Development of a core competency evaluation indicator system for weight management nurses: a Delphi and analytic hierarchy process study

Abstract

Background

Weight management services increasingly require nurses to contribute to risk assessment, behavioural support, multidisciplinary coordination and long-term follow-up. However, there is limited consensus on the competencies required for nurses working in this emerging field. This study aimed to develop an evaluation indicator system for the core competencies of weight management nurses.

Methods

A methodological study was conducted using semi-structured interviews, grounded theory coding, two rounds of Delphi consultation and the analytic hierarchy process. An initial indicator pool was developed from interviews with 20 weight management professionals and literature review. From April to June 2026, 18 experts in clinical nursing, nursing management, nursing education, clinical medicine and health management rated the importance of the indicators. Indicator screening was based on the mean importance score, coefficient of variation and expert comments. Expert consensus was evaluated using the coefficient of variation and Kendall’s coefficient of concordance, and indicator weights were determined using the analytic hierarchy process (AHP).

Results

The valid response rate was 100.0% in both Delphi rounds, and the expert authority coefficient was 0.843. Kendall’s coefficients of concordance for first-, second- and third-level indicators were 0.229, 0.183 and 0.139 in the first round and 0.241, 0.196 and 0.171 in the second round, respectively; all were statistically significant. In the second round, the coefficients of variation for all indicators were less than 0.25. The final system included 5 first-level, 21 second-level and 62 third-level indicators. The first-level weights were intervention implementation (0.211), knowledge integration (0.206), professional motivation (0.203), multidisciplinary coordination (0.198) and professional development (0.183).

Conclusions

The indicator system provides a structured framework for competency-based training, selection and evaluation of weight management nurses. Further validation in different healthcare settings is needed before broad application.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s12912-026-05273-9.

Background

Obesity is a major public health concern in China and worldwide. In China, more than half of adults are overweight or obese [1]. Obesity is associated with type 2 diabetes, cardiovascular disease and several cancers, and it increases both disease burden and healthcare resource use [2]. National initiatives such as the Healthy China 2030 Outline and the Year of Weight Management have called for comprehensive services covering prevention, treatment and long-term follow-up, as well as stronger multidisciplinary collaboration [3, 4]. These policy and practice changes have expanded the expected contribution of nurses in obesity care and weight management.

Weight management is not a single intervention but a continuous care process that integrates nutrition, physical activity, behavioural support, pharmacotherapy, monitoring and follow-up [5, 6]. Nurses often have sustained contact with patients and are well placed to provide assessment, education, self-management support and care coordination [7]. Previous studies have shown that nurse involvement can improve health behaviours, weight control and chronic disease management. Nevertheless, some clinical nurses still report limited weight management knowledge, insufficient confidence in behavioural counselling and unclear role recognition [8, 9]. These gaps suggest the need for a clear competency framework for nurses working in weight management services.

Existing studies on weight management nursing have mainly focused on intervention models, digital management, multidisciplinary clinics and patient outcomes such as body mass index, body weight, health behaviours and follow-up effects [10–12]. Comparatively little attention has been given to the competencies nurses need in order to deliver these services consistently. Without a competency-based framework, it is difficult to design training curricula, define job expectations, evaluate professional performance or support workforce development in this field.

Spencer’s Iceberg Model of Competence divides competence into explicit components, such as knowledge and skills, and implicit components, such as social roles, self-concept, traits and motivation. The implicit components are considered important determinants of sustained high performance [13, 14]. This model is suitable for weight management nursing because nurses must combine clinical knowledge and intervention skills with professional identity, empathy, motivation and resilience. Guided by this framework, this study developed an evaluation indicator system for the core competencies of weight management nurses using literature analysis, qualitative interviews, Delphi consultation and analytic hierarchy process (AHP). The study aimed to provide a structured basis for competency-based education, personnel selection and job evaluation in weight management nursing.

Methods

Study design and setting

This was a methodological study designed to develop a competency evaluation indicator system. The study included three phases: development of a preliminary indicator pool, two rounds of Delphi consultation and weight determination using AHP. The Delphi consultation was conducted from April to June 2026.

The study was conducted in tertiary Grade A hospitals in southwestern and central China. In this study, weight management nurses refer to nurses who participate in weight-related health assessment, lifestyle and behavioural support, medication education, follow-up management and multidisciplinary coordination for individuals requiring weight management services.

Research team

The research team consisted of seven members, including a doctoral supervisor in nursing, an endocrinology nursing manager, nursing master’s students and a senior nurse from a weight management clinic. The team was responsible for literature retrieval, interview design, review of the qualitative analysis, development of the preliminary indicator system, Delphi questionnaire design, expert recruitment, questionnaire distribution and data analysis.

Development of the preliminary indicator pool

Spencer’s Iceberg Model of Competence was used as the theoretical framework [14]. The model distinguishes explicit competencies above the waterline, including knowledge and skills, from implicit competencies below the waterline, including social roles, self-concept, traits and motivation. The framework was used to ensure that the indicator system included both observable professional abilities and underlying professional attributes.

Using purposive sampling, 20 professionals involved in weight management were recruited from endocrinology weight management clinics and health examination centres in tertiary Grade A hospitals. They included 14 nurses and 6 members of multidisciplinary teams. The semi-structured interview guide was developed specifically for this study by the research team according to Spencer’s Iceberg Model of Competence, the research objectives and a review of relevant literature. It has not been previously published. The guide focused on the knowledge, skills, attitudes and motivation required of weight management nurses. The English-language version of the interview guide is provided as Additional file 1. Interview data were analysed with NVivo 12 Plus using open coding, axial coding and selective coding. The preliminary codes, categories, and thematic structure were reviewed and discussed by the research team. The categorisation, naming, and final thematic structure were refined through team discussion until consensus was reached. A total of 241 initial codes, 29 concepts and 14 categories were extracted, from which five main categories were generated: knowledge integration, intervention implementation, multidisciplinary coordination, professional development and professional motivation. The preliminary indicator system comprised 5 first-level indicators, 22 second-level indicators and 68 third-level indicators.

Delphi expert panel

Experts were eligible if they met the following criteria: (1) at least five years of experience in weight management, endocrinology nursing, chronic disease management, nursing education or nursing administration; (2) a bachelor’s degree or above and an intermediate professional title or above; (3) familiarity with weight management-related nursing practice or research; and (4) willingness to participate in and complete two rounds of consultation. Eighteen experts from clinical nursing, nursing administration, nursing education, clinical medicine and health management were included.

Two rounds of consultation were conducted by email. Experts were asked to respond within two weeks. The first-round questionnaire included a cover letter, an indicator importance rating form using a 5-point Likert scale (5 = very important, 1 = not important), and a form collecting demographic information, familiarity and judgment basis. After the first round, indicators were revised according to the predefined screening criteria of mean importance score > 3.50 and coefficient of variation (CV) < 0.25 [15], together with written expert comments. The revised indicators were then sent to the same experts for the second round.

Weight determination and statistical analysis

SPSS 26.0 was used for statistical analysis, and Yaahp 10.3 was used to calculate indicator weights. Continuous variables were described using mean ± standard deviation (SD), and categorical variables were described using frequencies and percentages. Expert engagement was evaluated by the valid response rate. The expert authority coefficient (Cr) was calculated as the mean of the judgment coefficient (Ca) and familiarity coefficient (Cs), namely Cr = (Ca + Cs)/2 [16]. Expert consensus was evaluated using the CV and Kendall’s coefficient of concordance.

AHP was used to determine the local and combined weights of indicators. A hierarchical model was established according to the final indicator system. Local weights were derived from the expert importance ratings, and reciprocal judgment matrices were constructed for indicators at the same level. The maximum eigenvalue and corresponding eigenvector were used to calculate weights. The consistency ratio (CR) was used to evaluate the reliability of judgment matrices; CR < 0.10 was considered acceptable [17]. The overall development process is presented in Fig. 1.

Fig. 1.

Development process of the core competency evaluation indicator system for weight management nurses

Results

Expert characteristics

A total of 18 experts completed both rounds of consultation. They were from three tertiary Grade A hospitals in Yunnan, Sichuan and Hunan provinces. Their characteristics are shown in Table 1.

Table 1.

Demographic characteristics of the experts

Item	Value
Gender [n (%)]	Male 2 (11.1) Female 16 (88.9)
Mean age [years, mean ± SD]	42.8 ± 5.2
Mean years of work experience [years, mean ± SD]	16.4 ± 4.7
Professional title [n (%)]	Intermediate 7 (38.9) Associate Senior and Above 11 (61.1)
Professional background [n (%)]	Clinical Weight Management Nursing 7 (38.9) Nursing Management 4 (22.2) Nursing Education 3 (16.7) Clinical Medicine 3 (16.7) Health Management 1 (5.5)
Educational level [n (%)]	Bachelor’s degree 9 (50.0) Master’s degree or higher 9 (50.0)

Expert engagement, authority and consensus

In each round, 18 questionnaires were distributed and 18 valid questionnaires were returned, yielding a valid response rate of 100.0%. Eight experts (44.4%) provided revision suggestions in the first round, and three experts (16.7%) provided additional comments in the second round. The judgment coefficient (Ca), familiarity coefficient (Cs) and authority coefficient (Cr) were 0.933, 0.753 and 0.843, respectively.

After the first round, indicators were screened according to their mean scores and CVs and further revised based on expert comments. In the second round, the CVs of all indicators were < 0.25. Kendall’s coefficients of concordance for all levels of indicators were statistically significant in both rounds. The W values for the first-, second- and third-level indicators were higher in the second round than in the first round, indicating improved expert consensus (Table 2).

Table 2.

Degree of expert consensus

Item	Round 1 indicators	Round 1 W	Round 1 χ²	Round 1 P	Round 2 indicators	Round 2 W	Round 2 χ²	Round 2 P
First-level indicators	5	0.229	16.520	0.002	5	0.241	17.333	0.002
Second-level indicators	22	0.183	69.221	< 0.001	21	0.196	70.658	< 0.001
Third-level indicators	68	0.139	168.129	< 0.001	62	0.171	187.779	< 0.001

Final indicator system and weights

After the first round, a total of seven indicators were removed, including one second-level indicator (research exploration competence) and six third-level indicators (management of patients undergoing bariatric surgery, evaluation of research evidence, identification of clinical problems, basic knowledge of research methods, academic writing and communication, and participation in training programmes). Two additional second-level indicators were retained but renamed based on expert comments: evidence-based practice competence was revised to guideline retrieval and application, and teaching guidance competence was revised to mentoring new nurses. Some indicator names and descriptions were also refined.

After the second round, no additional indicators were removed. The final system included 5 first-level indicators, 21 second-level indicators and 62 third-level indicators. The calculated CR of the first-level judgment matrix was 0.000, and the CRs of all second- and third-level judgment matrices were < 0.10. The first-level weights, in descending order, were intervention implementation (0.211), knowledge integration (0.206), professional motivation (0.203), multidisciplinary coordination (0.198) and professional development (0.183). The importance scores, CVs, indicator weights and combined weights are shown in Table 3. The structure and weight distribution of the final indicator system are illustrated in Fig. 2.

Table 3.

Evaluation indicator system and weights for core competencies of weight management nurses

Indicator		Importance score (mean ± SD)	CV		Indicator weight	Combined weight
1 Knowledge integration		4.56 ± 0.51	0.112		0.206	—
1.1 Understanding of pathophysiology		4.61 ± 0.50	0.109		0.212	0.044
1.1.1 Pathophysiological Mechanisms of Obesity		4.61 ± 0.50	0.109		0.261	0.011
1.1.2 Epidemiology of Obesity		4.17 ± 0.62	0.148		0.236	0.010
1.1.3 Spectrum of Obesity-Related Comorbidities		4.78 ± 0.43	0.090		0.270	0.012
1.1.4 Fundamentals of Energy Metabolism		4.11 ± 0.68	0.165		0.233	0.010
1.2 Knowledge of weight-loss pharmacotherapy		4.33 ± 0.49	0.112		0.199	0.041
1.2.1 Knowledge and Guidance on GLP-1 Receptor Agonists		4.72 ± 0.46	0.098		0.265	0.011
1.2.2 Knowledge and Guidance on Other Weight-Loss Medications		4.33 ± 0.59	0.137		0.243	0.010
1.2.3 Drug Interactions and Safety Monitoring		4.56 ± 0.51	0.112		0.255	0.010
1.2.4 Identification of Drugs Associated with Weight Gain		4.22 ± 0.65	0.153		0.237	0.010
1.3 Application of nutrition science		4.50 ± 0.51	0.114		0.207	0.042
1.3.1 Knowledge of Macronutrients and Micronutrients		4.39 ± 0.61	0.138		0.250	0.011
1.3.2 Ability to Calculate Energy Requirements		4.50 ± 0.62	0.137		0.256	0.011
1.3.3 Dietary Pattern Assessment and Guidance		4.50 ± 0.51	0.114		0.256	0.011
1.3.4 Knowledge of Weight-Loss Dietary Patterns		4.17 ± 0.51	0.123		0.237	0.010
1.4 Fundamentals of exercise science		3.94 ± 0.42	0.106		0.181	0.037
1.4.1 FITT Principles for Exercise Prescription		4.28 ± 0.46	0.108		0.325	0.012
1.4.2 Effects of Different Types of Exercise		4.22 ± 0.65	0.153		0.321	0.012
1.4.3 Exercise Safety and Contraindications		4.67 ± 0.49	0.104		0.354	0.013
1.5 Understanding of obesity-related comorbidities		4.39 ± 0.61	0.138		0.202	0.041
1.5.1 Obesity and Metabolic Syndrome		4.61 ± 0.50	0.109		0.263	0.011
1.5.2 Obesity and Cardiovascular Disease		4.50 ± 0.71	0.157		0.257	0.011
1.5.3 Obesity and Sleep Apnea		4.06 ± 0.54	0.133		0.232	0.010
1.5.4 Obesity and Mental Health		4.33 ± 0.49	0.112		0.248	0.010
2 Intervention implementation		4.67 ± 0.49	0.104		0.211	—
2.1 Comprehensive assessment		4.61 ± 0.50	0.109		0.169	0.036
2.1.1 Collection of Anthropometric Measures		4.67 ± 0.49	0.104		0.347	0.012
2.1.2 Interpretation of Body Composition Analysis		4.56 ± 0.51	0.112		0.339	0.012
2.1.3 Assessment of Obesity Stages		4.22 ± 0.55	0.130		0.314	0.011
2.2 Systematic assessment of lifestyle factors		4.61 ± 0.50	0.109		0.169	0.036
2.2.1 Dietary Intake Assessment		4.67 ± 0.49	0.104		0.256	0.009
2.2.2 Physical Activity Assessment		4.56 ± 0.51	0.112		0.250	0.009
2.2.3 Sleep and Stress Assessment		4.28 ± 0.75	0.176		0.235	0.008
2.2.4 Assessment of Eating Behavior		4.72 ± 0.46	0.098		0.259	0.009
2.3 Assessment of readiness for behavioral change		4.39 ± 0.61	0.138		0.161	0.034
2.3.1 Application of the Stages of Behavior Change Model		4.22 ± 0.55	0.130		0.313	0.011
2.3.2 Assessment of Motivation and Self-Confidence		4.72 ± 0.46	0.098		0.350	0.012
2.3.3 Identification of Barriers and Facilitating Factors		4.56 ± 0.51	0.112		0.337	0.011
2.4 Development of personalized plans		4.67 ± 0.49	0.104		0.171	0.036
2.4.1 Comprehensive Goal Setting		4.56 ± 0.51	0.112		0.253	0.009
2.4.2 Individualized Dietary Plans		4.61 ± 0.50	0.109		0.256	0.009
2.4.3 Individualized Exercise Program		4.33 ± 0.69	0.158		0.241	0.009
2.4.4 Behavioral Change Action Plan		4.50 ± 0.51	0.114		0.250	0.009
2.5 Health education and empowerment		4.50 ± 0.51	0.114		0.165	0.035
2.5.1 Translation of Medical Knowledge into Lay Terms		4.50 ± 0.51	0.114		0.332	0.012
2.5.2 Motivational Interviewing Skills		4.39 ± 0.50	0.114		0.324	0.011
2.5.3 Self-Management Empowerment		4.67 ± 0.49	0.104		0.344	0.012
2.6 Ongoing follow-up and support		4.50 ± 0.62	0.137		0.165	0.035
2.6.1 Establishing a Therapeutic Relationship		4.39 ± 0.61	0.138		0.329	0.011
2.6.2 Follow-up Plans and Monitoring		4.61 ± 0.50	0.109		0.346	0.012
2.6.3 Coping with Relapse and Setbacks		4.33 ± 0.59	0.137		0.325	0.011
3 Multidisciplinary coordination		4.39 ± 0.70	0.159		0.198	—
3.1 Interprofessional communication		4.50 ± 0.62	0.137		0.340	0.067
3.1.1 Accurate Translation of Technical Terms		4.39 ± 0.50	0.114		0.335	0.023
3.1.2 Information Sharing Within the Team		4.44 ± 0.62	0.139		0.339	0.023
3.1.3 Conflict Resolution in Collaboration		4.28 ± 0.67	0.156		0.326	0.022
3.2 Patient-provider communication		4.67 ± 0.49	0.104		0.353	0.070
3.2.1 Language Used in Stigma-Reducing Communication		4.61 ± 0.50	0.109		0.337	0.024
3.2.2 Empathetic Listening		4.56 ± 0.51	0.112		0.333	0.023
3.2.3 Mobilization of Family and Social Support		4.50 ± 0.51	0.114		0.329	0.023
3.3 Resource integration and referral		4.06 ± 0.64	0.158		0.307	0.061
3.3.1 Initiation of Multidisciplinary Collaboration		4.22 ± 0.55	0.130		0.507	0.031
3.3.2 Familiarity with Referral Pathways		4.11 ± 0.68	0.165		0.493	0.030
4 Professional development		4.06 ± 0.73	0.179		0.183	—
4.1 Guideline retrieval and application		3.94 ± 0.87	0.221		0.329	0.060
4.1.1 Clinical Guideline Retrieval and Application		4.11 ± 0.68	0.165		0.521	0.031
4.1.2 Integration of Evidence and Patient Values		3.78 ± 0.55	0.145		0.479	0.029
4.2 Reflective practice		4.17 ± 0.62	0.148		0.347	0.064
4.2.1 Clinical Case Reflection		4.06 ± 0.64	0.158		0.521	0.033
4.2.2 Participation in Quality Improvement		3.72 ± 0.57	0.154		0.479	0.030
4.3 Mentoring new nurses		3.89 ± 0.83	0.214		0.324	0.059
4.3.1 Clinical teaching implementation		3.78 ± 0.55	0.145		1.000	0.059
5 Professional motivation		4.50 ± 0.71	0.157		0.203	—
5.1 Awareness of and response to weight bias		4.44 ± 0.51	0.115		0.253	0.051
5.1.1 Self-Bias Awareness		4.33 ± 0.49	0.112		0.335	0.017
5.1.2 Bias Coping Strategies		4.33 ± 0.69	0.158		0.335	0.017
5.1.3 Promoting Equitable Care		4.28 ± 0.46	0.108		0.330	0.017
5.2 Sense of professional value		4.61 ± 0.50	0.109		0.263	0.053
5.2.1 Sense of Professional Achievement		4.17 ± 0.62	0.148		0.487	0.026
5.2.2 Professional Role Identity		4.39 ± 0.50	0.114		0.513	0.027
5.3 Sources of intrinsic motivation		4.11 ± 0.68	0.165		0.234	0.048
5.3.1 Role-model influence		4.11 ± 0.68	0.165		0.477	0.023
5.3.2 Enthusiasm for Continuous Learning		4.50 ± 0.62	0.137		0.523	0.025
5.4 Professional resilience		4.39 ± 0.50	0.114		0.250	0.051
5.4.1 Patience with slow progress		4.33 ± 0.49	0.112		0.339	0.017
5.4.2 Coping with patient non-adherence		4.39 ± 0.50	0.114		0.343	0.017
5.4.3 Persistence despite limited system support		4.06 ± 0.64	0.158		0.317	0.016

Note: Abbreviations: CV, coefficient of variation; FITT, frequency, intensity, time and type; GLP-1, glucagon-like peptide-1; SD, standard deviation. Due to rounding to three decimal places, the sum of the displayed combined weights for the 62 third-level indicators is 0.998, which is approximately 1.000

Fig. 2.

Weight distribution of the competency evaluation indicator system from second-round AHP results

Discussion

Principal findings

This study developed a competency evaluation indicator system for weight management nurses through qualitative inquiry, Delphi consultation and AHP. The final system included five domains: knowledge integration, intervention implementation, multidisciplinary coordination, professional development and professional motivation. These domains reflect both the explicit competencies required for obesity care and the implicit professional attributes needed for sustained patient support.

The high response rate and expert authority coefficient indicate that the Delphi process was feasible and that the panel had relevant professional experience. In the second round, all CVs were below 0.25 and Kendall’s coefficients were statistically significant, suggesting that expert opinions had become relatively concentrated. The indicator system therefore provides a preliminary but structured framework for competency-based workforce development in weight management nursing.

Intervention implementation as the operational core of weight management nursing

Intervention implementation had the highest first-level weight. This finding suggests that the value of weight management nurses lies not only in possessing knowledge but also in translating assessment results into continuous, feasible and monitorable nursing actions. Weight management is a long-term and behaviour-dependent process [18, 19]. Patient outcomes are affected by diet, physical activity, medication adherence, psychological status, family support and follow-up intensity. The relatively high weights assigned to personalised plan development, comprehensive assessment and lifestyle assessment indicate that weight management nursing should move beyond general health education toward tailored intervention based on individual risks, behavioural characteristics and management stages. Training programmes should therefore prioritise behaviour change techniques, motivational interviewing, follow-up management and outcome evaluation.

Knowledge integration as the professional basis for safe and scientific practice

Knowledge integration ranked second among the first-level indicators. Obesity is not merely excessive body weight but a complex health condition associated with metabolic abnormalities, cardiovascular disease, sleep-disordered breathing, mental health problems and medication-related factors [20]. The indicators under this domain include pathophysiology, nutrition science, weight-loss pharmacotherapy, exercise science and obesity-related comorbidities. Together, these elements form a knowledge chain linking disease mechanisms, risk identification, intervention selection and safety monitoring. With the increasing use of glucagon-like peptide-1 (GLP-1) receptor agonists and other medications in weight management, nurses also need stronger competence in medication education, adverse event monitoring and recognition of drugs associated with weight gain.

Professional motivation and humanistic support in long-term care

Professional motivation ranked third, indicating that job competence in weight management nursing depends not only on knowledge and skills but also on professional identity, intrinsic motivation, awareness of weight bias and resilience. Weight management is often accompanied by fluctuating adherence, plateaus, weight regain, anxiety and shame [21]. During long-term follow-up, nurses may encounter repeated setbacks and communication challenges. If nurses lack recognition of the value of this role or hold implicit weight bias, the nurse-patient relationship and intervention effectiveness may be affected. Future training should therefore include content on weight stigma, therapeutic communication, professional identity and psychological resilience, so that nurses can provide respectful, supportive and sustained care while implementing technical interventions.

Multidisciplinary coordination and professional development

Multidisciplinary coordination ranked fourth but remains essential for service delivery. Weight management involves endocrinology, nutrition, physical activity, psychology, surgery, rehabilitation and health management. Nurses can act as a bridge for information transfer, need identification, resource linkage and team communication [7]. The relatively lower weight of resource integration and referral may reflect the fact that referral pathways for weight management are still developing in many institutions. Professional development had the lowest first-level weight, but this finding should not be interpreted as lack of importance. Rather, it suggests that experts prioritised clinical assessment, intervention implementation and follow-up management as foundational competencies for general weight management nurses. As weight management nursing becomes more standardised, professional development should be applied in a tiered manner: basic-level nurses may focus on guideline implementation and case reflection, whereas senior nurses and preceptors may place greater emphasis on quality improvement, training and evidence-based practice. Notably, mentoring new nurses retained only one third-level indicator after Delphi refinement. Because both the second-level domain and the retained indicator met the predefined inclusion criteria and mentoring was considered a distinct component of professional development, the domain was retained despite containing a single sub-indicator. Further studies may elaborate this domain by identifying and validating additional indicators related to mentoring and teaching competencies.

Comparison with existing competency frameworks and international literature

The present framework shows substantial conceptual convergence with existing international obesity competency frameworks. The Obesity Medicine Education Collaborative competencies encompass patient care and procedural skills, medical knowledge, practice-based learning and improvement, interpersonal and communication skills, professionalism, and systems-based practice [22]. Similarly, the UK Obesity Care Competencies comprise 29 competencies across five major areas, including obesity knowledge, patient care and procedural skills, practice-based learning and improvement, professionalism and interpersonal communication skills, and systems-based practice [23]. The Canadian Obesity Education Competencies further emphasise evidence-based, patient-centred obesity care and the mitigation of weight bias and stigma [24]. More recently, a scoping review of obesity competencies for healthcare professionals identified 11 domains, including clinical assessment, clinical management, evidence-based practice, communication, professionalism, patient-centred care, education, and health systems [25]. These areas broadly correspond to the knowledge integration, intervention implementation, multidisciplinary coordination, professional development, and professional motivation domains identified in our study.

However, the present framework differs from these broader competency initiatives in its nursing-specific focus and weighted hierarchical structure. Rather than describing obesity competencies for physicians or healthcare professionals in general, this study translates the role of weight management nurses into specific second- and third-level indicators with relative priorities. Intervention implementation received the highest weight, highlighting the importance of translating knowledge into sustained assessment, personalised intervention, behavioural support, and follow-up. In addition, professional motivation was retained as an independent domain, giving explicit attention to weight-bias awareness, professional value, intrinsic motivation, and resilience. This emphasis reflects the sustained patient contact and supportive role required in long-term weight management and complements broader international obesity competency frameworks with a nursing-specific perspective.

Implications for nursing practice, education, policy and research

The indicator system may support competency-based education by providing a structured map for curriculum development and continuing professional education. Training programmes could integrate foundational knowledge of obesity, nutrition, exercise and pharmacotherapy with higher-priority practice competencies such as comprehensive assessment, personalised planning, motivational interviewing, stigma-reducing communication and long-term follow-up. The relative weights may also help educators identify areas requiring greater emphasis rather than treating all competencies as equally important.

For professional assessment and clinical implementation, the framework may inform role descriptions, orientation programmes, continuing professional development and structured formative assessment for nurses working in weight management services. It may also help clarify nurses’ responsibilities within multidisciplinary teams and support more consistent referral, communication and follow-up processes. However, because the indicator system has not yet undergone psychometric and external validation, the current weights should be interpreted as relative priorities for competency development rather than fixed pass–fail thresholds for high-stakes professional credentialing.

At the organisational and policy levels, the framework may provide a preliminary reference for developing training standards and defining the professional role of weight management nurses. Nevertheless, implementation is likely to require contextual adaptation because nursing scope of practice, multidisciplinary resources, referral pathways, staffing and training capacity, and weight management service models may vary across institutions. International obesity competency frameworks have similarly required adaptation to specific healthcare systems and professional groups [23, 25]. Therefore, local stakeholder engagement, pilot implementation and further validation are needed before the framework is adopted as a formal competency standard across different healthcare settings.

For research, this study provides a basis for developing a measurable competency assessment tool. Future studies should test the content validity, construct validity, reliability and responsiveness of the indicator system in larger samples of nurses. Multicentre studies across different healthcare settings and cultural contexts are also needed to examine whether the framework can be adapted for broader use.

Strengths and limitations

This study has several strengths. The preliminary indicators were generated from both theoretical analysis and interviews with multidisciplinary professionals, which helped integrate clinical experience with a competency model. The Delphi panel included experts from clinical nursing, nursing management, nursing education, clinical medicine and health management, supporting the multidisciplinary relevance of the framework. The combination of Delphi consultation and AHP also allowed the study to identify both consensus and relative priority among indicators.

The study also has limitations. First, the interview data were primarily coded by one researcher, although the preliminary findings were subsequently reviewed by the research team; therefore, some degree of researcher interpretation bias cannot be excluded. Second, the expert panel was limited to selected regions in China, and the findings may not fully represent all healthcare settings or international weight management services. Third, the system has not yet been tested among practicing weight management nurses or linked to patient outcomes. Fourth, AHP weights were derived from expert importance ratings; future studies could use independent pairwise comparisons and psychometric testing to confirm the stability of the weights. Finally, the indicator system remains a developmental framework and requires application-based validation before it can be used as a formal assessment tool.

Conclusions

This study developed a core competency evaluation indicator system for weight management nurses using semi-structured interviews, Delphi consultation and AHP. The final system includes 5 first-level indicators, 21 second-level indicators and 62 third-level indicators. It reflects the knowledge, skills, coordination capacity, professional development needs and motivational attributes required for weight management nursing. The system can provide a preliminary reference for competency-based education, personnel selection, job evaluation and continuing professional development. Further multicentre validation and psychometric testing are needed before broad implementation.

Supplementary Information

Below is the link to the electronic supplementary material.

Abbreviations

AHP

Analytic Hierarchy Process

SD

Standard deviation

Ca

Judgment coefficient

Cr

Expert authority coefficient

Cs

Familiarity coefficient

CR

Consistency ratio

CV

Coefficient of variation

GLP-1

Glucagon-like peptide-1

FITT

Frequency, intensity, time and type

Author contributions

L.W., S.Y.Z., H.Y., Y.Z. and L.G. designed the study. X.W.W. and X.Y.Q. assisted in participant recruitment. Data collection was primarily conducted by H.Y., with L.W., Y.Z. and X.Y.Q. providing support. X.W.W. performed the transcriptions, and H.Y. analysed the data. Preliminary findings were presented to all authors for finalising the thematic scheme. X.W.W. and S.Y.Z. wrote the introduction, H.Y. wrote the methodology and results, Y.Z. and L.W. wrote the discussion and conclusions. X.Y.Q. managed the references and citations. All authors reviewed and approved the final version of the manuscript. L.W. did methodological and linguistic editing.

Funding

This work was supported by the Sichuan Provincial Department of Science and Technology General Program (2024NSFSC0562) and Sichuan Provincial Grassroots Health Development Research Center Project (SWFZ24-Z-15).

Data availability

The datasets generated and/or analysed during the current study are not publicly available because they contain qualitative interview data and expert consultation information that may compromise participant confidentiality, but are available from the corresponding author on reasonable request. Anonymised Delphi datasets may be provided where this does not compromise participant confidentiality.

Declarations

Ethics approval and consent to participate (Ethical Considerations)

This study was approved by the Institutional Review Board of Sichuan Provincial People’s Hospital (approval number: 2026-40). All methods were performed in accordance with relevant ethical guidelines and regulations and with the Declaration of Helsinki. Written informed consent was obtained from all interview participants and Delphi experts before data collection. Participation was voluntary, and all data were analysed anonymously.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.