Objective: To obtain expert consensus on indicators of quality rehabilitation services for individuals with limited English proficiency (LEP).
Design: Three-round Delphi study.
Setting: Delphi survey conducted online with 30 experts. Most experts worked in adult physical rehabilitation settings and were from Illinois (n=16), and the remaining participants were from 8 other US states or Canadian provinces.
Participants: Experts (N=30) had a minimum of 2 publications on health care services for patients with LEP and/or a minimum of 5 years clinical experience in physical rehabilitation. Of 43 experts (11 researchers, 32 clinicians) who received the round 1 survey by e-mail, 30 returned complete responses (70% response rate). Of those, 25 completed round 2 and 24 completed round 3. Of round 1 participants, most (n =21) identified their primary professional activity as clinical, whereas the others worked in research (n =5) or education (n =4). Twenty-four were women. The median age was 43 years (range, 27-67y). Disciplines included occupational therapy (n =14), physical therapy (n =13), psychology (n=1), nursing (n=1), and medicine (n=1).
Interventions: Not applicable.
Main Outcome Measures: Indicators were rated on a 7-point Likert scale for importance and feasibility. Interquartile range (IQR) and 95% confidence intervals were calculated for importance and feasibility ratings. Indicators with an IQR <2 and a median importance score ≥6 were accepted as reaching consensus for importance.
Results: Round 1 responses were categorized into 15 structural, 13 process, and 18 outcome indicators. All 15 structural indicators reached consensus for importance; 8 were rated as feasible. All 13 process indicators reached consensus, of which 8 were deemed feasible. Sixteen outcome indicators reached consensus, of which 7 were deemed feasible.
Conclusions: This Delphi study identified structural, process, and outcome indicators that can inform delivery and assessment of quality rehabilitation services for individuals with LEP. Future research should operationalize and measure these quality indicators in clinical practice.
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http://dx.doi.org/10.1016/j.apmr.2021.04.020 | DOI Listing |
Syst Rev
January 2025
Department of Epidemiology, Mailman School of Public Health, Columbia University Irving Medical Center, New York, NY, USA.
Background: Impaired intrauterine growth, a significant global health problem, contributes to a higher burden of infant morbidity and mortality, mainly in resource-poor settings. Maternal anemia and undernutrition, two important causes of impaired intrauterine growth, are prioritized by global nutrition targets of 2030. We synthesized the evidence on the role of preconception nutrition supplements in reducing maternal anemia and improving intrauterine growth.
View Article and Find Full Text PDFWorld J Surg Oncol
January 2025
Hunan University of Traditional Chinese Medicine, The Second Affiliated Hospital of Hunan University of Traditional Chinese Medicine, No. 233, Cai'e North Road, Kaifu District, Changsha, Hunan, 410005, China.
Background: In recent years, the association between systemic immune-inflammation index (SII) and the prognosis of patients with colorectal cancer (CRC) has remained a topic of considerable debate. To address this, the present study was carried out to investigate the prognostic significance of SII in CRC.
Methods: Databases including PubMed, Embase, the Cochrane Central Register of Controlled Trials (CENTRAL), and Web of Science were scrutinized up to March 27, 2024.
BMC Res Notes
January 2025
UQ Centre for Clinical Research, Faculty of Health Medicine and Behavioural Sciences, The University of Queensland, Brisbane, Australia.
Objectives: This data note presents a comprehensive geodatabase of cardiovascular disease (CVD) hospitalizations in Mashhad, Iran, alongside key environmental factors such as air pollutants, built environment indicators, green spaces, and urban density. Using a spatiotemporal dataset of over 52,000 hospitalized CVD patients collected over five years, the study supports approaches like advanced spatiotemporal modeling, artificial intelligence, and machine learning to predict high-risk CVD areas and guide public health interventions.
Data Description: This dataset includes detailed epidemiologic and geospatial information on CVD hospitalizations in Mashhad, Iran, from January 1, 2016, to December 31, 2020.
BMC Ophthalmol
January 2025
Department of Ophthalmology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Significance: Cataract surgery is one of the most performed surgical procedures worldwide. As a potential complication following cataract surgery, dry eye has the potential to impact visual outcomes, lower patient satisfaction, and be detrimental to quality of life.
Purpose: To evaluate the effect of cataract surgery on dry eye outcomes postoperatively.
BMC Med Imaging
January 2025
Department of Magnetic Resonance Imaging, The First Affiliated Hospital, Zhengzhou University, Zhengzhou, 450052, China.
Background: Conventional hip joint MRI scans necessitate lengthy scan durations, posing challenges for patient comfort and clinical efficiency. Previously, accelerated imaging techniques were constrained by a trade-off between noise and resolution. Leveraging deep learning-based reconstruction (DLR) holds the potential to mitigate scan time without compromising image quality.
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