The Experts below are selected from a list of 3483 Experts worldwide ranked by ideXlab platform

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

  • Creating Persona skeletons from imbalanced datasets a case study using u s older adults health data
    Designing Interactive Systems, 2019
    Co-Authors: Haining Zhu, Hongjian Wang, John M Carroll
    Abstract:

    Incorporating health Personas for older adults into design processes can help designers accurately represent older adults by evoking empathy, facilitating consideration of health issues and needs, and reducing stereotype reliance. Toward this goal, we create a two-level quantitative methodology for constructing Persona skeletons from imbalanced datasets. We demonstrate our methodology by constructing a set of 4 care-management Personas for U.S. older adults via filtering and analyzing demographic, behavior risk factor, and chronic health conditions from 170,704 randomly sampled older adults in a national survey with imbalanced coverage (i.e. between unconditional & conditional questions). We obtain 4 cluster centers for unconditional questions through K-means and iteratively dropping irrelevant features. Within each cluster, we analyze selected respondents for conditional questions. We synthesize results into Persona narratives and provide a weighting scheme to quantitatively measure each Persona's significance. We contribute a robust Persona construction methodology, here applied towards representing older adults.

  • Conference on Designing Interactive Systems - Creating Persona Skeletons from Imbalanced Datasets - A Case Study using U.S. Older Adults' Health Data
    Proceedings of the 2019 on Designing Interactive Systems Conference, 2019
    Co-Authors: Haining Zhu, Hongjian Wang, John M Carroll
    Abstract:

    Incorporating health Personas for older adults into design processes can help designers accurately represent older adults by evoking empathy, facilitating consideration of health issues and needs, and reducing stereotype reliance. Toward this goal, we create a two-level quantitative methodology for constructing Persona skeletons from imbalanced datasets. We demonstrate our methodology by constructing a set of 4 care-management Personas for U.S. older adults via filtering and analyzing demographic, behavior risk factor, and chronic health conditions from 170,704 randomly sampled older adults in a national survey with imbalanced coverage (i.e. between unconditional & conditional questions). We obtain 4 cluster centers for unconditional questions through K-means and iteratively dropping irrelevant features. Within each cluster, we analyze selected respondents for conditional questions. We synthesize results into Persona narratives and provide a weighting scheme to quantitatively measure each Persona's significance. We contribute a robust Persona construction methodology, here applied towards representing older adults.

Anne Moen - One of the best experts on this subject based on the ideXlab platform.

  • co Creating Persona scenarios with diverse users enriching inclusive design
    International Conference on Human-Computer Interaction, 2020
    Co-Authors: Kristin Skeide Fuglerud, Trenton Schulz, Astri Letnes Janson, Anne Moen
    Abstract:

    In this article, we will examine Personas as methodological approach and review some critiques about how its use may omit or stereotype users with disabilities or even restrict user involvement. We review previous Persona creation methods and compare it to our approach where we involve diverse users directly in the Personas creation process, to ensure more grounded Personas. This approach has recently been refined in a project where we are building a tool aiming to give citizens more control over their health information. We discuss our experiences and offer some experience based guidelines for using our method.

  • HCI (8) - Co-Creating Persona Scenarios with Diverse Users Enriching Inclusive Design
    Lecture Notes in Computer Science, 2020
    Co-Authors: Kristin Skeide Fuglerud, Trenton Schulz, Astri Letnes Janson, Anne Moen
    Abstract:

    In this article, we will examine Personas as methodological approach and review some critiques about how its use may omit or stereotype users with disabilities or even restrict user involvement. We review previous Persona creation methods and compare it to our approach where we involve diverse users directly in the Personas creation process, to ensure more grounded Personas. This approach has recently been refined in a project where we are building a tool aiming to give citizens more control over their health information. We discuss our experiences and offer some experience based guidelines for using our method.

Haining Zhu - One of the best experts on this subject based on the ideXlab platform.

  • Creating Persona skeletons from imbalanced datasets a case study using u s older adults health data
    Designing Interactive Systems, 2019
    Co-Authors: Haining Zhu, Hongjian Wang, John M Carroll
    Abstract:

    Incorporating health Personas for older adults into design processes can help designers accurately represent older adults by evoking empathy, facilitating consideration of health issues and needs, and reducing stereotype reliance. Toward this goal, we create a two-level quantitative methodology for constructing Persona skeletons from imbalanced datasets. We demonstrate our methodology by constructing a set of 4 care-management Personas for U.S. older adults via filtering and analyzing demographic, behavior risk factor, and chronic health conditions from 170,704 randomly sampled older adults in a national survey with imbalanced coverage (i.e. between unconditional & conditional questions). We obtain 4 cluster centers for unconditional questions through K-means and iteratively dropping irrelevant features. Within each cluster, we analyze selected respondents for conditional questions. We synthesize results into Persona narratives and provide a weighting scheme to quantitatively measure each Persona's significance. We contribute a robust Persona construction methodology, here applied towards representing older adults.

  • Conference on Designing Interactive Systems - Creating Persona Skeletons from Imbalanced Datasets - A Case Study using U.S. Older Adults' Health Data
    Proceedings of the 2019 on Designing Interactive Systems Conference, 2019
    Co-Authors: Haining Zhu, Hongjian Wang, John M Carroll
    Abstract:

    Incorporating health Personas for older adults into design processes can help designers accurately represent older adults by evoking empathy, facilitating consideration of health issues and needs, and reducing stereotype reliance. Toward this goal, we create a two-level quantitative methodology for constructing Persona skeletons from imbalanced datasets. We demonstrate our methodology by constructing a set of 4 care-management Personas for U.S. older adults via filtering and analyzing demographic, behavior risk factor, and chronic health conditions from 170,704 randomly sampled older adults in a national survey with imbalanced coverage (i.e. between unconditional & conditional questions). We obtain 4 cluster centers for unconditional questions through K-means and iteratively dropping irrelevant features. Within each cluster, we analyze selected respondents for conditional questions. We synthesize results into Persona narratives and provide a weighting scheme to quantitatively measure each Persona's significance. We contribute a robust Persona construction methodology, here applied towards representing older adults.

Kristin Skeide Fuglerud - One of the best experts on this subject based on the ideXlab platform.

  • co Creating Persona scenarios with diverse users enriching inclusive design
    International Conference on Human-Computer Interaction, 2020
    Co-Authors: Kristin Skeide Fuglerud, Trenton Schulz, Astri Letnes Janson, Anne Moen
    Abstract:

    In this article, we will examine Personas as methodological approach and review some critiques about how its use may omit or stereotype users with disabilities or even restrict user involvement. We review previous Persona creation methods and compare it to our approach where we involve diverse users directly in the Personas creation process, to ensure more grounded Personas. This approach has recently been refined in a project where we are building a tool aiming to give citizens more control over their health information. We discuss our experiences and offer some experience based guidelines for using our method.

  • HCI (8) - Co-Creating Persona Scenarios with Diverse Users Enriching Inclusive Design
    Lecture Notes in Computer Science, 2020
    Co-Authors: Kristin Skeide Fuglerud, Trenton Schulz, Astri Letnes Janson, Anne Moen
    Abstract:

    In this article, we will examine Personas as methodological approach and review some critiques about how its use may omit or stereotype users with disabilities or even restrict user involvement. We review previous Persona creation methods and compare it to our approach where we involve diverse users directly in the Personas creation process, to ensure more grounded Personas. This approach has recently been refined in a project where we are building a tool aiming to give citizens more control over their health information. We discuss our experiences and offer some experience based guidelines for using our method.

Hongjian Wang - One of the best experts on this subject based on the ideXlab platform.

  • Creating Persona skeletons from imbalanced datasets a case study using u s older adults health data
    Designing Interactive Systems, 2019
    Co-Authors: Haining Zhu, Hongjian Wang, John M Carroll
    Abstract:

    Incorporating health Personas for older adults into design processes can help designers accurately represent older adults by evoking empathy, facilitating consideration of health issues and needs, and reducing stereotype reliance. Toward this goal, we create a two-level quantitative methodology for constructing Persona skeletons from imbalanced datasets. We demonstrate our methodology by constructing a set of 4 care-management Personas for U.S. older adults via filtering and analyzing demographic, behavior risk factor, and chronic health conditions from 170,704 randomly sampled older adults in a national survey with imbalanced coverage (i.e. between unconditional & conditional questions). We obtain 4 cluster centers for unconditional questions through K-means and iteratively dropping irrelevant features. Within each cluster, we analyze selected respondents for conditional questions. We synthesize results into Persona narratives and provide a weighting scheme to quantitatively measure each Persona's significance. We contribute a robust Persona construction methodology, here applied towards representing older adults.

  • Conference on Designing Interactive Systems - Creating Persona Skeletons from Imbalanced Datasets - A Case Study using U.S. Older Adults' Health Data
    Proceedings of the 2019 on Designing Interactive Systems Conference, 2019
    Co-Authors: Haining Zhu, Hongjian Wang, John M Carroll
    Abstract:

    Incorporating health Personas for older adults into design processes can help designers accurately represent older adults by evoking empathy, facilitating consideration of health issues and needs, and reducing stereotype reliance. Toward this goal, we create a two-level quantitative methodology for constructing Persona skeletons from imbalanced datasets. We demonstrate our methodology by constructing a set of 4 care-management Personas for U.S. older adults via filtering and analyzing demographic, behavior risk factor, and chronic health conditions from 170,704 randomly sampled older adults in a national survey with imbalanced coverage (i.e. between unconditional & conditional questions). We obtain 4 cluster centers for unconditional questions through K-means and iteratively dropping irrelevant features. Within each cluster, we analyze selected respondents for conditional questions. We synthesize results into Persona narratives and provide a weighting scheme to quantitatively measure each Persona's significance. We contribute a robust Persona construction methodology, here applied towards representing older adults.