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| Name | Class |
|---|---|
| Premier Health | OTHER |
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This study will examine the impact of training primary care providers (PCPs) in motivational interviewing (MI) using artificial intelligence (AI) to augment the training process. MI is a patient-centered approach to engaging patients in their own care. There will be a control group and two intervention groups, with the intervention groups receiving a different amount of MI training. The hypothesis is that the AI-augmented MI training will result in improved patient outcomes, improved clinician wellbeing, and reduced behavioral manifestation of clinician biases. This mixed-methods project will also collect qualitative data from structured interviews and focus groups with participating PCPs to examine perceived facilitators and barriers to the use of the MI approach in primary care.
Motivational interviewing (MI) is an evidence-based patient-centered approach that has been demonstrated to be effective in increasing patient engagement in their own care. Using MI, a clinician is compassionate curious to understand patients' perspective on their behavior, and conversationally guides them to discover a need for behavior change. However, MI is not widely utilized in primary care practices and challenging to teach, in part because many primary care providers (PCPs) take a direct approach with their patients by educating and advising them regarding steps to improve their health. However, simply telling patient what to do tends to be ineffective, leading to frustration on the part of both patients and PCPs.
To help implement the MI approach more widely, our team has developed an artificial intelligence (AI) augmented tool for MI skill development, ReadMI™ (Real-time Assessment of Dialogue in Motivational Interviewing). The goal of this project is to: 1) examine the association of AI-measured proficiency in MI to patient outcomes, PCP wellbeing, and PCP manifestations of bias, and 2) to determine the extent to which AI-augmented MI skills training can impact the same outcome, wellbeing, and bias manifestation variables in a randomized controlled trial (RCT). This mixed-methods project will also employ structured interviews and focus groups of participating PCPs to collect qualitative data for better understanding both facilitators and barriers to the implementation of MI in primary care.
The overall hypothesis is that PCPs with the strongest MI proficiencies will have patients with better outcomes, and that those PCPs will also demonstrate less burnout and less manifestation of bias. Additionally, it is hypothesized that making use of AI in MI training will be seen by PCPs as a facilitator to the use of MI in their practices.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Control Group | No Intervention | The control group (CG) will provide survey data and complete role plays with standardized patients for motivational interviewing (MI) assessment at designated project intervals. Premier Physician Network data for these primary care providers (PCPs) will also be obtained at these intervals. | |
| BASIC AI-Augmented Motivational Interviewing Training | Active Comparator | The Basic intervention group will provide survey data and complete role plays with standardized patients for motivational interviewing (MI) assessment at designated project intervals. Premier Physician Network data for these primary care providers (PCPs) will also be obtained at these intervals. Basic PCPs will participate in a didactics session on MI, and subsequently complete two AI (artificial intelligence)-augmented MI training sessions that involve role-play practice of MI. |
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| PLUS AI-Augmented Motivational Interviewing Training | Active Comparator | The Plus intervention group will provide survey data and complete role plays with standardized patients for motivational interviewing (MI) assessment at designated project intervals. Premier Physician Network data for these primary care providers (PCPs) will also be obtained at these intervals. Plus intervention group PCPs will participate in a didactics session on MI, and subsequently complete four AI (artificial intelligence)-augmented MI training sessions that involve role-play practice of MI. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Basic AI (artificial intelligence)-Augmented Motivational Interviewing Training | Behavioral | Basic participants will participate in two motivational interviewing (MI) training sessions that involve role-play practice of MI. Artificial intelligence (AI) will be used to provide metrics on MI-skills (percentage of the time the clinician talks, use of open-ended questions, use of closed-ended questions, use of reflective statements, use of 0-10 scales) as measured by the ReadMI™ tool (Real-time Evaluation of Dialogue in Motivational Interviewing), and both the spirit of MI and presence of bias as measured by Dougall GPT. |
| Measure | Description | Time Frame |
|---|---|---|
| MI Communication Metrics | Motivational interviewing skills/metrics (percentage of time the clinician speaks, number of open-ended questions, number of close-ended questions, number of reflective statements, number of 0-10 scales). Each of the metrics is the total number of occurrences. | Months 4-7, Months 16-20, Months 30-33 |
| MI Spirit | Using a 0-10 scale, the spirit of motivational interviewing (MI) in a role play with a standardized patient will be measured by two artificial intelligence (AI) tools respectively: ReadMI and Dougall GPT. | Months 4-7, Months 16-20, Months 30-33 |
| Measure | Description | Time Frame |
|---|---|---|
| Bias Manifestation | Dougall GPT will be used to identify the number of biases evident in a role play with a standardized patient. | Months 4-7, Months 16-20, Months 30-33 |
| Mini Z (Zero) Burnout Scale 2.0 |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Paul J Hershberger, PhD | Contact | 937-245-7223 | paul.hershberger@wright.edu | |
| Mary Crane, MBA | Contact | 937-245-7218 | mary.crane@wright.edu |
| Name | Affiliation | Role |
|---|---|---|
| Paul J Hershberger, PhD | Wright State University Boonshoft School of Medicine | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Premier Health | Dayton | Ohio | 45409 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 24001658 | Background | Lundahl B, Moleni T, Burke BL, Butters R, Tollefson D, Butler C, Rollnick S. Motivational interviewing in medical care settings: a systematic review and meta-analysis of randomized controlled trials. Patient Educ Couns. 2013 Nov;93(2):157-68. doi: 10.1016/j.pec.2013.07.012. Epub 2013 Aug 1. | |
| 38443862 | Background |
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Only aggregate participant data will be made available to other researchers.
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Primary care provider (PCP) participants will be randomly assigned to intervention (IG) or control (CG) groups, with the Basic IG receiving two ReadMI (Real-time Evaluation of Dialogue in Motivational Interviewing)-supported motivational interviewing (MI) trainings and the Plus IG receiving four MI trainings. Plus will receive two MI trainings at the same time as Basic and will receive two additional MI trainings one year later.
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| Plus AI (artificial intelligence)-Augmented Motivational Interviewing Training | Behavioral | Plus participants will participate in four motivational interviewing (MI) training sessions that involve role-play practice of MI. Artificial intelligence (AI) will be used to provide metrics on MI-skills (percentage of the time the clinician talks, use of open-ended questions, use of closed-ended questions, use of reflective statements, use of 0-10 scales) as measured by the ReadMI™ tool, and both the spirit of MI and presence of bias as measured by Dougall GPT. |
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Ten survey questions (5 pt Likert scale) assessing perceived burnout and factors contributing to burnout. Scores range from 10-50, with 10 indicating the least amount of burnout.
| Months 4-5, Months 16-17, Months 25-26, Months 32-33 |
| Aggregated Patient Data for Each Participating PCP | Data routinely collected by the Premier Physician Network for participating primary care providers (PCPs). All measures are percentages of patients 0% - 100%) indicating that their PCP listened, explained things clearly, and would recommend the PCP). Also, percentages of patients (0%-100%) of patients with poor hemoglobin A1c control, with hypertension control, and completing recommended screenings for each participating PCP are provided. | Months 4-5, Months 16-17, Months 25-26, Months 32-33 |
| Perceived Stress Scale (PSS) | Scale with 10 items (4 pt Likert scale) measuring perceived experience of stress. Scores range from 0-40 with 0 being the least amount of stress. | Months 4-5, Months 16-17, Months 25-26, Months 32-33 |
| Brief Resilience Scale (BRS) | Six-item scale (5 pt Likert scale) assessing responses to stressful periods. Scores range from 6-30 with higher scores indicating more resilience. | Months 4-5, Months 16-17, Months 25-26, Months 32-33 |
| Clinician Support for Patient Activation Measure (CS-PAM) | This 13-item scale (response options range from 1 = not important to 4 = extremely important) assesses PCP (primary care provider) attitudes and self-reported behaviors related the patient engagement in the management of their health conditions. Scores are translated into a 1-100 scale (Rasch methods) with higher scores indicating more positive beliefs about patients' invovlement in their care. | Months 4-5, Months 16-17, Months 25-26, Months 32-33 |
| Stress Mindset Measure (SMM) | This 8-item (5 pt Likert scale ranging from 0=strongly disagree to 4=strongly agree) measures perspectives on stress as debilitating versus enhancing. Scores range from 0 to 32 with higher scores indicating a mindset that stress is enhancing. | Months 4-5, Months 16-17, Months 25-26, Months 32-33 |
| MI Survey Measure | Three items (5 pt Likert scale) assess PCP (primary care provider) attitudes regarding the impact of motivational interviewing (MI) training on confidence, intent to use/incorporation of the MI approach, and importance of MI training for other PCPs. Scores range from 3 to 15 with higher scores indicating more positive regard for MI. | Months 4-5, Months 16-17, Months 25-26, Months 32-33 |
| Diversity Awareness Self-Reflection Tool (DASRT) | SeventeenValues and Attitudes items (three response alternatives for each item ranging from 1=things I do often to 3=things I do rarely) from the Diversity Awareness Self-Reflection Tool will be used to assess PCP (primary care provider) self-awareness of their attitudes and behavior toward patient of diverse backgrounds. Scores range from 17 to 51 with lower scores indicating a higher degree of diversity competency. | Months 4-5, Months 16-17, Months 25-26, Months 32-33 |
| Wright State University | Dayton | Ohio | 45435 | United States |
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| Hershberger PJ, Pei Y, Bricker DA, Crawford TN, Shivakumar A, Castle A, Conway K, Medaramitta R, Rechtin M, Wilson JF. Motivational interviewing skills practice enhanced with artificial intelligence: ReadMI. BMC Med Educ. 2024 Mar 5;24(1):237. doi: 10.1186/s12909-024-05217-4. |
| 34457961 | Background | Hershberger PJ, Bricker DA, Conway K, Torcasio MH. Turning "Lose-Lose" into "Win-Win": What Is Good for Them Is Good for Us! Med Sci Educ. 2021 Mar 30;31(3):1177-1181. doi: 10.1007/s40670-021-01280-4. eCollection 2021 Jun. |
| 23576243 | Background | Chapman EN, Kaatz A, Carnes M. Physicians and implicit bias: how doctors may unwittingly perpetuate health care disparities. J Gen Intern Med. 2013 Nov;28(11):1504-10. doi: 10.1007/s11606-013-2441-1. Epub 2013 Apr 11. |
| 33860162 | Background | Hershberger PJ, Martensen LS, Crawford TN, Bricker DA. Promoting Motivational Interviewing in Primary Care: More Than Intention. PRiMER. 2021 Feb 4;5:7. doi: 10.22454/PRiMER.2021.287928. eCollection 2021. |
| ID | Term |
|---|---|
| D000071069 | Multiple Chronic Conditions |
| D010358 | Patient Participation |
| D002055 | Burnout, Professional |
| D000087302 | Bias, Implicit |
| ID | Term |
|---|---|
| D002908 | Chronic Disease |
| D020969 | Disease Attributes |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
| D010342 | Patient Acceptance of Health Care |
| D000074822 | Treatment Adherence and Compliance |
| D015438 | Health Behavior |
| D001519 | Behavior |
| D000073397 | Occupational Stress |
| D009784 | Occupational Diseases |
| D000077062 | Burnout, Psychological |
| D013315 | Stress, Psychological |
| D001526 | Behavioral Symptoms |
| D011287 | Prejudice |
| D012919 | Social Behavior |
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| ID | Term |
|---|---|
| D000468 | Alkalies |
| ID | Term |
|---|---|
| D007287 | Inorganic Chemicals |
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