Behavioral AI to Predict and Increase Peritoneal Dialysis Uptake

NCT ID: NCT06533254

Last Updated: 2024-12-02

Study Results

Results pending

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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Recruitment Status

RECRUITING

Total Enrollment

3000 participants

Study Classification

OBSERVATIONAL

Study Start Date

2024-09-01

Study Completion Date

2025-12-31

Brief Summary

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Scaled Insights Behavioral AI will be used to improve clinicians ability to detect and understand: The likelihood of patients with kidney failure opting for peritoneal dialysis and to select the right personalized nudge to get CKD patients to choose peritoneal dialysis

Scaled Insights' can utilize the data from this study to develop individualized nudges for healthcare professionals that can be broadly deployed within a digital platform so that clinics across the English speaking world can use it as a means of supporting patients with CKD in selecting peritoneal dialysis treatment.

Using Scaled Insights novel Behavioral Artificial Intelligence solution, the proposed project has two aims:

1. to identify personality attributes of patients with Chronic Kidney Disease and correlating their personality attributes with their subsequent choice of dialysis. Once correlated into personality based clusters, the AI Model will then be able will determine which personality cluster each net new patient will fall into and therefore predict their specific likelihood of opting for peritoneal dialysis or hemodialysis
2. once prediction is possible, customized nudges towards the selection of PD will be developed and tested to improve the likelihood that patients will opt for peritoneal dialysis

Hypotheses:

1. Scaled Insights Behavioral AI will identify the personality characteristics of patients with Chronic Kidney Disease who are likely to opt for both peritoneal dialysis and hemodialysis (Phase 1)
2. Scaled Insights Behavioral AI will identify the nudges that are most effective in encouraging or supporting patients with Chronic Kidney Disease in choosing peritoneal dialysis over hemodialysis (Phase 2)

Detailed Description

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Conditions

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Chronic Kidney Disease

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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Patients who have Chronic Kidney Disease (Phase 1)

Patients who have Chronic Kidney Disease attending clinics managed by Dallas Renal Group in Texas USA, Leeds Teaching Hospitals NHS Trust UK and Suffolk and North East Essex NHS Trust UK will be contacted via their health care provider to invite them to participate.

Predicting choice of dialysis

Intervention Type OTHER

Language data collected using survey 1, will be analyzed using Scaled Insights Behavioral AI solution to identify personality attributes and values. The resulting individual scores will be plotted on a graph and be used to identify specific personality clusters of patients.

Participants will respond to a survey that utilizes open and closed ended questions, asking broad questions about kidney failure and associated behaviors (e.g. diet, attitudes towards treatment). The open-ended questions will gather a natural language sample of 100-300 words whilst closed questions will capture data using Likert scale and multiple-choice responses.

The open-ended questions will gather a natural language sample of 100-300 words for analysis using Scaled Insights Behavioral AI approach. This language sample will be analyzed using Scaled Insights Behavioral AI system to identify personality attributes and values. Patients will also be asked their likelihood of selecting PD over HD.

Patients who have Chronic Kidney Disease (Phase 2)

Patients who have Chronic Kidney Disease and are attending the units managed by Dallas Renal Group in Texas USA, Leeds Teaching Hospitals NHS Trust UK and Suffolk and North East Essex NHS Trust UK.

Behavioral nudges

Intervention Type BEHAVIORAL

Patients with Chronic Kidney Disease, participants will be provided with their predicted personalized nudge to increase their likelihood of either maintaining their choice of peritoneal dialysis, or switching from hemodialysis to peritoneal dialysis.

Participants will respond to a survey that utilizes open and closed ended questions, asking broad questions about kidney failure and associated behaviors (e.g. diet, attitudes towards treatment). The open-ended questions will gather a natural language sample of 100-300 words whilst closed questions will capture data using Likert scale and multiple-choice responses.

Interventions

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Predicting choice of dialysis

Language data collected using survey 1, will be analyzed using Scaled Insights Behavioral AI solution to identify personality attributes and values. The resulting individual scores will be plotted on a graph and be used to identify specific personality clusters of patients.

Participants will respond to a survey that utilizes open and closed ended questions, asking broad questions about kidney failure and associated behaviors (e.g. diet, attitudes towards treatment). The open-ended questions will gather a natural language sample of 100-300 words whilst closed questions will capture data using Likert scale and multiple-choice responses.

The open-ended questions will gather a natural language sample of 100-300 words for analysis using Scaled Insights Behavioral AI approach. This language sample will be analyzed using Scaled Insights Behavioral AI system to identify personality attributes and values. Patients will also be asked their likelihood of selecting PD over HD.

Intervention Type OTHER

Behavioral nudges

Patients with Chronic Kidney Disease, participants will be provided with their predicted personalized nudge to increase their likelihood of either maintaining their choice of peritoneal dialysis, or switching from hemodialysis to peritoneal dialysis.

Participants will respond to a survey that utilizes open and closed ended questions, asking broad questions about kidney failure and associated behaviors (e.g. diet, attitudes towards treatment). The open-ended questions will gather a natural language sample of 100-300 words whilst closed questions will capture data using Likert scale and multiple-choice responses.

Intervention Type BEHAVIORAL

Eligibility Criteria

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Inclusion Criteria

* Phase 1: US and UK adult patients aged 18+ years, with Chronic Kidney Disease stage 4-5.
* Phase 2: US and UK adult patients aged 18+ years, with Chronic Kidney Disease stage 4-5.

Exclusion Criteria

* Phase 1: Young people aged \<18 years. People who do not have Chronic Kidney Disease. People who reside outside of the USA and UK.
* Phases 2: Young people aged \<18 years. People who do not have Chronic Kidney Disease stage 4-5. People who reside outside of the USA and UK.
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Dallas Renal Group

UNKNOWN

Sponsor Role collaborator

The Leeds Teaching Hospitals NHS Trust

OTHER

Sponsor Role collaborator

Suffolk and North East Essex NHS Trust

UNKNOWN

Sponsor Role collaborator

Scaled Insights

INDUSTRY

Sponsor Role lead

Responsible Party

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Stuart W. Flint

Dr Stuart W. Flint

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Stuart W Flint, PhD

Role: PRINCIPAL_INVESTIGATOR

Scaled Insights

Locations

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Dallas Renal Group

Dallas, Texas, United States

Site Status RECRUITING

Countries

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United States

Central Contacts

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Stuart W Flint, PhD

Role: CONTACT

+44 7929404094

Facility Contacts

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Veronica Almanza

Role: primary

214-697-7187

Kim Adams

Role: backup

214-697-7187

Irfan Agha, MD

Role: backup

References

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Flint SW, Brown A, Tahrani AA, Piotrkowicz A, Joseph AC. Cross-sectional analysis to explore the awareness, attitudes and actions of UK adults at high risk of severe illness from COVID-19. BMJ Open. 2020 Dec 29;10(12):e045309. doi: 10.1136/bmjopen-2020-045309.

Reference Type BACKGROUND
PMID: 33376185 (View on PubMed)

Flint SW, Leaver M, Griffiths A, Kaykanloo M. Disparate healthcare experiences of people living with overweight or obesity in England. EClinicalMedicine. 2021 Sep 15;41:101140. doi: 10.1016/j.eclinm.2021.101140. eCollection 2021 Nov.

Reference Type BACKGROUND
PMID: 34585130 (View on PubMed)

Related Links

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https://www.scaledinsights.com/

Website for the AI company that developed the AI solution that will be used in this study.

Other Identifiers

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AI-Dialysis

Identifier Type: -

Identifier Source: org_study_id