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Bjerke K, Brænd AM, Fossum GH. Parental Concerns for Children With Cold-like Symptoms With Reduced Access to Evaluation in Primary Care Settings During the COVID-19 Pandemic: A Qualitative Study. J Pediatr Health Care 2024; 38:695-702. [PMID: 38904595 DOI: 10.1016/j.pedhc.2024.05.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Revised: 05/06/2024] [Accepted: 05/22/2024] [Indexed: 06/22/2024]
Abstract
INTRODUCTION We aimed to explore the concerns of parents when their children had symptoms of infection during the COVID-19 pandemic. METHOD Two Norwegian internet forums were searched for parents' experiences when their children had upper respiratory infection symptoms in 2020-2021. A total of 197 posts were included and analyzed using thematic analysis. RESULTS Parents described COVID-19-related and general worries regarding their children with upper respiratory infection symptoms. The first theme, "It is not 'just a cold' during the pandemic," captures how infection control measures influenced parents' concerns. The second theme, "Concerns and consequences of fever and cold symptoms," describes general parental worries. Varying levels of worries regarding health care services, limitations of family life, and concerns for relatives were highlighted. DISCUSSION Knowledge of parents' concerns about cold symptoms may help primary health care providers target individual patient counseling and provide background information when policymakers develop information material for infection prevention and treatment.
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O'Donnell EA, Van Citters AD, Khayal IS, Wilson MM, Gustafson D, Barnato AE, Buccellato AC, Young C, Holthoff MM, Korsunskiy E, Tomlin SC, Cullinan AM, Steinbaugh AC, Hinson JJ, Johnson KR, Williams A, Thomson RM, Haines JM, Holmes AB, Bradley AD, Nelson EC, Kirkland KB. A Web-Based Peer Support Network to Help Care Partners of People With Serious Illness: Co-Design Study. JMIR Hum Factors 2024; 11:e53194. [PMID: 38717809 PMCID: PMC11112480 DOI: 10.2196/53194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 03/20/2024] [Accepted: 03/20/2024] [Indexed: 05/25/2024] Open
Abstract
BACKGROUND Care partners of people with serious illness experience significant challenges and unmet needs during the patient's treatment period and after their death. Learning from others with shared experiences can be valuable, but opportunities are not consistently available. OBJECTIVE This study aims to design and prototype a regional, facilitated, and web-based peer support network to help active and bereaved care partners of persons with serious illness be better prepared to cope with the surprises that arise during serious illness and in bereavement. METHODS An 18-member co-design team included active care partners and those in bereavement, people who had experienced serious illness, regional health care and support partners, and clinicians. It was guided by facilitators and peer network subject-matter experts. We conducted design exercises to identify the functions and specifications of a peer support network. Co-design members independently prioritized network specifications, which were incorporated into an early iteration of the web-based network. RESULTS The team prioritized two functions: (1) connecting care partners to information and (2) facilitating emotional support. The design process generated 24 potential network specifications to support these functions. The highest priorities included providing a supportive and respectful community; connecting people to trusted resources; reducing barriers to asking for help; and providing frequently asked questions and responses. The network platform had to be simple and intuitive, provide technical support for users, protect member privacy, provide publicly available information and a private discussion forum, and be easily accessible. It was feasible to enroll members in the ConnectShareCare web-based network over a 3-month period. CONCLUSIONS A co-design process supported the identification of critical features of a peer support network for care partners of people with serious illnesses in a rural setting, as well as initial testing and use. Further testing is underway to assess the long-term viability and impact of the network.
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Affiliation(s)
- Elizabeth A O'Donnell
- Communications, Marketing and Community Health, Alice Peck Day Memorial Hospital, Lebanon, NH, United States
- The Dartmouth Institute for Health Policy & Clinical Practice, Geisel School of Medicine at Dartmouth, Lebanon, NH, United States
| | - Aricca D Van Citters
- The Dartmouth Institute for Health Policy & Clinical Practice, Geisel School of Medicine at Dartmouth, Lebanon, NH, United States
| | - Inas S Khayal
- The Dartmouth Institute for Health Policy & Clinical Practice, Geisel School of Medicine at Dartmouth, Lebanon, NH, United States
- Dartmouth Cancer Center, Geisel School of Medicine, Dartmouth, Lebanon, NH, United States
| | - Matthew M Wilson
- Palliative Medicine, Geisel School of Medicine at Dartmouth, Lebanon, NH, United States
- Section of Palliative Medicine, Dartmouth Health, Lebanon, NH, United States
| | - David Gustafson
- College of Engineering, University of Wisconsin, Madison, WI, United States
| | - Amber E Barnato
- The Dartmouth Institute for Health Policy & Clinical Practice, Geisel School of Medicine at Dartmouth, Lebanon, NH, United States
- Palliative Medicine, Geisel School of Medicine at Dartmouth, Lebanon, NH, United States
- Section of Palliative Medicine, Dartmouth Health, Lebanon, NH, United States
| | - Andrea C Buccellato
- Dartmouth Cancer Center, Geisel School of Medicine, Dartmouth, Lebanon, NH, United States
| | - Colleen Young
- Mayo Clinic Connect, Mayo Clinic, Rochester, MN, United States
| | - Megan M Holthoff
- The Dartmouth Institute for Health Policy & Clinical Practice, Geisel School of Medicine at Dartmouth, Lebanon, NH, United States
| | - Eugene Korsunskiy
- Thayer School of Engineering, Dartmouth College, Hanover, NH, United States
| | - Stephanie C Tomlin
- Patient and Family Advisors, Dartmouth Health, Lebanon, NH, United States
| | - Amelia M Cullinan
- Palliative Medicine, Geisel School of Medicine at Dartmouth, Lebanon, NH, United States
- Section of Palliative Medicine, Dartmouth Health, Lebanon, NH, United States
| | | | - Jennifer J Hinson
- Patient and Family Advisors, Dartmouth Health, Lebanon, NH, United States
| | - Kristen R Johnson
- Section of Palliative Medicine, Dartmouth Health, Lebanon, NH, United States
| | - Andrew Williams
- Patient and Family Advisors, Dartmouth Health, Lebanon, NH, United States
| | - Ruth M Thomson
- Palliative Medicine, Geisel School of Medicine at Dartmouth, Lebanon, NH, United States
- Section of Palliative Medicine, Dartmouth Health, Lebanon, NH, United States
| | - Janet M Haines
- Patient and Family Advisors, Dartmouth Health, Lebanon, NH, United States
| | - Anne B Holmes
- Patient and Family Advisors, Dartmouth Health, Lebanon, NH, United States
| | - Ann D Bradley
- Patient and Family Advisors, Dartmouth Health, Lebanon, NH, United States
| | - Eugene C Nelson
- The Dartmouth Institute for Health Policy & Clinical Practice, Geisel School of Medicine at Dartmouth, Lebanon, NH, United States
| | - Kathryn B Kirkland
- The Dartmouth Institute for Health Policy & Clinical Practice, Geisel School of Medicine at Dartmouth, Lebanon, NH, United States
- Palliative Medicine, Geisel School of Medicine at Dartmouth, Lebanon, NH, United States
- Section of Palliative Medicine, Dartmouth Health, Lebanon, NH, United States
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Mavragani A, Duffin S, Gough RE, Bath PA. Use of Online Health Forums by People Living With Breast Cancer During the COVID-19 Pandemic: Thematic Analysis. JMIR Cancer 2023; 9:e42783. [PMID: 36473015 PMCID: PMC9907982 DOI: 10.2196/42783] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Revised: 11/24/2022] [Accepted: 12/05/2022] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND At the time of the UK COVID-19 lockdowns, online health forums (OHFs) were one of the relatively few remaining accessible sources of peer support for people living with breast cancer. Cancer services were heavily affected by the pandemic in many ways, including the closure of many of the customary support services. Previous studies indicate that loneliness, anxiety, distress, and depression caused by COVID-19 were common among people living with breast cancer, and this suggests that the role of OHFs in providing users with support, information, and empathy could have been of increased importance at that time. OBJECTIVE This study aimed to examine how people living with breast cancer shared information, experiences, and emotions in an OHF during the COVID-19 pandemic. METHODS This qualitative study thematically analyzed posts from the discussion forums of an OHF provided by the UK charity, Breast Cancer Now. We selected 1053 posts from the time of 2 UK lockdowns: March 16, 2020, to June 15, 2020 (lockdown 1), and January 6, 2021, to March 8, 2021 (lockdown 3), for analysis, from 2 of the forum's boards (for recently diagnosed people and for those undergoing chemotherapy). We analyzed the data using the original 6 steps for thematic analysis by Braun and Clarke but by following a codebook approach. Descriptive statistics for posts were also derived. RESULTS We found that COVID-19 amplified the forum's value to its users. As patients with cancer, participants were in a situation that was "bad enough already," and the COVID-19 pandemic heightened this difficult situation. The forum's value, which was already high for the information and peer support it provided, increased because COVID-19 caused some special information needs that forum users were uniquely well placed to fulfill as people experiencing the combined effects of having breast cancer during the pandemic. The forum also met the emotional needs generated by the COVID-19 pandemic and was valued as a place where loneliness during the pandemic may be relieved and users' spirits lifted in a variety of ways specific to this period. We found some differences in use between the 2 periods and the 2 boards-most noticeable was the great fear and anxiety expressed at the beginning of lockdown 1. Both the beginning and end of lockdown periods were particularly difficult for participants, with the ends seen as potentially increasing isolation. CONCLUSIONS The forums were an important source of support and information to their users, with their value increasing during the lockdowns for a variety of reasons. Our findings will be helpful to organizations offering OHFs and to health care workers advising people living with breast cancer about sources of support.
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Affiliation(s)
| | - Suzanne Duffin
- Information School, Faculty of Social Sciences, University of Sheffield, Sheffield, United Kingdom
| | - Rosemarie E Gough
- School of Health and Related Research, Faculty of Medicine, Dentistry and Health, University of Sheffield, Sheffield, United Kingdom
| | - Peter A Bath
- Information School, Faculty of Social Sciences, University of Sheffield, Sheffield, United Kingdom
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Wu H, Wang M, Wu J, Francis F, Chang YH, Shavick A, Dong H, Poon MTC, Fitzpatrick N, Levine AP, Slater LT, Handy A, Karwath A, Gkoutos GV, Chelala C, Shah AD, Stewart R, Collier N, Alex B, Whiteley W, Sudlow C, Roberts A, Dobson RJB. A survey on clinical natural language processing in the United Kingdom from 2007 to 2022. NPJ Digit Med 2022; 5:186. [PMID: 36544046 PMCID: PMC9770568 DOI: 10.1038/s41746-022-00730-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Accepted: 11/29/2022] [Indexed: 12/24/2022] Open
Abstract
Much of the knowledge and information needed for enabling high-quality clinical research is stored in free-text format. Natural language processing (NLP) has been used to extract information from these sources at scale for several decades. This paper aims to present a comprehensive review of clinical NLP for the past 15 years in the UK to identify the community, depict its evolution, analyse methodologies and applications, and identify the main barriers. We collect a dataset of clinical NLP projects (n = 94; £ = 41.97 m) funded by UK funders or the European Union's funding programmes. Additionally, we extract details on 9 funders, 137 organisations, 139 persons and 431 research papers. Networks are created from timestamped data interlinking all entities, and network analysis is subsequently applied to generate insights. 431 publications are identified as part of a literature review, of which 107 are eligible for final analysis. Results show, not surprisingly, clinical NLP in the UK has increased substantially in the last 15 years: the total budget in the period of 2019-2022 was 80 times that of 2007-2010. However, the effort is required to deepen areas such as disease (sub-)phenotyping and broaden application domains. There is also a need to improve links between academia and industry and enable deployments in real-world settings for the realisation of clinical NLP's great potential in care delivery. The major barriers include research and development access to hospital data, lack of capable computational resources in the right places, the scarcity of labelled data and barriers to sharing of pretrained models.
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Affiliation(s)
- Honghan Wu
- Institute of Health Informatics, University College London, London, UK.
| | - Minhong Wang
- Institute of Health Informatics, University College London, London, UK
| | - Jinge Wu
- Institute of Health Informatics, University College London, London, UK
- Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Farah Francis
- Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Yun-Hsuan Chang
- Institute of Health Informatics, University College London, London, UK
| | - Alex Shavick
- Research Department of Pathology, UCL Cancer Institute, University College London, London, UK
| | - Hang Dong
- Usher Institute, University of Edinburgh, Edinburgh, UK
- Department of Computer Science, University of Oxford, Oxford, UK
| | | | | | - Adam P Levine
- Research Department of Pathology, UCL Cancer Institute, University College London, London, UK
| | - Luke T Slater
- Institute of Cancer and Genomics, University of Birmingham, Birmingham, UK
| | - Alex Handy
- Institute of Health Informatics, University College London, London, UK
- University College London Hospitals NHS Trust, London, UK
| | - Andreas Karwath
- Institute of Cancer and Genomics, University of Birmingham, Birmingham, UK
| | - Georgios V Gkoutos
- Institute of Cancer and Genomics, University of Birmingham, Birmingham, UK
| | - Claude Chelala
- Centre for Tumour Biology, Barts Cancer Institute, Queen Mary University of London, London, UK
| | - Anoop Dinesh Shah
- Institute of Health Informatics, University College London, London, UK
| | - Robert Stewart
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London, UK
- South London and Maudsley NHS Foundation Trust, London, UK
| | - Nigel Collier
- Theoretical and Applied Linguistics, Faculty of Modern & Medieval Languages & Linguistics, University of Cambridge, Cambridge, UK
| | - Beatrice Alex
- Edinburgh Futures Institute, University of Edinburgh, Edinburgh, UK
| | | | - Cathie Sudlow
- Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Angus Roberts
- Department of Biostatistics & Health Informatics, King's College London, London, UK
| | - Richard J B Dobson
- Institute of Health Informatics, University College London, London, UK
- Department of Biostatistics & Health Informatics, King's College London, London, UK
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Deng Y, Park M, Chen J, Yang J, Xie L, Li H, Wang L, Chen Y. Emotional discourse analysis of COVID-19 patients and their mental health: A text mining study. PLoS One 2022; 17:e0274247. [PMID: 36112638 PMCID: PMC9481002 DOI: 10.1371/journal.pone.0274247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 08/24/2022] [Indexed: 11/30/2022] Open
Abstract
COVID-19 has caused negative emotional responses in patients, with significant mental health consequences for the infected population. The need for an in-depth analysis of the emotional state of COVID-19 patients is imperative. This study employed semi-structured interviews and the text mining method to investigate features in lived experience narratives of COVID-19 patients and healthy controls with respect to five basic emotions. The aim was to identify differences in emotional status between the two matched groups of participants. The results indicate generally higher complexity and more expressive emotional language in healthy controls than in COVID-19 patients. Specifically, narratives of fear, happiness, and sadness by COVID-19 patients were significantly shorter as compared to healthy controls. Regarding lexical features, COVID-19 patients used more emotional words, in particular words of fear, disgust, and happiness, as opposed to those used by healthy controls. Emotional disorder symptoms of COVID-19 patients at the lexical level tended to focus on the emotions of fear and disgust. They narrated more in relation to self or family while healthy controls mainly talked about others. Our automatic emotional discourse analysis potentially distinguishes clinical status of COVID-19 patients versus healthy controls, and can thus be used to predict mental health disorder symptoms in COVID-19 patients.
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Affiliation(s)
- Yu Deng
- College of Language Intelligence, Sichuan International Studies University, Chongqing, China
| | - Minjun Park
- Chinese Language and Literature, Duksung Women’s University, Seoul, Republic of Korea
| | - Juanjuan Chen
- Institute of Educational Planning and Assessment, Sichuan International Studies University, Chongqing, China
| | - Jixue Yang
- School of English, Sichuan International Studies University, Chongqing, China
| | - Luxue Xie
- School of English, Sichuan International Studies University, Chongqing, China
| | - Huimin Li
- School of English, Sichuan International Studies University, Chongqing, China
| | - Li Wang
- Science and Education Department, Chongqing Public Health Medical Center, Chongqing, China
| | - Yaokai Chen
- Division of Infectious Diseases, Chongqing Public Health Medical Center, Chongqing, China
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Grabar N, Grouin C. Year 2021: COVID-19, Information Extraction and BERTization among the Hottest Topics in Medical Natural Language Processing. Yearb Med Inform 2022; 31:254-260. [PMID: 36463883 PMCID: PMC9719758 DOI: 10.1055/s-0042-1742547] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/05/2022] Open
Abstract
OBJECTIVES Analyze the content of publications within the medical natural language processing (NLP) domain in 2021. METHODS Automatic and manual preselection of publications to be reviewed, and selection of the best NLP papers of the year. Analysis of the important issues. RESULTS Four best papers have been selected in 2021. We also propose an analysis of the content of the NLP publications in 2021, all topics included. CONCLUSIONS The main issues addressed in 2021 are related to the investigation of COVID-related questions and to the further adaptation and use of transformer models. Besides, the trends from the past years continue, such as information extraction and use of information from social networks.
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Affiliation(s)
- Natalia Grabar
- STL, CNRS, Université de Lille, Domaine du Pont-de-bois, Villeneuve-d'Ascq cedex, France
| | - Cyril Grouin
- Université Paris Saclay, CNRS, Laboratoire Interdisciplinaire des Sciences du Numérique, Orsay, France
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Lu Y, Wang Q. Doctors’ Preferences in the Selection of Patients in Online Medical Consultations: An Empirical Study with Doctor–Patient Consultation Data. Healthcare (Basel) 2022; 10:healthcare10081435. [PMID: 36011092 PMCID: PMC9408688 DOI: 10.3390/healthcare10081435] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 07/27/2022] [Accepted: 07/27/2022] [Indexed: 11/16/2022] Open
Abstract
Online medical consultation (OMC) allows doctors and patients to communicate with each other in an online synchronous or asynchronous setting. Unlike face-to-face consultations in which doctors are only passively chosen by patients with appointments, doctors engaging in voluntary online consultation have the option of choosing patients they hope to treat when faced with a large number of online questions from patients. It is necessary to characterize doctors’ preferences for patient selection in OMC, which can contribute to their more active participation in OMC services. We proposed to exploit a bipartite graph to describe the doctor–patient interaction and use an exponential random graph model (ERGM) to analyze the doctors’ preferences for patient selection. A total of 1404 doctor–patient consultation data retrieved from an online medical platform in China were used for empirical analysis. It was found that first, mildly ill patients will be prioritized by doctors, but the doctors with more professional experience may be more likely to prefer more severely ill patients. Second, doctors appear to be more willing to provide consultation services to patients from urban areas, but the doctors with more professional experience or from higher-quality hospitals give higher priority to patients from rural and medically underserved areas. Finally, doctors generally prefer asynchronous communication methods such as picture/text consultation, while the doctors with more professional experience may be more willing to communicate with patients via synchronous communication methods, such as voice consultation or video consultation.
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Affiliation(s)
- Yingjie Lu
- Correspondence: ; Tel.: +86-010-64434892
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