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Related Concept Videos

Sampling Methods: Overview01:06

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A sample refers to a smaller subset representative of a larger population. In analytical chemistry, studying or analyzing an entire population is often impractical or impossible. Therefore, samples are used to draw inferences and generalize the whole population. The sampling method selects individuals or items from a population to create a sample. Standard sampling methods include random, judgemental, systematic, stratified, and cluster sampling. 
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Data collection is a systematic method of obtaining, observing, measuring, and analyzing accurate information. An experimental study is a standard method of data collection that involves the manipulation of the samples by applying some form of treatment prior to data collection. It refers to manipulating one variable to determine its changes on another variable. The sample subjected to treatment is known as “experimental units.”
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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population.
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An Application for Pairing with Wearable Devices to Monitor Personal Health Status
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DOSE: An open-source, iOS watch-based tool for experience sampling.

Ian Kim, Sahiti Kunchay, Saeed Abdullah

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    |November 24, 2025
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    Summary
    This summary is machine-generated.

    Researchers created DOSE, an open-source framework for Apple Watch Experience Sampling Methods (ESMs). This practical tool enables easy deployment of ESM studies, showing high response rates and quick interactions in a field study.

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    Area of Science:

    • Digital Health
    • Human-Computer Interaction
    • Psychological Research Methods

    Background:

    • Smartwatches offer low-burden micro-interactions suitable for Experience Sampling Methods (ESMs).
    • The Apple Watch, despite its popularity, lacks accessible frameworks for ESM deployment, hindering research.
    • Existing methods often require technical expertise, limiting broader adoption.

    Purpose of the Study:

    • To develop and evaluate DOSE, an open-source framework for conducting ESM studies using the Apple Watch.
    • To provide researchers with a no-code solution for survey configuration, app building, and data deployment.
    • To assess the feasibility and effectiveness of the DOSE framework in a real-world setting.

    Main Methods:

    • Development of the DOSE framework, an open-source toolkit for Apple Watch ESMs.
    • A 28-day field study involving 18 participants (mean age = 55.3 years).
    • Evaluation of prompt delivery reliability, response rates, and interaction times.

    Main Results:

    • DOSE demonstrated reliable prompt delivery and achieved overall response rates exceeding 80%.
    • Median interaction times for ESM prompts were consistently under 10 seconds.
    • Participants showed improved response efficiency throughout the study duration.

    Conclusions:

    • The DOSE framework is a practical and scalable solution for Apple Watch-based ESMs.
    • It lowers the technical barrier for researchers, facilitating wider adoption of smartwatch-based studies.
    • DOSE provides a robust foundation for advancing mobile health and psychological research using smartwatches.