Empowering Caregivers in ADHD Treatment: Standard Care Vs. Decision Aid, Coaching, and AI Support

The goal of this clinical trial is to evaluate different decision-support interventions to help parents make informed treatment decisions for their children with ADHD. The study will compare four approaches to assess their impact on decision-making quality, decisional conflict, and treatment adherence among parents of children aged 6-17 years diagnosed with ADHD. The main questions it aims to answer are: Does providing parents with decision-support tools improve decision-making quality compared to standard care? Do decision aid, decision aid + decision coaching, and AI-driven support further enhance parental self-efficacy, knowledge, and adherence to treatment decisions? Standard care (physician consultation only) A written decision aid (structured booklet) Decision aid + decision coaching (booklet + one-on-one coaching session) AI-driven support (interaction with an AI tool) Participants will: Complete a baseline questionnaire before the intervention Receive their assigned decision-support intervention (if applicable) Complete follow-up questionnaires at 2 weeks and 3 months after the intervention Report on treatment decisions and medication adherence over 3 months This study will determine whether structured decision aids, coaching, or AI-driven tools improve parental decision-making and treatment adherence in ADHD care.

This randomized controlled trial (RCT) aims to evaluate the effectiveness of different decision-support interventions in helping parents of children with ADHD make informed treatment decisions. The study will assess the impact of structured decision aids, decision coaching, and AI-driven support on parental decision-making quality, decisional conflict, self-efficacy, knowledge, and treatment adherence. Participants will be randomly assigned to one of four study arms: standard care, a written decision aid, decision aid plus decision coaching, or AI-driven support. Outcomes will be measured at baseline, two weeks, and three months post-intervention. Rationale ADHD is a common neurodevelopmental disorder affecting children worldwide. Treatment options primarily include medication or no medication, each with associated risks and benefits. Shared Decision Making (SDM) is recognized as a best-practice model, ensuring treatment decisions align with parental values and preferences. However, parents often face challenges in weighing options, understanding treatment effects, and feeling confident in their decisions. This study seeks to compare decision-support interventions to determine their effectiveness in enhancing decision-making quality, reducing decisional conflict, and improving parental knowledge and treatment adherence. Study Design This is a four-arm, parallel-group, randomized controlled trial. Participants will be randomly assigned in a 1:1:1:1 ratio to one of four arms: Standard Care (Control Group): Parents receive a routine consultation with their physician, discussing ADHD treatment options without additional structured decision-support tools. Written Decision Aid (DA): Parents receive a structured booklet, developed using IPDAS guidelines, detailing medication vs. no medication options, including their risks and benefits, to facilitate informed decision-making. Decision Aid + Decision Coaching (DA+DC): Parents receive the written decision aid along with a one-on-one decision coaching session, where a trained facilitator helps them clarify values, address concerns, and enhance decision confidence. AI-Driven Support: Parents interact with an AI-based decision support tool (Claude), initially responding to 10 structured prompts, followed by 15 minutes of free interaction, and then receiving an AI-generated summary of their decision-relevant queries. Participant Recruitment and Enrollment Participants will be recruited through an open call from the research lab. Interested individuals will contact the research assistant, who will screen for eligibility and obtain informed consent before randomization. Upon enrollment, participants will complete a baseline questionnaire assessing their initial decision-making state, knowledge, and values. Those assigned to one of the intervention arms will receive their respective decision-support intervention immediately after completing the baseline assessment. Interventions Standard Care: Participants will discuss ADHD treatment options with their physician without structured decision support. Written Decision Aid: A booklet designed based on IPDAS criteria, containing balanced, evidence-based content about medication vs. no medication, value clarification exercises, and FAQs to enhance comprehension. Decision Coaching: A trained facilitator will conduct a structured decision coaching session, using a script developed based on the Ottawa Personal Decision Guide (OPDG). The session will help parents explore treatment preferences, clarify values, and express concerns in a structured manner. AI-Driven Support: Parents will interact with Claude, an AI-based large language model, following structured prompts and engaging in open-ended queries to explore ADHD treatment decisions. The AI-generated summary will provide key insights and reinforce understanding. Outcome Measures Primary Outcomes: Decisional Conflict (DCS): Measures parental uncertainty, clarity of values, and confidence in treatment decisions. Higher scores indicate greater uncertainty, while lower scores reflect improved decision-making clarity. Decision-Making Quality (DMQS): Evaluates how well-informed and values-aligned the parent's decision is, reflecting their engagement in a structured, evidence-based decision-making process. Secondary Outcomes: Parental Knowledge (CAKe): A 10-item questionnaire assessing understanding of ADHD and treatment options. Parents' Values: A 6-item scale measuring the importance parents assign to various treatment-related outcomes. Health Literacy (REALM): A validated tool screening for the ability to comprehend medical information. Numeracy (SNS): An 8-item scale assessing mathematical ability and preference for numerical information. Decision Self-Efficacy: An 11-item scale measuring parents' confidence in making an informed treatment decision. ADHD Care: Tracks treatment received and medication adherence over three months. Preparation for Decision-Making: A validated scale assessing how well the decision aid prepared parents for shared decision-making. Preference for SDM: A single-item question evaluating the parent's preferred level of involvement in decision-making. Demographics: Age, gender, education level, nationality, religion, religiosity, marital status, and number of children. Data Collection and Follow-Up Baseline Assessment: Participants complete questionnaires before the intervention. Post-Intervention Assessment: Follow-up assessments at two weeks and three months after intervention. ADHD Care Tracking: Parents report treatment choices and adherence over the three-month period. Sample Size and Randomization A power analysis determined that 144 participants (36 per arm) are needed to detect a meaningful difference in decisional conflict with 80% power and a 5% significance level, accounting for a 10% dropout rate. Randomization will be conducted using computer-generated block randomization to ensure balanced distribution across arms. Statistical Analysis Plan Data will be analyzed using SPSS version 29 and R. Statistical methods include: Descriptive statistics: Means, standard deviations, frequencies, and percentages for baseline characteristics. Comparative analyses: Paired t-tests or Wilcoxon signed-rank tests for pre-post changes. One-way ANOVA or Kruskal-Wallis tests for subgroup comparisons. Regression models: Linear regression for relationships between SDM measures and continuous outcomes. Logistic regression for categorical outcomes such as treatment adherence. Multiple imputation methods will address missing data if the rate exceeds 5%. Sensitivity analyses will validate the robustness of findings. Ethical Considerations This study has been approved by the Ariel University IRB (AU-HEA-YG-20240520). All participants will provide written informed consent before participation. Data confidentiality will be maintained through de-identified coding and secure storage. Expected Impact This study will provide valuable insights into the effectiveness of decision-support interventions in ADHD treatment. Findings may inform best practices for integrating decision aids, coaching, and AI-driven tools into clinical workflows, enhancing shared decision-making and improving parental confidence, treatment adherence, and child health outcomes.