Attitudes and Willingness to Participate in Drug Clinical Trials Among Patients With Cancer: Multistage Qualitative...

Cancer clinical trials are essential for advancing therapeutic innovations; however, patient enrollment remains a persistent challenge globally. Understanding the attitudes and willingness of patients with cancer to participate in clinical trials is critical for improving recruitment strategies. While previous studies have explored barriers and facilitators, few have integrated multiple data sources or used emerging analytical approaches, such as large language models (LLMs), to capture the multidimensional nature of patient decision-making. Furthermore, limited research has examined these perspectives within the Chinese health care context, where cultural, economic, and systemic factors may uniquely influence participation decisions.

This study aimed to examine the attitudes and willingness of patients with cancer to participate in drug clinical trials in China by (1) identifying key themes influencing patients' decision-making processes, (2) comparing thematic findings derived from investigator-led qualitative analysis with those generated by 2 LLMs (Gemini Pro 2.5 and DeepSeek R1), and (3) evaluating the complementary value of hybrid analytical approaches in qualitative health research.

A multistage qualitative study was conducted using 2 data sources: semistructured face-to-face interviews with patients with cancer (n=11) from a tertiary hospital in Shanghai and publicly available comments from 2 Chinese online health communities (Zhihu and Yuaigongwu). Of the 3148 initial comments, 219 met the inclusion criteria after systematic screening. Three parallel analytical approaches were used: investigator-led thematic analysis, Gemini Pro 2.5-assisted analysis, and DeepSeek R1-assisted analysis. Both LLMs received identical, structured prompts. Thematic outputs were systematically compared to identify convergent and divergent findings.

The 3 analytical methods jointly identified 7 core themes: treatment selection, financial burden relief, uncertain therapeutic efficacy, uncertainty regarding control groups, lack of cognition, misconceptions, and physician trust. Substantial thematic overlap was observed between investigator-led and DeepSeek R1 analyses (8 shared themes, including family-involved decisions and service-related factors) and between investigator-led and Gemini Pro 2.5 analyses (3 shared themes, including regional disparities and autonomous decision-making). Method-specific themes included recognition of medical value (investigator only), insufficient clinical data (DeepSeek R1 only), and lack of information resource (Gemini Pro 2.5 only). These findings highlight the multidimensional nature of trial participation decisions, encompassing treatment expectations, economic considerations, risk perceptions, cognitive factors, trust relationships, and structural barriers to accessibility.

The willingness of patients with cancer to participate in clinical trials is shaped by a complex interplay of treatment expectations, economic considerations, risk perceptions, cognitive factors, and relational dynamics. The hybrid analytical framework demonstrated complementary strengths: human analysis provided contextual depth and cultural sensitivity, while LLMs offered efficiency and identified additional thematic dimensions. These findings underscore the need for patient-centered communication strategies, transparent trial information, and culturally tailored recruitment approaches. Future research should expand sample diversity and further validate the use of LLMs in qualitative health research.