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Validation of myStrength's Macropersonalization Engine (PAG-Macro)

T

Teladoc Health

Status

Enrolling

Conditions

Depression, Anxiety
Trauma

Treatments

Other: myStrength Macropersonalization Enginge

Study type

Observational

Funder types

Industry

Identifiers

NCT05417178
PAG_Macro 2022

Details and patient eligibility

About

This is a study to validate myStrength's macropersonalization algorithm. Specifically, the study seeks to answer: Does myStrength's macropersonalization algorithm match what a clinician would offer as a diagnosis following an expert assessment? Participants will be treatment-seeking adults, ages 18 to 65, recruited from an evidence-based group psychotherapy practice. Participants will be asked to complete myStrength onboarding and a clinician-conducted initial assessment. Inter-rater reliability will be assessed to determine the consistency between myStrength and clinician in primary focus area of digital program.

Full description

Rationale and Background: Macropersonalization refers to the rules applied to a member's onboarding data that dictate their primary clinical focus and available interventions that will be recommended. Macropersonalization is a new myStrength feature that is meant to enable myStrength's ability to deliver evidence-based stepped care.

Research Questions: To examine the inter-rater reliability between myStrength's macropersonalization engine and expert clinical recommendations for members' primary clinical focus.

Study Design: This is a one-arm, prospective study.

Population: Study participants will be adults, ages 18 to 65, seeking therapy at an evidence-based psychotherapy group practice.

Data Sources: Anticipated data sources include members myStrength onboarding data, macropersonalization outputs, and clinician-administered clinical assessments.

Data Analysis: A Cohen's kappa will be generated for agreement between myStrength macro-personalization primary focus area and clinician diagnosis to fulfill the primary objective. Conditional kappas based on stratification, as well as a logistic regression, will be used to determine whether demographics or treatment history are associated with concordance, and qualitative analyes will be used to describe sub-clinical or secondary focus areas associated with clinician diagnoses.

Enrollment

200 estimated patients

Sex

All

Ages

18 to 85 years old

Volunteers

No Healthy Volunteers

Inclusion criteria

  • Aged 18 to 85, inclusive
  • Able to read, write, and speak in English
  • Has access to the Internet to complete study procedures
  • Currently engaged in therapy or has schedule an initial appointment with the Pacific Anxiety Group

Exclusion criteria

  • None

Trial contacts and locations

1

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Central trial contact

Sravanthi Dama, MD, MPH; Jessica Yu, PhD

Data sourced from clinicaltrials.gov

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