Interactive Journal of Medical Research

Deduplication across search results is one of the earliest and most critical steps in the systematic review methodological process; yet, existing solutions often lack the transparency, auditability, and reproducibility required by rigorous systematic review standards. Many automated deduplication tools introduce bias through opaque, nonconfigurable algorithmic decisions, while also potentially removing relevant references through false positive identification. We provide a tutorial on the Rayyan Method, including the Systematic Auto Resolver feature for the deduplication process. This method is defined by an enhanced deduplication approach that combines high-sensitivity duplicate detection with user-controlled resolution criteria. Systematic Auto Resolver enables research teams to define, apply, and document their own deduplication standards rather than relying on predetermined automated decisions. Users apply deduplication criteria, iteratively reviewing results after each pass, maintaining complete control over methodological decisions. The Rayyan Method addresses critical limitations in current deduplication approaches by supporting methodological rigor through user-controlled resolution while enhancing efficiency, transparency, and reproducibility. By empowering research teams to define their own deduplication criteria, this approach supports and aligns with the prescribed methodologically rigorous systematic review process. The method provides a citable framework for researchers to comprehensively document their deduplication methodology.

Mental health conditions, including depression, anxiety, and psychological distress, are prevalent among the aging population and affect their health, functioning, and quality of life. Access to proper and high-quality mental health treatment is necessary; however, mental health treatment and care remain underused due to stigma, workforce shortages, cost, and mobility limitations. Digital mental health interventions (DMHIs) are emerging as a promising strategy to improve the accessibility and effectiveness of mental health services for older adults, but older adults have historically been underrepresented in DMHI development and evaluation. Additionally, the effectiveness of different types of DMHIs and how age-centered design approaches influence outcomes remain underexplored.

Inclusive health education content has been shown to increase acceptability and accessibility for lesbian, gay, bisexual, transgender, queer, intersex, and asexual, as well as other sexual and gender minority (LGBTQ+) individuals. However, there has been some backlash among general audiences, with claims that such inclusive content is “woke” or otherwise problematic.

Generosity can function as a scientific method—a disciplined stance that aligns curiosity with openness, credit-sharing, and stewardship of data, specimens, and ideas. Rather than a soft add-on, generosity structures how questions are framed, teams are built, and results are disseminated, thereby improving rigor, reproducibility, and impact. This viewpoint article advances a conceptual and operational framework for “generosity in science,” aimed at researchers, institutions, and funders seeking alternatives to competition-driven models of knowledge production. I examine generosity as practice at the levels of people, collectives, and institutions and argue that persistent global challenges in health demand pro-collaborative architectures. Seen this way, generosity is not mere altruism; it is part of the epistemic engine that turns uncertainty into shared knowledge while distributing opportunity and recognition more fairly. I define core principles of generous research and organize them across three domains: research design, governance, and evaluation. The paper draws on illustrative examples and relevant literature to situate generosity within ongoing debates on open science, team science, and research assessment reform. I outline practical principles for embedding generosity into research design, governance, and evaluation and discuss how these principles can counter vanity metrics and short-term incentives. I conclude that embedding generosity in the infrastructure of science enables better questions, faster learning, and greater public value.

Effective physician-patient communication is essential for building trust and sustaining positive relationships, yet becomes increasingly challenging in China’s tertiary hospitals, where physicians face heavy workloads.

There is a worldwide movement toward competency-based medical education to equip dental students with essential competencies required to meet health care needs. In Syria, dental faculties currently lack a formal competency-based curriculum for endodontics at the undergraduate level. Moreover, the quality of root canal treatment performed by general dentists is frequently described as inadequate or substandard.

Long COVID, or postacute COVID-19 syndrome, presents with persistent cognitive and psychological symptoms such as , anxiety, depression, and fatigue, significantly impacting quality of life and daily functioning. Digital health interventions offer a scalable, accessible solution to bridge care gaps, especially where conventional neuropsychological support is limited. However, evidence regarding their effectiveness for neuropsychiatric symptoms in long COVID remains fragmented.

Observation of COVID-19 rebound after nirmatrelvir plus ritonavir (NPR) has driven important questions surrounding one of the only direct-acting antiviral treatments for COVID-19.

The use of artificial intelligence (AI) in medical imaging has been growing exponentially. Understanding patient perceptions and factors influencing their views of AI is critical to develop adequate strategies to support implementation and acceptance.

During a public health emergency, emergency department (ED) clinicians can improve care delivery if they identify and adopt innovations that are safe and effective. However, little is known about the factors that impact ED clinicians’ decision-making around using or discontinuing innovations when evidence-based information is limited.

Children’s eating habits are formed at an early age, making childhood a crucial period for introducing novel foods, such as pulse-based food products. Pulse Discovery Toolkit (PDTK) intervention was designed to increase familiarity with pulses and to eventually contribute to the consumption of pulse-based foods among preschool children in childcare centers (CCs).

Major depressive disorder (MDD) and treatment-resistant depression (TRD) are heterogeneous conditions in which key clinical details are split across structured fields and free-text notes in electronic health records (EHRs), constraining population-level insight and timely audit of care quality.