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Related Concept Videos

Assessment of the Gastrointestinal System I: Subjective Data01:17

Assessment of the Gastrointestinal System I: Subjective Data

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Assessing the gastrointestinal (GI) system is a complex process that begins with collecting subjective data. This data, collected through patient interviews, provides crucial insights into the patient's health history, perception patterns, and lifestyle habits, all contributing significantly to GI health.
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The initial step in assessing the GI system is obtaining a comprehensive health history. This includes inquiring about the patient's history or presence of problems...
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Concept Development and Use of an Automated Food Intake and Eating Behavior Assessment Method
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Collecting Food and Drink Intake Data With Voice Input: Development, Usability, and Acceptability Study.

Louise A C Millard1,2, Laura Johnson1,2,3,4, Samuel R Neaves1,2

  • 1Medical Research Council (MRC) Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom.

JMIR Mhealth and Uhealth
|March 31, 2023
PubMed
Summary
This summary is machine-generated.

Voice-based systems like Amazon Alexa show potential for real-time data collection in epidemiology studies. While some interaction issues exist, participants found the system acceptable for future research.

Keywords:
Amazon Alexadata collectiondigital healthfood and drinkself-reported datavoice-based approaches

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Area of Science:

  • Epidemiology
  • Human-Computer Interaction
  • Health Informatics

Background:

  • Traditional epidemiological data collection relies on infrequent questionnaires, potentially leading to errors and incomplete information.
  • Voice-based systems offer continuous, real-time self-reported data collection, a novel approach for epidemiological studies.
  • The use of voice-based systems like Amazon Alexa for collecting epidemiological data has not been previously evaluated.

Purpose of the Study:

  • To assess the technical feasibility of using Amazon Alexa for collecting participant data in research.
  • To investigate participant acceptability of voice-based data collection methods.
  • To conduct an initial evaluation of the validity of data collected via Alexa, using food and drink intake as an example.

Main Methods:

  • Recruited 45 participants (staff and students) at the University of Bristol for a 7-day study.
  • Participants reported food and drink intake via Amazon Alexa and a parallel web-based form.
  • Collected demographic information and participant feedback on their experience and system acceptability.

Main Results:

  • Out of 37 participants with valid data, 81% were aged 20-39, and 62% were female.
  • Alexa entries matched corresponding web entries for food and drink information in 60.1% of cases.
  • Participants reported frequent interjections from Alexa, particularly during food/drink entry (49%), but 80% expressed willingness to use voice systems in future research.

Conclusions:

  • Despite interaction challenges due to Alexa's conversational nature and interjections, participants showed a high willingness to engage in future research using this technology.
  • The study demonstrates the technical feasibility and participant acceptability of using voice-based systems for data collection in epidemiological research.
  • Further research is recommended to explore less conversational interfaces for voice-based data collection systems in scientific studies.