RESUMO
BACKGROUND: Natural language processing has been increasingly used in palliative care research over the last 5 years for its versatility and accuracy. AIM: To evaluate and characterize natural language processing use in palliative care research, including the most commonly used natural language processing software and computational methods, data sources, trends in natural language processing use over time, and palliative care topics addressed. DESIGN: A scoping review using the framework by Arksey and O'Malley and the updated recommendations proposed by Levac et al. was conducted. SOURCES: PubMed, Web of Science, Embase, Scopus, and IEEE Xplore databases were searched for palliative care studies that utilized natural language processing tools. Data on study characteristics and natural language processing instruments used were collected and relevant palliative care topics were identified. RESULTS: 197 relevant references were identified. Of these, 82 were included after full-text review. Studies were published in 48 different journals from 2007 to 2022. The average sample size was 21,541 (median 435). Thirty-two different natural language processing software and 33 machine-learning methods were identified. Nine main sources for data processing and 15 main palliative care topics across the included studies were identified. The most frequent topic was mortality and prognosis prediction. We also identified a trend where natural language processing was frequently used in analyzing clinical serious illness conversations extracted from audio recordings. CONCLUSIONS: We found 82 papers on palliative care using natural language processing methods for a wide-range of topics and sources of data that could expand the use of this methodology. We encourage researchers to consider incorporating this cutting-edge research methodology in future studies to improve published palliative care data.
Assuntos
Enfermagem de Cuidados Paliativos na Terminalidade da Vida , Cuidados Paliativos , Humanos , Cuidados Paliativos/métodos , Processamento de Linguagem Natural , Projetos de Pesquisa , BibliometriaRESUMO
Loss of appetite is related to undesirable loss of weight in amyotrophic lateral sclerosis (ALS) and affects up to two thirds of people with this disease. Little is known about the instruments used to measure appetite loss, its impact on quality of life (QoL), or strategies used to improve loss of appetite. In this study we aim to characterize the existing literature on the symptom of appetite loss in ALS through a systematic scoping review following the framework by Arksey and O'Malley and PRISMA guidelines. Studies assessing appetite in people with ALS (pALS) published in English and indexed on Web of Science, PubMed, and Scopus databases were included. A total of 156 full references were identified, of which 10 articles met the inclusion criteria and were eligible for data synthesis after screening. Seven unique instruments were used to assess appetite across the included studies, most commonly the Council of Nutrition Appetite Questionnaire. No studies included a subjective assessment of appetite loss. A total of 12 unique potential associated factors across five studies were identified. QoL was measured in seven studies using nine different QoL measurement tools. Few studies measure appetite in pALS and there is no consensus on the assessment tool used. Few studies evaluated the impact of appetite as a symptom on QoL. Furthermore, the heterogeneity of outcomes and risk factors of the existing data limit the clinical application of these findings. Future studies are needed to guide clinical management and interventions for people with ALS and appetite loss.