Introduction: Lung cancer remains a leading cause of cancer-related deaths globally. Lung cancer screening (LCS) with low-dose computed tomography (LDCT) can reduce lung cancer mortality, but its adoption in the U.S. has been limited. Digital interventions have the potential to improve uptake of LCS. This systematic review aims to summarize the evidence for the effectiveness of digital interventions in promoting LCS.
Methods: A systematic search of three electronic databases (PubMed, Embase, and Medline) was conducted to identify studies published between January 2014 and May 2023. Studies were reviewed and abstracted between February 2023 and July 2023. Outcomes related to knowledge, decision-making and screening were measured. Study quality was assessed using the Joanna Briggs Institute (JBI) critical appraisal tools.
Results: Of 1,979 screened articles, 30 studies were included in this review. Digital interventions evaluated included decision aids (n=20), electronic health record (EHR)-based interventions (n=7), social media campaigns and mobile applications (n=3). Decision aids were the most commonly studied digital interventions, with most studies showing improved knowledge (13/13) and reduced decisional conflict (7/9) but most did not show a substantial change in screening use. Fewer studies tested clinician-facing or multi-level interventions.
Discussion: Digital interventions, particularly decision aids, have shown promise in improving knowledge and the quality of decision-making around LCS. However, few interventions have been shown to substantially alter screening behavior and few clinician-facing or multi-level interventions have been rigorously tested. Further research is needed to develop effective tools for engaging patients in LCS, to compare the efficacy of different interventions, and evaluate implementation strategies in diverse healthcare settings.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11451259 | PMC |
http://dx.doi.org/10.1016/j.amepre.2024.01.007 | DOI Listing |
Front Educ (Lausanne)
January 2024
Division of Adolescent and Young Adult Medicine, Department of Pediatrics, University of California, San Francisco, San Francisco, CA, United States.
Background: Attention deficit hyperactivity disorder (ADHD) affects about 13% of adolescents and is associated with substance use-related morbidity and mortality. While evidence on effective interventions to reduce alcohol use among adolescents with ADHD is limited, parent-teen communication about alcohol use has been found to be protective. Other approaches, such as educational interventions, hold promise to reduce alcohol-related harms in adolescents with ADHD.
View Article and Find Full Text PDFInt J Chron Obstruct Pulmon Dis
January 2025
Department of Cardiology, Respiratory Medicine and Intensive Care, University Hospital Augsburg, Augsburg, Germany.
Background: Chronic obstructive pulmonary disease (COPD) affects breathing, speech production, and coughing. We evaluated a machine learning analysis of speech for classifying the disease severity of COPD.
Methods: In this single centre study, non-consecutive COPD patients were prospectively recruited for comparing their speech characteristics during and after an acute COPD exacerbation.
Objective: This study was conducted to investigate the social media practices and attitudes towards e-professionalism among undergraduate medical students in a medical college of Pakistan.
Methods: This cross-sectional study was conducted on 220 undergraduate medical students from 2 to final-year MBBS, at CMH Lahore Medical College from March to August 2022. After ethical approval, a printed questionnaire was distributed among students, selected by stratified random sampling technique.
Front Digit Health
January 2025
Biostatistics and Research Decision Sciences, Merck & Co., Inc., Rahway, NJ, United States.
Background: Current methods of measuring disease progression of neurodegenerative disorders, including Parkinson's disease (PD), largely rely on composite clinical rating scales, which are prone to subjective biases and lack the sensitivity to detect progression signals in a timely manner. Digital health technology (DHT)-derived measures offer potential solutions to provide objective, precise, and sensitive measures that address these limitations. However, the complexity of DHT datasets and the potential to derive numerous digital features that were not previously possible to measure pose challenges, including in selection of the most important digital features and construction of composite digital biomarkers.
View Article and Find Full Text PDFBioinform Adv
January 2025
Digital Technologies Research Centre, National Research Council of Canada, Ottawa, ON K1K 4P7, Canada.
Motivation: Missing values are prevalent in high-throughput measurements due to various experimental or analytical reasons. Imputation, the process of replacing missing values in a dataset with estimated values, plays an important role in multivariate and machine learning analyses. The three missingness patterns, including missing completely at random, missing at random, and missing not at random, describe unique dependencies between the missing and observed data.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!