The crossroads of digital phenotyping

Davidson, Brittany I.

doi:10.1016/j.genhosppsych.2020.11.009

Cited by 30 publications

(36 citation statements)

References 64 publications

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“…While APIs and proprietary data can be used to produce more nuanced measures of platform actions and user engagement than logs of usage duration, they are generally unable to provide insights into the user's responses or reactions. In terms of the type of social media content, novel approaches like the 'Human Screenome Project' [32] provide promising albeit ethically challenging results [33]. Alternatively, methods like stimulated recall interviews [31], or ESM designs incorporating both logged and self-reported data on uses and reactions may provide more insight into SMU-well-being relations.…”

Section: Using Behavioural Measures Of Smumentioning

confidence: 99%

Social Media and Well-being: A Methodological Perspective

Parry¹,

Fisher²,

Mieczkowski³

et al. 2021

Preprint

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Due to the methodological challenges inherent in studying social media use (SMU), as well as the methodological choices that have shaped research into the effects of SMU on well- being, clear conclusions regarding relationships between SMU and well-being remain elusive. We provide a review of five methodological developments poised to provide increased understanding in this domain: (1) the use of longitudinal and experimental designs; (2) the adoption of behavioural (rather than self-report) measures of SMU; (3) a shift away from aggregate use; (4) the emergence of an idiographic media effects paradigm; and (5) the use of formal modelling and machine learning. We focus on how these advances stand to bring us closer to understanding relations between SMU and well-being.

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Section: Using Behavioural Measures Of Smumentioning

confidence: 99%

Social Media and Well-being: A Methodological Perspective

Parry¹,

Fisher²,

Mieczkowski³

et al. 2021

Preprint

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“…Phenotyping provides specific benefits and opportunities for intervention in each of the aspects listed prior. This allows for better caretaking, especially on a large scale because population shifts are quantifiable through the collection of phenotype-based data points [9].…”

Section: Impact Of Phenotyping In the Livestock Sectormentioning

confidence: 99%

Digital Phenotyping in Livestock Farming

Neethirajan

Kemp

2021

Animals

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Currently, large volumes of data are being collected on farms using multimodal sensor technologies. These sensors measure the activity, housing conditions, feed intake, and health of farm animals. With traditional methods, the data from farm animals and their environment can be collected intermittently. However, with the advancement of wearable and non-invasive sensing tools, these measurements can be made in real-time for continuous quantitation relating to clinical biomarkers, resilience indicators, and behavioral predictors. The digital phenotyping of humans has drawn enormous attention recently due to its medical significance, but much research is still needed for the digital phenotyping of farm animals. Implications from human studies show great promise for the application of digital phenotyping technology in modern livestock farming, but these technologies must be directly applied to animals to understand their true capacities. Due to species-specific traits, certain technologies required to assess phenotypes need to be tailored efficiently and accurately. Such devices allow for the collection of information that can better inform farmers on aspects of animal welfare and production that need improvement. By explicitly addressing farm animals’ individual physiological and mental (affective states) needs, sensor-based digital phenotyping has the potential to serve as an effective intervention platform. Future research is warranted for the design and development of digital phenotyping technology platforms that create shared data standards, metrics, and repositories.

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“…Phenotyping provides specific benefits and opportunities for intervention at each of the aspects listed prior. This allows for better caretaking, especially on a large scale, since population shifts are quantifiable through the collection of phenotypebased data points [8].…”

Section: Impact Of Phenotyping In the Livestock Sectormentioning

confidence: 99%

Digital Phenotyping in Livestock Farming

Neethirajan¹,

Kemp²

2021

Preprint

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Currently, large volumes of data are being collected on farms using multimodal sensor technol-ogies. These sensors measure the activity, housing conditions, feed intake, and health of farm animals. With traditional methods, the data from farm animals and their environment can be collected intermittently. However, with the advancement of wearable and non-invasive sensing tools, these measurements can be made in real-time for continuous quantitation relating to clinical biomarkers, resilience indicators, and behavioral predictors. The digital phenotyping of humans has drawn enormous attention recently due to its medical significance, but much research is still needed for the digital phenotyping of farm animals. Implications from human studies show great promise for the application of digital phenotyping technology in modern livestock farming, but these technologies must be directly applied to animals to understand their true capacities. Due to species-specific traits, certain technologies required to assess phenotypes need to be tailored ef-ficiently and accurately. Such devices allow for the collection of information that can better inform farmers on aspects of animal welfare and production that need improvement. By explicitly ad-dressing farm animals’ individual physiological and mental (affective states) needs, sensor-based digital phenotyping has the potential to serve as an effective intervention platform. Future re-search is warranted for the design and development of digital phenotyping technology platforms that create shared data standards, metrics, and repositories.

show abstract

The crossroads of digital phenotyping

Cited by 30 publications

References 64 publications

Social Media and Well-being: A Methodological Perspective

Social Media and Well-being: A Methodological Perspective

Digital Phenotyping in Livestock Farming

Digital Phenotyping in Livestock Farming

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