriers to taking immunosuppressants (odds ratio [OR]: 11.48); smoking (OR: 2.19); family/healthcare provider level: frequency of having someone to help patients read health-related materials (OR: 0.85); organization level: clinicians reporting nonadherent patients were targeted with adherence interventions (OR: 0.66); pickup of medications at physician's office (OR: 2.31); and policy level: monthly out-of-pocket costs for medication (OR: 1.16). Factors associated with nonadherence are evident at multiple levels. Improving medication nonadherence requires addressing not only the patient, but also family/healthcare provider, organization, and policy levels

    Validation of the patient assessment of chronic illness care (PACIC) short form scale in heart transplant recipients: The international cross-sectional bright study

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    Background: Transplant recipients are chronically ill patients, who require lifelong follow-up to manage co-morbidities and prevent graft loss. This necessitates a system of care that is congruent with the Chronic Care Model. The eleven-item self-report Patient Assessment of Chronic Illness Care (PACIC) scale assesses whether chronic care is congruent with the Chronic Care Model, yet its validity for heart transplant patients has not been tested. Methods: We tested the validity of the English version of the PACIC, and compared the similarity of the internal structure of the PACIC across English-speaking countries (USA, Canada, Australia and United Kingdom) and across six languages (French, German, Dutch, Spanish, Italian and Portuguese). This was done using data from the cross-sectional international BRIGHT study that included 1378 heart transplant patients from eleven countries across 4 continents. To test the validity of the instrument, confirmatory factor analyses to check the expected unidimensional internal structure, and relations to other variables, were performed. Results: Main analyses confirmed the validity of the English PACIC version for heart transplant patients. Exploratory analyses across English-speaking countries and languages also confirmed the single factorial dimension, except in Italian and Spanish. Conclusion: This scale could help healthcare providers monitor level of chronic illness management and improve transplantation care. Trial registration: Clinicaltrials.gov ID: NCT01608477, first patient enrolled in March 2012, registered retrospectively: May 30, 2012

    TRY plant trait database - enhanced coverage and open access

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    This article has 730 authors, of which I have only listed the lead author and myself as a representative of University of HelsinkiPlant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.Peer reviewe

    TRY plant trait database - enhanced coverage and open access

    Get PDF
    Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

    TRY plant trait database – enhanced coverage and open access

    Get PDF
    Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives
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