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Efficacy of a Blended Low-Intensity Internet-Delivered Psychological Program in Patients With Multimorbidity in Primary Care: Randomized Controlled Trial

Efficacy of a Blended Low-Intensity Internet-Delivered Psychological Program in Patients With Multimorbidity in Primary Care: Randomized Controlled Trial

Despite the high prevalence of multimorbidity worldwide, with its consequent demand for care and important health and economic consequences [18], much work remains to be done. Multimorbidity interventions pose a challenge for present-day health care systems [19]. As pointed out by a previous meta-analysis, it is difficult to improve outcomes in people with multimorbidity, although interventions oriented toward depression or specific difficulties and risk factors are promising [17].

Alicia Monreal-Bartolomé, Adoración Castro, M Ángeles Pérez-Ara, Margalida Gili, Fermín Mayoral, María Magdalena Hurtado, Esperanza Varela Moreno, Cristina Botella, Azucena García-Palacios, Rosa M Baños, Yolanda López-Del-Hoyo, Javier García-Campayo, Jesus Montero-Marin

J Med Internet Res 2025;27:e56203

Technologies for Interoperable Internet of Medical Things Platforms to Manage Medical Emergencies in Home and Prehospital Care: Scoping Review

Technologies for Interoperable Internet of Medical Things Platforms to Manage Medical Emergencies in Home and Prehospital Care: Scoping Review

The aging world population and an increased prevalence of chronic conditions and multimorbidity have placed greater pressure on health care systems and professionals [1]. In Europe, over 50 million people have at least 1 chronic disease [2]; and in the United States, it is estimated that the number of people aged 50 years and older with at least 1 chronic disease will increase by 100%, from 71 million in 2020 to 142 million by 2050 [3].

Mattias Seth, Hoor Jalo, Åsa Högstedt, Otto Medin, Bengt Arne Sjöqvist, Stefan Candefjord

J Med Internet Res 2025;27:e54470

A Digital Tool for Clinical Evidence–Driven Guideline Development by Studying Properties of Trial Eligible and Ineligible Populations: Development and Usability Study

A Digital Tool for Clinical Evidence–Driven Guideline Development by Studying Properties of Trial Eligible and Ineligible Populations: Development and Usability Study

Multimorbidity is the presence of 2 or more long-term health conditions in a person [1]. Typically, multimorbidity was considered a problem for older populations but is increasingly recognized as a challenge in younger people as well [2]. Multimorbidity is associated with worse physical and mental health function, higher service use, and higher mortality [3-5].

Shahzad Mumtaz, Megan McMinn, Christian Cole, Chuang Gao, Christopher Hall, Magalie Guignard-Duff, Huayi Huang, David A McAllister, Daniel R Morales, Emily Jefferson, Bruce Guthrie

J Med Internet Res 2025;27:e52385

Leveraging an Electronic Health Record Patient Portal to Help Patients Formulate Their Health Care Goals: Mixed Methods Evaluation of Pilot Interventions

Leveraging an Electronic Health Record Patient Portal to Help Patients Formulate Their Health Care Goals: Mixed Methods Evaluation of Pilot Interventions

executive summary for the American Geriatrics Society guiding principles on the care of older adults with multimorbidity Reference 2: Healthcare task difficulty among older adults with multimorbiditymultimorbidity

Jody Naimark, Mary E Tinetti, Tom Delbanco, Zhiyong Dong, Kendall Harcourt, Jessica Esterson, Peter Charpentier, Jan Walker

JMIR Form Res 2024;8:e56332

Creating a Modified Version of the Cambridge Multimorbidity Score to Predict Mortality in People Older Than 16 Years: Model Development and Validation

Creating a Modified Version of the Cambridge Multimorbidity Score to Predict Mortality in People Older Than 16 Years: Model Development and Validation

People with multimorbidity, defined by those with 2 or more long-term conditions (LTCs) [1-6], have complex needs and impose increasing demands on primary care services given the aging population. Multimorbidity is associated with reduced life expectancy [7], lower quality of life [8], and an increased risk of hospitalization and death due to COVID-19 [9]. In clinical trials, vaccination against COVID-19 showed reduced risk of hospitalization and death in all groups [10,11].

Debasish Kar, Kathryn S Taylor, Mark Joy, Sudhir Venkatesan, Wilhelmine Meeraus, Sylvia Taylor, Sneha N Anand, Filipa Ferreira, Gavin Jamie, Xuejuan Fan, Simon de Lusignan

J Med Internet Res 2024;26:e56042

The Effectiveness of Collaborative Care Interventions for the Management of Patients With Multimorbidity: Protocol for a Systematic Review, Meta-Analysis, and Meta-Regression Analysis

The Effectiveness of Collaborative Care Interventions for the Management of Patients With Multimorbidity: Protocol for a Systematic Review, Meta-Analysis, and Meta-Regression Analysis

Multimorbidity lacks a universally accepted standard definition but is most commonly defined as the presence of 2 or more coexisting chronic conditions in one individual [1]. Multimorbidity is distinguished from the related concept of comorbidity by treating all conditions equally as opposed to prioritizing or designating an index condition in the case of comorbidity [1].

Anne-Maj Knudsen, Ann-Cathrine Dalgård Dunvald, Stine Hangaard, Ole Hejlesen, Thomas Kronborg

JMIR Res Protoc 2024;13:e58296

A Multimorbidity Analysis of Hospitalized Patients With COVID-19 in Northwest Italy: Longitudinal Study Using Evolutionary Machine Learning and Health Administrative Data

A Multimorbidity Analysis of Hospitalized Patients With COVID-19 in Northwest Italy: Longitudinal Study Using Evolutionary Machine Learning and Health Administrative Data

Studying multimorbidity using traditional methods can be labor-intensive, requiring the identification of high-dimensional combinatorial features. Also, there is no universally accepted list of medical conditions to define multimorbidity. To address these challenges, efforts must focus on identifying low-dimensional representations of multimorbidity features for effective outcome prediction.

Dayana Benny, Mario Giacobini, Alberto Catalano, Giuseppe Costa, Roberto Gnavi, Fulvio Ricceri

JMIR Public Health Surveill 2024;10:e52353