FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2978496786> ?p ?o ?g. }

• W2978496786 endingPage "e15544" @default.
• W2978496786 startingPage "e15544" @default.
• W2978496786 abstract "Background Mobile health (mHealth) is becoming more popular as a way of sharing medical information. For the patient, it saves time, reduces the need for travel, reduces the cost of searching for information, and brings medical services “to your fingertips.” However, it also brings information overload and makes the patient’s choice of physician more difficult. Objective This study aimed to identify the types of physician information that play a key role in patients’ choice of physician and to explore the mechanism by which this information contributes to this choice. Methods Based on the stimulus-organism-response (SOR) model and online trust theory, we proposed a research model to explain the influence of physician information on patients’ choice of physician. The model was based on cognitive trust and affective trust and considered the moderating role of patient expertise. Study 1 was an eye-tracking experiment (n=42) to identify key factors affecting patients’ choice of physician. Study 2 was a questionnaire study (n=272); Partial Least Squares Structural Equation Modeling was used to validate the research model. Results The results of Study 1 revealed that seven types of physician information played a key role in patients’ choice of physician. The results of Study 2 revealed that (1) physicians’ profile photo information affected patients’ choice of physician by positively influencing affective trust (P<.001); (2) physicians’ nonprofile photo information affected patients’ choice of physician by positively influencing cognitive trust (P<.001); (3) patient-generated information affected patients’ choice of physician by positively affecting cognitive trust (P<.001) and affective trust (P<.001), and patient expertise played a positive moderating role on both (P=.04 and P=.01, respectively); and (4) cognitive trust and affective trust both positively affected patients’ choice of physician, with affective trust playing a more significant role (P<.001 and P<.001, respectively). Conclusions Seven types of physician information were mainly used by patients when choosing physicians offering mHealth services; trust played an important role in this choice. In addition, the level of patient expertise was an important variable in moderating the influence of physician information and patients’ trust. This paper supports the theoretical basis of information selection and processing by patients. These findings can help guide app developers in the construction of medical apps and in the management of physician information in order to facilitate patients’ choice of physician." @default.
• W2978496786 created "2019-10-10" @default.
• W2978496786 creator A5018863416 @default.
• W2978496786 creator A5038823679 @default.
• W2978496786 creator A5073029784 @default.
• W2978496786 creator A5081253185 @default.
• W2978496786 date "2019-10-23" @default.
• W2978496786 modified "2023-10-16" @default.
• W2978496786 title "The Influence of Physician Information on Patients’ Choice of Physician in mHealth Services Using China’s Chunyu Doctor App: Eye-Tracking and Questionnaire Study" @default.
• W2978496786 cites W1235377039 @default.
• W2978496786 cites W1569276499 @default.
• W2978496786 cites W1770026754 @default.
• W2978496786 cites W181457025 @default.
• W2978496786 cites W1836486152 @default.
• W2978496786 cites W1933750417 @default.
• W2978496786 cites W1971200165 @default.
• W2978496786 cites W1973151518 @default.
• W2978496786 cites W1977350117 @default.
• W2978496786 cites W1985270055 @default.
• W2978496786 cites W1985771617 @default.
• W2978496786 cites W1991451950 @default.
• W2978496786 cites W1993959534 @default.
• W2978496786 cites W2001375017 @default.
• W2978496786 cites W2007343520 @default.
• W2978496786 cites W2017508593 @default.
• W2978496786 cites W2041360546 @default.
• W2978496786 cites W2061650887 @default.
• W2978496786 cites W2067980049 @default.
• W2978496786 cites W2069206189 @default.
• W2978496786 cites W2085756167 @default.
• W2978496786 cites W2089203823 @default.
• W2978496786 cites W2092100587 @default.
• W2978496786 cites W2097379719 @default.
• W2978496786 cites W2110078189 @default.
• W2978496786 cites W2118501966 @default.
• W2978496786 cites W2123841990 @default.
• W2978496786 cites W2124325639 @default.
• W2978496786 cites W2130892515 @default.
• W2978496786 cites W2134629032 @default.
• W2978496786 cites W2136407476 @default.
• W2978496786 cites W2147338703 @default.
• W2978496786 cites W2166140580 @default.
• W2978496786 cites W2170356717 @default.
• W2978496786 cites W2188426035 @default.
• W2978496786 cites W2259873046 @default.
• W2978496786 cites W2526066647 @default.
• W2978496786 cites W2551379735 @default.
• W2978496786 cites W2562065761 @default.
• W2978496786 cites W2562745534 @default.
• W2978496786 cites W2596916116 @default.
• W2978496786 cites W2742459750 @default.
• W2978496786 cites W2757087020 @default.
• W2978496786 cites W2783127432 @default.
• W2978496786 cites W2809671866 @default.
• W2978496786 cites W2898889914 @default.
• W2978496786 cites W2900639770 @default.
• W2978496786 cites W2904765011 @default.
• W2978496786 cites W2904794295 @default.
• W2978496786 cites W2905465522 @default.
• W2978496786 cites W2929198708 @default.
• W2978496786 cites W3122188364 @default.
• W2978496786 cites W3123967386 @default.
• W2978496786 cites W3124242707 @default.
• W2978496786 cites W3124686198 @default.
• W2978496786 cites W3124987483 @default.
• W2978496786 cites W3125732352 @default.
• W2978496786 cites W3144406692 @default.
• W2978496786 cites W4235678817 @default.
• W2978496786 cites W4240969601 @default.
• W2978496786 cites W4241241217 @default.
• W2978496786 cites W4249135598 @default.
• W2978496786 doi "https://doi.org/10.2196/15544" @default.
• W2978496786 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6913723" @default.
• W2978496786 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/31647466" @default.
• W2978496786 hasPublicationYear "2019" @default.
• W2978496786 type Work @default.
• W2978496786 sameAs 2978496786 @default.
• W2978496786 citedByCount "17" @default.
• W2978496786 countsByYear W29784967862020 @default.
• W2978496786 countsByYear W29784967862021 @default.
• W2978496786 countsByYear W29784967862022 @default.
• W2978496786 countsByYear W29784967862023 @default.
• W2978496786 crossrefType "journal-article" @default.
• W2978496786 hasAuthorship W2978496786A5018863416 @default.
• W2978496786 hasAuthorship W2978496786A5038823679 @default.
• W2978496786 hasAuthorship W2978496786A5073029784 @default.
• W2978496786 hasAuthorship W2978496786A5081253185 @default.
• W2978496786 hasBestOaLocation W29784967861 @default.
• W2978496786 hasConcept C118552586 @default.
• W2978496786 hasConcept C119857082 @default.
• W2978496786 hasConcept C15744967 @default.
• W2978496786 hasConcept C159110408 @default.
• W2978496786 hasConcept C169900460 @default.
• W2978496786 hasConcept C27415008 @default.
• W2978496786 hasConcept C2779363104 @default.
• W2978496786 hasConcept C41008148 @default.
• W2978496786 hasConcept C512399662 @default.
• W2978496786 hasConcept C71104824 @default.

• next