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. 2026 Jul 30;37(1):83–91. doi: 10.1177/20473087261449715

Content validation of the nursing diagnosis Adult Disuse Syndrome: A quantitative study

Edinson Fabian Ardila-Suárez 1, Vanessa Sánchez-Martínez 1,✉, Paula Escalada-Hernández 2
PMCID: PMC13424899  PMID: 42529990

Abstract

Purpose

This study aimed to establish the content validity of the proposed nursing diagnosis (ND) Adult Disuse Syndrome and all its components.

Method

This is an exploratory descriptive study of diagnostic content validation under Fehring's proposal. Forty three expert nurses with clinical, teaching, and research experience analyzed the components of the diagnosis. The representativeness and relevance of the components of the diagnosis under study were evaluated through a Likert-type questionnaire. Data distribution analysis was carried out, and the components were validated if their content validity index (CVI) was over 0.80. The overall CVI was obtained for the clinical indicators.

Findings

A total of 12 defining characteristics (DCs) were validated, 3 etiological factors were highly related, 6 risk populations were confirmed, and 11 conditions were considered associated. Most validated DCs refer to the physical dimension, but those focusing on the psychological and social dimensions were also validated. The etiological factors were related to the effects of immobility. The risk populations were validated in different contexts or situations, and associated conditions were mainly oriented toward chronic conditions.

Conclusions

This study validated the content of the elements of the proposed ND “Adult Disuse Syndrome.” These were considered relevant and appropriate by both academic and clinical experts.

Implications for nursing practice

The content validation by experts of the components of the ND “Adult Disuse Syndrome” provides nurses with a tool for the identification of the phenomenon that exceeds the risk and occurs frequently in patients exposed to the effects of immobility. At the same time, it will guide the results pursued in the care plan and the application of the respective nursing and interdisciplinary interventions that favor the reduction of the complications derived from disuse.

Keywords: content validation, disuse syndrome, nursing diagnosis

INTRODUCTION

The disuse syndrome was first described in 1984 as the impairment of multiple bodily functions secondary to predictable physical inactivity by Bortz (1984) after a literature review describing the specific physical consequences of prolonged immobility on the human body systems. On the basis of this concept, NANDA (Gordon, 1987) included the nursing diagnosis (ND) Risk of Disuse Syndrome (00040) in the first edition of its classification, defined as “Susceptible to deterioration of body systems as the result of prescribed or unavoidable musculoskeletal inactivity, which may compromise health.”

Other authors have described clinical situations with similar characteristics in the medical, nursing, and physical therapy fields and have also relied on disuse syndrome to strengthen their theoretical basis. Verbunt et al. (2003) introduced the syndrome of physical deconditioning secondary to chronic pain, whereas Van Wilgen et al. (2009) identified results caused by disuse not only at the physiological level but also at the psychological level, such as anxiety, depression, somatization, negative self-perception, and catastrophising. Currently, most research related to disuse has been conducted in intensive care units (ICUs), associated with medical diagnoses such as post-ICU syndrome (Yuan et al., 2021), which is defined as “new or worsening multidimensional impairments in physical, psychological, cognitive and social status arising from a critical illness that persists beyond hospital discharge.” Other authors have defined the concept ICU-acquired weakness and related it to prolonged stays in ICU and severe forms of COVID-19 (Qin et al., 2022).

Within the nursing discipline, the NANDA-International (NANDA-I) taxonomy of nursing diagnoses (Herdman et al., 2020) provides the levels of evidence (LOE) criteria for the validation of nursing diagnoses. These criteria are distributed in two levels: Level 1 refers to concept generation, and Level 2 deals with theoretical and clinical conceptual support. The NANDA-I taxonomy only includes the diagnosis Risk of Disuse Syndrome (00044) (Herdman et al., 2020), with an LOE under 2.1. However, no diagnosis encompasses the phenomenon of disuse as a real problem surpassing the risk barrier present in people who present prolonged immobility.

In this sense, Ardila-Suárez and Escalada-Hernández (2023) proposed the ND “Adult Disuse Syndrome,” defined as “Impairment of the physiological, psychological and social dimensions secondary to immobility, inactivity and loss of physical condition, leading to complications and/or disabilities that compromise health.” This proposal was conceptually validated according to the theoretical guidelines of Lopes et al. (2017). This ND proposal contemplated 25 defining characteristics (DCs), which are real or risk nursing diagnoses, 8-related factors (RFs), 8 risk populations (RPs), and 14 associated conditions (ACs).

According to Lopes et al. (2020), content validity in nursing diagnoses refers to how representative the components of the diagnosis are, which must have been previously validated at a conceptual level. However, the content validity of this diagnostic proposal had not yet been explored, which is necessary to continue to advance the LOE that supports the nursing diagnoses included in the classification. Moreover, current research (Romeiro et al., 2020) is oriented toward investigating and validating syndrome-type nursing diagnoses.

In this sense, the objective of this research was to validate the content for the components of the proposed ND “Adult Disuse Syndrome” by nursing experts, including DCs, RFs, at-risk populations, and ACs.

METHODS

Study design and setting

An exploratory, descriptive, cross-sectional content validation study for the proposed ND “Adult Disuse Syndrome” (Ardila-Suárez & Escalada-Hernández, 2023) was developed following the Diagnostic Content Validation Model proposed by Fehring (1987) and using the modified version by Sparks and Lien-Gieschen (1994). This model is based on obtaining the opinion of nurses considered experts on the degree to which each element of the proposed diagnosis is relevant or representative of the diagnosis.

Sample: experts profile

The criteria considered for the selection of experts were those proposed by Fehring (1987), Benner (1984), and Quatrini et al. (2016). Two profiles were identified for the expert panel. On the one hand, a subgroup of experts at the clinical level who were university graduates in nursing with at least 1 year of clinical experience in the ICU was included. On the other hand, a subgroup of academic experts with a minimum academic level of specialist or master's degree, teaching experience, and research experience in nursing methodology or critical patient care.

Recruitment and selection of experts

Experts were selected by non-probability convenience sampling through nursing associations and organizations, and purposive snowball sampling through the research group's network of contacts (Etikan et al., 2016). The potential participants were approached by email. The scope of the study was multicentric, with Spanish-speaking professionals primarily from Spain and Colombia.

Data collection

An ad hoc questionnaire was designed using the Google Forms platform and divided into two sections: one collected information on independent sociodemographic variables and selection criteria relating to each participant's healthcare or research profile. The other section collected all the components of the diagnosis based on the conceptual validation process of the ND proposal (Ardila-Suárez & Escalada-Hernández, 2023), with their respective operational definitions (dependent variables).

Concerning the DCs, the experts assessed the degree to which these represent the diagnosis. For the RFs and the RPs, they assessed the relationship between them, and for the ACs, they assessed their association. The scale used was a Likert-type scale from 1 to 5 (1 = not at all, 2 = somewhat, 3 = sufficient, 4 = quite, 5 = very much). A free text field was also included to collect possible comments or suggestions from the experts on the different elements of the diagnosis. The questionnaire was pilot-tested in August 2023 with five professionals who met the inclusion criteria to evaluate and determine the clarity of the content, response times, and clarity of the items. Total data collection was between October 2023 and January 2024.

Data analysis

The data were exported in Microsoft Excel, and the analysis was performed using The Jamovi Project version 2.3.28. The descriptive analysis included calculating frequencies with 95% confidence intervals for nominal variables. Quantitative variables were analyzed using measures of central tendency (mean and median) and dispersion (standard deviation). The distribution of the data was analyzed using the Shapiro–Wilk test. To calculate the content validity index (CVI), weighted ratios were determined on the basis of the scores assigned to each element. The average score, obtained from the responses of all experts, ranged between 0 and 1. The validated items were those with a CVI of >0.80 (Fehring, 1987). As a final step in the validation process, the overall weighted CVI was identified for the clinical indicators, by determining the average CVI rate for each of the validated DCs (Sparks & Lien-Gieschen, 1994).

RESULTS

A total of 43 experts participated in the study. The mean age of the participants was 37 ± 8.3 years; 72.1% were women, 23.3% had a doctorate, and 32.6% had a master's degree. Regarding the characterization by profile, 94.4% of the academic experts had more than 5 years of teaching experience, 88.9% had research experience, 44.4% had made some kind of scientific publication related to the classification of nursing diagnoses, and 27.8% had clinical experience in the adult ICU. Of the clinical profile, 44% of the clinical experts had completed specialist or master's studies, 32% had research experience, and 8% had made scientific publications in the ICU. The experts were classified according to their profile (Table 1).

Table 1.

Profile of experts.

Expert n % Expert n %
Academic 18 100 Clinic 25 100
Sex
Man 6 33.3 Male 6 24.0
Woman 12 66.7 Female 19 76.0
Academic background
Grade 0 0.0 Grade 14 56.0
Specialist 2 11.1 Specialist 3 12.0
Master's degree 6 33.3 Master's degree 8 32.0
Doctor 10 55.6 Doctor 0 0.0
Work experience in ICU
None 6 33.3 None 0 0.0
1–3 years 3 16.7 1–3 years 6 24.0
3–5 years 0 0.0 3–5 years 8 32.0
5–7 years 2 11.1 5–7 years 7 28.0
7–10 years 2 11.1 7–10 years 3 12.0
>10 years 5 27.8 >10 years 1 4.0
Teaching experience
None 0 0.0 None 13 52.0
<1 year 1 5.6 <1 year 5 20.0
1–3 years 0 0.0 1–3 years 1 4.0
3–5 years 0 0.0 3–5 years 3 12.0
>5 years 17 94.4 >5 years 3 12.0
Research experience
Yes 16 88.9 Yes 8 32.0
No 2 11.1 No 17 68.0
Publications in nursing
Yes 8 44.4 Yes 4 16.0
No 10 55.6 No 21 84.0
Publications in ICU
Yes 8 44.4 Yes 2 8.0
No 10 55.6 No 23 92.0
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Abbreviation: ICU, intensive care unit.

Analysis of the definition

The proposed definition of the diagnosis was approved with a CVI of 0.84 with a 95% CI (0.787–0.899). Different recommendations proposed by the experts were considered, resulting in the following definition: “Impairment of physical, psychological and social dimensions as a consequence of prescribed or unavoidable immobility and inactivity, leading to health-compromising complication or disabilities.”

Analysis of the clinical indicators

Twenty-five DCs were analyzed. According to the criteria for the respective validation, 12 DCs were validated and were found to be between 0.80 and 0.87 (Table 2). The other clinical indicators had a CVI between 0.67 and 0.79. According to the experts’ comments, the non-validated clinical indicators are directly related to situations associated with adult critical illness. Furthermore, the experts stressed the importance of validating all diagnostic indicators at the clinical level regardless of the context in which the patient is encountered. On the basis of the individual CVI analysis of the 12 validated DCs for the proposed ND, an overall CVI of 0.82 was obtained, showing that these elements are representative of the phenomenon under study.

Table 2.

CVI of the clinical indicator of the proposed diagnosis.

Shapiro–Wilk test IVC
Clinical indicators or DCs W p-value Medium Media 95% CI
DC1. Impaired bed mobility 0.670 <0.001 1.00 0.85 0.773 0.924
DC2. Impaired physical mobility 0.660 <0.001 1.00 0.87 0.793 0.928
DC3. Adult fall risk 0.769 <0.001 1.00 0.77 0.683 0.863
DC4. Decreased cardiac output 0.846 <0.001 0.75 0.72 0.637 0.805
DC5. Ineffective breathing pattern 0.828 <0.001 0.75 0.74 0.653 0.824
DC6. Ineffective airway clearance 0.784 <0.001 0.75 0.74 0.639 0.838
DC7. Aspiration risk 0.753 <0.001 0.75 0.77 0.685 0.862
DC8. Risk of thrombosis 0.648 <0.001 1.00 0.83 0.743 0.920
DC9. Constipation 0.705 <0.001 1.00 0.81 0.730 0.898
DC10. Dysfunctional gastrointestinal motility 0.714 <0.001 1.00 0.81 0.721 0.895
DC11. Impaired urinary elimination 0.823 <0.001 0.75 0.75 0.663 0.823
DC12. Risk of electrolyte imbalance 0.884 <0.001 0.75 0.67 0.583 0.754
DC13. Risk of unstable blood glucose levels 0.876 <0.001 0.75 0.68 0.592 0.768
DC14. Risk of metabolic syndrome 0.860 <0.001 0.75 0.70 0.610 0.786
DC15. Acute confusion 0.762 <0.001 0.75 0.79 0.700 0.870
DC16. Risk of peripheral neurovascular dysfunction 0.779 <0.001 0.75 0.80 0.721 0.872
DC17. Risk of ineffective thermoregulation 0.860 <0.001 0.75 0.70 0.617 0.790
DC18. Sleep pattern disorder 0.797 <0.001 0.75 0.76 0.678 0.845
DC19. Ineffective protection 0.692 <0.001 1.00 0.82 0.742 0.897
DC20. Risk of infection 0.786 <0.001 0.75 0.76 0.674 0.849
DC21. Adult pressure injury 0.689 <0.001 1.00 0.80 0.710 0.895
DC22. Impaired skin integrity 0.702 <0.001 1.00 0.80 0.704 0.889
DC23. Deterioration of tissue integrity 0.723 <0.001 1.00 0.80 0.702 0.879
DC24. Impairment of mood regulation 0.751 <0.001 0.75 0.80 0.716 0.866
DC25. Impaired social interaction 0.757 <0.001 1.00 0.80 0.709 0.873
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Note: DCs that were between 0.80 and 0.87 were validated (see bold and italics).

Abbreviations: CI, confidence interval; CVI, content validity index; DCs, defining characteristics.

Analysis of the etiological factors

According to the diagnostic approach, eight RFs were assessed by the experts. The experts validated three etiological factors, ranging from 0.80 to 0.88 (Table 3).

Table 3.

CVI of related factors of the diagnosis.

Shapiro–Wilk test IVC
Etiological factors or RFs W p-value Medium Media 95% CI
RF1. Immobility 0.596 <0.001 1.00 0.88 0.806 0.950
RF2. Chronic pain 0.797 <0.001 0.750 0.76 0.678 0.845
RF3. Nutritional deficits 0.795 <0.001 0.750 0.78 0.698 0.860
RF4. Isolation 0.824 <0.001 0.750 0.73 0.641 0.812
RF5. Physical inactivity 0.637 <0.001 1.00 0.85 0.768 0.930
RF6. Prescribed rest 0.813 <0.001 0.750 0.75 0.664 0.836
RF7. Physical restraint measures 0.753 <0.001 0.750 0.80 0.724 0.880
RF8. Lack of social support 0.828 <0.001 0.750 0.72 0.627 0.815
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Note: RFs between 0.80 and 0.88 were validated (see bold and italics).

Abbreviations: CI, confidence interval; CVI, content validity index; RF, related factors.

Analysis of risk populations

RPs were assessed for the proposed diagnosis, of which six were validated with a CVI between 0.84 and 0.94 (Table 4). In this section, experts questioned whether including older adults as an at-risk population would lead to the modification of axis 5 (age) in the diagnostic label. However, the clarification was made that although age was stipulated in the label, the NANDA taxonomy of diagnoses allows for including other age populations without modifying the diagnostic label.

Table 4.

CVI of risk populations of the diagnosis.

Shapiro–Wilk test IVC
Risk populations W p-value Medium Media 95% CI
RP1. Older adults 0.403 <0.001 1.00 0.94 0.880 0.403
RP2. People with a history of cognitive impairment 0.621 <0.001 1.00 0.88 0.820 0.947
RP3. Persons with a history of sensory deficit 0.696 <0.001 1.00 0.86 0.799 0.922
RP4. People in a situation of abandonment 0.786 <0.001 0.750 0.79 0.718 0.864
RP5. People with prolonged hospitalization 0.661 <0.001 1.00 0.90 0.856 0.946
RP6. People in intensive care units 0.527 <0.001 1.00 0.94 0.895 0.977
RP7. People in long-stay homes 0.731 <0.001 1.00 0.84 0.786 0.912
RP8. Persons receiving home care 0.826 <0.001 0.750 0.76 0.684 0.828
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Note: RPs between 0.84 and 0.94 were validated (see bold italics).

Abbreviations: CI, confidence interval; CVI, content validity index; RP, risk population.

Analysis of the associated conditions

A total of 11 of the 14 ACs proposed for validation by the experts met the criteria, with a CVI between 0.82 and 0.93 (Table 5). According to the experts’ comments, concepts, such as psychiatric illnesses and endocrine problems, are comprehensive; they, therefore, consider that they should be revised.

Table 5.

CVI of associated conditions of the diagnosis.

Shapiro–Wilk test IVC
Associated conditions W p-value Medium Media 95% CI
AC1. Obesity 0.721 <0.001 1.00 0.82 0.742 0.897
AC2. Depression 0.721 <0.001 1.00 0.83 0.765 0.898
AC3. Extensive surgical procedures 0.667 <0.001 1.00 0.88 0.827 0.940
AC4. Severe coronavirus disease 0.821 <0.001 0.750 0.76 0.681 0.842
AC5. Stroke 0.627 <0.001 1.00 0.90 0.859 0.955
AC6. Parkinson 0.777 <0.001 0.750 0.82 0.774 0.877
AC7. Severe burns 0.605 <0.001 1.00 0.91 0.866 0.960
AC8. Critical illness 0.555 <0.001 1.00 0.93 0.888 0.972
AC9. Advanced chronic disease 0.649 <0.001 1.00 0.90 0.866 0.948
AC10. Severe trauma 0.604 <0.001 1.00 0.90 0.857 0.957
AC11. Neurological deficits 0.553 <0.001 1.00 0.93 0.898 0.974
AC12. Psychiatric illnesses 0.794 <0.001 0.750 0.79 0.730 0.851
AC13. Neuromuscular disorders 0.639 <0.001 1.00 0.90 0.842 0.949
AC14. Endocrine problems 0.846 <0.001 0.750 0.74 0.676 0.812
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Note: ACs that were between 0.82 and 0.93 were validated (see bold and italics).

Abbreviations: AC, associated condition; CI, confidence interval; CVI, content validity index.

DISCUSSION

The aim of this study was to validate the content of the proposal of ND “Adult Disuse Syndrome” (Ardila-Suárez & Escalada-Hernández, 2023) and its components. To this end, a panel of 43 expert nurses with 2 profiles was consulted: academic, with extensive knowledge of nursing methodology, and clinical, with experience in the care of critical patients, with a high prevalence of the phenomenon studied, applying the diagnostic validation method of Fehring (1987) and Sparks and Lien-Gieschen (1994). The proposed diagnosis, its definition, 12 DCs, 3 RFs, 6 RPs, and 11 ACs were validated. The experts in this process provided suggestions that contributed to improve the decision and other components of the diagnosis. In this way, the LOE on which the diagnostic proposal under study is based has been increased, advancing the study of syndrome-type nursing diagnoses and serving as a tool for the care of patients affected by disuse.

Currently, research on content validation for ND is booming, especially for real or problem-focused nursing diagnoses, both on those already existing in the current versions of the taxonomy (Fontenele-Nascimento et al., 2024; Jordão et al., 2022; Sousa et al., 2019) and on proposals for new ND (Araújo et al., 2024; Eshghi et al., 2023). Regarding syndrome-type diagnoses, research validating new proposals has been identified (Silva et al., 2021). However, no research has been identified so far that validates the content of syndromic diagnoses found in NANDA-I.

In terms of the proposed methodological design, Fehring's content validation model is one of the methods used to obtain expert opinion in research on nursing diagnoses (Gonçalves et al., 2021). Recent content validation studies continue to be carried out using this methodology (Eshghi et al., 2023; Escalada-Hernández & Marín Fernández, 2021), as this is the one traditionally applied in this field. However, in recent years, some studies using this method have combined it with other statistical analyses (Gonçalves et al., 2021), and other content validation studies (Fontenele-Nascimento et al., 2024; Mendes et al., 2021; Manzoli et al., 2020) have applied the Wisdom of Collectives’ methodology proposed by de Oliveira Lopes et al. (2013).

In this study, the research team identified two profiles of experts, either with academic and research training or with clinical experience. According to Gazos et al. (2020), content validation studies using Fehring's approach have been adapted to the profiles of the experts, including those with clinical experience, research experience, and knowledge of NANDA-I taxonomy, which increases rigor and allows for a greater variety of opinions.

The expert analysis validated 12 DCs, all of which are ND included in the NANDA-I taxonomy (Herdman et al., 2020). Among the validated DCs, “Pressure injury in the adult 00312” has a LOE of 3.4: well-designed clinical studies with random samples of sufficient size for population generalization. Among the RFs for this diagnosis is “Factors identified using a standardised and validated rating scale” (Herdman et al., 2020). In this regard, recent nursing studies show that the Braden scale (Fu et al., 2023) remains one of the most widely used for predicting pressure injuries.

Continuing with the DCs, three of the validated have LOE 3.2: Clinical studies related to the diagnosis but not generalizable to the population, namely: “Ineffective protection (00043),” “Impaired skin integrity (00046),” and “Impaired tissue integrity (00044).” Despite having already been revised in the latest versions of the taxonomy, research is ongoing in order to update this type of diagnosis at a conceptual level, especially the impairment of skin and tissue integrity (Arantón-Areosa & Rumbo-Prieto, 2023). A DC with LOE 3.1: Literature synthesis was also validated; this is, “Constipation”; however, recent studies can be found where this concept has been validated for implementing scales in different contexts (Xiaoxiao et al., 2021).

Most of the DCs validated in this research have LOE 2.1: Label, definition, DCs, RFs or risk factors and bibliographic references. These nursing diagnoses, therefore, require studies that allow for an increase in their LOE. In this sense, the DC “Impairment of physical mobility (00085)” has been validated in polytraumatized patients (Ferreira & Duran, 2019), and among its RFs are the prevalence of pain, disuse, and activity intolerance. Another DC with a causal validation study is the “Risk of thrombosis (00291)” (Hilario et al., 2023), in which immobility is validated as one of the main etiological factors for its occurrence in the 2021–2023 version of NANDA-I (Herdman et al., 2020). Finally, “Risk of peripheral neurovascular dysfunction (00086)” was validated; being a DC with no LOE; this ND has not developed RFs; however, immobility and mechanical compression are among its ACs. Despite not having LOE, it is an ND widely used in care plans (Leandro et al., 2024).

Regarding the RFs validated by experts, Cardoso et al. (2022) mentioned that impaired mobility leads to the development of disuse syndrome, mainly due to decompensation of physiological balance, and is associated with increased morbidity and mortality. In turn, the early identification of clinical signs associated with the development of this syndrome is important, especially to guide interventions by early rehabilitation (Cardoso et al., 2022). Clemente-Suárez et al. (2022) also emphasize the importance of physical activity in preventing the deterioration of organ system functions and maintaining adequate mental health. However, early rehabilitation, especially in critically ill patients, presents barriers such as inadequate multidisciplinary staff, lack of medical prescription for mobilization, inappropriate facilities, patient frailty, and cardiovascular instability (Sumeet et al., 2020). According to Willigen et al. (2020), the rehabilitation of the critically ill patient brings not only physiological but also psychological benefits, both at the level of the patient and his or her family.

These risk populations validated by experts align with current studies from other health disciplines. There is now a large body of evidence for the presence of disuse atrophy in critically ill people (Qin et al., 2022), older adults (Endo et al., 2021), people in prolonged hospitalization (Takahashi et al., 2024), and any other type of population who are bedridden (Cardoso et al., 2022). In terms of ACs, current studies show links between disuse and critical illness (Vanhorebeek et al., 2020), obesity (Li et al., 2023), as well as chronic diseases and neuromuscular disorders (Nunes et al., 2022).

LIMITATIONS

Because the methodological design does not require sample size calculations, it is not possible to determine statistically whether the sample has sufficient power to generalize the data. However, to compensate for this, the CVI was carried out with the modified proposal, allowing only those components above 0.80 to be validated. Although there are currently other methodological designs for content validation with robust statistical tests, the Fehring method is still a traditionally used methodology.

CONCLUSIONS

The findings of the study allow us to establish the validation of the content of the proposed ND “Adult Disuse Syndrome” and its elements, being considered relevant and appropriate by the experts. At the definition level, the changes suggested by the evaluators were made. A total of 12 DCs, 3 RFs, 6 RPs, and 11 ACs were validated. It is recommended that the clinical validation stage be continued in different in-hospital and out-of-hospital contexts to continue advancing in its LOE.

Footnotes

AUTHOR CONTRIBUTIONS: Edinson Fabian Ardila-Suárez contributed to conceptualisation, methodology, analysis and writing original draft. Vanessa Sánchez-Martínez and Paula Escalada-Hernández contributed to conceptualisation, validation and writing—review and editing. The final manuscript was read and approved by all authors.

ACKNOWLEDGMENTS: This study is part of the first author’ doctoral thesis within the Clinical and Community Nursing Doctoral Program (University of Valencia, Spain).

The authors declare no conflicts of interest.

FUNDING INFORMATION: The authors declare they received no funding for this study.

ETHICS STATEMENT: The study approved by the Ethics Committee in Human Research of the University of Valencia in March 2023 with procedure number 2259050.

ORCID iDs: Edinson Fabian Ardila-Suárez, RN, MsC https://orcid.org/0000-0003-0655-3178

Vanessa Sánchez-Martínez, RN, MHN, MsC, PhD https://orcid.org/0000-0001-6097-7655

Paula Escalada-Hernández, RN, MsC, PhD https://orcid.org/0000-0003-2263-156X

SUPPORTING INFORMATION

Additional supporting information can be found online in the SupportingInformation section at the end of this article.

How to cite this article

Ardila-Suárez, E. F., Sánchez-Martínez, V., Escalada-Hernández, P. (2025). Content validation of the nursing diagnosis “Adult Disuse Syndrome”: A quantitative study. International Journal of Nursing Knowledge, 1–8. https://doi.org/10.1111/2047-3095.12507.

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