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Brain Morphology of Cannabis Users With or Without Psychosis: A Pilot MRI Study
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Using the experience sampling method to support clinical practice: An illustration with problematic cannabis use.

Marilyn L Piccirillo1,2, Matthew C Enkema1, Katherine T Foster1,3

  • 1Department of Psychology, University of Washington, Seattle, WA, USA.

Psychotherapy Research : Journal of the Society for Psychotherapy Research
|March 28, 2023
PubMed
Summary
This summary is machine-generated.

Experience sampling method (ESM) data can personalize cognitive-behavioral strategies for problematic cannabis use. Analyzing granular ESM data offers tailored clinical insights, overcoming interpretation challenges for better treatment outcomes.

Keywords:
cannabis useclinical recommendationscognitive–behavioral strategiesexperience sampling methodmeasurement-based care

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Area of Science:

  • Clinical Psychology
  • Behavioral Science
  • Digital Health

Background:

  • Experience sampling method (ESM) is valuable in clinical research but faces low adoption in practice.
  • Interpreting granular, individual-level ESM data poses challenges for clinical application.
  • Measurement-based care is common, yet ESM integration for personalized treatment remains limited.

Purpose of the Study:

  • To illustrate how experience sampling method (ESM) data can generate personalized cognitive-behavioral strategies for problematic cannabis use.
  • To demonstrate the utility of analyzing ESM data for tailored clinical insights and recommendations.
  • To highlight challenges in interpreting time-series data from ESM for treatment.

Main Methods:

  • Descriptive case series analysis of ESM data from 30 individuals with problematic cannabis use.
  • Data collected four times daily for 16 days, assessing cannabis use, craving, affect, and coping.
  • Analysis involved descriptive statistics and visualizations of individual-level data.

Main Results:

  • ESM data analysis yielded diverse personalized clinical insights and recommendations.
  • Recommendations included psychoeducation on affect/boredom regulation and functional analysis of non-use occasions.
  • Insights addressed the intersection of cannabis use with personal values.

Conclusions:

  • ESM data analysis can inform personalized treatment strategies for problematic cannabis use.
  • Visualizations and descriptive statistics aid in interpreting complex time-series data.
  • Further work is needed to address barriers in interpreting ESM data for widespread clinical use.