Adam Lockwood

Purpose: Artificial intelligence (AI) is advancing rapidly with new tools and capabilities emerging quickly. Speech-language pathologists (SLPs) utilize AI in clinical practice, but it is unclear how SLPs use AI tools and the factors that SLPs consider in their decision making. This study presents a survey of school-based SLPs to (a) document the extent and nature of AI use; (b) assess the perceived quality and general opinions of AI; (c) identify ethical, legal, and institutional factors influencing their decisions; and (d) identify the types of AI training currently used and the training SLPs report wanting to receive. Method: Two hundred fourteen school-based SLPs across Ohio completed a survey about the types of AI tools they use, the factors influencing their use, general opinions about AI, and specific concerns about the use of AI in the workplace. The sample was predominantly White (91.3%) and female (97.1%). The average age was 45.17 years, with 19.72 years of professional experience. Participants who used AI within the last 6 months were categorized as “AI users” compared to “non-AI users” who had not. Results: School-based SLPs reported using AI often in their practice across a wide range of tasks. SLPs reported concerns about accuracy or reliability, and ethical concerns as reasons for limiting or not using AI tools. Perceptions of AI quality were mixed, with SLPs divided on whether AI could produce outputs similar to an average practitioner. SLPs reported a significant need for guidance and training in AI tools and ethics. Conclusion: The results highlight the need for clear guidance on the use of AI tools, including ethical implications, along with additional training for school-based SLPs. Supplemental Material: https://doi.org/10.23641/asha.34515978

Psychoeducational reports translate assessment data into decisions about eligibility, services, and instruction, yet research documents persistent problems with their clarity, data-linkage, and usefulness to families and educators (Hale & Brown-Chidsey, 2023; Hite, 2026). Generative artificial intelligence (AI) has entered report writing, and early studies describe its adoption and effects on report quality (Farmer, Lockwood, Floyd, & Sisco, 2025; Lockwood, Farmer et al., 2025). School psychology lacks a structured way to determine when AI assistance is useful, equitable, and defensible and when it introduces risk. This conceptual article proposes a framework organized around three domains: utility, equity, and legal and ethical defensibility. Utility concerns whether reports help intended users understand and act on findings. Equity concerns whether reports improve access while avoiding bias, deficit framing, and unsupported cultural assumptions. Legal and ethical defensibility concerns whether reports preserve practitioner judgment, protect student information, and remain consistent with special education law and professional ethics. The framework considers both where AI is used in a report and the specific task it performs. It supports distinguishing lower-risk from higher-risk uses and informs a proposed risk-stratification system and decision pathway. Implications for practice, training, governance, and research across school psychology are discussed.

Importance: Occupational therapy practitioners are rapidly adopting generative artificial intelligence (GenAI) tools in clinical settings, yet little is known about current usage patterns, ethical concerns, or training needs specific to the profession. Objective: To examine how occupational therapy practitioners are using GenAI in practice and explore their ethical concerns, and training needs. Design: Cross-sectional survey study. Participants: 277 occupational therapists; 77 occupational therapy assistants with a mean age of 40.8 years and a mean of 14.8 years of occupational therapy practical experience. Outcomes and Measures: Self-report questionnaire examining AI usage patterns, perceived advantages and limitations, ethical and institutional factors influencing adoption, and training preferences. Results: 48.9% of participants reported using GenAI in the past 6 months, with common applications including answering work-related questions (38.7%) and generating clinical content. Primary concerns included preference for human judgment (46.2%), accuracy and reliability (45.7%), and ethical issues (38.2%). Only 6.2% reported formal institutional GenAI policies, and 94.8% never entered personally identifiable information into GenAI systems; only 12.2% obtained informed consent from clients, caregivers, or other relevant parties to use GenAI. While 68.3% believed practitioners should receive GenAI training, 42.2% reported receiving no training, with most (73.2%) desiring formal webinar-based instruction. Conclusions and Relevance: Occupational therapy practitioners reported significant GenAI use. Participants also noted substantial concerns about ethical implementation, data security, and loss of clinical skills. Findings suggest that critical gaps in formal training and institutional guidance exist. Evidence-based frameworks and structured educational initiatives to ensure GenAI integration aligns with client-centered, ethical practice standards are needed.

Artificial intelligence (AI) is rapidly influencing various fields. Its emergence has a strong potential to impact school consultation practice by reducing administrative burden, providing extensive support for the consultee, and supporting data-based decision-making. Although school consultants, such as school psychologists, increasingly adopt AI in summarization, writing, and recommendations during school consultation, the ethical use of AI in consultation has not yet been clearly delineated. This article describes how AI can support four phases of a well-established consultation modality, problem-solving consultation. We propose an augmented triad framework, where AI plays a partner that assists consultants with organization, reflection, skill development, follow-up intervention support, and data visualization. This framework also highlights ethical considerations when using AI in each phase. The article concludes with implications for research and practice that encourage empirical evaluation of AI use in school consultation, safeguards for privacy and bias, as well as professional training for responsible and equitable integration of AI into school consultation.

Consultation is a core function of school psychology practice and serves as a primary means of supporting student outcomes (i.e., National Association of School Psychologists, 2020). School-based c...

Multilingual (ML) students represent a growing portion of the U.S. public school population, yet school psychologists often lack the linguistic resources needed to provide translated psychoeducational materials. Machine translation (MT) tools such as Google Translate (GT) and ChatGPT-4o (GPT) offer potential solutions, but their effectiveness for translating psychoeducational reports remains underexamined. This study evaluated the fluency, accuracy, and error patterns of English-to-Spanish translations generated by GT, GPT, and a professional human translator (HT) using a fictional psychoeducational report summary. Two bilingual graduate students rated 71 translated sentences using fluency and accuracy rubrics, with disagreements resolved by a bilingual school psychologist. Results indicated no significant differences in fluency across systems. Accuracy differed significantly across systems overall, although follow-up pairwise comparisons were not statistically significant after correction. Analyses also revealed significant differences in the total number of errors produced across translations, but no significant differences in the distribution of specific error types. Across systems, errors included mistranslations, grammatical errors, untranslated words, and critical inaccuracies that affected interpretability. Overall, no translation method produced a perfect translation. However, results remain preliminary and require further study. Implications for school psychologists include the need to improve the readability of psychoeducational reports and ensure that translators’ workflows are supported by appropriate training and oversight.

Background and Purpose: Generative artificial intelligence (AI) tools are increasingly accessible to healthcare professionals, yet little is known about how physical therapists (PTs) and physical therapist assistants (PTAs) perceive and use these technologies. This study examined the extent and nature of generative AI adoption, perceptions of AI quality and ethicality, barriers to use, and training needs among physical therapy professionals in Ohio.Methods: A cross-sectional survey following STROBE guidelines was distributed to Ohio Physical Therapy Association members via email in April–May 2025. The analytic sample comprised 389 respondents (285 PTs, 104 PTAs). Descriptive statistics characterized adoption patterns, perceptions, barriers, and training experiences. Mann-Whitney U tests with Benjamini-Hochberg correction compared attitudes between professional groups.Results: The majority of PTs (57.9%) and PTAs (75.0%) reported no work-related AI use in the past six months. Among users, AI was applied primarily to administrative tasks such as answering questions, generating emails, and creating summaries rather than direct clinical decision-making. Nearly all users reported editing AI-generated content before professional use (PTs: 91.7%; PTAs: 96.0%), and over 97% of both groups had never entered personally identifiable information into AI systems. Perceptions of AI-generated content quality were cautiously neutral, with PTs rating quality slightly higher than PTAs across all domains. Both groups endorsed practitioner AI training as an ethical priority (PTs: M = 4.89; PTAs: M = 4.20 on a 7-point scale). More than half of respondents reported no formal workplace AI policy (PTs: 54.4%; PTAs: 60.6%), and the vast majority had received no training in AI prompt development (PTs: 81.8%; PTAs: 84.5%). The most common barriers were unfamiliarity with AI tools, uncertainty about clinical integration, and concerns about accuracy. PTs held significantly more favorable attitudes toward AI than PTAs regarding trust, perceived helpfulness, and report-writing capability.Conclusion: Generative AI adoption in physical therapy remains limited, constrained by knowledge gaps, insufficient training, and a substantial absence of institutional policy. Practitioners who use AI demonstrate appropriate oversight practices but lack formal guidance and professional development support. These findings highlight the need for targeted AI education, clear workplace policies, and profession-specific guidelines to support safe and effective integration of AI into physical therapy practice.

Objective:Artificial intelligence (AI) is increasingly used across healthcare and education professions, yet cross-professional evidence on adoption and governance practices remains limited. This study examined differences across allied health and related service professionals in AI use, disclosure practices, beliefs about informed consent, and training experiences.Methods:Participants were 1,350 allied health and related service professionals practicing in Ohio, including physical therapists, occupational therapists, speech-language pathologists, school psychologists, counselors, nurses, and assistant-level providers. The survey was adapted from prior school psychology AI studies and refined with multidisciplinary task force input. Analyses examined differences across professional roles in frequency of AI use, disclosure practices, informed consent beliefs, and type of AI training received. Missing data were addressed using multiple imputation.Results:AI use differed significantly across professional roles, with school psychologists, counselors, and speech-language pathologists reporting the highest levels of use, and occupational therapy assistants and physical therapy assistants reporting the lowest. Disclosure practices also varied significantly, with school psychologists and speech-language pathologists reporting greater disclosure than several other groups. Differences in informed consent practices were statistically significant but small, with school psychologists, counselors, and speech-language pathologists somewhat more likely to report obtaining consent, and assistants and nurses somewhat more likely to report not obtaining consent. Training disparities were pronounced: school psychologists, counselors, and speech-language pathologists were more likely to report formal AI training, whereas assistants were substantially more likely to report no AI training.Conclusions:AI adoption and governance-related practices vary meaningfully across school-based and related service professions. These differences suggest uneven preparedness for ethical and coordinated AI integration across professional roles. Findings underscore the need for clearer guidance, stronger training pathways, and greater attention to disclosure and consent practices as AI becomes more embedded in professional service delivery.

Artificial intelligence (AI) tools are increasingly available to psychologists, yet little is knownabout how licensed health service psychologists are integrating these technologies into practiceor how they perceive their ethical implications. This descriptive survey examined AI use, ethicalperceptions, privacy and disclosure practices, barriers to adoption, and training needs among 518members of the National Register of Health Service Psychologists. Roughly 57% reported usingAI for work purposes in the past six months; among AI users, 51.4% of AI users reported weeklyor daily use. The most common professional applications were answering work-relatedquestions, generating easy-to-understand explanations, creating presentation content, and writingsession or progress notes. Roughly 55% felt that AI is helpful in practice, whereas only 20.0%agreed that they trust AI. Ethical concerns were application-specific, with the greatest concernsinvolving AI-assisted test interpretation and report writing. Privacy and disclosure findingssuggested gaps between professional expectations and practice; 73.0% believed practitionersshould routinely disclose AI use to clients, yet reported disclosure was infrequent. Most AI usersreported that they had not entered protected health information into AI tools, although relativelyfew reported using HIPAA-compliant vendors or business associate agreements. Among nonusers,the most common barriers were ethical, privacy/confidentiality, and accuracy/reliabilityconcerns. Findings suggest that AI use in psychological practice is no longer hypothetical andunderscore the need for application-specific ethical guidance, privacy-compliance training, andevidence-informed professional development.Keywords: artificial intelligence, psychological practice, ethics, technology adoption,health service psychologistsIntroductionThe Rise of Artificial Intelligence in Professional PracticeThe integration of artificial intelligence (AI) technologies into professional practice hasaccelerated dramatically in recent years. Reports from major consulting firms indicate that AIadoption is reshaping how professionals across sectors—from healthcare to education tobusiness—accomplish their work (Singla et al., 2025; Microsoft & LinkedIn, 2024). Thesetechnologies, particularly large language models capable of generating human-like text, havemade powerful AI tools accessible to professionals without specialized technical expertise. Toolssuch as ChatGPT, Claude, and similar platforms have achieved unprecedented penetration intothe professional workforce, raising critical questions about how different professions areadopting, adapting to, and ethically integrating these technologies into their practice (NationalAcademies of Sciences, Engineering, and Medicine, 2024).

Many Catholic schools face resource challenges that result in limitations surrounding the implementation of multi‐tiered systems and support (MTSS). Artificial intelligence (AI) offers a potential tool for Catholic schools to strengthen systems of support. This article provides a conceptual analysis regarding opportunities for AI to strengthen core components of MTSS, such as identifying evidence‐based interventions, developing progress monitoring tools, analyzing student data, and facilitating personalized instruction. The article also discusses the challenges and limitations of leveraging AI within Catholic schools, specifically when supporting staff and students. Although the article is focused on US contexts, there are conceptual implications that may extend to Catholic schools' systems internationally, specifically related to strengthening the mission of Catholic education. Future researchers should consider evaluating and analyzing the implementation of AI tools within MTSS, specifically how AI tools may support Catholic schools with resource limitations, time constraints, and expertise barriers.