Human papillomavirus (HPV) is one of the most common sexually transmitted diseases and affects the quality of life (QoL) of individuals, necessitating interventions beyond physical treatments. The aim of this study is to determine the effectiveness of individual supportive counselling on the QoL in women with high-risk HPV.

This randomised clinical trial will include 80 women with HPV who will be selected from 2025 to 2026 in Babol, Iran. Following selection based on inclusion criteria, samples will be randomly allocated to intervention and control groups. Then, they will complete demographic–social questionnaires, QoL in HPV patients and general health questionnaires. Individuals in the intervention group will receive 4 weekly online supportive counselling sessions in addition to routine care. The control group will receive routine care. Both groups will complete the questionnaires again at 6 weeks and 4 months postbaseline. Data will be analysed using SPSS V.26 software and statistical tests including ², t-test and repeated measures analysis of variance, and regression models if necessary. A significance level of 5% will be used for the tests.

This study was approved by the Ethics Committee of Babol University of Medical Sciences (IR.MUBABOL.HRI.REC.1404.082). The trial will adhere to the ethical principles of the Declaration of Helsinki. Findings will be disseminated through publication in peer-reviewed journals and presentation at scientific conferences.

IRCT20180218038783N11, 14 September 2025.

Healthcare logistics involves the coordination of resources, services and infrastructure to ensure timely and efficient care delivery. Process mining offers data-driven insights into logistical workflows such as patient transport, inventory management and scheduling. This systematic review aims to synthesise evidence on the application of process mining in healthcare logistics, focusing on its impact on operational efficiency, resource utilisation and service delivery.

A systematic search will be conducted in MEDLINE, Embase, Google Scholar, Web of Science and ABI/Inform for studies published from 1999 onward. Eligible studies will include observational studies, case reports, conference papers and meta-analyses focusing on process mining applications to logistical processes in healthcare settings. Studies screening, data extraction and methodological quality assessment will be conducted using the Mixed Methods Appraisal Tool. Data will be extracted on key dimensions and performance indicators and will be presented in a structured format. A narrative synthesis will be conducted, and findings will be categorised and thematically analysed where appropriate. Primary outcomes include improvements in logistical efficiency, traceability, resource utilisation and sustainability. Secondary outcomes include implementation challenges, data integration issues and limitations in applying process mining techniques to logistical workflows.

The results of the systematic review will be disseminated via publication in a peer-reviewed journal and presented at a relevant conference. The data we will use do not include individual patient data, so ethical approval is not required.

CRD420251164812.

The surge in postsecondary students reporting mental health concerns, coupled with increased utilisation of on-campus and hospital-based mental healthcare, highlights a need to understand effective service navigation. To address this system gap, the University of Toronto and the Centre for Addiction and Mental Health (CAMH) leveraged their unique expertise and resources to develop the University of Toronto Navigation (UTN) service. UTN introduces care navigators to facilitate postsecondary student transitions from acute mental health services to community or campus mental healthcare. There has been limited implementation and evaluation of navigator models specific to the postsecondary context to date, which hinders scalability. This paper describes the study protocol of Navigation to Enhance Post-Secondary Students’ Acute Mental Health Care Transitions, a study that aims to collaborate with students, navigators and clinicians to evaluate the UTN service.

A one-stage, single-arm multimethods study design will be used to evaluate the UTN service. We will recruit 103 students following their UTN intake appointment. Students will complete quantitative measures assessing health outcomes, experiences of care and service utilisation at baseline and at three subsequent time points across a 6-month follow-up period. The quantitative data will be linked to administrative healthcare data. The primary evaluation outcome will be defined as attending an appointment with an appropriate care provider (in person or virtually) within 30 days of discharge from the hospital. We will conduct interviews with students and referring clinicians to gather perspectives regarding their experiences and satisfaction with the UTN service in greater depth.

Research ethics board approvals have been obtained from the University of Toronto and CAMH. Results will be disseminated through publications and presentations, and a toolkit will be cocreated to support implementation and adaptation of hospital-based navigator interventions in postsecondary contexts.

Digital technology in primary healthcare service delivery can enhance accessibility, service delivery and health outcomes in rural populations. The objective of this systematic review is to review and synthesise the scope and impact of digital health technology innovations within rural primary healthcare settings.

Systematic review.

Articles published on PubMed, PsycINFO, Cochrane Central, SCOPUS, Web of Science, EMBASE and CINAHL between January 2013 and October 2025 were searched using key search terms.

Patient, intervention, context, outcome model criteria guided article eligibility. Included articles were undertaken in rural populations, used digital health technology for treatment or management, explored the impact of digital health technology on rural primary healthcare and reported on healthcare outcomes. Included articles were in the English language and presented peer-reviewed primary research.

Extraction was performed using a bespoke standardised template by multiple reviewers. Quality assessment was undertaken using the Mixed Methods Appraisal Tool. Descriptive analysis and conventional inductive content analysis were applied to quantitative and qualitative data, respectively. The review is written in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols statement guidelines.

66 studies were included in the review. Most studies were conducted in the USA (n=26). Most studies focused on adult patient populations, with limited representation of Indigenous (In=3) and paediatric populations (n=2). Telemedicine/telehealth interventions using audio, video or both were the most common (n=36). Remote patient monitoring or point-of-care testing was integrated into 21 studies. Physical health conditions, particularly diabetes (n=17), cardiovascular diseases (n=11) and general primary healthcare concerns (n=13) were commonly reported. Others reported on areas including mental health, hypertension, obesity and pregnancy care.

Conventional inductive content analysis identified key themes: cost and time effectiveness, quality healthcare provision, consumer acceptance from both patients and practitioners, and healthcare service provider perspectives. Uptake barriers included staff workload and patient non-compliance, while facilitators encompassed process standardisation and practitioner acceptance and endorsement. Consumer acceptance was linked to satisfaction, willingness to engage and improved health outcomes and well-being.

Digital health interventions in rural primary healthcare offer significant potential to improve healthcare delivery, reduce costs and enhance patient access, satisfaction and health outcomes. However, careful consideration of factors such as feasibility, consumer and practitioner acceptance, and recognition of limitations is crucial for successful implementation. The review underscores the importance of flexible policies to support emerging digital healthcare solutions, including the integration of artificial intelligence. Overall, digital health interventions offer a promising avenue to improve healthcare outcomes in rural areas and should be prioritised for government funding and investment.

CRD42023477233.

Digital health interventions (DHIs) are changing the healthcare landscape. However, using these tools effectively for people with chronic conditions in rural areas comes with challenges, highlighting the need to understand their lived experiences. No systematic review was found that examines the inclusion of lived experience in DHI for individuals with chronic conditions in rural areas and how this impacts their acceptance of technology. A systematic review grounded by Technology Acceptance Model (TAM) will be conducted to examine the lived experiences of individuals in rural areas who use DHIs. Individuals with chronic conditions will be examined specifically and how their experiences influence the adoption, use and satisfaction with DHI for managing their health needs. This systematic literature review is significant because it will be used as a crucial starting point for a larger project aimed at creating digitally transformed primary healthcare in rural areas, particularly for Indigenous communities. The insights gained will inform the development of a digital transformation model for the larger project.

Guided by the TAM and PRISMA to explore the lived experiences of patients and caregivers with digital health, a search will be conducted for peer-reviewed studies on DHIs, including qualitative, quantitative and mixed-method approaches, including systematic reviews. The studies must be published in English from 2019 to the present and will be sourced from databases such as PubMed, EBSCO, Cochrane Library, Scopus and Web of Science. MeSH will be utilised to identify terms like user experience, acceptability and engagement with DHIs. Eligibility will be based on relevance, population, intervention and outcomes. A standardised data extraction form will be developed and tested to capture important information from each study included in the review. Data extraction and quality appraisal will be performed independently by two reviewers, with a third reviewer addressing any discrepancies. Software will be used to manage extracted data, assess risk of bias and synthesise the data. Meta-analysis will be included to enhance our findings if sufficient quantitative data is available. Our findings will be reported in accordance with the PRISMA guidelines. This review protocol was refined in June 2025; commencement of the study will be in July 2025 and will be completed in 2026.

This study used previously published literature and did not collect primary data from humans or animals. No ethical committee approval was required. Findings will be disseminated through peer-reviewed publication and will be presented at conferences related to the field.

osf.io/jw5yp.