{"title":"Digital-Use/Efficiency Phenotypes Versus Professional Role in Explaining Perceived Digital Benefit in Anaesthesia and Intensive Care.","authors":"Corina Vernic, Ovidiu Bedreag, Dorina Cristina Sulițanu, Liliana Ioana Muntean, Sorin Ursoniu","doi":"10.3390/healthcare14193306","DOIUrl":null,"url":null,"abstract":"<p><p><b>Background and Objectives</b>: We compared professional role with digital-use/efficiency phenotype as explanations of perceived digital benefit in anaesthesia and intensive care. <b>Materials and Methods</b>: Cross-sectional survey data from 161 professionals were analysed. Latent class analysis used 12 indicators of technology/educational-resource use and perceived operational efficiency; four benefit items remained external outcomes. Although BIC favoured two classes, a three-class exploratory solution was retained using aBIC, entropy, bootstrap testing, class size and interpretability. Nested logistic models with seniority retained in every model, likelihood-ratio tests and Shapley partitioning of McFadden's pseudo-R<sup>2</sup> compared role and phenotype; pre-planned sensitivity analyses re-estimated the comparison under two- and four-class solutions, with classification-error (BCH) correction and with use-only indicators, and discrimination was internally validated by bootstrap. Descriptive decomposition and Rasch/DIF analyses were exploratory. <b>Results</b>: The three phenotypes (<i>n</i> = 83, 44 and 34; entropy of 0.815) crossed professional boundaries (Cramér's V = 0.439). Phenotype did not improve seniority-and-role models for broad benefit (likelihood ratio 2.4, <i>p</i> = 0.301) or high uncertainty (2.8, <i>p</i> = 0.248), whereas adding role to seniority-and-phenotype models improved fit (23.6 and 26.2; both <i>p</i> < 0.001); this pattern was unchanged across all sensitivity specifications. Role received 68.3% and 62.3% of the Shapley-partitioned pseudo-R<sup>2</sup>, versus 11.9% and 11.4% for phenotype. Exploratory decompositions provided little evidence of an indirect association through adoption breadth or phenotype. Rasch analysis suggested patient safety was easiest and managerial benefit hardest to endorse; person separation reliability was 0.07, and DIF contrasts were descriptive. <b>Conclusions</b>: In this sample, professional role carried more explanatory information about perceived benefit than the exploratory phenotype, and this ranking was robust to class enumeration and classification-error correction. The phenotype findings remain exploratory, and cross-sectional associations do not establish causation.</p>","PeriodicalId":12977,"journal":{"name":"Healthcare","volume":"14 19","pages":""},"PeriodicalIF":3.4000,"publicationDate":"2026-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13665016/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Healthcare","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3390/healthcare14193306","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
Background and Objectives: We compared professional role with digital-use/efficiency phenotype as explanations of perceived digital benefit in anaesthesia and intensive care. Materials and Methods: Cross-sectional survey data from 161 professionals were analysed. Latent class analysis used 12 indicators of technology/educational-resource use and perceived operational efficiency; four benefit items remained external outcomes. Although BIC favoured two classes, a three-class exploratory solution was retained using aBIC, entropy, bootstrap testing, class size and interpretability. Nested logistic models with seniority retained in every model, likelihood-ratio tests and Shapley partitioning of McFadden's pseudo-R2 compared role and phenotype; pre-planned sensitivity analyses re-estimated the comparison under two- and four-class solutions, with classification-error (BCH) correction and with use-only indicators, and discrimination was internally validated by bootstrap. Descriptive decomposition and Rasch/DIF analyses were exploratory. Results: The three phenotypes (n = 83, 44 and 34; entropy of 0.815) crossed professional boundaries (Cramér's V = 0.439). Phenotype did not improve seniority-and-role models for broad benefit (likelihood ratio 2.4, p = 0.301) or high uncertainty (2.8, p = 0.248), whereas adding role to seniority-and-phenotype models improved fit (23.6 and 26.2; both p < 0.001); this pattern was unchanged across all sensitivity specifications. Role received 68.3% and 62.3% of the Shapley-partitioned pseudo-R2, versus 11.9% and 11.4% for phenotype. Exploratory decompositions provided little evidence of an indirect association through adoption breadth or phenotype. Rasch analysis suggested patient safety was easiest and managerial benefit hardest to endorse; person separation reliability was 0.07, and DIF contrasts were descriptive. Conclusions: In this sample, professional role carried more explanatory information about perceived benefit than the exploratory phenotype, and this ranking was robust to class enumeration and classification-error correction. The phenotype findings remain exploratory, and cross-sectional associations do not establish causation.
期刊介绍:
Healthcare (ISSN 2227-9032) is an international, peer-reviewed, open access journal (free for readers), which publishes original theoretical and empirical work in the interdisciplinary area of all aspects of medicine and health care research. Healthcare publishes Original Research Articles, Reviews, Case Reports, Research Notes and Short Communications. We encourage researchers to publish their experimental and theoretical results in as much detail as possible. For theoretical papers, full details of proofs must be provided so that the results can be checked; for experimental papers, full experimental details must be provided so that the results can be reproduced. Additionally, electronic files or software regarding the full details of the calculations, experimental procedure, etc., can be deposited along with the publication as “Supplementary Material”.