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Content Update Alert, Friday 17th March 2023
RECENTLY PUBLISHED
THE EFFICACY OF BE A MOM, A WEB-BASED INTERVENTION TO PREVENT POSTPARTUM DEPRESSION: EXAMINING MECHANISMS OF CHANGE IN A
RANDOMIZED CONTROLLED TRIAL
Carlos Carona, Marco Pereira, Anabela Araújo-Pedrosa, Maria Cristina Canavarro, Ana Fonseca
Source: The Authors / Placeit; Copyright: The Authors / Placeit; URL:
JMIR.
JMIR Ment Health 2023 (Mar 17); 10(1):e39253
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Background: Postpartum depression (PPD) is treatable and preventable, but most women do not seek professional help for their
perinatal depressive symptoms. One increasingly popular approach of improving access to care is the use of web-based intervention
programs.
Objective: The objective of this study was 2-fold: first, to assess the efficacy of Be a Mom, a brief web-based selective or
indicated preventive intervention, in reducing depressive and anxiety symptoms of women at high risk for PPD; and second, to
examine mechanisms of change linking modifiable self-regulatory skills (ie, emotion regulation, self-compassion, and psychological
flexibility) to improved perinatal mental health outcomes...
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CAPTURING THE DYNAMICS OF THE SOCIAL ENVIRONMENT THROUGH EXPERIENCE SAMPLING METHODS, PASSIVE SENSING, AND EGOCENTRIC NETWORKS:
SCOPING REVIEW
Anna M Langener, Gert Stulp, Martien J Kas, Laura F Bringmann
Source: Freepik; Copyright: master1305; URL:
JMIR Ment Health 2023 (Mar 17); 10(1):e42646
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Background: Social interactions are important for well-being, and therefore, researchers are increasingly attempting to capture
people’s social environment. Many different disciplines have developed tools to measure the social environment, which can be
highly variable over time. The experience sampling method (ESM) is often used in psychology to study the dynamics within a person
and the social environment. In addition, passive sensing is often used to capture social behavior via sensors from smartphones or
other wearable devices. Furthermore, sociologists use egocentric networks to track how social relationships are changing. Each of
these methods is likely to tap into different but important parts of people’s social environment. Thus far, the development and
implementation of these methods have occurred mostly separately from each other.
Objective: Our aim was to synthesize the literature on how these methods are currently used to capture the changing social
environment in relation to well-being and assess how to best combine these methods to study well-being...
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DIGITAL PRACTICES BY CITIZENS DURING THE COVID-19 PANDEMIC: FINDINGS FROM AN INTERNATIONAL MULTISITE STUDY
Hannah Ramsden Marston, Pei-Chun Ko, Vishnunarayan Girishan Prabhu, Shannon Freeman, Christopher Ross, Iryna Sharaievska, Matthew
HEM Browning, Sarah Earle, Loredana Ivan, Rubal Kanozia, Halime Öztürk Çalıkoğlu, Hasan Arslan, Burcu Bilir-Koca, Paula Alexandra
Silva, Sandra C Buttigieg, Franziska Großschädl, Gerhilde Schüttengruber
Source: Pixabay; Copyright: Geralt; URL:
Licensed by JMIR.
JMIR Ment Health 2023 (Mar 06); 10(1):e41304
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Background: The COVID-19 pandemic brought digital practices and engagement to the forefront of society, which were based on
behavioral changes associated with adhering to different government mandates. Further behavioral changes included transitioning
from working in the office to working from home, with the use of various social media and communication platforms to maintain a
level of social connectedness, especially given that many people who were living in different types of communities, such as rural,
urban, and city spaces, were socially isolated from friends, family members, and community groups. Although there is a growing
body of research exploring how technology is being used by people, there is limited information and insight about the digital
practices employed across different age cohorts living in different physical spaces and residing in different countries.
Objective: This paper presents the findings from an international multisite study exploring the impact of social media and the
internet on the health and well-being of individuals in different countries during the COVID-19 pandemic...
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TRENDS IN LANGUAGE USE DURING THE COVID-19 PANDEMIC AND RELATIONSHIP BETWEEN LANGUAGE USE AND MENTAL HEALTH: TEXT ANALYSIS BASED
ON FREE RESPONSES FROM A LONGITUDINAL STUDY
Rachel Weger, Juan Antonio Lossio-Ventura, Margaret Rose-McCandlish, Jacob S Shaw, Stephen Sinclair, Francisco Pereira, Joyce Y
Chung, Lauren Yvette Atlas
Source: Pexels; Copyright: Liza Summer; URL:
Licensed by JMIR.
JMIR Ment Health 2023 (Mar 01); 10(1):e40899
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Background: The COVID-19 pandemic and its associated restrictions have been a major stressor that has exacerbated mental health
worldwide. Qualitative data play a unique role in documenting mental states through both language features and content. Text
analysis methods can provide insights into the associations between language use and mental health and reveal relevant themes that
emerge organically in open-ended responses.
Objective: The aim of this web-based longitudinal study on mental health during the early COVID-19 pandemic was to use text
analysis methods to analyze free responses to the question, “Is there anything else you would like to tell us that might be
important that we did not ask about?” Our goals were to determine whether individuals who responded to the item differed from
nonresponders, to determine whether there were associations between language use and psychological status, and to characterize the
content of responses and how responses changed over time...
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FROM SOCIAL NETWORK TO PEER SUPPORT NETWORK: OPPORTUNITIES TO EXPLORE MECHANISMS OF ONLINE PEER SUPPORT FOR MENTAL HEALTH
Amy Rayland, Jacob Andrews
Source: Freepik; Copyright: onlyyouqj; URL:
JMIR Ment Health 2023 (Feb 28); 10(1):e41855
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An increasing number of psychological interventions are shifting to online modes of delivery. One such intervention is
peer-to-peer support, which in this context may provide internet users living with mental health disorders an opportunity to
connect with and support others living with similar conditions. This paper presents a call for further research into how platforms
such as Facebook could be used as channels for peer support and the mechanisms that may underlie their effectiveness. We discuss
the background of peer support, how it has transitioned online, and consider theories and models that may have relevance. We also
consider the importance of moderation within online peer support and the development of specific social network–based online
interventions. We conclude that for social network sites to be used as peer-to-peer support interventions, more research is needed
to understand their effectiveness, the role of moderation in these communities, and the mechanisms that produce the benefits
experienced by users.
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LATEST ANNOUNCEMENTS
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JMIR Mental Health Receives Sharp 44% Increase in Impact Factor to 6.33
(Toronto, June 28, 2022) JMIR Publications announced that JMIR Mental Health saw a sharp (44%) increase in Impact Factor to 6.33
in the 2022 Clarivate Journal Citation Report. This places JMIR Mental Health in the second quartile (Q2) of the ‘Psychiatry’
subject category. With the journal receiving its first impact factor two years ago, this significant jump in score is emblematic
of the high-interest and high-quality research JMIR Mental Health has striven to publish since its launch in 2014.Notably, the
flagship journal, Journal of Medical Internet Research, increased 30%+ to a 2022 IF of 7.08 and continues to retain its historical
position in the first quartile of both the ‘Medical Informatics’ and ‘Health Care Science & Services’ subject categories. The
Journal of Medical Internet Research also saw an increase in its Journal Citation Indicator (JCI) to 1.67. Journals with a JCI of
greater than 1.5 have 50% more citation impact than the...
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JMIR Mental Health Now Indexed in CABI’s Global Health Database
JMIR Publications is pleased to announce that JMIR Mental Health has been accepted and now indexed in CABI’s Global Health
database dedicated to public health research and practice.Additional JMIR Publications’ journals indexed in CABI’s Global Health
database include: Journal of Medical Internet Research, JMIR mHealth and uHealth, JMIR Public Health and Surveillance and JMIR
Dermatology. To review all JMIR Publication journals included in CABI’s Global Health database, click here.About CABICAB Direct
incorporating the leading bibliographic databases CAB Abstracts and Global Health. CAB Direct provides a convenient, single point
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JMIR Mental Health Sees Substantial Increase in Impact Factor to 4.39
Update: This is an archived post. The latest impact factor released in June 2022 is a 6.33 (2021).(Philadelphia/Toronto, June
30th, 2021) JMIR Publications is thrilled to announce that JMIR Mental Health saw a sharp (24%) increase in Impact Factor to 4.39
in the 2020 Clarivate Journal Citation Report. This places JMIR Mental Health in the first quartile of the ‘Psychiatry’ subject
category. With the journal receiving its first impact factor last year, this significant jump in score is emblematic of the
high-interest and high-quality research JMIR Mental Health has striven to publish since its launch in 2014.Notably, our flagship
journal, Journal of Medical Internet Research (IF 5.43), retains its historical position in the first quartiles of both the
‘Medical Informatics’ and ‘Health Care Science & Services’ subject categories.In addition to these achievements we are thrilled to
announce that JMIR Public Health & Surveillance received its first Impact Factor (IF 4.11) in the 2020 JCR,...
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LATEST SUBMISSIONS OPEN TO PEER REVIEW
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Forecasting Artificial Intelligence Trends in Healthcare: An International Patent Analysis
Bertalan Meskó, Stan Benjamens, Pranavsingh Dhunnoo, Márton Görög
Date Submitted: Mar 14, 2023
Open Peer Review Period: Mar 14, 2023 - May 09, 2023
Background:
Background: Artificial intelligence (AI)/machine learning (ML)-based medical devices and algorithms are rapidly changing the
medical field. To provide an insight into the trends in AI and ML in healthcare, we conducted an international patent analysis.
Objective: -
Methods:
Methods: A systematic patent analysis, focusing on AI/ML-based patents in healthcare, was performed using the Espacenet database
(from 01-2012 until 07-2022). This database includes patents from the China National Intellectual Property Administration (CNIPA),
European Patent Office (EPO), Japan Patent Office (JPO), Korean Intellectual Property Office (KIPO), United States Patent and
Trademark Office (USPTO).
Results:
Results: We identified 10967 patents: 7332 (66.9%) from CNIPA, 191 (1.7%) from EPO, 163 (1.5%) from JPO, 513 (4.7%) from KIPO and
2768 (25.2%) from USPTO. The number of published patents showed a yearly doubling from 2015 until 2021. Five international
companies had the greatest impact on this increase: Ping An Medical and Healthcare Management with 568 (5.2%) patents, Siemens
Healthineers with 273 (2.5%), IBM with 226 (2.1%), Philips Healthcare with 150 (1.4%) and Shanghai United Imaging Healthcare with
144 (1.3%).
Conclusions:
Conclusion: This international patent analysis showed a linear increase in patents published by the five largest patent offices.
An open access database with interactive search options was launched for AI/ML-based patents in healthcare.
Results:
Results: We identified 10967 patents: 7332 (66.9%) from CNIPA, 191 (1.7%) from EPO, 163 (1.5%) from JPO, 513 (4.7%) from KIPO and
2768 (25.2%) from USPTO. The number of published patents showed a yearly doubling from 2015 until 2021. Five international
companies had the greatest impact on this increase: Ping An Medical and Healthcare Management with 568 (5.2%) patents, Siemens
Healthineers with 273 (2.5%), IBM with 226 (2.1%), Philips Healthcare with 150 (1.4%) and Shanghai United Imaging Healthcare with
144 (1.3%).
Conclusions:
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Mapping the evidence on the impact of mHealth interventions on patient-reported outcomes in breast cancer patients: A systematic
review
Santiago Frid, Clara Amat Fernández, Ángeles Fuentes Expósito, Monsterrat Muñoz Mateu, Antonis Velachis, Antoni Sisó-Almirall,
Immaculada Grau-Corral
Date Submitted: Mar 13, 2023
Open Peer Review Period: Mar 13, 2023 - May 08, 2023
Background: The field of mHealth has grown exponentially in the last decade due to the widespread use of smartphones and the
advancements in mobile technology, which has created opportunities to find solutions to unmet healthcare needs for patients with
chronic diseases. Furthermore, healthcare is entering a new value-based paradigm, founded on three main pillars: efficiency,
safety, and value for patients.
Objective: The objective of this review is to summarize the current knowledge on the impact of mHealth on patient-reported
outcomes in breast cancer (BC) patients.
Methods: Three databases were systematically searched to identify studies that met eligibility criteria: PubMed, PsychInfo, and
Google Scholar. Relevant systematic reviews and the references of the research articles they contained were also searched in case
that studies were missed during the initial search. Searches were made on December 17th, 2021. Two investigators independently
reviewed the titles and abstracts of the identified studies and then read the full text of all selected papers. In case a
discrepancy was found, It was discussed with a third investigator in order to make a final decision. The quality of the included
studies was analyzed by the Cochrane Collaboration Risk of Bias Tool and the Methodological Index for Non-Randomized Studies.
Results: Twenty-two unique studies involving 3,502 patients were included. The focus of the interventions in the studies included
in the review were physical activity (11 studies), tailored information for better self-management of the disease (8 studies),
mental health therapies (6 studies), symptom tracker (4 studies), and others (6 studies). All interventions were at least 8 weeks
long of duration, with a median duration of 12 weeks (interquartile range 4-18 weeks). mHealth interventions showed better results
on symptom burden, fatigue, quality of life and physical activity. Likewise, tailored information, symptom tracker, nutrition and
physical activity were the interventions that yielded better results. Apps with interactive support had a higher rate of positive
findings, while interventions targeted to survivors showed worse results.
Conclusions: mHealth applications in BC patients is a highly heterogeneous field. Our study suggests that interventions focused on
newly diagnosed patients or patients while on chemotherapy, interventions with interactive human support and those with a duration
of 12 weeks or more showed better results in terms of patient-reported outcome. Interventions must be adapted to each patient’s
characteristics and disease stage to meet their specific needs at the time of deployment. Positive impact on endpoints show what
can be achieved with the right mHealth intervention. The reproducibility of the studies reporting mHealth interventions is
currently uncertain.
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Large Language Models in Surgical Education: Do they Reach Human Level on Fundamentals of Robotic Surgery Test?
Andrea Moglia, Konstantinos Georgiou, Richard Satava, Alfred Cuschieri
Date Submitted: Mar 13, 2023
Open Peer Review Period: Mar 13, 2023 - May 08, 2023
Background: Large language models are capable of answering questions as if they were engaged in active conversation with users.
However, currently, there are no data on whether their performances will remain static or vary over time when answering questions
in the medical domain.
Objective: The aim of the present study was to assess ChatGPT and InstructGPT on multiple trials on the Fundamentals of Robotic
Surgery (FRS) test. Additionally, different releases of ChatGPT were compared to establish whether its performance improved after
retraining.
Methods: We tested the performance of ChatGPT and InstructGPT on the 44 multiple choice questions of FRS didactic test, for which
a pass mark requires 35 correct answers (79.5%). Seven attempts were performed using ChatGPT on the January 30, 2023 release and
seven with the February 13, 2023 version. Three trials were performed with InstructGPT.
Results: ChatGPT achieved a mean score of 64.6% and 65.6% respectively for the first and second release, without any significant
difference between the two (p = 0.32). The score ranged from 54.5% to 72.7% with both versions. On baseline it achieved 54.5% in
both releases, higher than InstructGPT (50.0%). The highest rate of correct answers of ChatGPT was observed for questions on team
training and communication (77.5% with both releases), followed by those on the introduction of the robotic system (67.5% and 62.7
% respectively for the first and second versions), psychomotor skills (64.3% and 57.1%), and naming correctly clinical steps of a
procedure of robot-assisted surgery (53.8% and 65.9%).
Conclusions: Even though ChatGPT did not pass FRS test in any of the 14 trials, the 72.7% score observed by the present study
represents a remarkable result, taking into consideration the generic nature of ChatGPT as distinct from a domain specific LLM.
This level represents the highest score by ChatGPT in a high-stake examination in medicine.
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