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Implementation of Patient-Reported Outcomes in a Medical Oncology Setting (the iPROMOS Study): Type II Hybrid Implementation Study

Implementation of Patient-Reported Outcomes in a Medical Oncology Setting (the iPROMOS Study): Type II Hybrid Implementation Study

For health services, the use of PROMs for symptom measurement has led to a reduction in emergency presentations and hospital admissions, without increasing clinical workloads [5-7]. These benefits are thought to be due to improved symptom detection by clinicians enabling better supportive care [8-10]. Despite this evidence and an increased uptake of PROMs in routine care, successful implementation in routine care has been inconsistent due to the complex nature of PROMs interventions [4].

Natasha Anne Roberts, Anita Pelecanos, Kimberly Alexander, David Wyld, Monika Janda

J Med Internet Res 2024;26:e55841

Development of a Digital Patient Assistant for the Management of Cyclic Vomiting Syndrome: Patient-Centric Design Study

Development of a Digital Patient Assistant for the Management of Cyclic Vomiting Syndrome: Patient-Centric Design Study

This study aimed to develop for patients with CVS an artificial intelligence (AI)–powered digital patient assistant (DPA) that provides more than symptom tracking, using the iterative design principles of user design and user interface alongside the design thinking approach, which has been adopted successfully for the development of health care applications [15,22-24].

Gaurav Narang, Yaozhu J Chen, Nicole Wedel, Melody Wu, Michelle Luo, Ashish Atreja

JMIR Form Res 2024;8:e52251

Using Social Media to Help Understand Patient-Reported Health Outcomes of Post–COVID-19 Condition: Natural Language Processing Approach

Using Social Media to Help Understand Patient-Reported Health Outcomes of Post–COVID-19 Condition: Natural Language Processing Approach

For the rest of this paper, mapped terms refer to the raw symptom and condition terms mapped to their common base in the first step of the normalization process. In addition, normalized terms refers to normalized symptom and condition terms further transformed to the 203 standardized unique concepts derived from 3762 patients with PCC. To determine how good the BERT models are at extracting the symptom and condition terms, we created a human-annotated corpus from Twitter.

Elham Dolatabadi, Diana Moyano, Michael Bales, Sofija Spasojevic, Rohan Bhambhoria, Junaid Bhatti, Shyamolima Debnath, Nicholas Hoell, Xin Li, Celine Leng, Sasha Nanda, Jad Saab, Esmat Sahak, Fanny Sie, Sara Uppal, Nirma Khatri Vadlamudi, Antoaneta Vladimirova, Artur Yakimovich, Xiaoxue Yang, Sedef Akinli Kocak, Angela M Cheung

J Med Internet Res 2023;25:e45767

Use of a Data Repository to Identify Delirium as a Presenting Symptom of COVID-19 Infection in Hospitalized Adults: Cross-Sectional Cohort Pilot Study

Use of a Data Repository to Identify Delirium as a Presenting Symptom of COVID-19 Infection in Hospitalized Adults: Cross-Sectional Cohort Pilot Study

Delirium has been noted as a common presentation to emergency departments (EDs) during the current pandemic but is an atypical symptom of COVID-19 in hospitalized patients [6]. Recognizing delirium as a possible presenting symptom of COVID-19 may decrease the effects on the patient and the health care system.

Laurence M Solberg, Laurie J Duckworth, Elizabeth M Dunn, Theresa Dickinson, Tanja Magoc, Urszula A Snigurska, Sarah E Ser, Brian Celso, Meghan Bailey, Courtney Bowen, Nila Radhakrishnan, Chirag R Patel, Robert Lucero, Ragnhildur I Bjarnadottir

JMIR Aging 2023;6:e43185

Effectiveness of a Personalized, Chess-Based Training Serious Video Game in the Treatment of Adolescents and Young Adults With Attention-Deficit/Hyperactivity Disorder: Randomized Controlled Trial

Effectiveness of a Personalized, Chess-Based Training Serious Video Game in the Treatment of Adolescents and Young Adults With Attention-Deficit/Hyperactivity Disorder: Randomized Controlled Trial

Furthermore, significant pre-post symptom reductions were found for several scales measuring secondary end points, and they differ depending on the type of intervention (as explained in the following sections). We found no improvements in executive functioning after using TSTM. This finding is consistent with literature using other serious video games such as ACTIVATE [60] or Plan-It Commander [61].

María Rodrigo-Yanguas, Marina Martín-Moratinos, Carlos González-Tardón, Fernando Sanchez-Sanchez, Ana Royuela, Marcos Bella-Fernández, Hilario Blasco-Fontecilla

JMIR Serious Games 2023;11:e39874

A Spatiotemporal Solution to Control COVID-19 Transmission at the Community Scale for Returning to Normalcy: COVID-19 Symptom Onset Risk Spatiotemporal Analysis

A Spatiotemporal Solution to Control COVID-19 Transmission at the Community Scale for Returning to Normalcy: COVID-19 Symptom Onset Risk Spatiotemporal Analysis

A spatiotemporal solution has been developed to enable the prediction of COVID-19 symptom onset risk and provide support for Hong Kong’s new direction of pandemic prevention. The improved intercity-scale [14,15] and urban-community–scale [16] weighted kernel density estimation (WKDE) models have been applied to predict spatiotemporal COVID-19 symptom onset risk [17,18].

Chengzhuo Tong, Wenzhong Shi, Anshu Zhang, Zhicheng Shi

JMIR Public Health Surveill 2023;9:e36538

Usability and Acceptability of a Palliative Care Mobile Intervention for Older Adults With Heart Failure and Caregivers: Observational Study

Usability and Acceptability of a Palliative Care Mobile Intervention for Older Adults With Heart Failure and Caregivers: Observational Study

In general, symptom control and good communication are basic palliative care principles highly recommended to improve the quality of life for patients with HF [5]. Although relatively underexplored, digital health [6] innovations (ie, telehealth, wearable devices, and mobile health [m Health]) provide modern opportunities for patients and their social convoy to engage in palliative care [7-11].

Jennifer Paola Villalobos, Sheana Salyers Bull, Jennifer Dickman Portz

JMIR Aging 2022;5(4):e35592

Machine Learning–Based Predictive Modeling of Anxiety and Depressive Symptoms During 8 Months of the COVID-19 Global Pandemic: Repeated Cross-sectional Survey Study

Machine Learning–Based Predictive Modeling of Anxiety and Depressive Symptoms During 8 Months of the COVID-19 Global Pandemic: Repeated Cross-sectional Survey Study

The second aim was to characterize how associations between demographic and environmental factors and symptom scores changed over time. The third aim was to identify predictors that moderated or exacerbated the effects of others on depression and anxiety by examining two-way variable interactions in our model.

Katrina Hueniken, Nibene Habib Somé, Mohamed Abdelhack, Graham Taylor, Tara Elton Marshall, Christine M Wickens, Hayley A Hamilton, Samantha Wells, Daniel Felsky

JMIR Ment Health 2021;8(11):e32876

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