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The Impact of Long COVID-19 on Mental Health: Observational 6-Month Follow-Up Study

The Impact of Long COVID-19 on Mental Health: Observational 6-Month Follow-Up Study

A confirmed diagnosis was based on a computed tomography (CT) scan or reverse transcription PCR (RT-PCR). Self-reported health status (good, moderate, or poor), symptoms during the infection and during follow-up, as well as the date of the onset of these COVID-19 symptoms were assessed as previously described [15,23]. The Trauma Screening Questionnaire (TSQ) was used as a screening instrument for PTSD [26].

Sarah Houben-Wilke, Yvonne MJ Go�rtz, Jeannet M Delbressine, Anouk W Vaes, Roy Meys, Felipe VC Machado, Maarten van Herck, Chris Burtin, Rein Posthuma, Frits ME Franssen, Herman Vijlbrief, Yvonne Spies, Alex J van 't Hul, Martijn A Spruit, Daisy JA Janssen

JMIR Ment Health 2022;9(2):e33704


Features of a Mobile Support App for Patients With Chronic Obstructive Pulmonary Disease: Literature Review and Current Applications

Features of a Mobile Support App for Patients With Chronic Obstructive Pulmonary Disease: Literature Review and Current Applications

Other factors, such as adopting a healthy lifestyle (good nutrition and exercise), result in a better quality of life in patients with COPD [13]. The main objective of this study was to review mobile apps, COPD management systems, and the literature in order to identify features for a COPD mobile support app.

Drishty D Devi Sobnath, Nada Philip, Reem Kayyali, Shereen Nabhani-Gebara, Barbara Pierscionek, Anouk W Vaes, Martijn A Spruit, Evangelos Kaimakamis

JMIR Mhealth Uhealth 2017;5(2):e17


Wearable Finger Pulse Oximetry for Continuous Oxygen Saturation Measurements During Daily Home Routines of Patients With Chronic Obstructive Pulmonary Disease (COPD) Over One Week: Observational Study

Wearable Finger Pulse Oximetry for Continuous Oxygen Saturation Measurements During Daily Home Routines of Patients With Chronic Obstructive Pulmonary Disease (COPD) Over One Week: Observational Study

Figure 1 provides a general overview of the methods applied in this single-center, 1-week observational study. COPD patients at Global Initiative for Chronic Obstructive Lung Disease stages II-IV (GOLD II-IV) were recruited at the Centre of Expertise for Chronic Organ Failure (CIRO), a COPD treatment center located in Horn, the Netherlands, during a standard baseline assessment prior to pulmonary rehabilitation [21]. The target sample size was set a priori to 20 patients.

Joren Buekers, Jan Theunis, Patrick De Boever, Anouk W Vaes, Maud Koopman, Eefje VM Janssen, Emiel FM Wouters, Martijn A Spruit, Jean-Marie Aerts

JMIR Mhealth Uhealth 2019;7(6):e12866


Severe Fatigue in Long COVID: Web-Based Quantitative Follow-up Study in Members of Online Long COVID Support Groups

Severe Fatigue in Long COVID: Web-Based Quantitative Follow-up Study in Members of Online Long COVID Support Groups

This study is a prospective web-based survey of members of two Facebook peer support groups for patients with long COVID in the Netherlands (approximately 11,000 members; [22]) and Flanders (Belgium, approximately 1200 members; [23]), and a panel of approximately 1200 people who registered at a website of the Netherlands Lung Foundation (coronaplein [24]), an online platform providing additional information, advice, and peer support.

Maarten Van Herck, Yvonne M J Goërtz, Sarah Houben-Wilke, Felipe V C Machado, Roy Meys, Jeannet M Delbressine, Anouk W Vaes, Chris Burtin, Rein Posthuma, Frits M E Franssen, Bita Hajian, Herman Vijlbrief, Yvonne Spies, Alex J van 't Hul, Daisy J A Janssen, Martijn A Spruit

J Med Internet Res 2021;23(9):e30274


Development of a Pipeline for Adverse Drug Reaction Identification in Clinical Notes: Word Embedding Models and String Matching

Development of a Pipeline for Adverse Drug Reaction Identification in Clinical Notes: Word Embedding Models and String Matching

One of the widespread topics in NLP is the use of word embeddings—a vector representation of a text, often established through evaluation of the word’s context. The use of word embeddings for the evaluation of clinical free text for research purposes is increasing [11]. Research has shown that training word embedding models on a domain-specific data set generates better results than training on a general data set [12,13].

Klaske R Siegersma, Maxime Evers, Sophie H Bots, Floor Groepenhoff, Yolande Appelman, Leonard Hofstra, Igor I Tulevski, G Aernout Somsen, Hester M den Ruijter, Marco Spruit, N Charlotte Onland-Moret

JMIR Med Inform 2022;10(1):e31063


Exergaming as a Functional Test Battery in Patients Who Received Arthroscopic Ankle Arthrodesis: Cross-sectional Pilot Study

Exergaming as a Functional Test Battery in Patients Who Received Arthroscopic Ankle Arthrodesis: Cross-sectional Pilot Study

This pilot study was a stepwise approach to design a test protocol with an exergaming device for the rehabilitation of patients who received arthroscopic AA (AAA). For extrapolation purposes, we performed a gait analysis with a treadmill system. This cross-sectional pilot study was performed at the Zuyderland Medical Center, Department of Orthopedic Surgery and Traumatology. This study was approved by the Clinical Research Ethics Committee (protocol 2016/43).

Roel Hendrickx, Tim van der Avoird, Peter Pilot, Gino Kerkhoffs, Martijn Schotanus

JMIR Rehabil Assist Technol 2021;8(2):e21924


How Natural Language Processing Can Aid With Pulmonary Oncology Tumor Node Metastasis Staging From Free-Text Radiology Reports: Algorithm Development and Validation

How Natural Language Processing Can Aid With Pulmonary Oncology Tumor Node Metastasis Staging From Free-Text Radiology Reports: Algorithm Development and Validation

Reports were included when a primary pulmonary malignancy was described by a radiologist. The included free-text radiological reports have been constructed by several different radiologists, other than the authors, using a speech recognition tool (G2 Speech). Exclusion criteria were (1) restaging and follow-up reports, (2) cases with 2 primary tumors, and (3) incomplete reports.

Sander Puts, Martijn Nobel, Catharina Zegers, I�igo Bermejo, Simon Robben, Andre Dekker

JMIR Form Res 2023;7:e38125


Machine Learning–Based Prediction Models for Different Clinical Risks in Different Hospitals: Evaluation of Live Performance

Machine Learning–Based Prediction Models for Different Clinical Risks in Different Hospitals: Evaluation of Live Performance

This alternate model could be a model that is trained in the same hospital with a different training strategy, as well as a model that is trained on the data from a different hospital. For example, in Figure 3, the logging information stored in hospital A (ie, the hospital where risk predictions in a live EHR system are made) can be used to generate predictions with a model trained at hospital B (ie, a different hospital where a different risk prediction model is trained).

Hong Sun, Kristof Depraetere, Laurent Meesseman, Patricia Cabanillas Silva, Ralph Szymanowsky, Janis Fliegenschmidt, Nikolai Hulde, Vera von Dossow, Martijn Vanbiervliet, Jos De Baerdemaeker, Diana M Roccaro-Waldmeyer, Jörg Stieg, Manuel Domínguez Hidalgo, Fried-Michael Dahlweid

J Med Internet Res 2022;24(6):e34295


Using Online Health Communities to Deliver Patient-Centered Care to People With Chronic Conditions

Using Online Health Communities to Deliver Patient-Centered Care to People With Chronic Conditions

Such a group could include patients with a particular condition (eg, patients with diabetes mellitus type II), a group of professionals with a shared medical interest (eg, diabetologists), or a mixture of both patients and professionals. Members might know each other from the “real” physical world, but the strength of OHCs is their potential to connect members who would otherwise never have met because of geographical distances.

Martijn van der Eijk, Marjan J Faber, Johanna WM Aarts, Jan AM Kremer, Marten Munneke, Bastiaan R Bloem

J Med Internet Res 2013;15(6):e115