Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

Currently submitted to: JMIR Formative Research

Date Submitted: May 8, 2026
Open Peer Review Period: May 9, 2026 - Jul 4, 2026
(currently open for review)

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Engagement, Satisfaction, and Therapeutic Alliance with an Artificial Intelligence Conversational Agent for Parents: Quantitative Descriptive Study

  • Karin Mostovoy; 
  • Blanca S. Pineda; 
  • Arjun Bharat; 
  • Tyrique Patterson; 
  • Jing Mao; 
  • Carlos Felipe Rivera-Cepeda; 
  • Daniel M Bagner; 
  • Antonio Y. Hardan; 
  • Eduardo E. Bunge

ABSTRACT

Background:

Parent Management Training (PMT) is an evidence-based intervention for addressing child behavioral difficulties; however, caregivers often need additional guidance when implementing skills in daily life. Pat is an artificial intelligence (AI) conversational agent (CA) designed to augment a therapist-led PMT program by providing caregivers with real-time guidance, reinforcement, and answers to parenting questions between sessions.

Objective:

The present study explored caregivers’ engagement with Pat, satisfaction, and the therapeutic alliance formed between caregivers and Pat during group PMT delivered online.

Methods:

Data from 88 caregivers of children aged 3 to 14 years participating in an online PMT program were analyzed at three time points (Week 4, 8, and 12). Engagement with Pat was measured through the number of messages exchanged with Pat, modules completed, in-the-moment support chats, and days the platform was used. Satisfaction with the intervention was measured using the Net Promoter Score (NPS) and the Therapy Attitude Inventory (TAI). The therapeutic alliance between caregivers and Pat was assessed using the Working Alliance Inventory-Short Form Revised.

Results:

Caregivers exchanged a high number of messages with Pat (M = 383.09 by week 4 and M = 726.47 by week 8) and completed multiple required and optional modules (M = 5.41 at week 4; M = 10.49 at week 8). Satisfaction remained high across all time points, with strong NPS (77.8 at week 4; 76.7 at week 8; and 75 at week 12) and no significant differences across Weeks 4, 8, and 12 (F(2,114) = 0.10, p = .909). Therapy attitudes increased significantly from Week 4 (M = 4.22) to Week 8 (M = 4.49) and remained stable through Week 12 (F, 2, 114) = 5.69, p = .004). Therapeutic alliance ratings with Pat were consistently high across time points (M = 4.10 at week 4; M = 4.10 at week 8; and M = 4.04 at week 12), with no significant differences across weeks (F(2,114) = 0.182, p = .834).

Conclusions:

These findings show that caregivers meaningfully engaged with Pat, remained highly satisfied across time, established a strong therapeutic alliance, and held positive therapy attitudes. Overall, the hybrid group model integrating human therapists with Pat may represent a promising and efficient strategy for enhancing engagement and providing scalable and real-time support to parenting programs.


 Citation

Please cite as:

Mostovoy K, Pineda BS, Bharat A, Patterson T, Mao J, Rivera-Cepeda CF, Bagner DM, Hardan AY, Bunge EE

Engagement, Satisfaction, and Therapeutic Alliance with an Artificial Intelligence Conversational Agent for Parents: Quantitative Descriptive Study

JMIR Preprints. 08/05/2026:100302

DOI: 10.2196/preprints.100302

URL: https://preprints.jmir.org/preprint/100302

Download PDF


Request queued. Please wait while the file is being generated. It may take some time.

© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.