Telemetry is a key, widely used tool to understand marine megafauna distribution, habitat use, behavior, and physiology; however, a critical question remains: "How many animals should be tracked to acquire meaningful data sets?" This question has wide-ranging implications including considerations of statistical power, animal ethics, logistics, and cost. While power analyses can inform sample sizes needed for statistical significance, they require some initial data inputs that are often unavailable. To inform the planning of telemetry and biologging studies of marine megafauna where few or no data are available or where resources are limited, we reviewed the types of information that have been obtained in previously published studies using different sample sizes. We considered sample sizes from one to >100 individuals and synthesized empirical findings, detailing the information that can be gathered with increasing sample sizes. We complement this review with simulations, using real data, to show the impact of sample size when trying to address various research questions in movement ecology of marine megafauna. We also highlight the value of collaborative, synthetic studies to enhance sample sizes and broaden the range, scale, and scope of questions that can be answered.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1002/eap.1947 | DOI Listing |
BMC Nurs
January 2025
College of Medicine and Health Sciences, School of Nursing and Midwifery, University of Rwanda, Po. Box: 3286, Kigali, Rwanda.
Background: Pressure injuries are costly and can lead to mortality and psychosocial consequences if not managed effectively. Proper management of pressure injuries is crucial for quality nursing care. However, there is limited research on nurses' knowledge and practices in preventing and managing pressure injuries among critically ill patients in Rwanda.
View Article and Find Full Text PDFBMC Complement Med Ther
January 2025
Department of Neurology, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China.
Background: Suhexiang (SHX) pill is widely used for treating acute ischemic stroke (AIS). Experimental and randomized controlled trials suggested that SHX pill was beneficial for patients with AIS. However, the effectiveness of SHX pill in real-world practice setting remains unclear.
View Article and Find Full Text PDFBMC Med Imaging
January 2025
Department of Radiological Sciences, College of Health and Rehabilitation Sciences, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia.
Background: Quantitative molecular imaging via single-photon emission computed tomography-derived standardised uptake value (SPECT/CT-SUV) is used to assess the response of metastatic castration-resistant prostate cancer (mCRPC) patients to targeted radionuclide therapy (TRT) with [Lu]Lu-PSMA. This imaging technique determines the radiopharmaceutical distribution and internal dosimetry in patients who receive TRT. However, there is limited evidence regarding the role of image quantification in monitoring changes induced by [Lu]Lu-PSMA.
View Article and Find Full Text PDFBMC Med Res Methodol
January 2025
Division of Public Health Sciences, Washington University in St Louis, 660 S. Euclid Ave, St Louis, MO, 63110, USA.
Background: Propensity Score Matching (PSM) stands as a widely embraced method in comparative effectiveness research. PSM crafts matched datasets, mimicking some attributes of randomized designs, from observational data. In a valid PSM design where all baseline confounders are measured and matched, the confounders would be balanced, allowing the treatment status to be considered as if it were randomly assigned.
View Article and Find Full Text PDFBMC Med Res Methodol
January 2025
Leeds Institute of Clinical Trials Research, University of Leeds, Clarendon Way, Leeds, LS2 9NL, UK.
Background: Early detection and diagnosis of cancer are vital to improving outcomes for patients. Artificial intelligence (AI) models have shown promise in the early detection and diagnosis of cancer, but there is limited evidence on methods that fully exploit the longitudinal data stored within electronic health records (EHRs). This review aims to summarise methods currently utilised for prediction of cancer from longitudinal data and provides recommendations on how such models should be developed.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!