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Objective: To examine the risk of bias in chiropractic mixed methods research.
Methods: We performed a secondary analysis of a meta-epidemiological review of chiropractic mixed methods studies. We assessed risk of bias with the Mixed Methods Appraisal Tool (MMAT) and used generalized estimating equations to explore factors associated with risk of bias.
Results: Among 55 eligible studies, a mean of 62% (6.8 [2.3]/11) of MMAT items were fulfilled. In our adjusted analysis, studies published since 2010 versus pre-2010 (adjusted odds ratio [aOR] = 2.26; 95% confidence interval [CI], 1.39 to 3.68) and those published in journals with an impact factor versus no impact factor (aOR = 2.21; 95% CI, 1.33 to 3.68) were associated with lower risk of bias.
Conclusion: Our findings suggest opportunities for improvement in the quality of conduct among published chiropractic mixed methods studies. Author compliance with the MMAT criteria may reduce methodological bias in future mixed methods research.
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JMIR Res Protoc
September 2025
Department of Health Services Research & Administration, College of Public Health, University of Nebraska Medical Center, Omaha, NE, United States.
Background: With the availability of more advanced and effective treatments, life expectancy has improved among patients with metastatic breast cancer (MBC), but this makes communication with their medical oncologist more complex. Some patients struggle to learn about their therapeutic options and to understand and articulate their preferences. Mobile health (mHealth) apps can enhance patient-provider communication, playing a crucial role in the diagnosis, treatment, quality of life, and outcomes for patients living with MBC.
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September 2025
Department of Urology, Center for Health Outcomes Research and Dissemination, University of Washington, Seattle.
Importance: Black individuals have a twofold higher rate of prostate cancer death in the US compared with the average population with prostate cancer. Few guidelines support race-conscious screening practices among at-risk Black individuals.
Objective: To examine structural factors that facilitate or impede access to prostate cancer screening among Black individuals in the US.
Adv Ther
September 2025
Sanofi, Gentilly, France.
Introduction: No head-to-head studies comparing the efficacy of avalglucosidase alfa (AVA) with cipaglucosidase alfa + miglustat (Cipa+mig) have been conducted in patients with late-onset Pompe disease (LOPD). Two indirect treatment comparisons (ITCs) were conducted to estimate the effects of AVA versus Cipa+mig.
Methods: ITCs were conducted using simulated treatment comparisons (STCs), adjusting for differences in prognostic factors and treatment effect modifiers.
Rev Esc Enferm USP
September 2025
Universidade de São Paulo, Escola de Enfermagem, Departamento de Enfermagem Médico-Cirúrgica, São Paulo, SP, Brazil.
Objective: To compare the performance of trauma severity indices (ISS, NISS, REMS, mREMS) in predicting hospital and Intensive Care Unit (ICU) admission outcomes.
Method: Retrospective cohort study carried out with patients treated at the Emergency Room of a private hospital from January 2020 to January 2022. Medical records of adults with blunt, penetrating, or mixed trauma admitted up to 24 hours after the trauma were analyzed.
Multivariate Behav Res
September 2025
Department of Social Psychology and Methodology, Universidad Autonoma de Madrid, Madrid, Spain.
Wording effects, the systematic method variance arising from the inconsistent responding to positively and negatively worded items of the same construct, are pervasive in the behavioral and health sciences. Although several factor modeling strategies have been proposed to mitigate their adverse effects, there is limited systematic research assessing their performance with exploratory structural equation models (ESEM). The present study evaluated the impact of different types of response bias related to wording effects (random and straight-line carelessness, acquiescence, item difficulty, and mixed) on ESEM models incorporating two popular method modeling strategies, the correlated traits-correlated methods minus one (CTC[M-1]) model and random intercept item factor analysis (RIIFA), as well as the "do nothing" approach.
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