The Experts below are selected from a list of 29466 Experts worldwide ranked by ideXlab platform

Samuel D Gosling - One of the best experts on this subject based on the ideXlab platform.

  • using smartphones to collect Behavioral data in psychological science opportunities practical considerations and challenges
    Perspectives on Psychological Science, 2016
    Co-Authors: Gabriella M Harari, Nicholas D Lane, Benjamin S Crosier, Andrew T. Campbell, Samuel D Gosling, Rui Wang
    Abstract:

    Smartphones now offer the promise of collecting Behavioral data unobtrusively, in situ, as it unfolds in the course of daily life. Data can be collected from the onboard sensors and other phone logs embedded in today's off-the-shelf smartphone devices. These data permit fine-grained, continuous collection of people's social interactions (e.g., speaking rates in conversation, size of social groups, calls, and text messages), daily activities (e.g., physical activity and sleep), and mobility patterns (e.g., frequency and duration of time spent at various locations). In this article, we have drawn on the lessons from the first wave of smartphone-sensing research to highlight areas of opportunity for psychological research, present practical considerations for designing smartphone studies, and discuss the ongoing methodological and ethical challenges associated with research in this domain. It is our hope that these practical guidelines will facilitate the use of smartphones as a Behavioral Observation tool in psychological science.

  • using smartphones to collect Behavioral data in psychological science opportunities practical considerations and challenges
    Perspectives on Psychological Science, 2016
    Co-Authors: Gabriella M Harari, Nicholas D Lane, Benjamin S Crosier, Andrew T. Campbell, Samuel D Gosling, Rui Wang
    Abstract:

    Smartphones now offer the promise of collecting Behavioral data unobtrusively, in situ, as it unfolds in the course of daily life. Data can be collected from the onboard sensors and other phone logs embedded in today’s off-the-shelf smartphone devices. These data permit fine-grained, continuous collection of people’s social interactions (e.g., speaking rates in conversation, size of social groups, calls, and text messages), daily activities (e.g., physical activity and sleep), and mobility patterns (e.g., frequency and duration of time spent at various locations). In this article, we have drawn on the lessons from the first wave of smartphone-sensing research to highlight areas of opportunity for psychological research, present practical considerations for designing smartphone studies, and discuss the ongoing methodological and ethical challenges associated with research in this domain. It is our hope that these practical guidelines will facilitate the use of smartphones as a Behavioral Observation tool i...

Nicholas D Lane - One of the best experts on this subject based on the ideXlab platform.

  • using smartphones to collect Behavioral data in psychological science opportunities practical considerations and challenges
    Perspectives on Psychological Science, 2016
    Co-Authors: Gabriella M Harari, Nicholas D Lane, Benjamin S Crosier, Andrew T. Campbell, Samuel D Gosling, Rui Wang
    Abstract:

    Smartphones now offer the promise of collecting Behavioral data unobtrusively, in situ, as it unfolds in the course of daily life. Data can be collected from the onboard sensors and other phone logs embedded in today's off-the-shelf smartphone devices. These data permit fine-grained, continuous collection of people's social interactions (e.g., speaking rates in conversation, size of social groups, calls, and text messages), daily activities (e.g., physical activity and sleep), and mobility patterns (e.g., frequency and duration of time spent at various locations). In this article, we have drawn on the lessons from the first wave of smartphone-sensing research to highlight areas of opportunity for psychological research, present practical considerations for designing smartphone studies, and discuss the ongoing methodological and ethical challenges associated with research in this domain. It is our hope that these practical guidelines will facilitate the use of smartphones as a Behavioral Observation tool in psychological science.

  • using smartphones to collect Behavioral data in psychological science opportunities practical considerations and challenges
    Perspectives on Psychological Science, 2016
    Co-Authors: Gabriella M Harari, Nicholas D Lane, Benjamin S Crosier, Andrew T. Campbell, Samuel D Gosling, Rui Wang
    Abstract:

    Smartphones now offer the promise of collecting Behavioral data unobtrusively, in situ, as it unfolds in the course of daily life. Data can be collected from the onboard sensors and other phone logs embedded in today’s off-the-shelf smartphone devices. These data permit fine-grained, continuous collection of people’s social interactions (e.g., speaking rates in conversation, size of social groups, calls, and text messages), daily activities (e.g., physical activity and sleep), and mobility patterns (e.g., frequency and duration of time spent at various locations). In this article, we have drawn on the lessons from the first wave of smartphone-sensing research to highlight areas of opportunity for psychological research, present practical considerations for designing smartphone studies, and discuss the ongoing methodological and ethical challenges associated with research in this domain. It is our hope that these practical guidelines will facilitate the use of smartphones as a Behavioral Observation tool i...

Gabriella M Harari - One of the best experts on this subject based on the ideXlab platform.

  • using smartphones to collect Behavioral data in psychological science opportunities practical considerations and challenges
    Perspectives on Psychological Science, 2016
    Co-Authors: Gabriella M Harari, Nicholas D Lane, Benjamin S Crosier, Andrew T. Campbell, Samuel D Gosling, Rui Wang
    Abstract:

    Smartphones now offer the promise of collecting Behavioral data unobtrusively, in situ, as it unfolds in the course of daily life. Data can be collected from the onboard sensors and other phone logs embedded in today's off-the-shelf smartphone devices. These data permit fine-grained, continuous collection of people's social interactions (e.g., speaking rates in conversation, size of social groups, calls, and text messages), daily activities (e.g., physical activity and sleep), and mobility patterns (e.g., frequency and duration of time spent at various locations). In this article, we have drawn on the lessons from the first wave of smartphone-sensing research to highlight areas of opportunity for psychological research, present practical considerations for designing smartphone studies, and discuss the ongoing methodological and ethical challenges associated with research in this domain. It is our hope that these practical guidelines will facilitate the use of smartphones as a Behavioral Observation tool in psychological science.

  • using smartphones to collect Behavioral data in psychological science opportunities practical considerations and challenges
    Perspectives on Psychological Science, 2016
    Co-Authors: Gabriella M Harari, Nicholas D Lane, Benjamin S Crosier, Andrew T. Campbell, Samuel D Gosling, Rui Wang
    Abstract:

    Smartphones now offer the promise of collecting Behavioral data unobtrusively, in situ, as it unfolds in the course of daily life. Data can be collected from the onboard sensors and other phone logs embedded in today’s off-the-shelf smartphone devices. These data permit fine-grained, continuous collection of people’s social interactions (e.g., speaking rates in conversation, size of social groups, calls, and text messages), daily activities (e.g., physical activity and sleep), and mobility patterns (e.g., frequency and duration of time spent at various locations). In this article, we have drawn on the lessons from the first wave of smartphone-sensing research to highlight areas of opportunity for psychological research, present practical considerations for designing smartphone studies, and discuss the ongoing methodological and ethical challenges associated with research in this domain. It is our hope that these practical guidelines will facilitate the use of smartphones as a Behavioral Observation tool i...

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

  • pain assessment in persons with dementia relationship between self report and Behavioral Observation
    Journal of the American Geriatrics Society, 2009
    Co-Authors: Ann L Horgas, Amanda F Elliott, Michael Marsiske
    Abstract:

    OBJECTIVES: To investigate the relationship between self-report and Behavioral indicators of pain in cognitively impaired and intact older adults. DESIGN: Quasi-experimental, correlational study of older adults. SETTING: Data were collected from residents of nursing homes, assisted living, and retirement apartments in north-central Florida. PARTICIPANTS: One hundred twenty-six adults, mean age 83; 64 cognitively intact, 62 cognitively impaired. MEASUREMENTS: Pain interviews (pain presence, intensity, locations, duration), pain behavior measure, Mini-Mental State Examination, analgesic medications, and demographic characteristics. Participants completed an activity-based protocol to induce pain. RESULTS: Eighty-six percent self-reported regular pain. Controlling for analgesics, cognitively impaired participants reported less pain than cognitively intact participants after movement but not at rest. Behavioral pain indicators did not differ between cognitively intact and impaired participants. Total number of pain behaviors was significantly related to self-reported pain intensity (β=0.40, P=.000) in cognitively intact elderly people. CONCLUSION: Cognitively impaired elderly people self-report less pain than cognitively intact elderly people, independent of analgesics, but only when assessed after movement. Behavioral pain indicators do not differ between the groups. The relationship between self-report and pain behaviors supports the validity of Behavioral assessments in this population. These findings support the use of multidimensional pain assessment in persons with dementia.

  • pain assessment in persons with dementia relationship between self report and Behavioral Observation
    Journal of the American Geriatrics Society, 2009
    Co-Authors: Ann L Horgas, Amanda F Elliott, Michael Marsiske
    Abstract:

    OBJECTIVES: To investigate the relationship between self-report and Behavioral indicators of pain in cognitively impaired and intact older adults. DESIGN: Quasi-experimental, correlational study of older adults. SETTING: Data were collected from residents of nursing homes, assisted living, and retirement apartments in north-central Florida. PARTICIPANTS: One hundred twenty-six adults, mean age 83; 64 cognitively intact, 62 cognitively impaired. MEASUREMENTS: Pain interviews (pain presence, intensity, locations, duration), pain behavior measure, Mini-Mental State Examination, analgesic medications, and demographic characteristics. Participants completed an activity-based protocol to induce pain. RESULTS: Eighty-six percent self-reported regular pain. Controlling for analgesics, cognitively impaired participants reported less pain than cognitively intact participants after movement but not at rest. Behavioral pain indicators did not differ between cognitively intact and impaired participants. Total number of pain behaviors was significantly related to self-reported pain intensity (β=0.40, P=.000) in cognitively intact elderly people. CONCLUSION: Cognitively impaired elderly people self-report less pain than cognitively intact elderly people, independent of analgesics, but only when assessed after movement. Behavioral pain indicators do not differ between the groups. The relationship between self-report and pain behaviors supports the validity of Behavioral assessments in this population. These findings support the use of multidimensional pain assessment in persons with dementia.

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

  • using smartphones to collect Behavioral data in psychological science opportunities practical considerations and challenges
    Perspectives on Psychological Science, 2016
    Co-Authors: Gabriella M Harari, Nicholas D Lane, Benjamin S Crosier, Andrew T. Campbell, Samuel D Gosling, Rui Wang
    Abstract:

    Smartphones now offer the promise of collecting Behavioral data unobtrusively, in situ, as it unfolds in the course of daily life. Data can be collected from the onboard sensors and other phone logs embedded in today's off-the-shelf smartphone devices. These data permit fine-grained, continuous collection of people's social interactions (e.g., speaking rates in conversation, size of social groups, calls, and text messages), daily activities (e.g., physical activity and sleep), and mobility patterns (e.g., frequency and duration of time spent at various locations). In this article, we have drawn on the lessons from the first wave of smartphone-sensing research to highlight areas of opportunity for psychological research, present practical considerations for designing smartphone studies, and discuss the ongoing methodological and ethical challenges associated with research in this domain. It is our hope that these practical guidelines will facilitate the use of smartphones as a Behavioral Observation tool in psychological science.

  • using smartphones to collect Behavioral data in psychological science opportunities practical considerations and challenges
    Perspectives on Psychological Science, 2016
    Co-Authors: Gabriella M Harari, Nicholas D Lane, Benjamin S Crosier, Andrew T. Campbell, Samuel D Gosling, Rui Wang
    Abstract:

    Smartphones now offer the promise of collecting Behavioral data unobtrusively, in situ, as it unfolds in the course of daily life. Data can be collected from the onboard sensors and other phone logs embedded in today’s off-the-shelf smartphone devices. These data permit fine-grained, continuous collection of people’s social interactions (e.g., speaking rates in conversation, size of social groups, calls, and text messages), daily activities (e.g., physical activity and sleep), and mobility patterns (e.g., frequency and duration of time spent at various locations). In this article, we have drawn on the lessons from the first wave of smartphone-sensing research to highlight areas of opportunity for psychological research, present practical considerations for designing smartphone studies, and discuss the ongoing methodological and ethical challenges associated with research in this domain. It is our hope that these practical guidelines will facilitate the use of smartphones as a Behavioral Observation tool i...