Actionable companion · Assessment and evidence of learning

From evidence to district action: Generative AI use and social disparities in pediatric rehabilitation: a cross-sectional study of ChatGPT use among parents of children with speech and language disorders in Türkiye

AI-assisted editorial implementation guide. The district actions are proposed applications, not findings or recommendations attributed to the original authors. No additional peer review is asserted.

Evidence and context

Confirm the study population, setting and task before applying its findings to your district.

Original authors’ abstract, reproduced under the linked source license:

Abstract Background Generative artificial intelligence (AI) tools such as ChatGPT are increasingly used for health information seeking. However, little is known about how the adoption of generative AI is socially patterned, particularly in pediatric rehabilitation contexts. This study aimed to examine the prevalence and sociodemographic determinants of ChatGPT use among parents of children with speech and language disorders (SLDs) in Türkiye and to explore its association with engagement in formal speech and language therapy services. Methods This cross-sectional study included 204 parents of children with SLDs recruited through online parent networks between October and November 2025. Data were collected using a structured questionnaire assessing sociodemographic characteristics, therapy attendance frequency, and ChatGPT use for SLD-related information. Bivariate associations were analyzed using chi-square tests, and multivariable logistic regression was conducted to identify independent predictors of ChatGPT use. Results Overall, 28.4% of participants reported using ChatGPT to seek information related to their child’s speech or language disorder. ChatGPT use was significantly associated with gender, age group, and educational level. In multivariable analyses, male gender (aOR = 3.09; 95% CI: 1.36–7.02) and postgraduate education (aOR = 5.20; 95% CI: 1.56–17.27) were independently associated with higher odds of ChatGPT use, while undergraduate education did not reach statistical significance (aOR = 1.55; 95% CI: 0.70–3.42; p = 0.277). Attending therapy several times per year (aOR = 4.01; 95% CI: 1.08–14.92) and monthly or weekly (aOR = 2.75; 95% CI: 1.01–7.48) were both associated with higher odds of ChatGPT use relative to never attending therapy. Conclusion Generative AI use among parents of children with SLDs appears relatively common but socially stratified. Educational attainment, gender, and engagement with formal therapy services significantly influence AI adoption. Without equity-oriented strategies and digital health literacy initiatives, the diffusion of generative AI tools may reinforce existing informational disparities in pediatric rehabilitation. Keywords: ChatGPT, digital divide, generative artificial intelligence, pediatric rehabilitation, speech and language disorders

A 90-day district pilot

1. Days 1–15 · Appraise. Have the curriculum lead and a teacher read the methods and limitations. Record the study design, sample, comparator, outcomes and evidence gaps. Define a local question that the study can help inform.
2. Days 16–30 · Design. Redesign one low-stakes assessment: require a first attempt, an AI-assisted revision, a source-check log and a short oral explanation. Use the same rubric for the comparison task. Name an accountable owner and set the baseline, success threshold and budget before implementation.
3. Days 31–60 · Test. Start with a small voluntary cohort, preserve an accessible non-AI route and require teacher review. Use synthetic or de-identified examples; approve data handling and tool terms through district processes.
4. Days 61–90 · Decide. Blind-score reasoning, factual accuracy and unaided transfer on a fresh task. Record suspected misconduct separately from demonstrated evidence. Compare with baseline, document uncertainty and stop or revise if learning worsens, access is unequal or critical errors persist.

The board decision brief

Report the learning problem, evidence quality, participating population, total cost including review time, measured benefit, errors, access differences and remaining uncertainties. Make a dated recommendation to stop, revise or expand. A positive perception survey alone does not establish learning improvement.

Attribution and reuse

Agit Şimşek; Zehra Güneş. Generative AI use and social disparities in pediatric rehabilitation: a cross-sectional study of ChatGPT use among parents of children with speech and language disorders in Türkiye. Frontiers in Public Health (2026-06-08). https://doi.org/10.3389/fpubh.2026.1817290

Companion prepared 2026-10-30. Original authorship and DOI are preserved. The abstract is an attributed source extract; the implementation plan is new AI-assisted editorial material, offered under the same CC BY 4.0 license. This guide has not undergone independent peer review.