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The Needs of Older Adults With Disabilities With Regard to Adaptation to Aging and Home Care: Questionnaire Study

By the degree of influence, dysfunction ranked the highest, followed by age, monthly income, and living conditions (Table 4).Table 4Factors affecting needs of the participants for adaptation to aging.VariableSample regression coefficient (b)Beta level (β)t

Laiyou Li, Ning Sun, Libo Yu, Xiaoxin Dong, Jing Zhao, Yuchen Ying

JMIR Rehabil Assist Technol 2020;7(2):e16012

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Influence of Scanner Precision and Analysis Software in Quantifying Three-Dimensional Intraoral Changes: Two-Factor Factorial Experimental Design

The secondary null hypothesis was that the software used to analyze the data will not influence the volume change, average profile loss, and maximum point loss observed for either scanner.MethodsParticipantsData were collected from a larger clinical longitudinal

Saoirse O'Toole, David Bartlett, Andrew Keeling, John McBride, Eduardo Bernabe, Luuk Crins, Bas Loomans

J Med Internet Res 2020;22(11):e17150

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Patients’ Acceptance of Smartphone Health Technology for Chronic Disease Management: A Theoretical Model and Empirical Test

As the leading preventable risk factor for myocardial infarction, cerebral infarction, and heart failure, hypertension is an ongoing challenge to health care systems [2].

Kaili Dou, Ping Yu, Ning Deng, Fang Liu, YingPing Guan, Zhenye Li, Yumeng Ji, Ningkai Du, Xudong Lu, Huilong Duan

JMIR Mhealth Uhealth 2017;5(12):e177

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Factors Affecting Bone Mineral Density Among Snowy Region Residents in Japan: Analysis Using Multiple Linear Regression and Bayesian Network Model

Nutrition, exercise habits, and muscle mass, which have been thought to affect bone density, were not selected for the model.Figure 2 shows the Bayesian network in determining the influence level between bone density and each associated factor.

Teppei Suzuki, Tomoko Shimoda, Noriko Takahashi, Kaori Tsutsumi, Mina Samukawa, Sadako Yoshimura, Katsuhiko Ogasawara

Interact J Med Res 2018;7(1):e10

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The French eHealth Acceptability Scale Using the Unified Theory of Acceptance and Use of Technology 2 Model: Instrument Validation Study

The UTAUT2 comprises 26 items divided into 8 constructs: Performance Expectancy (PE, 3 items), Effort Expectancy (EE, 4 items), Social Influence (SI, 3 items), Facilitating Conditions (FC, 4 items), Hedonic Motivation (HM, 3 items), Price Value (PV, 3 items

Meggy Hayotte, Pierre Thérouanne, Laura Gray, Karine Corrion, Fabienne D'Arripe-Longueville

J Med Internet Res 2020;22(4):e16520

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Feasibility and Utility of mHealth for the Remote Monitoring of Parkinson Disease: Ancillary Study of the PD_manager Randomized Controlled Trial

Moreover, deterioration of a caregiver’s social life seemed to be the most influential factor among Zarit items.

Dimitris Gatsios, Angelo Antonini, Giovanni Gentile, Andrea Marcante, Clelia Pellicano, Lucia Macchiusi, Francesca Assogna, Gianfranco Spalletta, Heather Gage, Morro Touray, Lada Timotijevic, Charo Hodgkins, Maria Chondrogiorgi, George Rigas, Dimitrios I Fotiadis, Spyridon Konitsiotis

JMIR Mhealth Uhealth 2020;8(6):e16414

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Engagement and Retention: Measuring Breadth and Depth of Participant Use of an Online Intervention

DEPTH approximates the second component from the PCA.Using the factor loadings from the PCA yielded similar results to those using the methods described above. The measures of BREADTH and DEPTH were again standardized (mean 0, SD 1) for further analyses.

Mick P Couper, Gwen L Alexander, Noel Maddy, Nanhua Zhang, Michael A Nowak, Jennifer B McClure, Josephine J Calvi, Sharon J Rolnick, Melanie A Stopponi, Roderick JA Little, Christine Cole Johnson

J Med Internet Res 2010;12(4):e52

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Development of a Web-Accessible Population Pharmacokinetic Service—Hemophilia (WAPPS-Hemo): Study Protocol

IntroductionHemophilia A and B are X chromosome–linked bleeding disorders caused by mutations in the factor VIII (FVIII) and factor IX (FIX) genes. Both factors take part in the intrinsic pathway of blood coagulation.

Alfonso Iorio, Arun Keepanasseril, Gary Foster, Tamara Navarro-Ruan, Alanna McEneny-King, Andrea N Edginton, Lehana Thabane

JMIR Res Protoc 2016;5(4):e239

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Wearable Technology Acceptance in Health Care Based on National Culture Differences: Cross-Country Analysis Between Chinese and Swiss Consumers

Performance expectancy, social influence, and health consciousness influenced the behavior intention of the Chinese significantly, whereas performance expectancy, hedonistic motivation, effort expectancy, and social influence had a significant influence on

Dong Yang Meier, Petra Barthelmess, Wei Sun, Florian Liberatore

J Med Internet Res 2020;22(10):e18801

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School Counselors’ Perspectives of a Web-Based Stepped Care Mental Health Service for Schools: Cross-Sectional Online Survey

It is likely that these barriers influence the uptake of other Web-based programs and resources, although there is little research examining school counselors’ perspectives toward more recent developments such as mobile technology, e-monitoring tools, automated

Bridianne O'Dea, Catherine King, Mirjana Subotic-Kerry, Kathleen O'Moore, Helen Christensen

JMIR Ment Health 2017;4(4):e55

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