Testing a Precision Psychotherapy System for Low-income Patients
NCT ID: NCT05118594
Last Updated: 2021-11-18
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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NOT_YET_RECRUITING
NA
111 participants
INTERVENTIONAL
2026-02-28
2026-11-30
Brief Summary
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Detailed Description
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Conditions
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Keywords
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Study Design
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NA
SINGLE_GROUP
TREATMENT
NONE
Study Groups
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Pre-treatment recommendations
Therapists receive automatized feedback at the beginning of the treatments with recommendations regarding the most appropriate interventions to use with their patients based on a machine learning algorithm developed on a previous study.
Pre-treatment psychotherapy recommendations
After patients complete an intake evaluation and prior to starting therapy, the assigned therapist will receive automatized feedback that consists of recommendations regarding the most suitable interventions (i.e., cognitive, behavioral, interpersonal or patient-centered) for each individual patients, based on patients' baseline characteristics and a machine learning algorithm developed in a previous study. Besides the interventions recommended, therapist will receive within the system guideline and tutorial videos showing how to deliver adequately the specific interventions recommended.
Interventions
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Pre-treatment psychotherapy recommendations
After patients complete an intake evaluation and prior to starting therapy, the assigned therapist will receive automatized feedback that consists of recommendations regarding the most suitable interventions (i.e., cognitive, behavioral, interpersonal or patient-centered) for each individual patients, based on patients' baseline characteristics and a machine learning algorithm developed in a previous study. Besides the interventions recommended, therapist will receive within the system guideline and tutorial videos showing how to deliver adequately the specific interventions recommended.
Eligibility Criteria
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Inclusion Criteria
* A score of at least two (mild) in any the five items from the depression and anxiety domains of the DSM-5 Self-Rated Level 1 Cross-Cutting Symptom Measure-Adult
* A total family income below the poverty index threshold, determined by a Licensed Social Worker
* Aged 18 to 65
* Fluency in Spanish language
* Capacity to consent
Exclusion Criteria
* Mania
* Suicidal ideation with intent and/or plan
* Substance abuse disorders
* History of organic mental disease.
18 Years
65 Years
ALL
No
Sponsors
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National Council of Scientific and Technical Research, Argentina
OTHER_GOV
Responsible Party
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Juan Martin Gomez Penedo
Assistant Researcher
Principal Investigators
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Juan M Gomez Penedo, PhD
Role: PRINCIPAL_INVESTIGATOR
National Council of Scientific and Technical Research
Central Contacts
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References
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Solomonov N, McCarthy KS, Gorman BS, Barber JP. The Multitheoretical List of Therapeutic Interventions - 30 items (MULTI-30). Psychother Res. 2019 Jul;29(5):565-580. doi: 10.1080/10503307.2017.1422216. Epub 2018 Jan 16.
Sheehan DV, Lecrubier Y, Sheehan KH, Amorim P, Janavs J, Weiller E, Hergueta T, Baker R, Dunbar GC. The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J Clin Psychiatry. 1998;59 Suppl 20:22-33;quiz 34-57.
Ustun TB, Chatterji S, Kostanjsek N, Rehm J, Kennedy C, Epping-Jordan J, Saxena S, von Korff M, Pull C; WHO/NIH Joint Project. Developing the World Health Organization Disability Assessment Schedule 2.0. Bull World Health Organ. 2010 Nov 1;88(11):815-23. doi: 10.2471/BLT.09.067231. Epub 2010 May 20.
Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001 Sep;16(9):606-13. doi: 10.1046/j.1525-1497.2001.016009606.x.
Spitzer RL, Kroenke K, Williams JB, Lowe B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med. 2006 May 22;166(10):1092-7. doi: 10.1001/archinte.166.10.1092.
Other Identifiers
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ML_LMIC_2021
Identifier Type: -
Identifier Source: org_study_id