Users’ preference for using emoji in the online medical community

doi:10.21203/rs.3.rs-2118706/v1

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Research Article

Users’ preference for using emoji in the online medical community

https://doi.org/10.21203/rs.3.rs-2118706/v1

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Background

The application of information technology in the medical industry is growing. The traditional face-to-face doctor–patient interaction has turned into an online doctor–patient interaction, particularly in the case of an epidemic outbreak. Online doctor–patient communication has become increasingly common. Text communication can no longer meet people’s new communication needs. The appearance of emoji compensates for the challenges in online doctor–patient interactions to convey nontext information, such as facial emoji, gestures and voice tones.

Objective

This study aimed to explore the impact of using emoji during online doctor–patient communication on users’ perception of the medical community by considering the moderating effect of demographics.

Methods

An online questionnaire survey was conducted amongst 520 people from December 2021 to January 2022 by random sampling. The frequency, emoji use style and the users’ previous consultation experience score were used as the main independent variables in this study. The perceived effect of the user was adopted as the dependent variable. Wilcoxon signed-rank test and multiple regression analysis were used for data analysis.

Result

For the use frequency and style of emoji mentioned in this study, a significant difference exists between the preference of users who use emoji for a single time and those who use the same emoji continuously (P < 0.001), with the former showing a better performance than the latter. A significant difference exists between users who use open-style emoji and users who use neutral-style emoji (P < 0.001). The emoji perception effect of open style was better than that of neutral style. Users’ preference for emoji use is not affected regardless of whether they are platform users a platform is used (P > 0.05). Men and individuals under 30 are easily influenced by the use of emoji and the characteristics of emoji use. People (users) with educational attainment not higher than high school education tend to have preferences for the frequency of emoji use.

Conclusion

The characteristics of emoji use affected the perceived effect of online communication with doctors. Single use of emoji and relatively open style of emoji had a positive impact on the degree of acceptance of doctors’ information. Men and people under the age of 30 showed more expressive preferences for facial features than women and people over the age of 30. Therefore, doctors should properly use emoji for patients with different characteristics to help strengthen the communication between doctors and patients. Moreover, the online medical community should design diversified emoji for patients with different characteristics to provide personalized services.

doctor-patient communication

online medical community

emoji

characteristics

With the development of social media, emoji has gradually become a popular computer-mediated communication (CMC) in people’s daily life[1]. Emoji was first developed from emoticon. At present, it is collectively referred to as emoticon and emoticon package. Emoticon, a clever combination of emotion and icon, has become a brand-new word and is now known as ‘facial text’ [2]. Emoji not only means ‘facial text’ but also includes various abstract concepts and ideas, body parts and gestures, animals and plants, daily necessities and activities [3]. It can be used alone or embedded in an SMS, email, post and other media together with text. Emoji is more colourful, diverse, visual and personalized than emoticon. Unlike punctuation, emoji allows users to express emotion to information recipients in a clear and personalized way [4–6]. The eMarketer survey shows that more than 6 billion emojis are used every day by 90% of the world’s online population [7]. Emoji and its application in CMC and artificial intelligence, such as semantic pattern recognition and emotion analysis, have gained increasing attention in different fields.

However, the emotions expressed by emoji have received little attention from researchers despite the rapid development of emoji in the past few years [8]. Some researchers believe that ignoring emojis during emotion research is unreasonable because they convey crucial emotional information and play an important role in expressing emotions and views on social media[9]. Some studies showed that the use of emoji in marketing may affect consumers’ emotional state[10], thereby affecting consumers’ purchase intention [11]. At present, the research on emoji has extended from the fields of communication and linguistics to the fields of psychology, sociology, computer science, law and marketing. However, the research on emoji is mainly involved in marketing but rarely used in interpersonal communication in the medical field[12].

In the medical field, online consultation has become a trend with the rise of the Internet medical industry, and online doctor–patient communication has become an essential link. However, in an online doctor–patient communication scenario, the doctor–patient communication mode may have varying relationship dominance because of the differences in communication scenarios and role relationships[13, 14]. According to cue-filtered-out theory, the essential difference between CMC (Computer-mediated Communication) and face-to-face communication lies in the lack of nonverbal cues, such as voice intonation, facial expression, body language, interpersonal distance and communication scene. The lack of social cues in online doctor–patient communication affects the perception and judgement of doctors and patients on each other’s communication behaviour. Forming complete trust between doctors and patients is difficult because of the lack of rich interpersonal clues and details, and misunderstandings may exist in the communication process. Emoji can be used for online communication to express emotions decorate information content or replace words in statements that can affect people’s perceived effect of emotions to influence the text information to some extent. Riordan et al.[15] determined that nonfacial emoji can convey emotions and eliminate information ambiguity. The rational use of emoji helps users understand clearly the information behind the text[16]. It can also make the silent and rigid network text language dynamic, thereby increasing the realism of the network language. The improper use of emoji brought by its prevalence may also cause misunderstanding between both parties. Therefore, the characteristics of emoji use must be given attention. Understanding the use of emoji helps in assessing users’ states, emotions and preferences to provide personalize services and optimise the user experience.

In previous studies, the use of emoji is measured in two ways: frequency and style. Frequency refers to the number of times the same emoji is used continuously. The style of emoji refers to the emoji with different effects. Oleszkiewicz, et al. took frequency as an element for measurement to predict population attributes based on Facebook user data in the research of analysing emoji[17]. Park, et al. [18] compared the emoji usage habits in different countries based on 1213163 twitter texts from 78 countries by focusing on the frequency and style of use. Chen, et al.[19] investigated the use of emoji by young Chinese people. The researchers asked the frequency of using emoji of different styles and emotional colors through questionnaires. In general, the frequency and style of use is the most common and most reflective way to measure the intensity of emoji. Several emojis used in this study are frequently used in various social relations (including doctor–patient relations). We define the emoji without obvious emotional colour as neutral style and those with obvious positive emotional colour as open style[20].

In addition to the characteristics of emoji use, demographic characteristics can affect people’s behaviours. Previous studies showed that gender is one of the important factors influencing emoji usage behaviours. Women use emoji more frequently than men (Liu Liqun and Liu Xichen, 2021)[21]. They also mainly use emoji that convey positive emotions (Tossell et al., 2012)[22]. Moreover, age is a factor influencing emoji use. For example, Liu Xuetai et al. (2019) [23] analysed the chat data of WeChat groups and found that compared with older individuals, individuals aged 25 years tend to use fashionable and open emoji that convey negative emotions. In comparison, older individuals prefer to use neutral and conservative emoji. These studies showed that the characteristics of the population have some influence on the acceptance of information. Therefore, we should deeply explore the influence of emoji usage behaviour on user-perceived effects according to the characteristics of the population.

The use of emoji in doctor–patient communication in online medical communities has become increasingly common, thereby promoting clear communication between doctors and patients.

Therefore, what role does emoji play in the medical field? Do people with different characteristics have different preferences for emoji? We discuss the role of emoji in the medical field, find out the preferences of different groups for emoji and discuss how to use emoji for the improvement of the perceived effect of patients in doctor–patient communication.

Study Design

A study of the preferences of people using emoji for online doctor–patient interactions was conducted in Chongqing, China, from December 2021 to January 2022. An online questionnaire survey was adopted to explore the impact of emoji use on patients’ perceptions. We discussed the effect of emoji’s frequency and style on patients’ perceptions of online doctor–patient communication. The regulatory role of participants’ gender, age and education profile were also examined.

Participant Selection

We first selected voluntary participants by random sampling. They could freely choose whether to submit the questionnaire after reading the informed consent form.

Questionnaire

The content of the questionnaire was finally determined after a discussion with some experts in informatics, statistics and nursing group. The questionnaire was divided into three parts: basic information (including demographic characteristics), an investigation of users’ consulting experience and an emoji case study.

Part I: We referred to the article on demographic characteristics that express usage preferences to determine the questionnaire content of this part[24–26]. Demographic characteristics include gender, age, education background of the respondents and whether the respondents have used the online medical community platform.

Part II: In this part, a scale was used to measure whether doctors use polite words, actively encourage and comfort patients and maintain respect for patients. It also measured whether users trust doctors in the consultation experience. As shown in Table 1, question 1–1 is from the Liverpool doctors’ communication ability evaluation scale [27], question 1–2 is from the scale prepared by Yang Teng[28], question 1–3 is from the interpersonal process of care [29] and question 1–4 is from the medical inertia scale (care).

Table 1

Questionnaire materials in part 2
Question
1-1. Doctors use polite words during online visits
1–2. Doctors actively encourage and comfort patients during online consultation
1–3. Your doctor treats you with respect during your online interview
1–4. Do you trust your doctor’s advice (diagnosis and treatment plan) during online consultation

Part III: This part determined the influence of the characteristics of emoji use on user perception. The simulated dialogue mode was adopted. It was divided into two cases for independent comparative research. It mainly measured the emoji dimension (emoji use frequency and emoji use style). As shown in Table 2, questions 2-a-1, 2-a-2, 2-b-1 and 2-b-2 are users’ satisfaction scores on the continuous use and type style of emoji. These four questions were used as the main independent variables in the present study to explore the willingness of users to participate after using emoji. The frequency of emoji use was based on whether the emoji was used continuously, whereas the emoji style was based on the use of emojis with different effects, as shown in Figs. 1 and 2. Case 1 consists of emoji used alone and neutral-style emoji, whereas case 2 consists of continuous use of the same emoji and open-style emoji. Case 1 generally expresses an implicit emotion, whereas case 2 expresses an open and enthusiastic emotion. Given that doctors and patients tend to communicate positively, negative emotions were not included in this study.

Table 2

Questionnaire materials in part 3
Case 1	Case 2
2-a-1. Please rate the emoji used in case 1: frequency use	2-b-1. Please rate the emoji used in case 2: frequency use
2-a-2. Please rate the emoji used in case 1: style use	2-b-2. Please rate the emoji used in case 2:style use
2-a-3. The way emoji are used in case 1 will create psychological distance between doctors and patients	2-b-3. The way emoji are used in case 2 will create psychological distance between doctors and patients
2-a-4. The use of emoji in case 1 will make you happy	2-b-4. The use of emoji in case 2 will make you happy
2-a-5. The use of emoji in case 1 helps to create a doctor-friendly image	2-b-5. The use of emoji in case 2 helps to create a doctor-friendly image
2-a-6. The way emoji are used in case 1 tends to make you trust the doctor	2-b-6. The way emoji are used in case 2 tends to make you trust the doctor

In February 2022, a presurvey of 50 participants was conducted to test the reliability of the questionnaire. The Cronbach’s alpha value in the questionnaire was 0.904.

Data Collection

After answering demographic and medical experience questions, participants were given two facial emoji case modules with different facial emoji usage characteristics. Each option was rated from 1 to 5, indicating ‘strongly disagree’, ‘disagree’, ‘neutral’, ‘agree’ and ‘strongly agree’. The results of the questionnaire were downloaded by the interviewer on the computer.

Ethical Aspects

The study protocol was approved by the Ethics Committee of Chongqing Medical University (record number 2018011). The participants gave their informed consent before answering the questionnaire.

Statistical Analysis

The collected data were processed using Microsoft Excel before being entered into the database. SPSS 26.0 (IBM Corporation, Armonk, NY, US) was used for data analysis. The frequency and percentage of categorisation variables were calculated for the demographic characteristics of the participants. The preference values recorded in the third part of the questionnaire were statistically grouped. Wilcoxon signed-rank test of symbols was used to test whether significant differences existed between the use features of different emojis. The calculated median was used to represent the perceived effects of specific use features. Multivariate linear regression analysis was used to explore the factors affecting the subjects’preferences. Control variables included gender, age and education to supplement the effect of participants’characteristics (e.g. demographic characteristics) on their preference for using traits. A P value not greater than 0.05 was considered statistically significant.

Quality Control

The questionnaire was modified several times after expert interviews and a pilot survey. The offline research team members, including three students (two postgraduate and one undergraduate), received standardised investigation training. These investigators should understand the purpose and methodology of the study in detail and have extensive experience in dealing with potentially sensitive issues.

This study adopted a non-probabilistic sampling method to conduct an online questionnaire survey with the help of the Questionnaire Star Platform. A total of 10 invalid questionnaires were removed, 510 valid questionnaires were collected, and the recovery rate was 98.1%.

Demographic Characteristics of Participants

The demographic characteristics of the participants are shown in Table 3. The number of male participants (53.3%) was almost the same as that of female participants (46.7%). Of the participants, 53.5% were aged ≤ 30 years. Moreover, the vast majority (69.0%) of the participants were undergraduate or junior college students.

Table 3

Demographic characteristics of the participants (n = 510)
Variables	Group	Frequency (n) or sample percentage (%)
Age	≤ 30 > 30	273 (53.5%) 237 (46.5%)
Gender	Male Female	272(53.3%) 238 (46.7%)
Education	Junior high school and below High school or technical secondary school Undergraduate or junior college Master's degree or above	21 (4.1%) 37 (7.3%) 352 (69%) 100 (19.6%)

Usage of the online medical platform

Several of the most popular Chinese online medical platforms, such as Online Good Doctor, Clove Doctors and Dr. Chun Yu, were included in the survey. These online medical platforms are similar to Doctolib and Doctor on Demand, which are famous in Europe and the United States, respectively. We were not limited to the users of the online medical platform because we also hoped to obtain the expectations of nonusers who may be potential users of the platform. As shown in Table 4, the number of users (57%) was almost equal to that of non-user participants (43%). For the user group, the main platforms chosen were Online Good Doctors (42.6%) and Clove Doctors (39.9%). The hospital has its own Internet platform (32.4%). The majority of users (59.1%) and nonusers (65.0%) were willing to pay the consulting fee on the platform online.

Table 4

Online medical platform usage (n = 510)
Variables	Group	Frequency (n) or sample percentage (%)
Variables	Group	User (n = 291)	Nonuser (n = 219)
Platforms used (multiple choices)	Online Good Doctor Spring Rain Doctors Clove Doctors Sought treatment The hospital has its own Internet platform Other	126 (42.6%) 39 (13.2%) 118 (39.9%) 49 (16.6%) 96 (32.4%) 52 (17.6%)
(Intended) Purpose of Using the platform (multiple choices)	Searching for medical knowledge Online consultation (for yourself) Online consultation (helping others) Online prescription Other	181 (62.2%) 141 (48.5%) 88 (30.2%) 35 (11.3%) 29 (10.0%)	155 (70.8%) 116 (53.0%) 62 (28.3%) 35 (16.0%) 22 (10.0%)
(Intended) to pay the service	Yes No	172 (59.1%) 119 (40.9%)	142 (65.0%) 77 (35.0%)

Score survey of consultation experience

The participants’medical experience scores are shown in Table 5. The average value of the previous consultation experience scores of the user group is 16.33, whereas the average value of the previous consultation experience scores of the nonuser group is 16.07.

Table 5

Users’ medical experience score (n = 510)
Variables	Group	Mean (m) or standard deviation (sd)
Variables	Group	User (n = 291)	Nonuser (n = 219)
Consultation experience	Total score	16.33 (3.007)	16.07 (3.468)
	Polite expressions	4.20 (0.859)	4.03 (0.979)
	Active comfort	3.95 (0.875)	3.92 (0.922)
	Maintain respect	4.20 (0.827)	4.09 (0.912)
	Trust	3.98 (0.865)	3.98 (0.901)

Choice of emoji preferences

We set up two scenes: using neutral-style emoji alone, which is implicit; using open-style emoji continuously, which is enthusiastic. As shown in Table 6, we used Wilcoxon signed-rank test to analyse the differences in perceptual effects of different emoji use methods. Significant differences existed between the two use features mentioned in this study in the perceptual effects of single and continuous use of emoji (P < 0.001). These emojis tended to exhibit single-use features (large median). The results of type and style (P < 0.001) were consistent with the results of emotional intensity. A significant difference existed between neutral-style emoji and open-style emoji (P < 0.001). The effect of the open-style emoji was better (with a large median) than that of the neutral-style emoji. Moreover, the experimental results showed that no significant difference existed between users and nonusers (P > 0.05)

Table 6

Choice of emoji preferences
Frequency of emoji
Options	Median (average)	Z	P
Single use	4.19	−5.186b	.000**
Continuous use	3.97
Styles of emoji
Options	Median (average)	Z	P
Neutral style	3.93	−4.904b	.000**
Open style	4.13
Participant characteristics
Options	Median (average)	Z	P
User			.058
Nonuser

Influence of demographic characteristics on emoji preference

In the third part of the questionnaire, the total scores of the four questions about users’ overall perception after using emoji were used as dependent variables to reflect users’ satisfaction with doctors’ online answers. The following statistical description was made for the topics of this part. Table 7 shows the specific statistical description results. In the dimension of use frequency, the score range of case 1 and case 2 is 1–5 points, the average value of case 1 is 4.11, and the average value of case 2 is 3.90. In the dimension of use style, the average score of case 1 is 4.05, whereas the average score of case 2 is 3.88. The total scores of the two cases showed that the average total score of case 1 is 16.15, and the average total score of case 2 is 15.61.

The independent variables concerned in this study mainly include three aspects. The first aspect is the related dimension of the same emoji uses frequency. The second aspect is the style dimension of emoji, and the third aspect is the total score of emotional support experience of users before seeing a doctor.

The questions related to the use times of emoji (used alone or continuously) are ‘please score the use method of emoticons in case 1 (used alone)’ and ‘please score the use method of emoticons in case 2 (used continuously)’ in the questionnaire. They were sorted according to the Likert scale score of 1–5.

The items related to the style dimension of emoji are ‘please rate the style of emoji in case 2’ and ‘please rate the style of emoji in case 2’ in the questionnaire. They were also sorted according to the Likert scale score of 1–5.

The questions related to the emotional support experience of the users’ previous treatment experience are as follows: ‘Chinese medical students use polite language in the consultation’, ‘Chinese medical students actively encourage and comfort patients in the consultation’, ‘doctors maintain respect for you during the consultation’, and ‘you will trust the condition information (such as diagnosis, treatment plan) fed back by doctors during the consultation’. All four questions are five-point scoring questions, where 1 means very dissatisfied, whereas 5 means very satisfied. In this study, the main demographic characteristics of the subjects, including gender, age and education level, were included in the analysis as control variables. In this study, the participants were divided according to gender (men and women), age (≤ 30 years old and > 30 years old) and educational background (not higher than high school [technical secondary school] and not lower than undergraduate [college]) to test further the emoji use of different groups. The statistical method of multiple linear regression was used to investigate further the impact of the use of emoji on the overall perception of users. As shown in Table 8, there was a significant correlation between the number, type and style of male emoticons and user perception (P < 0.001). The effect index decreased with the increase of using the same expression. However, in the experiment of case 2, the number of emoji used by women was not statistically significant. In the dimension of emoji use style, there are significant statistical significance for both men and women. Among participants aged 30 years or younger, there was a significant correlation between emoji frequency, style, and user perception (P < 0.001). However, there was no significant correlation between the number of emoji used by participants over 30 years old in case 2 experiment (P > 0.05). There was a significant correlation between the two emoji usage modes in people with different educational backgrounds (P < 0.05). With the increasing frequency of emoji use, the influence coefficient showed a downward trend. Comparing case 1 with case 2, the influence coefficient of the group with education background less than high school (technical secondary school) decreased. However, the influence coefficient of the group with higher education level than undergraduate (junior college) increased.

Table 7

Statistical description of emoji cases
Title	Minimum value	Maximum value	Mean	Standard deviation
Please rate the emoji used in case 1: frequency use	1	5	4.11	.888
Please rate the emoji used in case 1: style use	1	5	4.05	.889
The use of emoji in case 1 will shorten the psychological distance between doctors and patients	1	5	4.10	.892
The use of emoji in case 1 will make you feel happy	1	5	4.05	.919
The use of emoji in case 1 helps to create a friendly image of doctors	1	5	4.06	.906
The use of emoji in case 1 can easily give you a sense of trust in the doctor	1	5	3.95	.973
Total score of case 1	4	20	16.15	3.433
Please rate the emoji used in case 2: frequency use	1	5	3.90	.958
Please rate the emoji used in case 2: style use	1	5	3.88	.942
The use of emoji in case 2 will shorten the psychological distance between doctors and patients	1	5	3.93	.923
The use of emoji in case 2 will make you feel happy	1	5	3.90	.961
The use of emoji in case 2 helps to create a friendly image of doctors	1	5	3.91	.947
The use of emoji in case 2 can easily give you a sense of trust in the doctor	1	5	3.87	.977
Total score of case 2	4	20	15.61	3.633

Table 8

Influence of emoji usage on the overall user perception
Variable	Case 1		Case 2
Variable	Male	Female	Male	Female
Frequency of emoji	0.346***(6.327)	0.271***(4.423)	0.295***(5.924)	0.044 (0.793)
Style of emoji	0.207***(6.327)	0.579***(9.519)	0.664***(13.184)	0.873***(15.461)
Observed value	272	238	272	238
Variable	Case 1		Case 2
Variable	Age ≤ 30	Age > 30	Age ≤ 30	Age > 30
Frequency of emoji	0.268***(5.308)	0.393***(5.807)	0.230***(4.749)	0.055(0.934)
Style of emoji	0.616***(12.060)	0.455***(6.692)	0.712***(14.236)	0.487***(14.604)
Observed value	273	273	273	237
Variable	Case 1		Case 2
Variable	Educational background not higher than high school (technical secondary school)	Bachelor’s degree or above (junior college)	Educational background not higher than high school (technical secondary school)	Bachelor’s degree or above (junior college)
Frequency of emoji	0.318***(3.050)	0.315***(7.131)	0.200**(1.757)	0.173***(4.350)
Style of emoji	0.639***(5.773)	0.546***(12.296)	0.563***(4.602)	0.778***(19.276)
Observed value	58	452	58	452
Note: The values are standardised regression coefficients. , * and *** indicate significance at the statistical level of 1%, 5% and 10%, respectively. The values in parentheses are the values of regression variables.

Clove Doctors (42 6%) and Online Good Doctors (39.9%) had the highest utilization rate amongst 291 users. For users or nonusers, the purpose of the use or possible use of the platform is to consult for themselves and others. The survey results showed that most participants are willing to pay for service on online medical platforms. Research showed that the number of Internet users in China and the use of medical data are increasing[30], particularly after the COVID-19 pandemic [31]. Research also showed that an increasing number of people pay considerable attention to their health and choose online medical services, such as online consultation, to meet their health needs; this finding is consistent with our research results [32].

The results showed that users prefer to use emoji once rather than repeatedly. Some studies stated that users sprefer to use emoji multiple times in a row; however, these studies are in the field of sociology [33, 34]. The results of the present study indicated that people have become increasingly cautious and strict in terms of health. For the emoji use style, users prefer open-style emoji in doctor–patient communication, possibly because people also want to be comfortable in communicating with doctors[35, 36]. Our study also found that emoji preferences were unaffected by whether or not they were users of a doctor-patient communication platform.

According to regression analysis, both frequency and emoji use style affect men’s willingness in doctor–patient communication (P < 0.001). However, only the emoji use style affects women’s willingness to communicate (P < 0.001). This finding may indicate that men are more vulnerable to the influence of emoji use times than women, and they prefer single use of emoji. Men and women have different attitudes towards the use of emoji[37]. Moreover, people aged less than or equal to 30 years tend to be affected by the number of emoji used. They also tend to prefer the single use of emoji. Furthermore, people with education not higher than high school (users) prefer open-style emoji.

The intervention of emoji can be used as a kind of situational language in certain online consultation scenarios to compensate for the lack of nonverbal cues, such as voice intonation, facial expression, body language, interpersonal distance and communication scenes, in the traditional offline consultation by changing the characteristics of emoji use, such as frequency and style, in the online doctor–patient dialogue. For example, we can maximize the effect of emoji in promoting strategies in doctor–patient communication by reducing the use of the same emoji and using some relatively open emojis. The regulatory role of group characteristics is also reflected in it. Therefore, users with different characteristics should use different facial emoji features to produce good communication results. For example, men younger than 30 should reduce the use of the same emoji and use different emojis with an open emotion.

Ethical approval and consent to participate

The studies involving human participants were reviewed and approved by the Ethics Committee of the Chongqing Medical University (record number 2018011). All methods of this study are in accordance with relevant guidelines and regulations. The participants gave their written informed consent before answering the questionnaire，they know the purpose of the study.

Competing interests

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

DATA AVAILABILITY

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation. If anyone wants to obtain the data of this study, contact the author: [email protected].

Author Contributions

J.L., M.J., P.W., and Y.D. performed the experiments, J.L. and Y.D. helped collect data, Y.D. and J.L. analyzed the data and wrote the paper. J.L., Z.Z., and X.Z., assisted in the data analysis. X.H. and J.L. helped draft the manuscript. Y.D. and J.L. contributed equally to this work. All authors have read and approved the final manuscript.

Funding

This research was funded by the Ministry of Education in China Project of Humanities and Social Sciences (Research on the mechanism and intervention countermeasures of framing effects in the formation of adolescent health literacy, grant number 20YJCZH043); the Intelligent Health Knowledge Discovery and Information Service in Chongqing Medical University (grant number ZHYX2019006); the Chongqing Medical University Future Medical Innovation Team Support Program (W0054); Chongqing Medical University, China, the Intelligent Medical Foundation of Chongqing Medical University (grant number YJSZHYX202016); the College of Medical Informatics, Chongqing Medical University, China, Student Research and Innovation Experiment Project (grant number 2019C009); Chongqing Municipal Education Commission, China, Chongqing Graduate Scientific Research Innovation Project (grant number CYS20225); Chongqing Postgraduate Innovation Project of Chongqing Municipal Education Commission of China (Approval No.: CYS22388).

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Users’ preference for using emoji in the online medical community

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Abstract

Background

Objective

Methods

Result

Conclusion

Figures

Introduction

Materials And Methods

Study Design

Participant Selection

Questionnaire

Data Collection

Ethical Aspects

Statistical Analysis

Quality Control

Results

Demographic Characteristics of Participants

Usage of the online medical platform

Score survey of consultation experience

Choice of emoji preferences

Influence of demographic characteristics on emoji preference

Discussion

Conclusion

Declarations

References

Additional Declarations

Supplementary Files

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