Artificial Intelligence (AI) Usage Policy

Authors may use generative AI or AI-assisted technologies to support activities such as language improvement, literature organization, idea development, transcription support, preliminary coding, thematic organization, data exploration, visualization, or manuscript preparation. AI tools must not replace the authors' critical thinking, scientific judgment, qualitative interpretation, health-promotion judgment, contextual understanding, reflexivity, or original scholarly contribution.

Authors are responsible for:

• verifying factual accuracy and checking references generated by AI;
• reviewing and substantially editing AI-assisted content;
• checking for bias, hallucination, fabricated citations, misleading health information, or inappropriate interpretation;
• independently validating AI-assisted transcription, coding, theme development, classification, analysis, and interpretation;
• protecting confidential, personal, health-related, copyrighted, culturally sensitive, and unpublished data;
• ensuring that identifiable participant information, interview transcripts, recordings, field notes, and sensitive health information are not entered into public AI systems without lawful authorization and appropriate safeguards; and
• ensuring that the final manuscript represents the authors' own scholarly interpretation and professional judgment.

Meaningful use of generative AI in manuscript preparation, transcription, coding, thematic analysis, literature synthesis, data analysis, visualization, or other research activities must be disclosed in a separate AI Declaration. The declaration should identify the tool or model used, its purpose, the tasks performed, and the extent of human review, verification, reflexive assessment, and scholarly oversight.

Basic spelling, grammar, punctuation, or conventional language editing does not normally require disclosure. If AI forms part of the research method, transcription process, qualitative coding, thematic analysis, health-promotion intervention, predictive model, data processing, or statistical analysis, its use must be described in sufficient detail in the Methods section.

AI tools, chatbots, autonomous systems, and language models must not be listed as authors or co-authors. Authorship requires human responsibility for the integrity of the work, approval of the final manuscript, accountability for scientific and ethical content, and the ability to respond to questions regarding the research, participants, qualitative interpretation, health-promotion implications, data, analysis, and conclusions.

Generative AI must not be used to create, manipulate, obscure, remove, or introduce features in participant photographs, fieldwork images, screenshots, health-promotion materials, interview-related visual data, charts, figures, or other research images submitted as evidence in a manner that misrepresents the underlying research.

AI-assisted enhancement must not alter participant characteristics, contextual meaning, health-related findings, observational evidence, or the scientific interpretation of the visual material.

An exception may apply when AI-assisted image analysis, computer vision, synthetic-data generation, visual-content analysis, or digital-health technology is part of the research design or methodology. In such cases, authors must describe the tool, model/version, procedure, validation process, dataset characteristics, ethical safeguards, and its role in generating or interpreting research data in the Methods section.

Submitted manuscripts are confidential documents. Reviewers must not upload manuscripts, manuscript excerpts, participant information, interview transcripts, recordings, field notes, health data, supplementary files, datasets, or review reports into public generative AI systems.

Peer review is a human scholarly responsibility. AI tools must not be used to generate scientific assessments, independently evaluate qualitative rigor, determine credibility or trustworthiness, interpret participant narratives, assess health-promotion relevance, or produce review recommendations. Reviewers remain personally responsible for the accuracy, fairness, confidentiality, and integrity of their reports.

Editors must not upload submitted manuscripts, confidential correspondence, reviewer reports, participant information, interview transcripts, field notes, sensitive health data, or editorial decision letters into public generative AI systems.

AI must not replace human editorial judgment or be used to determine acceptance, revision, or rejection. Editors remain fully responsible for scientific evaluation, methodological assessment, qualitative rigor, health-promotion relevance, ethical review, confidentiality, communication, and final publication decisions.