The Experts below are selected from a list of 1099650 Experts worldwide ranked by ideXlab platform

John Lynch - One of the best experts on this subject based on the ideXlab platform.

  • Evaluating Population-Level interventions for young people's mental health: challenges and opportunities.
    Early Intervention in Psychiatry, 2011
    Co-Authors: Michael G. Sawyer, Nina Borojevic, John Lynch
    Abstract:

    Aim: To identify key issues relevant to the delivery and evaluation of Population-Level mental health interventions for children and adolescents. Methods: The benefits and limitations of clinical, targeted and universal interventions were initially reviewed. Subsequently, experience gained in evaluations of targeted and universal interventions was utilized to identify key challenges that must be addressed by researchers responsible for evaluating Population-Level interventions and potential solutions to these challenges. Results: To be effective, Population-Level interventions must engage large numbers of individuals in community or regional areas. Successfully evaluating Population-Level interventions delivered in routine services requires a clear agreement about outcomes, use of strong research methodologies, and the availability of adequate research funding. Sustaining service-research partnerships over the several-year life of typical Population interventions requires careful attention to these issues. Electronic databases with the capacity to efficiently collect, store and allow retrieval of large amounts of data in electronic format are also an essential component of Population-Level interventions. Finally, research leaders need high-quality administrative skills to manage research teams responsible for evaluating large-scale Population-Level interventions delivered at a regional or national Level. Conclusion: Population-Level interventions have the potential to play an important role in reducing the incidence and prevalence of mental health problems experienced by young people in the community. However, if they are to achieve their full effectiveness, ongoing evaluations are needed.

  • Evaluating Population-Level interventions for young people's mental health: challenges and opportunities.
    Early intervention in psychiatry, 2011
    Co-Authors: Michael G. Sawyer, Nina Borojevic, John Lynch
    Abstract:

    To identify key issues relevant to the delivery and evaluation of Population-Level mental health interventions for children and adolescents. The benefits and limitations of clinical, targeted and universal interventions were initially reviewed. Subsequently, experience gained in evaluations of targeted and universal interventions was utilized to identify key challenges that must be addressed by researchers responsible for evaluating Population-Level interventions and potential solutions to these challenges. To be effective, Population-Level interventions must engage large numbers of individuals in community or regional areas. Successfully evaluating Population-Level interventions delivered in routine services requires a clear agreement about outcomes, use of strong research methodologies, and the availability of adequate research funding. Sustaining service-research partnerships over the several-year life of typical Population interventions requires careful attention to these issues. Electronic databases with the capacity to efficiently collect, store and allow retrieval of large amounts of data in electronic format are also an essential component of Population-Level interventions. Finally, research leaders need high-quality administrative skills to manage research teams responsible for evaluating large-scale Population-Level interventions delivered at a regional or national Level. Population-Level interventions have the potential to play an important role in reducing the incidence and prevalence of mental health problems experienced by young people in the community. However, if they are to achieve their full effectiveness, ongoing evaluations are needed. © 2011 Blackwell Publishing Asia Pty Ltd.

  • Original Article Evaluating Population-Level interventions for young people's mental health: challenges and opportunities
    2010
    Co-Authors: Michael G. Sawyer, Nina Borojevic, John Lynch
    Abstract:

    Aim: To identify key issues relevant to the delivery and evaluation of Population-Level mental health interventionsforchildrenandadolescents. Methods: The benefits and limitations of clinical, targeted and universal interventions were initially reviewed. Subsequently, experience gained in evaluations of targeted and universalinterventionswasutilizedto identify key challenges that must be addressed by researchers responsible for evaluating Population-Level interventions and potential solutions to these challenges. Results: To be effective, PopulationLevel interventions must engage large numbers of individuals in community or regional areas. Successfully evaluating Population-Level interventions delivered in routine services requires a clear agreement about outcomes, use of strong research methodologies, and the availability of adequate research funding. Sustaining serviceresearch partnerships over the several-year life of typical Population interventions requires careful attention to these issues. Electronic databases with the capacity to efficiently collect, store and allow retrieval of large amounts of data in electronic format are also an essential component of Population-Level interventions. Finally, research leaders need high-quality administrative skills to manage research teams responsible for evaluating large-scale PopulationLevel interventions delivered at a regional or national Level. Conclusion: Population-Level interventions have the potential to play an important role in reducing the incidence and prevalence of mental health problems experienced by young people in the community. However, if they are to achieve their fulleffectiveness,ongoingevaluations are needed.

Gerald T Ankley - One of the best experts on this subject based on the ideXlab platform.

  • adverse outcome pathways and ecological risk assessment bridging to Population Level effects
    Environmental Toxicology and Chemistry, 2011
    Co-Authors: Vincent J Kramer, Cheryl A. Murphy, Markus Hecker, Matthew A Etterson, Guritno Roesijadi, Daniel J Spade, Julann A Spromberg, Magnus Wang, Gerald T Ankley
    Abstract:

    Maintaining the viability of Populations of plants and animals is a key focus for environmental regulation. Population-Level responses integrate the cumulative effects of chemical stressors on individuals as those individuals interact with and are affected by their conspecifics, competitors, predators, prey, habitat, and other biotic and abiotic factors. Models of Population-Level effects of contaminants can integrate information from lower Levels of biological organization and feed that information into higher-Level community and ecosystem models. As individual-Level endpoints are used to predict Population responses, this requires that biological responses at lower Levels of organization be translated into a form that is usable by the Population modeler. In the current study, we describe how mechanistic data, as captured in adverse outcome pathways (AOPs), can be translated into modeling focused on Population-Level risk assessments. First, we describe the regulatory context surrounding Population modeling, risk assessment and the emerging role of AOPs. Then we present a succinct overview of different approaches to Population modeling and discuss the types of data needed for these models. We describe how different key biological processes measured at the Level of the individual serve as the linkage, or bridge, between AOPs and predictions of Population status, including consideration of community-Level interactions and genetic adaptation. Several case examples illustrate the potential for use of AOPs in Population modeling and predictive ecotoxicology. Finally, we make recommendations for focusing toxicity studies to produce the quantitative data needed to define AOPs and to facilitate their incorporation into Population modeling. Environ. Toxicol. Chem. 2011;30:64–76. © 2010 SETAC

  • adverse outcome pathways and ecological risk assessment bridging to Population Level effects
    Environmental Toxicology and Chemistry, 2011
    Co-Authors: Vincent J Kramer, Cheryl A. Murphy, Markus Hecker, Matthew A Etterson, Guritno Roesijadi, Daniel J Spade, Julann A Spromberg, Magnus Wang, Gerald T Ankley
    Abstract:

    Maintaining the viability of Populations of plants and animals is a key focus for environmental regulation. Population-Level responses integrate the cumulative effects of chemical stressors on individuals as those individuals interact with and are affected by their conspecifics, competitors, predators, prey, habitat, and other biotic and abiotic factors. Models of Population-Level effects of contaminants can integrate information from lower Levels of biological organization and feed that information into higher-Level community and ecosystem models. As individual-Level endpoints are used to predict Population responses, this requires that biological responses at lower Levels of organization be translated into a form that is usable by the Population modeler. In the current study, we describe how mechanistic data, as captured in adverse outcome pathways (AOPs), can be translated into modeling focused on Population-Level risk assessments. First, we describe the regulatory context surrounding Population modeling, risk assessment and the emerging role of AOPs. Then we present a succinct overview of different approaches to Population modeling and discuss the types of data needed for these models. We describe how different key biological processes measured at the Level of the individual serve as the linkage, or bridge, between AOPs and predictions of Population status, including consideration of community-Level interactions and genetic adaptation. Several case examples illustrate the potential for use of AOPs in Population modeling and predictive ecotoxicology. Finally, we make recommendations for focusing toxicity studies to produce the quantitative data needed to define AOPs and to facilitate their incorporation into Population modeling.

Jeffrey A. Johnson - One of the best experts on this subject based on the ideXlab platform.

  • Population-Level response shift: novel implications for research
    Quality of Life Research, 2012
    Co-Authors: Darren Lau, Calypse Agborsangaya, Fatima Al Sayah, Arto Ohinmaa, Jeffrey A. Johnson
    Abstract:

    Objectives Response shift is a change in perceived HRQL that occurs as a result of recalibration, reprioritization, or reconceptualization of an individual respondent’s internal standards, values, or conceptualization of HRQL. In this commentary, we suggest that response shift may also occur at the Population Level, triggered by causes that affect the distribution of individual-Level risk. Methods We illustrated the nature and consequences of potential Population-Level response shift with two examples: the September 11 terror attacks, and the recent denormalization of smoking. Results Response shift may occur at the Population-Level, when a large proportion of the Population experiences the shift simultaneously, as a unit, and when the cause of the response shift is a socially significant event or trend. Such catalysts are of a qualitatively different nature than the causes leading to health status changes among individuals, and speak to the determinants affecting the underlying distribution of risk in the Population. Conclusions We do not know if Population-Level causes have actually resulted in response shifts. Nonetheless, response shifts at the Population-Level may be worthwhile to investigate further, both to assess the validity of research evidence based on the measurement of HRQL in large Populations, and as a desirable intermediate outcome in evaluations of Population health programs.

  • Population-Level response shift: novel implications for research
    Quality of life research : an international journal of quality of life aspects of treatment care and rehabilitation, 2011
    Co-Authors: Darren Lau, Calypse Agborsangaya, Fatima Al Sayah, Arto Ohinmaa, Jeffrey A. Johnson
    Abstract:

    Objectives Response shift is a change in perceived HRQL that occurs as a result of recalibration, reprioritization, or reconceptualization of an individual respondent’s internal standards, values, or conceptualization of HRQL. In this commentary, we suggest that response shift may also occur at the Population Level, triggered by causes that affect the distribution of individual-Level risk.

Michael G. Sawyer - One of the best experts on this subject based on the ideXlab platform.

  • Evaluating Population-Level interventions for young people's mental health: challenges and opportunities.
    Early Intervention in Psychiatry, 2011
    Co-Authors: Michael G. Sawyer, Nina Borojevic, John Lynch
    Abstract:

    Aim: To identify key issues relevant to the delivery and evaluation of Population-Level mental health interventions for children and adolescents. Methods: The benefits and limitations of clinical, targeted and universal interventions were initially reviewed. Subsequently, experience gained in evaluations of targeted and universal interventions was utilized to identify key challenges that must be addressed by researchers responsible for evaluating Population-Level interventions and potential solutions to these challenges. Results: To be effective, Population-Level interventions must engage large numbers of individuals in community or regional areas. Successfully evaluating Population-Level interventions delivered in routine services requires a clear agreement about outcomes, use of strong research methodologies, and the availability of adequate research funding. Sustaining service-research partnerships over the several-year life of typical Population interventions requires careful attention to these issues. Electronic databases with the capacity to efficiently collect, store and allow retrieval of large amounts of data in electronic format are also an essential component of Population-Level interventions. Finally, research leaders need high-quality administrative skills to manage research teams responsible for evaluating large-scale Population-Level interventions delivered at a regional or national Level. Conclusion: Population-Level interventions have the potential to play an important role in reducing the incidence and prevalence of mental health problems experienced by young people in the community. However, if they are to achieve their full effectiveness, ongoing evaluations are needed.

  • Evaluating Population-Level interventions for young people's mental health: challenges and opportunities.
    Early intervention in psychiatry, 2011
    Co-Authors: Michael G. Sawyer, Nina Borojevic, John Lynch
    Abstract:

    To identify key issues relevant to the delivery and evaluation of Population-Level mental health interventions for children and adolescents. The benefits and limitations of clinical, targeted and universal interventions were initially reviewed. Subsequently, experience gained in evaluations of targeted and universal interventions was utilized to identify key challenges that must be addressed by researchers responsible for evaluating Population-Level interventions and potential solutions to these challenges. To be effective, Population-Level interventions must engage large numbers of individuals in community or regional areas. Successfully evaluating Population-Level interventions delivered in routine services requires a clear agreement about outcomes, use of strong research methodologies, and the availability of adequate research funding. Sustaining service-research partnerships over the several-year life of typical Population interventions requires careful attention to these issues. Electronic databases with the capacity to efficiently collect, store and allow retrieval of large amounts of data in electronic format are also an essential component of Population-Level interventions. Finally, research leaders need high-quality administrative skills to manage research teams responsible for evaluating large-scale Population-Level interventions delivered at a regional or national Level. Population-Level interventions have the potential to play an important role in reducing the incidence and prevalence of mental health problems experienced by young people in the community. However, if they are to achieve their full effectiveness, ongoing evaluations are needed. © 2011 Blackwell Publishing Asia Pty Ltd.

  • Original Article Evaluating Population-Level interventions for young people's mental health: challenges and opportunities
    2010
    Co-Authors: Michael G. Sawyer, Nina Borojevic, John Lynch
    Abstract:

    Aim: To identify key issues relevant to the delivery and evaluation of Population-Level mental health interventionsforchildrenandadolescents. Methods: The benefits and limitations of clinical, targeted and universal interventions were initially reviewed. Subsequently, experience gained in evaluations of targeted and universalinterventionswasutilizedto identify key challenges that must be addressed by researchers responsible for evaluating Population-Level interventions and potential solutions to these challenges. Results: To be effective, PopulationLevel interventions must engage large numbers of individuals in community or regional areas. Successfully evaluating Population-Level interventions delivered in routine services requires a clear agreement about outcomes, use of strong research methodologies, and the availability of adequate research funding. Sustaining serviceresearch partnerships over the several-year life of typical Population interventions requires careful attention to these issues. Electronic databases with the capacity to efficiently collect, store and allow retrieval of large amounts of data in electronic format are also an essential component of Population-Level interventions. Finally, research leaders need high-quality administrative skills to manage research teams responsible for evaluating large-scale PopulationLevel interventions delivered at a regional or national Level. Conclusion: Population-Level interventions have the potential to play an important role in reducing the incidence and prevalence of mental health problems experienced by young people in the community. However, if they are to achieve their fulleffectiveness,ongoingevaluations are needed.

Vincent J Kramer - One of the best experts on this subject based on the ideXlab platform.

  • adverse outcome pathways and ecological risk assessment bridging to Population Level effects
    Environmental Toxicology and Chemistry, 2011
    Co-Authors: Vincent J Kramer, Cheryl A. Murphy, Markus Hecker, Matthew A Etterson, Guritno Roesijadi, Daniel J Spade, Julann A Spromberg, Magnus Wang, Gerald T Ankley
    Abstract:

    Maintaining the viability of Populations of plants and animals is a key focus for environmental regulation. Population-Level responses integrate the cumulative effects of chemical stressors on individuals as those individuals interact with and are affected by their conspecifics, competitors, predators, prey, habitat, and other biotic and abiotic factors. Models of Population-Level effects of contaminants can integrate information from lower Levels of biological organization and feed that information into higher-Level community and ecosystem models. As individual-Level endpoints are used to predict Population responses, this requires that biological responses at lower Levels of organization be translated into a form that is usable by the Population modeler. In the current study, we describe how mechanistic data, as captured in adverse outcome pathways (AOPs), can be translated into modeling focused on Population-Level risk assessments. First, we describe the regulatory context surrounding Population modeling, risk assessment and the emerging role of AOPs. Then we present a succinct overview of different approaches to Population modeling and discuss the types of data needed for these models. We describe how different key biological processes measured at the Level of the individual serve as the linkage, or bridge, between AOPs and predictions of Population status, including consideration of community-Level interactions and genetic adaptation. Several case examples illustrate the potential for use of AOPs in Population modeling and predictive ecotoxicology. Finally, we make recommendations for focusing toxicity studies to produce the quantitative data needed to define AOPs and to facilitate their incorporation into Population modeling. Environ. Toxicol. Chem. 2011;30:64–76. © 2010 SETAC

  • adverse outcome pathways and ecological risk assessment bridging to Population Level effects
    Environmental Toxicology and Chemistry, 2011
    Co-Authors: Vincent J Kramer, Cheryl A. Murphy, Markus Hecker, Matthew A Etterson, Guritno Roesijadi, Daniel J Spade, Julann A Spromberg, Magnus Wang, Gerald T Ankley
    Abstract:

    Maintaining the viability of Populations of plants and animals is a key focus for environmental regulation. Population-Level responses integrate the cumulative effects of chemical stressors on individuals as those individuals interact with and are affected by their conspecifics, competitors, predators, prey, habitat, and other biotic and abiotic factors. Models of Population-Level effects of contaminants can integrate information from lower Levels of biological organization and feed that information into higher-Level community and ecosystem models. As individual-Level endpoints are used to predict Population responses, this requires that biological responses at lower Levels of organization be translated into a form that is usable by the Population modeler. In the current study, we describe how mechanistic data, as captured in adverse outcome pathways (AOPs), can be translated into modeling focused on Population-Level risk assessments. First, we describe the regulatory context surrounding Population modeling, risk assessment and the emerging role of AOPs. Then we present a succinct overview of different approaches to Population modeling and discuss the types of data needed for these models. We describe how different key biological processes measured at the Level of the individual serve as the linkage, or bridge, between AOPs and predictions of Population status, including consideration of community-Level interactions and genetic adaptation. Several case examples illustrate the potential for use of AOPs in Population modeling and predictive ecotoxicology. Finally, we make recommendations for focusing toxicity studies to produce the quantitative data needed to define AOPs and to facilitate their incorporation into Population modeling.