Factors influencing nurses’ knowledge on peripherally inserted central catheter care in Guizhou, China: A web-based cross-sectional study

Abstract

Understanding factors influencing nurses’ knowledge of peripherally inserted central catheter (PICC) care is crucial for developing interventions to improve knowledge and ensure care quality. However, evidence remains limited in low-resource areas. This study aimed to examine factors influencing nurses’ PICC care knowledge in Guizhou Province of China, and to explore potential differences across hospital levels. A cross-sectional study was conducted among 3528 nurses from 18 hospitals across nine cities in Guizhou, China. PICC care knowledge was assessed using a standardized questionnaire, and multiple linear regressions were used to identify influencing factors. The mean knowledge score was 48.67 ± 12.94, with 17.2% achieving a passing score (≥ 60). Higher scores were associated with higher professional titles, higher education, PICC care experience, workplace guidelines, prior training, self-reported training needs, and tertiary hospital employment (all p < 0.05). In secondary/primary hospitals, nurses’ knowledge was significantly associated with professional title, educational level, PICC care experience, and prior training (all p < 0.05). In tertiary hospitals, nurses’ knowledge was significantly associated with professional title, PICC care experience, workplace guidelines, and self-reported training needs (all p < 0.05). Nurses in Guizhou have suboptimal PICC care knowledge, with different factors associated with knowledge observed across hospital levels. Interventions are needed to improve nurses’ PICC care knowledge and enhance care quality, with tailored strategies for tertiary versus secondary/primary hospitals.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1038/s41598-026-55786-1.

Introduction

The peripherally inserted central catheter (PICC) is a thin, flexible tube inserted into a peripheral vein and advanced into the central venous system, with the catheter tip positioned at the cavoatrial junction^1,2. It provides safe and reliable intravenous access for patients requiring medium- to long-term infusions, such as cancer patients undergoing chemotherapy³. PICC are widely used globally and in China. In the United States, approximately 5 million PICCs are inserted annually⁴. In China, a national survey reported that 93.6% of tertiary hospitals provide PICC services⁵. Furthermore, a multicentre survey in 2022 found that among hospitalized hematology patients, 55.69% used central venous access, of which 85.74% were PICCs, indicating that PICC has become a predominant choice for central vascular access⁶. Compared with peripheral venous catheters, PICCs offer advantages of longer indwelling times, reduced need for repeated punctures, minimized vascular damage, and a lower risk of infusion extravasation^2,3. However, despite its benefits, proper monitoring is crucial to mitigate potential complications associated with PICC use, including catheter obstruction, thrombosis, breakage, and infection^3,7,8. These complications may result in unplanned extubation, adversely affecting patients’ physical and psychological well-being, delaying treatment, and reducing survival outcomes^9,10.

Standardized and effective PICC care is essential to minimize the risk of complications¹¹. Key components of effective PICC care include regular evaluation of PICC function, timely replacement of infusion connectors and dressings, routine flushing and sealing of the catheter, and patient education regarding PICC maintenance¹¹. Suboptimal PICC care, such as non-adherence to aseptic techniques, inadequate infection surveillance, and poor hand hygiene, has been identified as a major contributor to PICC-related infections and other complications⁴.

Nurses, as the primary healthcare providers responsible for PICC care^12–15, play a pivotal role in ensuring patient safety and well-being. However, studies have shown that nurses’ practices related to PICC care are often suboptimal^12,15,16. According to the knowledge, attitude, and practice framework, enhancing healthcare providers’ knowledge is a key step in improving clinical practices¹⁷. Specifically, increasing nurses’ understanding of PICC care is essential for improving their practice and, ultimately, patient outcomes.

A scoping review conducted across several countries—including the United States, India, Turkey, Italy, Jordan, Brazil, Egypt, Poland, the United Kingdom, Malaysia, Scotland, Belgium, France, and Canada—examined nurses’ knowledge regarding the routine care of vascular access devices, including both central and peripheral catheters¹⁴. The review highlighted the need for improvement in nurses’ knowledge of PICC care globally¹⁴. In China, studies conducted in Hunan province revealed that nurses’ knowledge of PICC care was at a low to moderate level^18,19. A study conducted in Guizhou province found that only 29.6% of nurses demonstrated adequate knowledge of PICC care¹². These findings underscore the need for targeted educational interventions to improve nurses’ PICC care knowledge and subsequently improve their clinical practice.

Understanding the factors influencing nurses’ knowledge of PICC care is crucial for developing effective interventions. Previous studies have suggested that factors such as sex, age, professional title, educational level, working years, work setting, and prior training in PICC care are associated with PICC care knowledge^14,16,18,19. However, these studies were primarily conducted among nurses outside China or relatively better-developed regions of China, such as Hunan and Shandong provinces, where healthcare infrastructure and training resources are relatively better. Consequently, these findings may not be applicable to low-resource areas.

Guizhou, a southwestern province with a gross domestic product per capita ranking 28th among 31 provinces in Chinese mainland in 2023²⁰, has only 6% of its hospitals classified as tertiary, lower than the national average of 13%^21,22. In China, hospitals are classified into three tiers based on size and service level. Primary hospitals (township/community, < 100 beds) provide preventive, basic, and rehabilitation care to a single community. Secondary hospitals (city/county/district, 100–500 beds) offer comprehensive health services to multiple communities. Tertiary hospitals (city/provincial/national, > 500 beds) are comprehensive referral centres providing specialist care and training to multiple regions. The relatively low proportion of tertiary hospitals in Guizhou limits specialized training resources. Examining the factors influencing nurses’ PICC care knowledge in Guizhou could offer insights for developing targeted training programs in low-resource areas.

Additionally, previous studies have indicated that hospital level may play a role in nurses’ knowledge of PICC care, with higher-tier hospitals demonstrating better knowledge^18,19. Tertiary hospitals, with more advanced healthcare infrastructure and access to specialized training, are likely to provide nurses with more and better opportunities to enhance their knowledge²³. Conversely, secondary and primary hospitals frequently have limited resources and less specialized training, which may impede nurses’ capacity to remain current with best practices for PICC care^23–25. Given these disparities between hospital levels, the factors influencing nurses’ knowledge of PICC care may vary across institutions. Exploring whether factors associated with PICC care knowledge differ across hospital levels may help inform targeted interventions to improve nurses’ knowledge.

Therefore, the present study aimed to examine whether previously identified factors influencing nurses’ PICC care knowledge are applicable in Guizhou, a low-resource setting, and to explore potential differences across hospital levels. The findings may enable the identification of region- and hospital-specific educational needs and inform the development of targeted training programs to improve PICC care across the region, ultimately enhancing patient outcomes.

Methods

Study design and setting

We conducted a web-based cross-sectional study in 18 hospitals (three tertiary hospitals, ten secondary hospitals, and five primary hospitals) across nine cities in Guizhou Province, China, from July 1 to July 30, 2022. This study was reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement²⁶.

Participants

Participants were included if they were registered nurses involved in intravenous therapy-related clinical work and volunteered for this study. Nurses on leave during the data collection period were excluded.

Sample size and sampling

The sample size was calculated using G*Power 3.1.9.7, estimating that at least 787 participants were needed for multiple linear regression, assuming a small effect size (f² = 0.01)²⁷, with a power of 0.80 and an α level of 0.05. Given the planned subgroup analysis based on hospital level (tertiary vs. secondary/primary), the sample was designed to ensure that at least 787 participants could be recruited from both tertiary and secondary/primary hospitals.

Participants were recruited through convenience sampling including two stages (Fig. 1). In the first stage, two hospitals were selected from each of the nine cities in Guizhou Province, totalling 18 hospitals. In the second stage, eligible participants were recruited from the selected hospitals.

Fig. 1.

Schematic diagram of the two-stage sampling and recruitment strategy.

Outcome variables and measures

The dependent variable was nurses’ PICC care knowledge, measured using the PICC care knowledge questionnaire^12,19. This instrument includes 19 items covering various aspects of PICC care, such as the content of PICC care, PICC function evaluation, selection of skin disinfectants, disinfection range, type and volume of flushing and sealing fluid, techniques for PICC flushing and sealing, complication management, and health education. Each item is a single-choice question, with a correct response scoring 1 point and an incorrect response scoring 0, leading to a total score ranging from 0 to 19. The original score was converted to a hundred-point scale using the formula: Converted total score = original total score * 100 / 19. Scores were categorized into two groups: pass (60 or above) and fail (below 60)¹². This questionnaire demonstrates good validity and acceptable reliability, with a scale content validity index of 0.94 and a Cronbach’s α of 0.71¹².

The independent variables were potential factors affecting nurses’ PICC care knowledge, including age, gender, professional title, educational level, hospital level, working years, experience in conducting PICC care, availability of PICC care guidelines in the workplace, experience in attending PICC care training, and need for further PICC care training. These variables were measured using a researcher-developed self-reported questionnaire. The item content and response format can be found in the Supplementary Table S1.

Data collection

Data collection took place from July 1 to July 30, 2022. Before data collection, the research team contacted the nursing directors of the 18 selected hospitals, explained the study purpose, and requested their permission and assistance with participant recruitment and data collection. Subsequently, we sent the online questionnaire and the e-informed consent form to these nursing directors and provided them with uniform training on participant recruitment and data collection procedures. The nursing directors then helped identify eligible nurses and distribute the electronic survey questionnaire, along with a study introduction, via WeChat work groups (a widely used multipurpose messaging and social media platform in China, similar to WhatsApp). Finally, nurses who consented to participate completed the anonymous online survey independently using mobile devices.

Bias

Measures were taken to minimize potential bias. Anonymous data collection was used to reduce reporting bias, and all questionnaire items were mandatory to minimize missing data. Standardized procedures were implemented across all study sites to ensure consistency in participant recruitment and data collection. To further reduce potential bias associated with recruitment via workplace WeChat groups (e.g., peer pressure or social desirability bias), participants were clearly informed that participation was entirely voluntary, with no professional consequences. It was also explicitly stated that no identifiable information would be collected, that responses would be accessible only to the research team, and that the data would be used solely for research purposes without any impact on employment or promotion. These assurances were provided in the electronic informed consent form and reiterated at the beginning of the questionnaire.

Ethical considerations

This study was conducted following the principles outlined in the Declaration of Helsinki and obtained approval from the ethics committee of the Affiliated Hospital of Guizhou Medical University (NO.2022 − 542). Prior to data collection, electronic informed consent was obtained from all participants.

Data analysis

All data were analysed using SPSS software version 23 (IBM Corp., Armonk, NY, USA). Categorical data were presented as frequencies and percentages, while continuous variables were expressed as means and standard deviations (SDs) due to their normal distribution. Primary hospitals were combined with secondary hospitals in the analysis because both levels have limited PICC training resources compared with tertiary hospitals, and the number of participants from primary hospitals was small, making separate analyses statistically underpowered.

Univariate analyses were conducted for descriptive purposes to examine the associations between independent variables and nurses’ knowledge of PICC care. A multiple linear regression was used to analyse factors associated with nurses’ PICC care knowledge. Then, seperate multiple linear regression analyses were conducted to analyze factors associated with nurses’ PICC knowledge in tertiary and secondary/primary hospitals, respectively. The enter method was used for the regression analysis. All independent variables were selected based on prior literature and theoretical considerations and entered simultaneously into the model. Multicollinearity among independent variables was assessed using variance inflation factors (VIFs), and the results can be found in the Supplementary Table S2. Multicollinearity diagnostics indicated a high correlation between age and working years (VIF > 5); therefore, working years was retained in the final model as a more direct indicator of clinical experience, while age was excluded to improve model stability. Dummy variables were created for categorical variables. A two-tailed p-value of < 0.05 was considered statistically significant.

Results

Participant characteristics

Among the 18 hospitals (three tertiary hospitals, ten secondary hospitals, and five primary hospitals) willing to participate in the study, 7041 eligible nurses were invited, and 3528 completed the questionnaire, with a response rate of 50.1%. Of these, 1957 nurses were from secondary/primary hospitals, and 1571 were from tertiary hospitals. The mean age of participants was 31.60 ± 6.13 years, with the majority being female (94.6%), holding a junior professional title (i.e., ‘Nurse’ or ‘Senior Nurse’) (73.4%), and possessing an educational level of undergraduate or above (75.0%). The details of participants’ characteristics are presented in Table 1.

Table 1.

Participants’ characteristics and stratified by hospital level (N = 3528).

Characteristics	Overall (N = 3528)	Secondary/primary (n = 1957)	Tertiary (n = 1571)
	n (%)	n (%)	n (%)
Age (years) [Mean ± SD]	31.60 ± 6.13	31.00 ± 5.93	32.35 ± 6.28
Sex
Female	3339 (94.6)	1868 (95.5)	1471 (93.6)
Male	189 (5.4)	89 (4.5)	100 (6.4)
Professional title
Nurse/Senior nurse	2591 (73.4)	1491 (76.2)	1100 (70.0)
Supervision nurse/Co-chief nurse/Chief nurse	937 (26.6)	466 (23.8)	471 (30.0)
Educational level
Specialized secondary school/Junior college	883 (25.0)	579 (29.6)	304 (19.4)
Undergraduate or above	2645 (75.0)	1378 (70.4)	1267 (80.6)
Working years [Mean ± SD]	8.69 ± 6.35	7.99 ± 5.97	9.57 ± 6.69
Experience in conducting PICC care
No	2410 (68.3)	1452 (74.2)	958 (61.0)
Yes	1118 (31.7)	505 (25.8)	613 (39.0)
Availability of PICC care guideline in workplace
No	707 (20.0)	538 (27.5)	169 (10.8)
Yes	2821 (80.0)	1419 (72.5)	1402 (89.2)
Experience in attending PICC care training
No	1576 (44.7)	971 (49.6)	605 (38.5)
Yes	1952 (55.3)	986 (50.4)	966 (61.5)
Need for further PICC care training
No	1060 (30.0)	625 (31.9)	435 (27.7)
Yes	2468 (70.0)	1332 (68.1)	1136 (72.3)

PICC: peripherally inserted central catheter; SD: standard deviation.

Nurses’ PICC care knowledge

The overall mean score for PICC care knowledge was 48.67 ± 12.94. Nurses in tertiary hospitals scored higher (50.19 ± 13.41) than those in secondary/primary hospitals (47.44 ± 12.42). The overall pass rate (score ≥ 60) was 17.2%, with a higher pass rate in tertiary hospitals (21.6%) than in secondary/primary hospitals (13.6%) (Table 2).

Table 2.

Nurses’ PICC care knowledge score and stratified by hospital level (N = 3528).

Overall	Knowledge score Mean ± SD	Pass (60 or above) n (%)	Fail (below 60) n (%)
	48.67 ± 12.94	606 (17.2)	2922 (82.8)
Secondary/Primary hospitals	47.44 ± 12.42	267 (13.6)	1690 (86.4)
Tertiary hospitals	50.19 ± 13.41	339 (21.6)	1232 (78.4)

PICC: peripherally inserted central catheter; SD: standard deviation.

Influencing factors of PICC care knowledge

Univariate analyses showed that nurses’ PICC care knowledge varied across several variables, including age, professional title, educational level, working years, experience in conducting PICC care, availability of PICC care guidelines in the workplace, experience in attending PICC care training, the need for further PICC care training, and hospital level (all p<0.001) (Table 3).

Table 3.

Influencing factors of nurses’ PICC care knowledge score (N = 3528).

Characteristics	Univariate analysis		Multiple linear regression#
	Pearson correlation/ Mean ± SD	p-value	B (95% CI)	p-value
Age (years)*	r = 0.088	< 0.001	–	–
Sex		0.918
Male	48.76 ± 13.69		Reference
Female	48.66 ± 12.90		-0.002 (-1.811 to 1.807)	0.998
Professional title		< 0.001
Nurse/Senior nurse	47.25 ± 12.16		Reference
Supervision nurse/Co-chief nurse/Chief nurse	52.58 ± 14.18		4.910 (3.744 to 6.077)	< 0.001
Educational level		< 0.001
Specialized secondary school/Junior college	46.06 ± 11.94		Reference
Undergraduate or above	49.54 ± 13.14		1.845 (0.883 to 2.808)	< 0.001
Working years	r = 0.101	< 0.001	-0.079 (-0.160 to 0.002)	0.057
Experience in conducting PICC care		< 0.001
No	46.36 ± 11.76		Reference
Yes	53.64 ± 13.93		5.700 (4.742 to 6.658)	< 0.001
Availability of PICC care guideline in workplace		< 0.001
No	45.22 ± 12.29		Reference
Yes	49.53 ± 12.95		1.267 (0.153 to 2.382)	0.026
Experience in attending PICC care training		< 0.001
No	46.02 ± 11.70		Reference
Yes	50.81 ± 13.48		1.092 (0.119 to 2.064)	0.028
Need for further PICC care training		< 0.001
No	45.60 ± 12.46		Reference
Yes	49.98 ± 12.92		1.836 (0.878 to 2.794)	< 0.001
Hospital level		< 0.001
Secondary/Primary hospital	47.44 ± 12.42		Reference
Tertiary hospital	50.19 ± 13.41		1.214 (0.371 to 2.056)	0.005

^# Variables included in the multivariable analysis were selected based on prior literature and theoretical considerations, rather than solely on univariate associations.

^* Substantial multicollinearity between age and working years exists. Given that working years are conceptually more directly related to clinical experience, age was excluded.

PICC: peripherally inserted central catheter; SD: standard deviation; B: regression coefficient; CI: confidence interval.

Multiple regression analysis revealed that higher knowledge scores were significantly associated with being a supervision nurse/co-chief nurse/chief nurse (B = 4.910, 95% confidence interval [CI]: 3.744 to 6.077, p < 0.001), holding an undergraduate degree or higher (B = 1.845, 95% CI: 0.883 to 2.808, p < 0.001), and having experience in conducting PICC care (B = 5.700, 95% CI: 4.742 to 6.658, p < 0.001). Additionally, the availability of PICC care guidelines in the workplace (B = 1.267, 95% CI: 0.153 to 2.382, p = 0.026), the experience in attending PICC care training (B = 1.092, 95% CI: 0.119 to 2.064, p = 0.028), reporting a need for further training (B = 1.836, 95% CI: 0.878 to 2.794, p < 0.001), and working in tertiary hospitals (B = 1.214, 95% CI: 0.371  to 2.056, p < 0.001) were all significantly associated with higher knowledge scores. However, sex and working years were not independently associated with knowledge scores (both p > 0.05) (Table 3).

In secondary/primary hospitals, significant predictors of higher knowledge scores included being a supervision nurse/co-chief nurse/chief nurse (B = 4.147, 95% CI: 2.567 to 5.727, p < 0.001), holding an undergraduate degree or higher (B = 2.204, 95% CI: 1.002 to 3.406, p < 0.001), having experience in conducting PICC care (B = 4.716, 95% CI: 3.405 to 6.026, p < 0.001), and having experience in attending PICC care training (B = 1.731, 95% CI: 0.457 to 3.005, p = 0.008) (Table 4).

Table 4.

Influencing factors of nurses’ PICC care knowledge score in secondary/primary hospitals (n = 1957).

Characteristics	Univariate analysis		Multiple linear regression #
	Pearson correlation/ Mean ± SD	p-value	B (95% CI)	p-value
Age (years) *	r = 0.069	0.002	–	–
Sex
Male	47.84 ± 14.56		Reference
Female	47.42 ± 12.31	0.757	0.067 (-2.504 to 2.638)	0.959
Professional title
Nurse/Senior nurse	46.41 ± 11.94		Reference
Supervision nurse/Co-chief nurse/Chief nurse	50.76 ± 13.33	< 0.001	4.147 (2.567 to 5.727)	< 0.001
Educational level
Specialized secondary school/Junior college	45.22 ± 11.86		Reference
Undergraduate or above	48.38 ± 12.53	< 0.001	2.204 (1.002 to 3.406)	< 0.001
Working years	r = 0.069	0.002	-0.096 (-0.209 to 0.017)	0.094
Experience in conducting PICC care
No	45.88 ± 11.53		Reference
Yes	51.94 ± 13.74	< 0.001	4.716 (3.405 to 6.026)	< 0.001
Availability of PICC care guideline in workplace
No	45.19 ± 12.36		Reference
Yes	48.30 ± 12.34	< 0.001	0.968 (-0.343 to 2.278)	0.148
Experience in attending PICC care training
No	45.31 ± 11.38		Reference
Yes	49.54 ± 13.03	< 0.001	1.731 (0.457 to 3.005)	0.008
Need for further PICC care training
No	45.07 ± 12.26		Reference
Yes	48.56 ± 12.34	< 0.001	1.069 (-0.186 to 2.325)	0.095

^# Variables included in the multivariable analysis were selected based on prior literature and theoretical considerations, rather than solely on univariate associations.

^* Substantial multicollinearity between age and working years exists. Given that working years are conceptually more directly related to clinical experience, age was excluded.

PICC: peripherally inserted central catheter; SD: standard deviation; B: regression coefficient; CI: confidence interval.

In tertiary hospitals, higher knowledge scores were significantly associated with being a supervision nurse/co-chief nurse/chief nurse (B = 5.829, 95% CI: 4.097 to 7.561, p < 0.001), having experience in conducting PICC care (B = 6.693, 95% CI: 5.273 to 8.112, p < 0.001), the availability of PICC care guidelines in the workplace (B = 2.140, 95% CI: 0.025 to 4.254, p = 0.047), and the need for further training (B = 2.828, 95% CI: 1.348 to 4.308, p < 0.001) (Table 5).

Table 5.

Influencing factors of nurses’ PICC care knowledge score in tertiary hospitals (n = 1571).

Characteristics	Univariate analysis		Multiple linear regression #
	Pearson correlation/ Mean ± SD	p-value	B (95% CI)	p-value
Age (years) *	r = 0.088	< 0.001	–	–
Sex
Male	49.58 ± 12.90		Reference
Female	50.23 ± 13.44	0.638	-0.220 (-2.786 to 2.347)	0.867
Professional title
Nurse/Senior nurse	48.39 ± 12.36		Reference
Supervision nurse/Co-chief nurse/Chief nurse	54.39 ± 14.76	< 0.001	5.829 (4.097 to 7.561)	< 0.001
Educational level
Specialized secondary school/Junior college	47.66 ± 11.93		Reference
Undergraduate or above	50.80 ± 13.67	< 0.001	1.433 (-0.168 to 3.035)	0.079
Working years	r = 0.111	< 0.001	-0.076 (-0.193 to 0.042)	0.209
Experience in conducting PICC care
No	47.09 ± 12.07		Reference
Yes	55.04 ± 13.94	< 0.001	6.693 (5.273 to 8.112)	< 0.001
Availability of PICC care guideline in workplace
No	45.34 ± 12.13		Reference
Yes	50.77 ± 13.44	< 0.001	2.140 (0.025 to 4.254)	0.047
Experience in attending PICC care training
No (ref)	47.14 ± 12.12		Reference
Yes	52.10 ± 13.82	< 0.001	0.289 (-1.214 to 1.792)	0.706
Need for further PICC care training
No	46.36 ± 12.71		Reference
Yes	51.65 ± 13.38	< 0.001	2.828 (1.348 to 4.308)	< 0.001

^# Variables included in the multivariable analysis were selected based on prior literature and theoretical considerations, rather than solely on univariate associations.

^* Substantial multicollinearity between age and working years exists. Given that working years are conceptually more directly related to clinical experience, age was excluded.

PICC: peripherally inserted central catheter; SD: standard deviation; B: regression coefficient; CI: confidence interval.

Discussion

This study examined the factors associated with nurses’ knowledge of PICC care in Guizhou, China, using a hospital-level subgroup analysis. Significant differences were observed in PICC care knowledge across hospital levels, with nurses in tertiary hospitals showing higher knowledge scores and pass rates compared to those in secondary and primary hospitals. The analysis found seven key factors of PICC care knowledge and suggested potential differences in associated factors across hospital levels, offering insights for targeted interventions.

Interpretation of overall PICC care knowledge levels

The overall mean PICC care knowledge score was low (48.67 ± 12.94), with only 17.2% of nurses achieving a passing score, indicating an unsatisfactory PICC care knowledge among nurses in Guizhou, China. This result is consistent with a previous study¹², further underscoring the urgent need for strategies to improve PICC care knowledge among nurses in Guizhou Province. Nurses in tertiary hospitals exhibited significantly higher scores (50.19 ± 13.41) and pass rates (21.6%) compared to their counterparts in secondary/primary hospitals (47.44 ± 12.42, 13.6%). These disparities may reflect variations in institutional resources, access to training, and professional support between higher- and lower-tier hospitals, suggesting that special attention should be given to lower-tier hospitals.

Factors associated with PICC care knowledge

Our study identified five factors associated with higher knowledge of PICC care, in line with previous research^14,16,18,19: higher professional title, higher educational level, experience in performing PICC care, participation in PICC care training, and working in a higher-level hospital. These results reinforce the need for nursing administrators to focus on nurses with lower professional titles, lower educational level, insufficient experience in PICC care, and those who have not participated in PICC care training, particularly in lower-level hospitals.

This study found that working years were not independently associated with PICC care knowledge after adjustment for other variables. This finding is consistent with the results of a study examining factors associated with nurses’ practice regarding PICC care¹² and a study examining factors associated with nurses’ knowledge of drug extravasation prevention and treatment²⁸. A possible explanation is that the influence of clinical experience may be better captured by more specific indicators, such as professional title and direct experience in conducting PICC care. This finding indicates that simple accumulation of years in clinical practice does not necessarily translate into higher levels of PICC-related knowledge, and nurses with long working years should not be ignored when designing and implementing targeted training programs.

Additionally, our study found that the presence of institutional PICC guidelines was associated with higher knowledge scores, which supports existing evidence that accessible protocols reduce practice variation²⁹. Guidelines not only serve as procedural references but also as educational tools that reinforce evidence-based practices through repeated exposure. Their presence suggests that departments prioritize PICC care quality, likely implementing additional measures to enhance nurses’ knowledge. Our findings recommend that hospitals provide easier access to guidelines, such as purchasing clinical guideline databases and providing training on how to access and use guidelines effectively.

Interestingly, nurses who expressed a need for further training scored higher on PICC care knowledge. This finding contrasts with our initial assumption that reporting unmet training needs might be associated with lower knowledge levels. This association may reflect reverse causation, which may be driven by awareness bias and is conceptually consistent with the Dunning–Kruger effect³⁰. Nurses with higher levels of knowledge may be more accurate in perceiving their own learning gaps and thus report a greater need for further training, whereas those with lower knowledge may underestimate their deficiencies and consequently underreport training needs³⁰. Given the cross-sectional design of this study, causal relationships cannot be established, and the finding should be interpreted with caution. Nevertheless, regardless of the direction of causality, the observed positive association suggests that expressed training needs may reflect not only knowledge gaps but also higher professional awareness. Therefore, fostering an environment that encourages self-assessment, supports open communication, actively responds to nurses’ needs, and provides continuing education opportunities may contribute to improved nursing competence and patient care quality^31–34.

Stratified analyses by hospital level

Exploratory stratified analyses were conducted to explore potential differences in factors of PICC care knowledge between tertiary and secondary/primary hospitals. In tertiary hospitals, the presence of PICC care guidelines and the self-reported need for further training were significantly associated with higher knowledge scores, whereas these factors were non-significant in secondary/primary hospitals. Conversely, in secondary/primary hospitals, educational level and prior PICC care training experience showed significant associations with knowledge scores.

This difference may reflect systemic disparities within China’s hierarchical healthcare system³⁵. Tertiary hospitals, as regional centers of excellence, benefit from better access to educational resources and training programs^23,36. In this context, nurses have multiple avenues to acquire PICC-related knowledge, which may reduce the reliance on formal training. Consequently, the presence of PICC care guidelines in the workplace and the self-directed learning needs of nurses may play a role in shaping their knowledge. In contrast, secondary and primary hospitals, particularly in underdeveloped regions like Guizhou, have limited training resources and fewer complex cases to handle³⁷. As a result, nurses in these settings may rely more on formal education, such as obtaining undergraduate degrees, and on-the-job training to gain PICC-related knowledge. However, the observed differences in factors associated with PICC care knowledge between tertiary and secondary/primary hospitals should be interpreted with caution, as formal tests of interaction between hospital level and these factors were not conducted in this study.

Clinical and research implications

Our study has several implications for clinical management and research. Nursing managers are expected to focus on nurses with lower professional titles, lower educational level, insufficient experience in PICC care, and those who have not participated in PICC care training, particularly in lower-level hospitals. In secondary/primary hospitals, the focus should be on standardizing in-service training, particularly for nurses with lower educational levels. This could include establishing mandatory, competency-based PICC training modules delivered through regional hub hospitals or online platforms to overcome geographic and financial barriers^38–40, as well as encouraging nurses to pursue further education. In tertiary hospitals, efforts should focus on optimizing the implementation of clinical guidelines and promoting self-directed learning⁴¹. Practical recommendations include providing training on how to access and use guidelines effectively, conducting regular audits to ensure adherence to evidence-based practices, and establishing micro-credentialing programs⁴²(e.g., “PICC Care Champions” certifications) to capitalize on nurses’ intrinsic motivation for ongoing education. Additionally, providing protected time for nurses to pursue specialized courses or attend professional development activities is recommended to support their continuous learning.

Future research should explore the potential of artificial intelligence (AI)-driven educational tools and decision-support systems to enhance nurses’ knowledge and adherence to PICC care guidelines^43,44. AI-powered simulations, adaptive learning platforms, and real-time clinical alerts could provide personalized and efficient training, addressing gaps identified in this study. Additionally, integrating nursing engineering research⁴⁵, which applies principles of engineering and technology to optimize nursing care, could lead to the development of innovative solutions such as automated monitoring systems and smart PICC care devices.

Limitations

Our study had several limitations. First, although participants were recruited from 18 hospitals across different levels in nine cities to enhance sample diversity, the use of convenience sampling may introduce selection bias due to systematic differences between participants and non-participants, thereby limiting the representativeness and generalizability of the findings. Therefore, the results should be interpreted with caution. Second, the data were collected using an online survey and the response rate was relatively low, which may further threaten the representativeness of the sample. Third, the cross-sectional design cannot establish causal relationships. Fourth, although we attempted to mitigate peer pressure or social desirability bias resulting from workplace‑based distribution, this bias may still exist. Future studies should consider alternative recruitment strategies to further minimize such bias. Finally, the combination of primary and secondary hospitals into one group for analysis may have obscured meaningful differences between primary and secondary hospitals. Future studies with larger samples of primary hospitals are needed to explore potential heterogeneity within lower‑level hospitals.

Conclusions

This study revealed that nurses in Guizhou Province have suboptimal knowledge of PICC care, with only 17.2% achieving a passing score. Seven factors were identified as significant predictors of higher PICC care knowledge: higher professional title, higher educational level, experience in performing PICC care, participation in PICC care training, working in a higher-level hospital, availability of PICC care guidelines in the workplace, and self-perceived need for further training. In secondary/primary hospitals, nurses’ knowledge was significantly associated with professional title, educational level, PICC care experience, and prior training. In tertiary hospitals, nurses’ knowledge was significantly associated with professional title, PICC care experience, workplace guidelines, and self-reported training needs. These findings underscore the urgent need for targeted interventions to improve PICC care knowledge across Guizhou Province, with tailored strategies for nurses in different hospital settings.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contributions

B.X. conceived and designed the study, wrote the original draft of the manuscript, and revised the manuscript; Y.W. and Y.M. were responsible for data analysis and interpretation of results; R.Z. and H.C. contributed to online data collection package preparation and data collection; L.H. and X.Z. conceived and design the study and revised the manuscript. All authors reviewed and approved the final version of the manuscript for publishing.

Data availability

The original data of this study are available on reasonable request from the corresponding author.

Declarations

Competing interests

The authors declare no competing interests.