Article Text

Original research
Determinants of physicians’ online medical services uptake: a cross-sectional study applying social ecosystem theory
  1. Xueqing Peng1,
  2. Zhiguang Li2,3,
  3. Chi Zhang4,
  4. Rui Liu5,
  5. Yongzhi Jiang5,
  6. Jiayu Chen3,
  7. Zixin Qi5,
  8. Jinjin Ge1,
  9. Shiqi Zhao1,
  10. Meng Zhou4,
  11. Hua You1,4
  1. 1School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
  2. 2Center for Health Policy and Management Studies, Nanjing University, Nanjing, Jiangsu, China
  3. 3The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu, China
  4. 4School of Nursing, Nanjing Medical University, Nanjing, Jiangsu, China
  5. 5School of Health Policy & Management, Nanjing Medical University, Nanjing, Jiangsu, China
  1. Correspondence to Dr Hua You; youhua98{at}


Objective To investigate the determinants of willingness and practice of physicians’ online medical services (OMS) uptake based on social ecosystem theory, so as to formulate OMS development strategies.

Design Cross-sectional survey.

Setting Research was conducted in two comprehensive hospitals and two community hospitals in Jiangsu, China, and the data were gathered from 1 June to 31 June 2020.

Participants With multistage sampling, 707 physicians were enrolled in this study.

Outcome measure Descriptive statistics were reported for the basic characteristics. χ2 test, Mann-Whitney U test and Spearman’s correlation analysis were used to perform univariate analysis. Linear regression and logistic regression were employed to examine the determinants of physicians’ OMS uptake willingness and actual uptake, respectively.

Results The mean score of the physicians’ OMS uptake willingness was 17.33 (range 5–25), with an SD of 4.39, and 53.3% of them reported having conducted OMS. In the micro system, factors positively associated with willingness included holding administrative positions (b=1.03, p<0.05), OMS-related awareness (b=1.32, p<0.001) and OMS-related skills (b=4.88, p<0.001); the determinants of actual uptake included holding administrative positions (OR=2.89, 95% CI 1.59 to 5.28, p<0.01), OMS-related awareness (OR=1.90, 95% CI 1.22 to 2.96, p<0.01), OMS-related skills (OR=2.25, 95% CI 1.35 to 3.74, p<0.01) and working years (OR=2.44, 95% CI 1.66 to 3.59, p<0.001). In the meso system, the hospital’s incentive mechanisms (b=0.78, p<0.05) were correlated with willingness; hospital advocated for OMS (OR=2.34, 95% CI 1.21 to 4.52, p<0.05), colleagues’ experiences (OR=3.81, 95% CI 2.25 to 6.45, p<0.001) and patients’ consultations (OR=2.93, 95% CI 2.02 to 4.25, p<0.001) were determinants of actual uptake. In the macro system, laws and policies were correlated with willingness (b=0.73, p<0.05) and actual uptake (OR=1.98, 95% CI 1.31 to 2.99, p<0.01); media orientation was also associated with willingness (b=0.74, p<0.05).

Conclusion Multiple determinants influence physicians’ OMS application. Comprehensive OMS promotion strategies should be put forward from multidimensional perspectives including the micro, meso and macro levels.

  • telemedicine
  • health policy
  • organisation of health services
  • public health
  • social medicine

Data availability statement

Data are available upon reasonable request. Data are available upon reasonable request from the corresponding author. E-mail:

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:

Statistics from

Request Permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

Strengths and limitations of this study

  • This study is one of the first to interpret the determinants of online medical services (OMS) uptake among physicians.

  • Social ecosystem theory was applied as the theoretical framework to explore the multidimensional determinants of OMS uptake.

  • This was a cross-sectional study; no causal relationships were identified.

  • The causes that can explain the correlations still need to be verified through qualitative research.


‘Universal health coverage’ (UHC) is the primary goal of the WHO; the key to achieving it is to ensure that everyone has timely access to necessary healthcare services.1 Online medical services (OMS) refers to health services and information delivered or enhanced through the Internet and related technologies, including disease consultation, telemedicine, online re-examination, chronic disease management, rehabilitation guidance and so on.2 3 Generally, there are many ways to conduct OMS, such as videoconferencing, telephone audio, text information exchange.4 In China, OMS are usually carried out on specific internet medical platforms (eg, Doctor Chunyu, WeDoctor,, and the internet hospitals built by physical medical institutions), which can provide varieties of ways to conduct OMS.

As a novel medical service mode that uses the internet as the carrier, and which integrates both traditional medical and health services, OMS plays a vital role in narrowing the gap between medical resources and realising UHC. Due to a vast territory and large population, the uneven development of medical services between urban and rural zones has become a long-term, disturbing issue in China; the emergence of OMS provides an effective solution. Cao and Wang5 found that OMS can promote the flow of health resources from urban to rural areas and reduce the health gap between them. Moreover, OMS have exerted great effects on reducing the risk of cross-infection6 and delaying the spread of pandemics such as COVID-19.7 There is a rapid expansion of OMS during the COVID-19 pandemic,8 but many barriers of OMS uptake and expansion still exist, especially during the post-pandemic.

In spite of developing OMS has crucial practical value for building health services (eg, reducing healthcare costs, improving the medical services’ efficiency,and increasing access to services, etc), in China, however, the OMS employed have always been at a low level. According to the 46th China Statistical Report on Internet Development,3 among the country’s 276 million netizens, only 29.4% have participated in OMS. A number of studies have been conducted to try to identify the causes of the underuse of OMS. An extensive body of research has focused on the OMS demand side (patients),9–11 but ignored OMS providers. As a direct provider of OMS, physician’s application of OMS is crucial for OMS development.

Physicians tend to have a positive view of OMS.12 13 For example, Levine et al14 carried out a study where primary care providers were interested in applying telemedicine when caring for older adults with chronic, non-cancer pain for cost and time efficiency. However, certain factors hindered the physicians from adopting OMS. Prior research has discovered that these obstacles primarily include physicians’ deficits in cognition15 16 and skills17 as well as inadequate external funding and equipment support.18 Since the factors discussed in existing studies are relatively scattered, there is a lack of holistic exploration. Moreover, preceding research tends to focus on individual factors,12 19 but comparatively lacks an investigation of external factors, so the revealed factors are not sufficient.

Social ecosystem theory (SET) involves humans and their living environments and states that individual behaviour is affected by many internal and environmental factors, forming micro, meso and macro ecosystems, respectively.20 In the micro system, it pertains to individual demographics, health conditions, awareness of information and others; the meso system mainly entails those directly related to individuals, such as families, communities, organisations, institutions and so on; and the macro system usually includes policies, culture, social norms and so on.21 Inspired by SET, multilevel interventions have been carried out that seek to create changes on diverse levels; for instance, by increasing individuals’ health literacy, as well as by modifying social norms within communities.22 In one study, researchers used programmes based on the social ecological framework to enrich their understanding of the behaviour of complying with a children’s asthma action plan among caregivers and providers. They inferred that such comprehensive intervention programmes are suitable for other health behaviours.23 A previous study had applied the social-ecological framework to explore the individual and contextual determinants of telemedicine utilisation among Senegal’s physicians. And the meso and macro level determinants were merely explored by qualitative interview.24 To the best of our knowledge, however, there has been little research on SET’s application to enriching social and cultural dimensions in grasping the behaviour of OMS offerings.

This study comprehensively explores the determinants of OMS application among physicians from three levels on the basis of SET (micro, meso and macro systems) and provides an insightful, comprehensive foundation for the development of OMS.


Study design and participants

A cross-sectional survey was carried out from 1 June to 31 June 2020 in Jiangsu Province, China. Multistage sampling was used to select the participants. In the first stage, two cities were randomly selected (Nanjing and Huai’an in northern and southern Jiangsu province, respectively). In the second phase, two large comprehensive hospitals and two community hospitals were randomly selected from each city. Finally, in the sampled hospitals, physicians (with the job title of resident physician and above) were summoned to department conference rooms together to participate in our survey. After trained investigators have explained the purpose of the study to participants and obtained their informed consent, all these participants were required to complete a structured questionnaire anonymously within 30 min. About 719 entitled physicians were recruited for our investigation. After excluding incomplete questionnaires, a total of 707 completed questionnaires were gathered for analysis, with an effective response rate of 98.3%.

Measurement tools

This study adopted a self-designed questionnaire. To develop the questionnaire, our research team first formulated the initial questions pool by learning the SET framework and referencing the OMS utilisation-related published studies. Through multiple discussions between study team members, we drafted the first version of questionnaire. To ensure the content validity of the questionnaire, we invited experts to review the first draft of the questionnaire and modified it according to their comments. Then, we piloted the questionnaire among 20 physicians from different hospitals to test whether the questions were understandable and clear. After re-review by experts, we formed the latest version of questionnaire.

Specifically, the questionnaire consists of two parts.

Questions based on SET

The micro system contains basic characteristics, awareness of OMS-related information and OMS-related skills, with a total of 18 questions. Basic demographic characteristics (seven questions) include gender, age, education, job title, years of work experience, department and administrative positions25 26; for awareness of OMS-related information, five items were used to measure whether physicians sufficiently know about it.27 For example, ‘Physicians can conduct OMS in multiple online medical platforms at the same time’, with choices of Yes/No/I don’t know; and the OMS-related skills refer to some of the skills necessary to offer OMS,28 29 and five items were used to measure whether physicians sufficiently possessed these skills. For example, ‘Can you operate the online medical platform proficiently?’, with choices of Yes/No (figure 1).

Figure 1

The constructs of the online medical services (OMS) uptake questionnaire based on social ecosystem theory.

The meso system mainly involves influencing factors from the environment directly related to physicians, such as patients, colleagues, hospitals and so on. It entails whether hospitals advocate for OMS, hold training activities for physicians, formulate incentive mechanisms, and have adequate equipment and technical support; colleagues’ experience in using OMS, colleagues’ recommendation for OMS uptake; patients’ consultations30–33; with a total of seven questions. For example, ‘Has the hospital ever conducted OMS training activities?’, ‘Have the colleagues or leaders recommended OMS to you?’, and ‘Have offline patients asked about your experience in providing OMS?’. All of those were Yes/No questions.

The macro system refers to the outer environmental factors that affect physicians’ OMS uptake, such as culture, laws and policies and so on. In this study, we measured it from three aspects, including the laws and policies on medical disputes, media orientation and the platform construction,29 34 35 with a total of five questions. The first two aspects include only one Yes/No question. For example, ‘Whether the laws and policies can well solve the medical disputes occurred in the online medical process will affect you conducting OMS?’. Platform construction refers to the features of the platforms used to conduct OMS; it was tested by three Yes/No questions, including legitimacy, humanistic care for physicians, and the proportion of withdrawing diagnostic fees. For example, ‘Whether the legitimacy of the online medical platform will affect you conducting online medical services?’.

OMS uptake by physicians

The content of this part mainly includes two measurement contents, that is, OMS uptake willingness and actual OMS uptake. The measurement of OMS uptake willingness includes five scaled items. For example, ‘I will provide OMS to patients when needed’. Each item comprises a Likert scale ranging from absolutely disagree (1 point) to absolutely agree (5 points), with a total score ranging from 5 to 25. A higher score signals a greater level of OMS uptake willingness. To test the internal consistency and reliability, we calculated this scale’s Cronbach’s alpha, which was 0.94. The actual OMS uptake was measured by one question—‘Have you used OMS to provide medical services to patients before?’. If the physicians answered ‘Yes’, it meant that they have actually provided OMS; otherwise, they have not provided.

See online supplemental file 1 for all the above questionnaire questions.

Data analysis

There were two dependent variables for this study; one was the OMS uptake willingness, and another was actual OMS uptake.

The independent variables were micro, meso and macro system-related factors based on SET. Participants were considered to possess sufficient OMS-related awareness and skills if they correctly answered three or more questions in the sections on information and skills, respectively. If the answer to any one of the questions in the section on platform construction was affirmative, then the participant was deemed to be affected by platform construction.

In the descriptive analysis, frequency, percentage, mean and SD were used. Kolmogorov-Smirnov was used to test the normality of continuous variables. In the univariate analysis, according to the normality test outcomes, Mann-Whitney U tests were performed to compare OMS uptake willingness among different categorical independent variables groups; Spearman’s correlation analyses were used to test the correlations between continuous independent variable and OMS uptake willingness. The comparisons of continuous independent variable among two actual OMS uptake groups were conducted by Mann-Whitney U test, and χ2 test was used to compare categorical independent variables among two actual OMS uptake groups. Taking these independent variables with p<0.1 in the univariate analysis as candidate variables for the stepwise selection procedure of multivariate analysis is a standard statistical method commonly employed to screen independent variables.36 Hence, in this study, those independent variables with p<0.1 in the univariate analysis were taken as candidate variables for the next multivariate analysis. Multivariate, linear, stepwise regression was performed to explore the determinants of the OMS uptake willingness, and multivariate, forward, stepwise logistic regression was carried out to explore the determinants of actual OMS uptake.

Data were statistically examined using the software SPSS, V.25.0. All statistical tests were two-tailed, and p<0.05 was considered statistically significant.

Patient and public involvement

The public and patients were not involved in the survey design, administration of the survey, reporting or the dissemination plans of this research.


Basic characteristics

Based on the 707 valid questionnaires, the participants were, on average, 35.53 years old; 51.8% were male and 48.2% were female. Nearly half (45.7%) of them reported having a master’s degree. Attending physicians comprised the majority of job titles (35.6%). The share of physicians and surgeons was not much different. Years of work experience varied; 22.9% reported having worked less than 3 years, 13.0% 3–5 years, 25.7% 5–10 years, 15.7% 10–15 years, and the remaining 22.6% more than 15 years. Only 12.4% held administrative positions. Stratified, the basic demographic characteristics of physicians in community and comprehensive hospitals were similar. But the education level of physicians in comprehensive hospitals is higher than that of community hospitals physicians. The mean score for OMS uptake willingness was 17.33±4.39. 377 physicians stated they had offered OMS, accounting for 53.3%; the proportion of OMS uptake among comprehensive hospital physicians (54.5%) was higher than that among community hospital physicians (28.1%). (See table 1 for details.)

Table 1

Basic characteristics and OMS uptake of participants

SET-related determinants (except for demographic characteristics)

Table 2 displays the participants’ answers to SET-related determinants. Micro system-related factors (besides the basic characteristics of the participants mentioned in table 1) accounted for 1/4 of the participants who did not possess sufficient OMS-related awareness. Nearly 1/5 of them did not have sufficient OMS-related skills. For meso system-related factors, the participants mostly gave affirmative answers. For macro system-related factors, they mainly gave negative answers, except for factors related to media orientation and the legitimacy of the platform. After stratified by hospital level, almost all SET-related determinants had similar compositions except for ‘OMS advocated by hospitals’. 68.8% of community hospital physicians reported that hospitals do not advocate for OMS, compared with only 8.4% in comprehensive hospitals.

Table 2

Participants’ answers to the SET-related determinants

Univariate analysis

Univariate analysis demonstrated that physicians’ OMS uptake willingness was not statistically affected by their age, education, years of work experience, job title, hospital level and online medical platform construction. The physicians’ education and online medical platform construction did not show a significant difference in actual OMS uptake. The factors with statistical differences were presented in table 3.

Table 3

Univariate analysis for physicians’ OMS uptake willingness and actual uptake

Determinants of OMS uptake willingness

Table 4 depicts the results of the multivariate linear regression for physicians’ OMS uptake willingness. In the micro system, physicians who held administrative positions were more willing to offer OMS (b=1.03, p<0.05). Possessing sufficient awareness of OMS-related information (b=1.32, p<0.001) can increase physicians’ OMS uptake willingness, and likewise with possessing sufficient OMS-related skills (b=4.88, p<0.001). In the meso system, incentive mechanisms in hospitals (b=0.78, p<0.05) could have boosted physicians’ OMS uptake willingness. In the macro system, physicians who believed that laws and policies can resolve medical disputes in OMS were more willing to offer OMS (b=0.73, p<0.05). Those who reported that they would be influenced by media orientation (b=0.74, p<0.05) were also more willing to offer OMS. The six variables explained 31.4% of the variance in physicians’ intentions to offer OMS.

Table 4

Multivariate analysis of OMS uptake willingness

Determinants of actual OMS uptake

Table 5 portrays the outcomes of the multivariate logistic regression for physicians’ actual OMS uptake. In the micro system, significant differences were observed for years of work experience, holding administrative positions, and possessing sufficient awareness of OMS-related information and OMS-related skills. Physicians with more than 5 years of work experience (OR=2.44, 95% CI 1.66 to 3.59) reported a higher uptake of OMS than physicians with less than 5 years. Physicians who held administrative positions were more likely to offer OMS (OR=2.89, 95% CI 1.59 to 5.28) than physicians without them. Possessing sufficient awareness of OMS-related information (OR=1.90, 95% CI 1.22 to 2.96) and skills (OR=2.25, 95% CI 1.35 to 3.74) were facilitating factors for OMS. In the meso system, the likelihood of offering OMS was significantly higher for physicians from hospitals that advocated for OMS. Physicians who heard about their colleagues’ experiences with OMS (OR=3.81, 95% CI 2.25 to 6.45) were more likely to offer OMS. Physicians who had been asked by their offline patients about OMS reported a higher use of OMS than those who had never been asked. In the macro system, laws and policies were significantly associated with OMS uptake. Physicians who believed that laws and policies can resolve medical disputes that occur in OMS reported higher OMS uptake. The Hosmer-Lemeshow test was performed (χ2=4.517, p=0.808), and the model fitted well.

Table 5

Multivariate analysis of actual OMS uptake


Physicians were generally willing to offer OMS, but the usage rate was only 53.3%, which is still relatively low compared with other developed nations.37 Based on SET, this study provides fresh insight into the determinants of physicians’ OMS uptake. There were corresponding influencing factors in the micro, meso and macro systems according to SET, which indicated that physicians’ OMS uptake was not only determined by individuals, but also affected by the external environment (such as communities, organisations, policies and culture).

Micro system factors

Good cognition is a prerequisite for the formation of, and changes in, human behaviour.38 Relevant skills should also be mastered to facilitate actual behaviour.39 Cognition and skills are essential for physicians’ uptake of OMS, and an extensive body of research has confirmed this.40 41 Similar to previous studies, the current one has verified this as well; that is, awareness of OMS-related information and skills are common facilitating factors for physicians’ OMS uptake willingness (and actual OMS uptake).

Nevertheless, many studies have reported that physicians have trouble with cognitive impairment and lack skills. For instance, a British study pointed out that healthcare professionals have misconceptions about telehealth.42 A study in Germany showed that more than 80% of participants expressed that their cognition regarding the legal aspects and data safety of medical apps and cloud computing was insufficient.15 For the future implementation of OMS, physicians should recognise the importance of improving information and skills, such as the application and specific operation of health information technology.

The results also indicated that physicians in administrative positions are more willing (and more likely to actually) to offer OMS than those without administrative positions, suggesting that physicians in administrative positions have a positive attitude towards offering OMS. Leadership support is an important factor promoting physicians offering OMS.43 A study in Senegal reported that years of work experience was negatively correlated with physicians’ OMS uptake willingness.44 However, unlike their results, in this study, years of work experience did not show an association with physicians’ willingness to implement OMS. But we found that it was related to physicians’ actual OMS uptake, which physicians with more years of work experience were more likely to actually employ OMS. Several reasons might explain this finding. One is that the more years physicians have worked, the more access they have to OMS. Another possibility is that in China, physicians must have more than 3 years of independent consultation experience to be allowed to perform OMS.45

Meso system factors

Incentive mechanisms, such as financial rewards,46 can increase physicians’ OMS uptake willingness. Their OMS uptake willingness was positively associated with whether the hospital had an incentive mechanism, similar to the study by Ruiz Morilla et al.47 These findings also underscore that advocacy from hospitals is a facilitating factor for physicians performing OMS, which can be attributed that physicians may have easy access to (and offer) OMS if hospitals advocate for (or even organise) OMS.

Under peer influence and endorsement,48 a physician would be prompted to perform OMS if he/she learnt that his/her colleagues had experience in OMS uptake. Notably, the impact from patients cannot be ignored. More than half of the physicians in this study reported that they have been asked by offline patients about their experience in conducting OMS. Those who had been consulted were more likely to offer OMS. This outcome is similar to findings on primary care physicians based on the improved technology acceptance model by Francesc Saigi-Rubió et al,49 who implied that patients’ attitudes toward OMS can influence physicians’ use of telemedicine.

Macro system factors

Medical disputes between physicians and patients have always attracted much attention; inevitably, they can occur in both online and offline medical activities. A qualitative study noted that the dearth of interpretation and application of the law and policy caused a lack of willingness among medical personnel to participate in telecare due to fear of disputes.50 In addition, many quantitative studies have pointed out that physicians have strong concerns about OMS-related laws and policies.51 In China, although, a series of policies and laws have been issued to promote OMS, they were still imperfections and not been implemented very well,52 which exacerbated physicians’ worries and hesitations about OMS. In the study of Cai et al in Gansu Province of China, one of the reasons why physicians were reluctant to participate in telemedicine in the future was the imperfect laws and regulations.53 The findings revealed that 69.3% of the physicians believe that existing laws and policies cannot solve the problem of medical disputes in online medical activities. The multivariate analysis demonstrated that physicians who believe that existing laws and policies can solve physician–patient disputes well were more willing to offer OMS. As such, laws and policies related to online healthcare should also be considered.

To the best of our knowledge, limited research has depicted the relationship between media and OMS uptake of physicians, but other studies in the health behaviour field have already revealed that media coverage and communication can affect individuals’ cognition and behaviour.54 Similar to these conclusions, this study found a positive relationship between media orientation and physicians’ OMS uptake willingness.


This study offers practical insight for future interventions in advancing physicians’ OMS uptake. At the micro level, health administration departments should pay more attention to improving physicians’ correct awareness of OMS-related information and knowledge, carry out skills training to improve physicians’ OMS operating skills, and take measures to increase the opportunities for qualified young physicians to carry out OMS. At the meso level, hospitals should establish appropriate incentive mechanisms to encourage OMS uptake willingness among physicians. Meanwhile, hospitals (especially comprehensive ones) should optimise internal resource allocation and create their own online medical platforms to provide physicians with a helpful online medical environment. Hospitals or departments can advocate for or organise internal activities with OMS as the theme, so as to facilitate the exchange of experiences between colleagues. At the macro level, the government should improve laws and policies related to medical disputes, especially those that may occur in OMS. Meanwhile, mass media should be guided to actively report on and publicise relevant policies of OMS. Due to the extensive existence of factors based on SET, these recommendations may inspire research into other areas besides the study sites.


Some limitations should be acknowledged. First, this was a cross-sectional study. Consequently, the relationships between these factors and conclusions were exploratory. Hence, longitudinal studies are necessary to further investigate factors that affect OMS uptake among physicians, since cross-sectional design results may lead to difficulty in establishing cause-and-effect relationships among the study variables.55 Second, quantitative outcomes can be combined with qualitative findings to provide more comprehensive insight.56 In this study, only quantitative investigation was carried out. The results revealed correlative factors. However, the reasons explaining the correlations still need to be clarified through qualitative research. Therefore, a combination of qualitative and quantitative studies should be performed to better understand the causes that affect OMS uptake. Third, the data were collected by self-reported, and thus, the current results were at risk of subjectivity and response bias. Fourth, limited by the small number of medical staff, participants from community hospitals accounted for only a small proportion. This may bias study results when applied to community physicians. Finally, this study was implemented during the COVID-19 pandemic; due to its effects, the execution of OMS has increased.57 Therefore, the correlations between obtained determinants and OMS uptake among physicians may be overestimated.


Based on SET, this study explored the determinants of physicians’ OMS uptake. Accordingly, multidimensional interventions from the micro, meso, and macro systems should be carried out to encourage physicians to offer OMS. Certain measures should be taken, including enhancing physicians’ awareness and skills, creating access opportunities for qualified young physicians, attaching importance to peer roles, strengthening the construction of OMS in hospitals, improving relevant policies and laws, and guiding positive media orientation.

Data availability statement

Data are available upon reasonable request. Data are available upon reasonable request from the corresponding author. E-mail:

Ethics statements

Patient consent for publication

Ethics approval

This study was approved by the Ethics Review Committee of Nanjing Medical University ((2020)592), and all the methods were performed in accordance with the relevant guidelines and regulations.


Supplementary materials

  • Supplementary Data

    This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.


  • XP, ZL and CZ contributed equally.

  • Contributors HY designed the study and critically reviewed, commented and revised the manuscript. XP, ZL and CZ participated in the data analysis, performed the final statistical analyses and prepared the first version of manuscript. YJ, RL, JC, and ZQ collected the data. MZ, SZ and JG collected literature materials.

  • Funding National Natural Science Foundation of China (No. 72074122), Jiangsu college students’ innovation and entrepreneurship training programme (No. 202010312066Z).

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.