Journal of evaluation in clinical practice最新文献

Rationale: Digital health is widely promoted in low- and middle-income countries (LMICs), yet investment is often constrained by fiscal rules and borrowing limits. Policymakers also struggle to explain how digital health improves fiscal sustainability and, by proxy, fiscal credibility, creating a gap between technical promise and investable policy narratives.

Aims and objectives: To synthesise practice-based evidence on whether and how digital health initiatives in LMICs contribute to fiscal sustainability and signal fiscal credibility to governments, funders, investors, and to identify design and governance conditions that make these benefits investable under fiscal-rule frameworks.

Methods: A scoping review following PRISMA-ScR analysed 45 studies (2010-2025) of LMIC digital health interventions that reported economic outcomes (e.g., cost-effectiveness, cost savings, ROI, budget impact) and/or credibility proxies (e.g., integration with public financial management, budget absorption, stakeholder trust). Findings were synthesised thematically.

Results: Evidence shows that digital platforms curb leakage and generate efficiency gains (e.g., reduced wastage, streamlined claims) and avert future costs through prevention and adherence, while integration with budgeting and public financial management improves predictability, transparency, and trust, thereby strengthening credibility signals. Yet benefits are frequently non-cashable without managerial and policy reforms; costs and savings are misaligned across actors; and classifying digital outlays as recurrent restricts access to capital envelopes despite favourable economics. Investability improves when core platforms are treated as public digital infrastructure with clear depreciation and financing arrangements, when efficiency gains are translated into real budget space via gain-sharing and performance-based budgeting, and when reporting explicitly links digital performance to fiscal outcomes. These effects depend on foundational enablers, including infrastructure, workforce capacity, and sustained user engagement.

Conclusion: When embedded in robust governance and public financial management, and framed as rule-consistent investment, digital health can expand fiscal space, support compliance with fiscal rules, and strengthen fiscal credibility, helping LMICs reassure lenders and justify sustainable borrowing for health system strengthening.

Aim: To explore the dynamic process of family participation in postoperative care for atrial fibrillation and identify its potential conflicts.

Design: A qualitative study with a phenomenological approach.

Methods: From April to June 2025, semi-structured interviews were conducted with 10 atrial fibrillation patients who underwent surgical treatment 1-3 months prior in the cardiology department of a tertiary hospital in Shanghai, along with their primary caregivers, and the data were analyzed using Colaizzi's seven-step analysis method.

Results: This study identified three main themes and seven sub-themes: (1) the current situation of family participation in care, (2) the interaction perception and role identity among family members, and (3) the emotional and resource dilemma under the pressure of care.

Conclusion: While focusing on the health problems of patients with atrial fibrillation after surgery, the burden and related problems of family caregivers should not be ignored. Family involvement in the care of patients after AF ablation is a double-edged sword, and a structured support system needs to be established to alleviate conflicts. Family education and conflict mediation are recommended to be included in the discharge plan.

Impact: This study reveals three common tensions in the postoperative care of patients with atrial fibrillation: the conflict between overprotection and restricting patients' autonomy, the disconnection between knowledge acquisition and care behavior, and the multiple burdens on caregivers at both psychological and economic levels. To address the problems existing in family care, efforts should be made from the three levels of the system, education, and service to build a diversified and collaborative family care support system.

Reporting method: This study followed the Consolidated Criteria for Reporting Qualitative Research checklist.

Patient or public contribution: Two patients and their primary caregivers were involved in the early phases of this study. They helped in formulating the interview outline.

Rationale: The p value has long been used as the primary criterion for statistical significance; however, its dichotomous interpretation has been increasingly criticized for oversimplifying uncertainty and distorting scientific inference, particularly in health and sports sciences.

Aims and objectives: This study aimed to critically analyze the limitations of using the p value as the central criterion of statistical significance and to discuss more robust methodological alternatives for statistical inference.

Methods: A critical review was conducted using the PubMed/MEDLINE database covering the period from 2015 to 2025, complemented by citation tracking. Reviews, editorials, guidelines, and methodological essays that directly addressed the interpretation of p values and complementary metrics were included. A total of 46 articles were selected and evaluated using a self-developed critical appraisal checklist.

Results: Among the included studies, 38 (82.6%) explicitly criticized the isolated or dichotomous use of the p value, whereas eight adopted a more moderate position, supporting its use only when combined with confidence intervals, effect sizes, or Bayesian approaches. No article defended the p value as a standalone criterion for scientific decision-making. The most frequent recommendations involved abandoning the term "statistically significant," prioritizing the estimation of effect magnitude and precision, and promoting the use of compatibility intervals, effect sizes, and Bayesian methods.

Conclusion: Overcoming the binary logic of p < 0.05 is essential to enhance transparency, reduce bias, and better align statistical practice with the scientific and clinical relevance of research findings, particularly in the health and sports sciences.