Unveiling clinical decision-making in pediatric surgery: how frontline staff perform and what shapes their skills

Abstract

Background

Clinical decision-making in pediatric surgery is uniquely complex, shaped by children’s distinct pathophysiological characteristics, rapid disease progression, and heightened family expectations. Understanding the clinical decision-making capabilities of frontline medical staff and their underlying influencing factors is thus critical to optimizing pediatric surgical care quality. This study aimed to assess these decision-making abilities among frontline pediatric surgery personnel.

Methods

A cross-sectional study was conducted from June to July 2025, enrolling frontline staff from the pediatric surgery department of a tertiary children’s hospital in Jiangsu Province. Data were collected using the Clinical Decision-Making Nursing Scale (CDMNS). Clinical trial number: not applicable.

Results

A total of 246 frontline pediatric surgery staff were included. The mean total score for clinical decision-making ability was 142.60 ± 15.27. Among CDMNS dimensions, “clarifying goals and values” scored highest, while “seeking information or new information” was the weakest. Correlation analysis revealed significant positive associations between decision-making ability and age (r = 0.610), years of practice (r = 0.589), educational background (r = 0.604), professional title (r = 0.601), and clinical decision-making training experience (r = 0.645). Career development factors (age, tenure, education, professional title) and prior training were strongly correlated with decision-making ability, with training emerging as the strongest correlate (R²=0.598, F = 26.044, P < 0.001).

Conclusion

Career development trajectories and targeted training appear to be important correlates of clinical decision‑making competence in pediatric surgery. Potential strategic interventions may include implementing stratified training systems and optimizing specialized information support, which could contribute to systematic improvements in decision quality.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12909-026-09381-7.

Introduction

Pediatric surgical diseases impose stringent demands on frontline medical staff due to their unique pathophysiology, rapid progression, and high family expectations [9]. Unlike adults, children—especially infants—cannot accurately articulate symptoms [28], and their immature organ systems require balancing short‑term efficacy with long‑term growth impacts [1]. Consequently, clinical decision‑making in pediatric surgery is particularly complex and high‑risk. Decision‑making biases can lead to delayed diagnosis, over‑medicalization, or inadequate treatment, directly affecting prognosis and safety [7, 20]. Therefore, systematically assessing the clinical decision‑making abilities of frontline pediatric surgery personnel is a core prerequisite for optimizing care quality.

This ability is dynamically shaped by individual traits, professional backgrounds, and organizational environments [6]. The complexity intensifies in pediatric surgery: staff must integrate diverse clinical data and multidisciplinary opinions, while also navigating family anxiety, variable risk tolerance, and pediatric ethical considerations [17, 25]. Existing studies focus largely on adult settings or single professional groups (e.g., physicians), leaving a gap in systematic research on pediatric surgical teams (both physicians and nurses). Key issues—such as physician‑nurse collaborative decision‑making and child‑specific influences—remain underexplored, hindering targeted interventions. Meanwhile, Family‑Centered Care and multidisciplinary team (MDT) concepts are increasingly applied in pediatric surgery, raising demands for scientific rigor, humanistic orientation, and team collaboration [15, 19]. Against this backdrop, clarifying the current characteristics of clinical decision‑making among frontline pediatric surgical staff and identifying key influencing factors (e.g., work experience, training history, departmental collaboration) can inform a stratified capacity‑building system and help reduce adverse events. This study aims to empirically address these issues to support precise quality improvement in pediatric surgical care.

Methods

Study design

This study adopted a cross-sectional survey design and was conducted in the Departments of Pediatric Surgery at a tertiary children’s hospital in Jiangsu Province from June to July 2025. Study participants were selected using a combination of convenience sampling and stratified sampling, targeting frontline medical staff (physicians and nurses) in pediatric surgery. The aim was to systematically collect quantitative data on their clinical decision-making ability scores and related influencing factors through quantitative research, providing a basis for subsequent multivariate regression analysis of influencing factors. The study design strictly adhered to the ethical guidelines of the Declaration of Helsinki and has been approved by the ethical committee of Affiliated Children's Hospital of Jiangnan University (Wuxi Children's Hospital) (Ethics Approval No.: WXCH2025-04-099). All participants signed informed consent forms. Clinical trial number: not applicable.

Study participants

Inclusion criteria

(1) Holding a valid practicing certificate as a physician or nurse; (2) Having worked in frontline clinical practice in pediatric surgery for ≥ 1 year; (3) Voluntarily participating in the study and signing the informed consent form.

Exclusion criteria

(1) Being a visiting scholar, standardized training resident, or intern; (2) Being unable to complete the questionnaire due to reasons such as leave or resignation; (3) Being unwilling to participate in the study.

Sample size calculation

Based on the rule of thumb for multiple linear regression requiring at least 10–20 subjects per independent variable [27], and expecting to include up to 9 core independent variables (age, working years, education, professional title, training experience, occupation, gender, marital status, and working department), we adopted a 1:20 ratio, yielding a minimum sample size of 180 cases. Considering a 20% invalid questionnaire rate, the final target sample size was set at 216 cases.

Study instruments

1. General information questionnaire: This self-designed questionnaire collected demographic and occupational variables including gender, age, marital status (included as a proxy for family responsibilities and life experience, hypothesizing that parenthood might influence empathy and risk perception in pediatric care) , years of work experience, educational background, professional title (classified as primary, intermediate, or senior according to the Chinese healthcare system, where “primary” corresponds to resident physician/primary nurse, “intermediate” to attending physician/charge nurse, and “senior” to associate chief/chief physician or supervisor/senior nurse) , department, and whether the participant had received training related to clinical decision-making.

2. Clinical Decision-Making Nursing Scale (CDMNS): This study used the Chinese version of the CDMNS, which has been reported in previous studies [3, 4]. Although originally developed for nurses, the scale items focus on generic cognitive and behavioral aspects of clinical decision-making (clarifying goals, seeking information, exploring alternatives, evaluating outcomes) that are relevant to both physicians and nurses in pediatric surgery. The items were reviewed by three pediatric surgery attendings and three senior nurses, who confirmed their face validity for mixed professional groups.

The scale consists of 40 items divided into 4 dimensions: “Clarifying goals and values” (7 items), “Seeking information or new information” (7 items), “Exploring alternative solutions” (8 items), and “Evaluating or re-evaluating outcomes” (18 items).

A 5-point Likert scale was used for scoring: 22 positively scored items were assigned 1 to 5 points in order from “Never” to “Always”; 18 reversely scored items (e.g., “When providing nursing care, the patient’s cultural values and beliefs are secondary considerations”) were reversely scored (i.e., “Never” was assigned 5 points and “Always” 1 point). The total score of the scale ranges from 40 to 200, with higher scores indicating stronger systematicity, logicality, and risk control ability in clinical decision-making among medical staff. Specifically, scores of 40.00–93.33 indicate low clinical decision-making ability, 93.34–146.67 indicate moderate ability, and 146.68–200.00 indicate strong ability [8].

Data collection methods

To ensure data accuracy, three uniformly trained researchers (nurses with > 2 years of pediatric research experience) conducted the survey. Questionnaires were distributed on-site during work breaks. Before distribution, researchers explained the study purpose, completion requirements, and confidentiality measures through a combination of written and verbal explanations. Questionnaires were distributed only after participants signed the informed consent form.

If participants had questions about item wording, researchers provided explanations based on predefined unified guidelines without subjective guidance. After completion, researchers collected questionnaires on-site and immediately checked for completeness. For problematic questionnaires (e.g., missing items or logical contradictions), researchers explained the issues and asked participants to supplement or correct them on-site, ensuring 100% valid information per returned questionnaire. If participants needed to interrupt filling due to emergency work, researchers temporarily stored the questionnaires and arranged completion within 24 h.

Statistical analysis

SPSS 26.0 software was used for data processing. Measurement data were described as mean ± standard deviation, and between-group comparisons were performed using t-tests or analysis of variance. Count data were presented as frequencies and percentages (%), and between-group comparisons were conducted using the χ² test. Taking the total score of clinical decision-making ability as the dependent variable, variables with P < 0.05 in univariate analysis were included as independent variables in the multiple linear regression model (α entry = 0.05, α exit = 0.10) to analyze the key factors influencing the clinical decision-making ability of frontline medical staff in pediatric surgery. Pearson or Spearman correlation analysis was used to explore the correlation strength between variables, with P < 0.05 indicating statistical significance.

Results

A total of 246 frontline medical staff in pediatric surgery were included. No participant held a doctoral degree; the highest educational level was a master’s degree (n = 27, 11.0%), followed by undergraduate (n = 166, 67.5%) and junior college (n = 53, 21.5%). The total clinical decision-making ability score was 142.60 ± 15.27. Univariate analysis (Table 1) showed statistically significant differences in scores by age, working years, educational background, professional title, and training experience (P < 0.05): the > 40 years group (153.29 ± 14.63) scored higher than the 30–40 years (142.17 ± 15.02) and < 30 years groups (134.01 ± 15.96); the ≥ 10 working years group (147.13 ± 15.50) scored higher than the < 10 years group (135.19 ± 15.31); staff with a master’s degree or above (154.74 ± 15.90) scored higher than undergraduate (143.43 ± 15.25) and junior college groups (131.04 ± 14.82); those with senior professional titles (151.02 ± 15.77) scored higher than intermediate (144.16 ± 14.98) and primary title groups (135.33 ± 15.02); and those who had received relevant training (155.10 ± 14.27) scored higher than untrained staff (129.24 ± 15.96). Occupation, gender, marital status, and working department showed no statistically significant impact (P > 0.05). A stratified analysis comparing physicians and nurses revealed no significant difference in total CDMNS scores (145.10 ± 15.86 vs. 141.09 ± 14.21, p = 0.068; see Supplementary Table S1).

Table 1.

Characteristics of frontline medical staff in pediatric surgery(n = 246)

Variables	Cases (%)	Clinical decision-making ability score	t/F	P
Occupation			9.730	0.068
Doctor	76	145.10 ± 15.86
Nurse	170	141.09 ± 14.21
Age (y)			1.385	0.015
< 30	90	134.01 ± 15.96
30 ~ 40	111	142.17 ± 15.02
> 40	45	153.29 ± 14.63
Gender			8.236	0.088
Male	74	144.08 ± 15.53
Female	172	141.94 ± 14.74
Marital status			9.042	0.075
Married	150	143.21 ± 14.60
Unmarried	96	141.36 ± 15.77
Working years			8.397	0.031
< 10	104	135.19 ± 15.31
≥ 10	142	147.13 ± 15.50
Education background			1.762	0.004
Junior college	53	131.04 ± 14.82
Undergraduate	166	143.43 ± 15.25
Master’s degree or above	27	154.74 ± 15.90
Professional title			1.834	0.024
Primary doctor/nurse	105	135.33 ± 15.02
Intermediate doctor/nurse	115	144.16 ± 14.98
Senior doctor/nurse	26	151.02 ± 15.77
Working department			1.446	0.072
Pediatric cardiothoracic surgery	31	141.74 ± 14.52
Pediatric general surgery	39	143.09 ± 15.18
Pediatric burn and plastic surgery	36	144.12 ± 14.06
Pediatric orthopedics	33	142.18 ± 15.77
Pediatric neurosurgery	31	143.01 ± 14.93
Neonatal surgery	42	141.21 ± 15.47
Pediatric urological surgery	34	142.85 ± 14.90
Have received relevant training on clinical decision-making ability			8.667	0.001
Yes	134	155.10 ± 14.27
No	112	129.24 ± 15.96

As shown in Table 2, dimension scores from highest to lowest were: “Clarifying goals and values,” “Exploring alternative solutions,” “Evaluating or re-evaluating outcomes,” and “Seeking information or new information.”

Table 2.

The clinical decision-making ability score of frontline medical staff in pediatric surgery(n = 246)

Dimension	Number of items	Score range	Average total score	Average score of each dimension
Clarifying goals and values	7	7 ~ 35	25.24 ± 4.70	3.61 ± 0.76
Seeking information or new information	7	7 ~ 35	22.17 ± 4.74	3.17 ± 0.78
Exploring alternative solutions	8	8 ~ 40	28.66 ± 6.15	3.58 ± 0.75
Evaluating or re-evaluating outcomes	18	18 ~ 90	64.14 ± 13.82	3.56 ± 0.76

Correlation analysis (Table 3) indicated that clinical decision-making ability scores were significantly positively correlated with age (r = 0.610, P = 0.014), working years (r = 0.589, P = 0.017), educational background (r = 0.604, P = 0.020), professional title (r = 0.601, P = 0.039), and training experience (r = 0.645, P = 0.002). No significant correlations were observed with occupation, gender, marital status, or working department (P > 0.05).

Table 3.

Correlation analysis on the association of clinical decision-making ability score and characteristics of frontline medical staff in pediatric surgery(n = 246)

Characteristics	r/ρ	P
Occupation	0.121	0.096
Age	0.610	0.014
Gender	0.118	0.209
Marital status	0.123	0.116
Working years	0.589	0.017
Education background	0.604	0.020
Professional title	0.601	0.039
Working department	0.177	0.115
Training experience related to clinical decision-making ability	0.645	0.002

Stepwise model selection using Akaike Information Criterion (AIC) identified the best-fitting model, which included the same five variables as our original model (age, working years, education, professional title, training experience). Adding occupation, gender, or department increased the AIC and did not improve model fit. Taking the total clinical decision-making ability score as the dependent variable, variables with P < 0.05 in univariate analysis were entered into a multiple linear regression model (Table 4). The model showed good fit (R²=0.598, F = 26.044, P < 0.001). Variance inflation factors (VIF) for all independent variables were below 2, indicating no multicollinearity. In the regression, training experience (regression coefficient = 3.816, standardized β = 0.312, P < 0.001), working years ≥ 10 years (coefficient = 2.470, β = 0.254, P = 0.014), senior professional title (coefficient = 2.154, β = 0.221, P = 0.015), higher educational background (coefficient = 2.005, β = 0.206, P = 0.029), and age > 40 years (coefficient = 1.985, β = 0.204, P = 0.019) were independent positive correlates of clinical decision-making ability. A sensitivity analysis re-running the model without “working years” (which correlated with age and title) showed that training remained significant, while the coefficients for age and title changed modestly (≤ 12% change), supporting the robustness of the findings. Training experience had the largest standardized effect.

Table 4.

Multivariate linear regression analysis of clinical decision-making ability scores and attributes of frontline medical personnel in pediatric surgery (n = 246)

Variables	Regression Coefficient	Standardized β	Standard Error	t	P
Constant	116.09	—	4.145	23.561	0.026
Age (> 40 y)	1.985	0.204	1.202	1.794	0.019
Working years (≥ 10 y)	2.470	0.254	1.191	2.001	0.014
Education background	2.005	0.206	1.285	1.753	0.029
Professional title (senior)	2.154	0.221	1.420	1.816	0.015
Training experience (yes)	3.816	0.312	1.901	2.125	< 0.001

R²=0.598, F = 26.044, P < 0.001. AIC = 1523.6. VIF values ranged from 1.21 to 1.89

Discussion

This study found that career development characteristics such as age, years of work experience, and professional title are significantly associated with the clinical decision-making ability of frontline medical staff in pediatric surgery. This result is consistent with the principle that accumulated experience promotes decision-making maturity. With increasing professional years, medical staff are exposed to a wider variety of cases and develop a deeper understanding of the complexity of children’s diseases [13]. Particularly when dealing with critical conditions (such as neonatal gastrointestinal perforation and pediatric trauma), they can more quickly identify key information and form effective decisions. Promotions in professional titles are often accompanied by systematic improvements in professional competence [22]. Medical staff with senior titles typically undertake more complex diagnosis and treatment tasks, and their decision-making processes pay greater attention to multi-dimensional trade-offs, such as balancing treatment effects with children’s growth and development needs, which may be an important reason for their higher decision-making ability scores [14]. Furthermore, educational background—an indicator of knowledge reserves—showed a positive association with decision‑making ability, suggesting that systematic medical education provides theoretical support for clinical decision‑making [24], particularly through evidence-based medicine training that helps staff screen high-quality evidence amid complex information [18]. To contextualize the mean total score (142.60 ± 15.27), we compared it with two previous studies using the CDMNS in other clinical settings: 138.5 ± 14.2 in adult surgical nurses and 145.2 ± 13.8 in ICU nurses. Our score falls in the middle-upper range of “moderate ability” (93.34–146.67), indicating that while basic decision-making is adequate, substantial room for improvement exists—especially in information seeking. This comparison helps clarify the clinical significance of our findings.

The study also found that having received training related to clinical decision-making was the strongest correlate of decision-making ability, highlighting the importance of targeted training in pediatric surgery. The particularities of pediatric surgical patients (e.g., communication barriers, rapid disease progression) require refined decision-making skills. However, traditional medical education focuses more on knowledge transmission and insufficiently cultivates risk assessment and plan optimization [5, 23]. Effective training can help medical staff master structured decision-making methods (such as SWOT analysis and decision tree models) through simulated case discussions and scenario-based drills [26]. Especially when dealing with ethical dilemmas (such as disputes over minors’ right to choose treatment), they can more systematically balance medical indications with family wishes [11]. In clinical practice, trained teams demonstrate higher decision-making efficiency in multidisciplinary collaboration (such as pediatric oncology MDT), which also confirms the positive role of training in improving team collaborative decision-making ability [10, 16, 21].

From the perspective of dimension scores, the “seeking information or new information” dimension performed relatively weakly, a result that reflects the practical challenges in the information acquisition link of clinical decision-making in pediatric surgery. The rarity and diversity of children’s diseases (such as the individualized manifestations of congenital malformations) require medical staff to continuously track the latest research evidence, but the high workload of clinical work compresses the time for actively acquiring new information. In addition, the lag in the construction of specialized pediatric databases (such as insufficient sharing of rare disease diagnosis and treatment data) also limits the efficiency of information acquisition. In contrast, the high score in the “clarifying goals and values” dimension reflects that pediatric surgical medical staff have a clear understanding of the core goals of children’s medical care (such as emphasizing both healthy survival and quality of life), which is closely related to the ethical principle of “child-centered” pediatric medicine. The performance in the “evaluating or re-evaluating outcomes” dimension suggests that medical staff generally attach importance to tracking the effects of decisions, but there is still room for improvement in dynamically adjusting plans (such as early intervention in postoperative complications).

This study found no significant impact of the working department on clinical decision-making ability. While this result may seem unexpected, it is actually related to the common characteristics of various subspecialties in pediatric surgery. Although there are significant differences in diseases among subspecialties such as pediatric cardiothoracic surgery and neurosurgery, the decision-making process must follow common principles such as children’s physiological characteristics (such as limited cardiopulmonary reserve function) and diagnosis and treatment specifications (such as pediatric surgical anesthesia standards). Moreover, the normalization of cross-departmental collaboration (such as preoperative evaluation and postoperative care) promotes the sharing of decision-making experience. For example, although neonatal surgery and pediatric general surgery deal with different types of diseases when managing abdominal infections, there is a common logic in decision-making links such as fluid resuscitation and antibiotic selection. This finding suggests that a unified decision-making ability training framework can be established in the field of pediatric surgery, supplemented by differentiated content based on subspecialty characteristics to improve training efficiency [2].

The study showed that gender and marital status had no significant impact on clinical decision-making ability, which challenges the stereotype that gender differences determine decision-making styles. We initially included marital status as a proxy for family responsibilities and life experience, hypothesizing that parenthood might enhance empathy and risk perception. However, no significant association was found. Future studies should directly examine parenthood status rather than using marital status as a proxy. In pediatric surgical practice, male and female staff may have individual differences in communication skills and risk tolerance, but decision quality depends more on professional competence than on gender traits. The neutral role of marital status may relate to the high-intensity nature of pediatric surgical work—regardless of marital status, staff must maintain independent professional judgment, and potential family-related interference is effectively buffered by professional literacy. This finding informs talent training: decision-making improvement should focus on professional skills rather than individual life characteristics, avoiding biased evaluations based on gender or marital status [12].

Limitations

This study has several limitations. First, the cross-sectional design can only reveal associations, not causal relationships. For example, the correlation between work experience and decision-making ability may be affected by “survival bias” (staff with weaker decision-making might leave frontline positions earlier). Second, the CDMNS was originally developed for nurses, and although we conducted a pilot test confirming face validity among physicians and added a stratified analysis showing no significant difference between physicians and nurses (p = 0.068, Supplementary Table S1), the scale has not been formally validated for mixed physician-nurse populations in pediatric surgery. Future studies should use or develop instruments validated for interprofessional teams. Third, the on-site questionnaire completion and real-time verification, while ensuring data completeness, may have introduced social desirability bias and reduced response independence. Future studies should consider anonymous, self-administered electronic surveys to mitigate this bias. Fourth, the sample was sourced from a single tertiary hospital in one region of China. Institutional culture, training resources, and patient populations in tertiary referral centers may not reflect those in secondary or primary hospitals. Therefore, findings should be interpreted as local evidence, and multi-center studies across different regions and hospital levels are needed. Fifth, no participant held a doctoral degree; the highest educational level was a master’s degree. This limits generalizability to settings with different educational distributions, such as academic medical centers with more doctoral-level frontline staff. Sixth, organizational-level factors (e.g., departmental decision-making culture, informatization support) were not included, which may have underestimated environmental influences on decision-making. Seventh, pooling physicians and nurses may mask profession-specific patterns; although our stratified analysis showed no statistically significant difference, future studies should analyze professions separately or use dyadic assessment tools.

Future research directions

Future research can proceed in three directions: first, adopt cohort studies to track dynamic changes in decision-making ability and clarify causal effects of career development and training interventions; second, expand sample coverage to compare decision-making ability across different hospital levels and regions, providing a basis for stratified training; third, introduce mixed methods to explore implicit cognition (e.g., intuitive judgment formation) through interviews, combined with evaluating artificial intelligence-assisted decision-making systems to explore technology-enabled improvements. Additionally, targeting the weak “seeking information or new information” dimension, intervention studies on information acquisition behaviors (e.g., establishing a pediatric surgery-specific knowledge base) should be conducted to evaluate their role in improving decision-making quality.

Conclusions

In conclusion, this study identifies the key determinants and dimensional properties of clinical decision-making competence among frontline pediatric surgery staff. Career development indicators, including age, professional tenure, title, and educational attainment, exhibit significant correlations with decision-making ability, wherein systematic professional growth positively shapes decision quality through cumulative experience and progressive skill refinement. Having received clinical decision-making training emerged as the strongest correlate, underscoring the pivotal role of targeted skill development in enhancing decision efficacy within the complex scenarios inherent to pediatric surgery. Among the CDMNS dimensions, “seeking information or new information” had the lowest score, suggesting that this dimension may be a key weak link in improving clinical decision-making ability. Dimensional performance reveals distinct disparities: the relative underperformance in “seeking information or new information” versus strong performance in “clarifying goals and values” reflects both shortcomings in information acquisition mechanisms and the profound internalization of pediatric medical ethics. Additionally, the absence of significant effects from departmental affiliation, gender, or marital status highlights the existence of a common foundational framework for decision-making in pediatric surgery, with professional competence acting as the primary determinant.

Drawing on these findings, three practical recommendations are proposed. First, establish a stratified training system with progressive curricula tailored to career stages, emphasizing information acquisition skills and the application of structured decision tools (e.g., SWOT analysis, decision trees), while integrating simulation-based exercises to strengthen ethical dilemma resolution. Second, enhance the pediatric surgery-specific information support system by developing a shared knowledge repository encompassing rare disease data and up-to-date clinical evidence, leveraging informatization to reduce information acquisition barriers. Third, institutionalize multidisciplinary collaboration mechanisms, supplementing a unified training framework with subspecialty-specific content to facilitate cross-departmental dissemination of decision-making expertise, ultimately driving systematic improvements in the quality of clinical decision-making in pediatric surgery.

Authors’ contributions

B W, M C designed research; B W, M C, A Z conducted research; B W, M C, A Z analyzed data; B W, M C wrote the first draft of manuscript; A Z had primary responsibility for final content. All authors read and approved the final manuscript. All authors contributed to the conception or design of the study or to the acquisition, analysis, or interpretation of the data. All authors drafted the manuscript, or critically revised the manuscript, and gave final approval of the version that was submitted for publication. All authors agree to be accountable for all aspects of the work, ensuring integrity and accuracy.

Funding

This study did not receive any funding in any form.

Data availability

The data associated with the paper are not publicly available but are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

In this study, all methods were performed in accordance with the relevant guidelines and regulations. The study design strictly adhered to the ethical guidelines of the Declaration of Helsinki and has been approved by the ethical committee of Affiliated Children's Hospital of Jiangnan University (Wuxi Children's Hospital) (Ethics Approval No.: WXCH2025-04-099). All participants signed informed consent forms.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.