We designed an internet-based survey to explore the collaborative relationships in TMR among clinicians in China. The required sample size was determined to be at least 129, which was calculated with a confidence level of 95%, an admissible error of 0.1, and the probability of approval of TMR among clinicians of 74.9% . A preliminary investigation involving 85 clinicians was conducted before the formal survey. Based on the preliminary participants’ responses, several items were revised to improve the reliability and validity of this questionnaire. The internal consistency of the formal questionnaire was examined using a Cronbach’s α coefficient, which was calculated as 0.930, indicating good reliability. Factorability was tested using the Kaiser–Meyer–Olkin test and Bartlett’s test of sphericity, which yielded values of 0.724 and 5103.91 (p < 0.0001), respectively, suggesting good validity.
The formal questionnaire included 24 items that were compiled through a review of references and consultations with experts. Information on demographic characteristics, current status of personal TMR, collaborative willingness in TMR, and perceptions of collaboration in TMR was collected. Items that collected participants’ perceptions were rated using a five-point Likert scale.
Regarding demographic characteristics, we analyzed the clinicians’ sex, age, educational level, professional title, and department. Regarding the current status of personal TMR, we asked about the clinicians’ research type (e.g., clinical, laboratory, or public health management), role in TMR (e.g., principal investigator [PI] or participant), research pressure (low or high), and communication methods used in collaborations (e.g., face-to-face, telephone, or WeChat). The scale of collaborative willingness in TMR contained five items, including willingness to collaborate and preferred collaboration partners at an institutional or individual level. Perceptions of collaboration in TMR were addressed via 11 items that focused on collaborative relationships, positive and negative aspects of collaboration, and factors that influence collaboration. The measure of collaborative relationships explored the preferences for independent or interdependent relationships .
Referring to the positive aspects of collaboration, items addressed understanding of collaboration advantages, extra resources made available through collaboration, and improved personal capabilities. The advantages of collaboration included additional funds or resources, knowledge transfer, enhancement of reputation, increase in number of publications, improvement in publication quality, enrichment of academic influence, additional clinical resources, more equipment resources, new technologies, promotion of treatment capability, and acceleration of the research process [3, 9, 25]. Extra resources made available through collaboration referred to funds, patients, technologies, equipment, talents, and information. Personal capabilities could be improved in terms of communication, receiving new knowledge and technology, and control over research programs.
When considering the negative aspects, we focused on the disadvantages such as the costs, risks, and challenges of collaboration. Disadvantages included more time spent on communication, personal resource transfer to partners, loss of research autonomy and control, deviation from one’s main research, and conflicts regarding key research points [3, 26]. Collaboration costs included the costs of selecting partners and collecting information, negotiation, implementation, and supervision . The risks of collaboration were identified as the risks associated with coordinating all partners, an imbalance of duties and responsibilities among partners, and dropping out or breaking of promises by partners . The challenges faced during collaboration referred to competition from other research organizations, the ethics review process, insufficient research funds, and the recruitment of project managers .
Factors that influence collaboration included those related to the implementation and the success of the collaboration. The former involved factors such as geographical locations, funds, technologies, information, academic status, mutual relationships, and partners’ cooperation patterns . The latter included explicit collaboration aims, specific collaboration periods, appropriate partners, clear collaboration rules, clear-cut benefit distribution rules, explicit risk-taking rules, maintaining cooperative network relationships, establishing coordination and supervision mechanisms, specific penalty rules for violations of the collaboration agreement, and definite rules for dealing with disputes or emergencies [30, 31].
The formal internet-based investigation was conducted from July 29 to October 12, 2020. Of the 806 questionnaires distributed at random to clinicians nationally, 804 were returned with valid responses (valid response rate = 99.8%). The inclusion criteria were (1) clinicians should have TMR experience, (2) all clinicians should voluntarily participate, (3) participating clinicians should complete the survey online and provide informed consent. Those who were not clinicians, did not have TMR experience, or could not complete the online survey were excluded from this investigation. Only completed questionnaires could be submitted to the online survey system.
Our statistical analyses were performed using SAS 8.2 (SAS Institute Inc., Cary, NC, USA) and PASW Statistics for Windows, Version 18.0 (SPSS Inc., Chicago, IL, USA). The descriptive statistics, univariate analysis, and multivariate analysis were implemented step by step. First, we employed frequency and percentage to obtain detailed descriptions in the descriptive statistics. Second, the univariate analysis was conducted to confirm the influence of one factor on collaborative willingness in TMR. If p < 0.05, the influence was statistically significant. Third, by including all factors with statistical significance in the univariate analysis, we used a stepwise logistic regression model to determine the influence of multiple factors on collaborative willingness in TMR. In particular, descriptive statistics were used to describe the basic characteristics of the participants. Nonparametric tests, including the Wilcoxon rank test and Kruskal–Wallis H test, were used to test participants’ willingness to collaborate in TMR. A stepwise logistic regression analysis was used to analyze the factors influencing the willingness to collaborate in TMR, with inclusion and exclusion criteria of 0.10 and 0.15, respectively. All tests were two-tailed, with p < 0.05 considered to be statistically significant.
Based on the results of the univariate analyses, only factors with a statistically significant influence on collaborative willingness in TMR among clinicians were included in the logistic regression analysis.