Global ageing populations require accessible, non-invasive tools for early detection and monitoring of neurological chronic and neurodegenerative diseases. Current diagnostic methods face limitations including invasiveness, high costs and infrequent clinical assessments. The human voice has emerged as a promising digital biomarker, with vocal characteristics reflecting physiological and cognitive changes associated with conditions like dementia and Parkinson’s disease. While artificial intelligence (AI) and machine learning have enabled sophisticated vocal analysis, the literature remains fragmented without comprehensive synthesis. This scoping review protocol delineates a systematic approach to collate and synthesise existing research on the application of AI-driven audio biomarkers for the detection and management of neurological diseases (eg, cognitive decline, Parkinson’s disease, Alzheimer’s, dementia and depression) in older adults aged 65 years and above.

This scoping review will be conducted in accordance with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines and the methodological framework proposed by Arksey and O’Malley, incorporating recent methodological advancements. The eligibility criteria for study selection will be formulated using the PCC (Population, Concept, Context) framework. A comprehensive literature search will be performed across several electronic databases, including PubMed/MEDLINE, Scopus, Web of Science, IEEE Xplore, Embase, Compendex, CINAHL, Scientific Information Database (SID), Magiran, IranMedex and Barakat Knowledge Network System (BKNS). The search will encompass peer-reviewed articles published in Persian and English from 1 January 2012 to 31 March 2026. Two independent reviewers will screen titles, abstracts and full texts and extract data according to the predefined PCC-based eligibility criteria. Discrepancies will be resolved through discussion or, if necessary, by consultation with a third reviewer. The results will be synthesised and presented narratively, accompanied by summary tables, charts and figures to address each research question.

The Research Ethics Committee of Tabriz University of Medical Sciences approved the protocol for this scoping review (approval number: IR.TBZMED.VCR.REC.1404.223). They concluded that since the review involves only analysis of existing literature without direct patient involvement or clinical procedures, it meets the relevant ethical standards. Results from the review will be shared through peer-reviewed journals and conference presentations to provide valuable insights for researchers, clinicians and policymakers on the use of audio-based biomarkers in older adults.

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Programmes based on early childhood development (ECD) services play a vital role in improving child health and developmental outcomes. Across many countries, these programmes target children under 5 years of age—including those who are healthy, at risk or with developmental disorders—and are implemented in governmental and non-governmental organisations in both the health and non-health sectors globally. This protocol outlines a scoping review designed to systematically map and synthesise existing evidence on the components, implementation strategies and delivery mechanisms of ECD services worldwide. The review aims to inform the development of optimised and comprehensive interventions that support holistic child development.

This review will be conducted by Arksey and O’Malley’s framework and its recent advances. Several databases, including PubMed/MEDLINE, Scopus, Science Direct and Web of Science, Scientific Information Database, Magiran, IranMedex and Barakat knowledge network system, will be initially searched for studies up to December 2024. All searches will be done for published or unpublished articles/reports without time and language restrictions. Two researchers will independently carry out screening of the included studies and extraction of data. Any discrepancies will be resolved by consensus. In case no initial consensus is reached, a third researcher will be consulted to make a decision. The findings will be synthesised through the content-analysis method.

The findings of this review may offer a novel perspective for developing a comprehensive package of ECD services within the Iranian health system. Furthermore, it provides a detailed roadmap for researchers and stakeholders aiming to enhance child health and prevent developmental disorders. This study received ethical approval from Tabriz University of Medical Sciences (ID: IR.TBZMED.REC.1404.139), with no ethical concerns as it involves no patient participation or interventions.

There are many barriers to mental health services, including cost and stigma. Even when individuals receive professional care, assessments are intermittent and may be limited in part by the cyclical nature of psychiatric symptoms. The human voice might have the potential to serve as a valuable biomarker in the identification, early diagnosis or monitoring of psychiatric conditions. Therefore, this protocol presents a proposed scoping review with the aim of synthesising existing knowledge on the application of artificial intelligence (AI) or machine learning (ML) in the management of individuals at risk of/suffering from schizophrenia through audio samples as a biomarker.

Guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines and Arksey & O’Malley’s scoping review framework (with recent advancements), we systematically mapped the literature on the application of voice-based biomarkers in schizophrenia. Several databases (PubMed/MEDLINE, Scopus, Web of Science, IEEE Xplore, Embase, Compendex, CINAHL, Scientific Information Database, Magiran, IranMedex and Barakat knowledge network system) will be systematically searched for relevant studies through 2025. All searches will be conducted for peer-reviewed articles/studies published in Persian and English between 1 January 2012 and 1 September 2025. Two researchers will independently carry out screening of the included studies and extraction of data. Any discrepancies will be resolved by consensus. In case no initial consensus is reached, a third researcher will be consulted to make a decision. Findings will be presented narratively in the form of text, summary tables, charts and figures for each research question.

This proposed scoping review is based on publicly available information and is also a review of primary studies, so ethics and publication ethics approval are not required because all data from this study have been previously published. The findings of this review will be published in a peer-reviewed journal and presented at national or international congresses and conferences. Importantly, the initial results from this review will serve as a basis for the design and validation of an intelligent clinical decision support system based on acoustic biomarkers for patients with schizophrenia, using AI or ML techniques.

Not registered.