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Cocreative Development of the QoL-ME: A Visual and Personalized Quality of Life Assessment App for People With Severe Mental Health Problems

Cocreative Development of the QoL-ME: A Visual and Personalized Quality of Life Assessment App for People With Severe Mental Health Problems

First, some of the feedback received in the design stage corresponds to existing recommendations reported by Rotondi et al [28] as part of their FEDM and by Bernard et al [21] in their review of factors that facilitate the Web usage of people with mental disorders

David C Buitenweg, Ilja L Bongers, Dike van de Mheen, Hans A M van Oers, Chijs van Nieuwenhuizen

JMIR Ment Health 2019;6(3):e12378


Using Digital Health Technologies to Understand the Association Between Movement Behaviors and Interstitial Glucose: Exploratory Analysis

Using Digital Health Technologies to Understand the Association Between Movement Behaviors and Interstitial Glucose: Exploratory Analysis

Compared with uninterrupted sitting, both activity conditions lowered the net glucose response to a standardized drink (light: −1.7 mmol/L; moderate: −2.0 mmol/L) [9].

Andrew P Kingsnorth, Maxine E Whelan, James P Sanders, Lauren B Sherar, Dale W Esliger

JMIR Mhealth Uhealth 2018;6(5):e114


Patients’ Participation in Health Research: A Classification of Cooperation Schemes

Patients’ Participation in Health Research: A Classification of Cooperation Schemes

compared to Dewey’s self-inquiries [10].Figure 2 shows how this encoding allows comparing 2 such protocols: an evidence-based medicine (EBM) randomized placebo-controlled trial and an autoethnography.Table 1Phases of an investigation described with the stages of Bernard

Olivier Las Vergnas

J Participat Med 2017;9(1):e16


Lifestyle Intervention Enabled by Mobile Technology on Weight Loss in Patients With Nonalcoholic Fatty Liver Disease: Randomized Controlled Trial

Lifestyle Intervention Enabled by Mobile Technology on Weight Loss in Patients With Nonalcoholic Fatty Liver Disease: Randomized Controlled Trial

10.1)46.8 (11.1).7646.1 (10.3)46.2 (11.0).96Weight (kg)86.1 (19.4)81.5 (15.2).1786.6 (19.6)82.0 (15.7).20BMIb (kg/m2)30.8 (4.8)30.1 (4.0).0430.9 (4.8)30.1 (4.1).37Waist circumference (cm), mean (SD)101.7 (11.4)98.6 (9.0).14101.9 (11.6)98.9 (10.2).17ALTc (IU/L)

Su Lin Lim, Jolyn Johal, Kai Wen Ong, Chad Yixian Han, Yiong Huak Chan, Yin Mei Lee, Wai Mun Loo

JMIR Mhealth Uhealth 2020;8(4):e14802


Development and Evaluation of a Mobile Personalized Blood Glucose Prediction System for Patients With Gestational Diabetes Mellitus

Development and Evaluation of a Mobile Personalized Blood Glucose Prediction System for Patients With Gestational Diabetes Mellitus

glycemic curve 2 hours after the start of the meal ([mmol/L]/hour);BG60: blood glucose level 1 hour after the start of the meal (mmol/L); andPeak BG: peak value on a postprandial BG curve (mmol/L).Step 5The resulting data were supplemented by the data used

Evgenii Pustozerov, Polina Popova, Aleksandra Tkachuk, Yana Bolotko, Zafar Yuldashev, Elena Grineva

JMIR Mhealth Uhealth 2018;6(1):e6


Adherence of Female Health Care Workers to the Use a Web-Based Tool for Improving and Modifying Lifestyle: Prospective Target Group Pilot Study

Adherence of Female Health Care Workers to the Use a Web-Based Tool for Improving and Modifying Lifestyle: Prospective Target Group Pilot Study

The worst quality of sleep was associated with the graduated nurse working in the surgery room group, which also showed elevated levels of serum cortisol (>690 nmol/L).Besides elevated S-cortisol levels, the graduated nurse working in the surgery room group

Tomislav Jukic, Alojz Ihan, Marija Petek Šter, Vojko Strojnik, David Stubljar, Andrej Starc

J Med Internet Res 2020;22(8):e19500