Specialized nursing terminology for the prevention of falls in the elderly in primary care

Terminología especializada de enfermería para la prevención de caídas en adultos mayores en la atención primaria

ABSTRACT

Objective:

to build a specialized nursing terminology for the prevention of falls in the elderly in primary healthcare, based on the ICNP^®.

Method:

this is a methodological study developed in two stages: (1) identification of relevant terms for the prevention of falls in the elderly in official documents; (2) cross mapping of the identified terms with the terms contained in the ICNP^® Seven-Axis Model, version 2019/2020.

Results:

a total of 13,408 terms was extracted from official documents, which were submitted to manual screening, resulting in the inclusion of 391 relevant terms. Cross mapping revealed 283 constant terms (67.8% with level of equivalence 1; 32.2% with level of equivalence 2) and 108 non-constant terms (88.9% with level of equivalence 5; 6.5% with level of equivalence 4; 4.6% with level of equivalence 3). In the set of constant terms, the terms of the Focus (43.1%), Action (26.1%), and Means (13.1%) axes stood out; in non-constant terms there was a predominance of the Focus (38.0%), Means (23.1%), and Judgment (15.7%) axes.

Conclusion:

we obtained a specialized nursing terminology that will support the development of nursing diagnoses, outcomes, and interventions to contribute to the prevention of falls in the elderly in primary healthcare.

DESCRIPTORS
Nursing; Standardized Nursing Terminology; Classification; Aged; Accidental Falls; Primary Health Care

RESUMEN

Objetivo:

construir una terminología especializada de enfermería para la prevención de caídas en adultos en la atención primaria a la salud, fundamentada en la Clasificación Internacional de la Práctica de Enfermería CIPE^®.

Método:

estudio metodológico desarrollado en dos etapas: (1) identificación de los términos relevantes para la prevención de caídas en adultos mayores en documentos oficiales; (2) mapeo cruzado de los términos identificados con los términos constantes en el Modelo de Siete Ejes de la Clasificación Internacional de la Práctica de Enfermería CIPE^® versión 2019/2020.

Resultados:

se obtuvieron 13.408 términos de los documentos oficiales, los cuales fueron sometidos al triaje manual lo que resultó la inclusión de 391 términos relevantes. El mapeo cruzado reveló 283 términos constantes (67,8% con grado de equivalencia 1; 32,2 % con grado de equivalencia 2) y 108 términos no constantes (88,9% con grado de equivalencia 5; 6,5% con grado de equivalencia 4; 4,6% con grado de equivalencia 3). En el conjunto de términos constantes se destacaron términos de los ejes Enfoque (43,1%), Acción (26,1%) y Medio (13,1%); en los términos no constantes hubo predominancia de los ejes Foco (38,0%), Medio (23,1%) y Juicio (15,7%).

Conclusión:

Se pudo obtener una terminología especializada de enfermería que irá fundamentar la elaboración de diagnósticos, resultados e intervenciones de enfermería para contribuir en la prevención de caídas en adultos mayores en la atención primaria a la salud.

DESCRIPTORES
Enfermería; Terminología Normalizada de Enfermería; Clasificación; Anciano; Accidentes por Caídas; Atención Primaria de Salud

RESUMO

Objetivo:

construir uma terminologia especializada de enfermagem para a prevenção de quedas em idosos na atenção primária à saúde, fundamentada na CIPE^®.

Método:

estudo metodológico desenvolvido em duas etapas: (1) identificação dos termos relevantes para a prevenção de quedas em idosos em documentos oficiais; (2) mapeamento cruzado dos termos identificados com os termos constantes no Modelo de Sete Eixos da CIPE^® versão 2019/2020.

Resultados:

foram extraídos 13.408 termos dos documentos oficiais, os quais foram submetidos à triagem manual resultando na inclusão de 391 termos relevantes. O mapeamento cruzado revelou 283 termos constantes (67,8% com grau de equivalência 1; 32,2% com grau de equivalência 2) e 108 termos não constantes (88,9% com grau de equivalência 5; 6,5% com grau de equivalência 4; 4,6% com grau de equivalência 3). No conjunto de termos constantes destacaram-se termos dos eixos Foco (43,1%), Ação (26,1%) e Meio (13,1%); nos termos não constantes houve predominância dos eixos Foco (38,0%), Meio (23,1%) e Julgamento (15,7%).

Conclusão:

obteve-se uma terminologia especializada de enfermagem que irá fundamentar a elaboração de diagnósticos, resultados e intervenções de enfermagem para contribuir na prevenção de quedas em idosos na atenção primária à saúde.

DESCRITORES
Enfermagem; Terminologia Padronizada em Enfermagem; Classificação; Idoso; Acidentes por Quedas; Atenção Primária à Saúde

INTRODUCTION

In the elderly healthcare settings, one of the phenomena deserving visibility is falls, considered an important public health problem in Brazil and worldwide. Falls consist of events in which the individual inadvertently goes to the ground or to another level below the initial position and have multifactorial causes, involving biological, behavioural, environmental, and socioeconomic risk factors(¹).

Worrying statistics indicate that between 28% and 35% of individuals aged ≥65 years suffer at least one fall episode per year; in those aged ≥70 years, this estimate increases to 32% to 42%(¹). The consequences of falls in this population are varied, such as lacerations, fractures, or traumatic brain injuries, as well as decreased functional capacity, increased risk of subsequent falls and hospitalizations(²).

Thus, the adoption of a comprehensive approach to elderly health is critical, with an emphasis on health promotion and disease prevention, with the work of Primary Health Care (PHC)(³) being highlighted. As members of the health team, nurses contribute to the strengthening of PHC actions and their work is characterized by behaviours centred on comprehensiveness, addressing risk factors and prevention(⁴).

One of the challenges of nursing work is the need to standardize the language in the profession. With this purpose, there are classification systems in nursing, instruments that favour communication among nurses and with other health professionals, the increase of the quality of care, care standardization, and the evaluation of the results of the care provided(⁵).

In this context, the International Classification for Nursing Practice (ICNP^®) is highlighted, the structure of which includes pre-combined nursing diagnoses (ND), nursing outcomes (NO), and nursing interventions (NI), and allows for the elaboration of new statements using the primitive terms contained in the Seven-Axis Model(⁶).

The use of ICNP^® facilitates clinical reasoning and care documentation, increases the visibility of the profession and promotes safety and quality of care. Furthermore, it can be adopted in different scenarios to serve specific populations, priorities, or nursing phenomena(⁷).

It is understood that the ways of thinking about nursing care for the elderly susceptible to falls advance towards a sustained look at practice based on standardized languages. Due to the relevance of falls in the context of aging, it is essential to propose a terminology that guides and improves the work of nurses in PHC, enabling the identification of ND, NO, and NI relevant to the public in question.

It is worth mentioning that ICNP^®-based terminologies are identified in the literature for community elderly(⁸) and other populations/health priorities, such as people with spinal cord injury(⁹) and metabolic syndrome(¹⁰). However, there remains a gap in terms of specialized terminology for the prevention of falls in the elderly in PHC, which can contribute to the recording of elements of nursing practice in this context, as well as favour the generation of care indicators, warranting the development of the present study.

Given the above, the question was: which terms can constitute a specialized nursing terminology guiding the prevention of falls in the elderly in the context of PHC? Therefore, this study aimed to build a specialized nursing terminology, based on the ICNP^®, for the prevention of falls in the elderly in the context of PHC.

METHOD

Design of Study

This is a methodological study, conducted in two stages, in accordance with the Brazilian guidelines for the development of specialized nursing terminologies based on ICNP®(¹¹): (¹) identification of relevant terms for the prevention of falls in elderly people in PHC settings; (²) cross mapping of the identified terms with the primitive terms contained in the ICNP^® Seven-Axis Model, version 2019/2020.

Data Collection

In the first stage, carried out between June and September 2020, the identification of relevant terms for the prevention of falls in the elderly in PHC settings was carried out in official documents about the population of interest to the study. Therefore, a manual search was performed with free terms (synonyms for healthcare for the elderly and for prevention of falls) on official websites, including the World Health Organization, the Pan-American Health Organization, the Ministry of Health and national health departments. The selection of documents was guided by the following inclusion criteria: covering content related to falls in the elderly population, published in Brazil, in Portuguese, and files available in full. The publication period was not delimited. Nine documents(¹,¹²,¹³,¹⁴,¹⁵,¹⁶,¹⁷,¹⁸,¹⁹) were selected, published from 2000 to 2018, with free access, whose themes contemplated healthcare for the elderly and the approach to falls in this population, especially in PHC settings.

Subsequently, the official documents were carefully read for the selection of contents that would form the text corpus for the extraction of terms. We opted for the full inclusion of some(¹,¹³–¹⁴,¹⁸) documents. As for the other sources(¹²,¹⁵–¹⁷,¹⁹), due to their extensions, only the sections addressing content relevant to the population/health priority defined in this research were selected. In all documents, sections with low potential for acquisition of relevant terms, such as the identification of authors, table of contents, and bibliographical references, were excluded.

Aiming at the construction of the text corpus, the basis for terminological analysis, the contents selected in the official documents were compiled in a single Word for Windows^® file, organized in a single paragraph, with no line spacing between documents. The file was saved in PDF format, totalling one hundred pages.

The extraction of terms was performed in an automated way using the software PORONTO(²⁰). Filters for the extraction of “one-word terms” and “sets of words” were selected. The tool broke down the corpus into a list of one-word terms and set of words, indicating the number of repetitions of the terms. The list was exported from the software through an Excel for Windows^® spreadsheet.

Then, the reading and manual screening of one-word term and sets of words was performed, using the consensus validation technique(²¹), in which three study researchers independently classified the terms as included, excluded due to relevance, or excluded due to repetition. The terms excluded due to relevance were those that were not related to the subject of the study; the terms excluded due to repetition were those whose repetition was not identified by PORONTO or terms that appeared both in the singular and in the plural, with the term being kept in the singular form. The frequency of term repetition in the corpus was not used as a determining exclusion criterion, since some important terms for the study theme had few repetitions (e.g.: “Safety” – 14 repetitions; “Mat” – 11 repetitions). Subsequently, the researchers proceeded with the consensus of the terms presenting divergence in the classification, in online meetings, to determine which terms would be included.

The terms classified as included were submitted to the normalization process regarding spelling, inflections of gender, number and degree, as well as standardization with the ICNP^® terms. Adjectives and nouns were normalized preferably in the male gender and singular, and verbs were normalized in the infinitive.

The first step resulted in an Excel for Windows^® spreadsheet with the list of one-word and sets of words terms arranged in alphabetical order.

In the second stage, produced between October and December 2020, the list of terms previously obtained was subjected to cross mapping with the terms of the ICNP^® Seven-Axis Model, using the Access for Windows^® tool. Theoretical and conceptual fundamentals for the mapping of terminologies in the field of nursing were followed, according to the ISO/TR 12300:2016(²²) standard.

Data Analysis and Treatment

To conduct the cross mapping, two spreadsheets were imported into Access for Windows^®: the first with relevant terms for the prevention of falls in elderly people in PHC settings, resulting from the first stage; the second with the primitive terms contained in the ICNP^® Seven-Axis Model, version 2019/2020. This procedure resulted in a list of constant and non-constant terms in the classification.

The terms not included in the ICNP^® were submitted to the analysis of the level of equivalence of the mapping suggested in the ISO/TR 12300:2016 Standard, and classified as: (¹) lexical as well as conceptual equivalence of meaning; (²) equivalence of meaning, but with synonymy; (³) source concept is broader and has less specific meaning than the concept/target term; (⁴) source concept is more restricted and has more specific meaning than the concept/target term; (⁵) no mapping is possible(²²).

After analysing the level of equivalence, the terms evaluated with equivalence 1 and 2 were grouped in the set of constant terms identified in the mapping, being replaced by the equivalent terms of the ICNP^® with their respective classification codes; and the terms evaluated with level of equivalence 3, 4 or 5 remained in the group of non-constant terms, and were classified according to the axes proposed by the combinatorial terminology: Action, Client, Focus, Judgment, Location, Means, and Time.

Ethical Aspects

This methodological research used data from the public domain, thus being exempted from the consideration and approval of the Research Ethics Committee, supported by Resolution No. 510 of the National Health Council, of April 7, 2016.

RESULTS

In the first stage, the text corpus analysis resulted in the automatic extraction of 13,408 terms, of which 5,648 were one-word terms and 7,760 were sets of words. Then, the manual screening of terms relevant to specialized nursing terminology resulted in the inclusion of 391 terms, 276 being one-word terms and 115 sets of words.

As for the frequency of repetition, the one-word- terms and the sets of words included presented from 1 to 966 repetitions. Terms with a repetition frequency greater than or equal to 30 were highlighted in Table 1, in descending order.

Table 1.
One-word and set-of-words terms included with a repetition frequency greater than or equal to 30. Brasília, DF, Brazil, 2021.

Term	F	Term	F	Term	F
Elder	966	Environmental barrier	66	Stairs	39
Fall	449	Osteoporosis	63	Access	38
Health	435	Patient	62	Physician	38
Risk	395	Identifying	60	Dependence	37
Aging	155	Quality of life	60	Promoting	36
Attention	152	Family	56	Group	36
Intervention	135	Walking	56	Sight	36
Pathological process	118	Community	55	Body region	36
Performing	116	Fracture	54	Fall prevention	36
Action	106	Family caregiver	52	Foot	35
Risk factor	91	Participation	51	Adequate	35
Environment	91	Impaired cognition	48	Chair	35
Inserting	86	Medication effect	48	Information processing	34
Status	86	Mobility pattern	48	Fragile	34
Ability	85	Evaluating	47	Effective	33
Balance	85	Using	46	Weight	32
Disability	82	Independence	45	Inadequate	32
Considering	82	Autonomy	43	Fragility	31
Increasing	78	Behaviour	43	Minute	31
Response to treatment	78	Service	42	Collaborating	30
Need	76	Health education service	41	Result	30
Active	76	Chronic	41	Community	30
Injury	74	Maintaining	40
Presenting	70	Exercising	39
Low	66	Clinical pathway	39

• F = absolute frequency.

In the second stage, the previously selected terms (N = 391) were submitted to the cross mapping process with the terms contained in the ICNP^® Seven-Axis Model^®, version 2019/2020, through the Access for Windows^® tool, resulting in a list of constant terms and non-constant terms in the ICNP^®.

Subsequently, the non-constant terms were analysed for the mapping level of equivalence, resulting in 283 constant terms (67.8% with degree of level of 1; 32.2% with level of equivalence 2) and 108 non-constant terms (88.9% with level of equivalence 5; 6.5% with level of equivalence 4; 4.6% with level of equivalence 3) in the ICNP^®.

Of the 283 constant terms, 43.1% are from the Focus axis, 26.1% from the Action axis, 13.1% from the Means axis, 6.4% from the Judgment axis, 5.3% from the Location axis, 3.2% of the Time axis, and 2.8% of the Client axis, as shown in Chart 1. It should be noted that the constant terms were presented with the respective codes assigned by the ICNP^®.

Chart 1.
Terms of specialized nursing language for the prevention of falls in the elderly in Primary Health Care, contained in ICNP^® 2019/2020. Brasilia, Brazil, 2021.

As for the 108 terms not included in the ICNP^®, 38.0% were classified in the Focus axis, 23.1% in the Means axis, 15.7% in the Judgment axis, 13.0% in the Location axis, 5.6% in the Action axis, 3.7% on the Time axis, and 0.9% on the Client axis, as shown in Chart 2.

Chart 2.
Terms of specialized nursing language for the prevention of falls in the elderly in Primary Health Care, non-constant in ICNP^® 2019/2020. Brasilia, Brazil, 2021.

DISCUSSION

The results obtained represent a specialized nursing terminology for the prevention of falls in the elderly in PHC settings. This terminology can be considered an instrument of the nurses’ work process, favouring the documentation of care in a uniform way and the evaluation of results, aspects that help to demonstrate the value of nursing and its contribution to health care(²³).

In the methodological course of this study, cross mapping is highlighted, which is a method for comparing non-standardized data with nursing classification systems, to identify similarities and validate their use in a specific context(²⁴). Therefore, it can be said that this procedure provides an opportunity to update the ICNP^®, as it identifies needs that are not covered or are incomplete in the classification systems.

In this study, cross mapping revealed a significant number of terms constant in the ICNP^®, suggesting that the classification already includes terms that characterize the prevention of falls in the elderly; it also confirms its reliability for inclusion in health information systems and registration of clinical nursing practice, aiming at the scientific and technological development of the profession(⁹).

However, the number of non-constant terms identified deserves attention, reinforcing the importance of this study and indicating the need for continuous ICNP^® updating, with the incorporation of new terms identified in methodological research(²⁵). The inclusion of terms in nursing classifications contributes to the improvement of records, communication consistency, continuity and safety of care, as well as the integration of instruments, information systems, and theoretical models(¹⁰).

As for the analysis of terms, one of the aspects that drew attention was the predominance of the Focus Axis in constant and non-constant terms. This finding can be explained by the nature of this Axis, consisting of terms representing the areas of care that are relevant for nursing and that are the basis for the elaboration of diagnostic statements(²⁶).

With regard to the Focus Axis, in the set of constant terms, terms such as Fall (10007512), Balance (10003110) and Walking (10020886) stood out. Regarding non-constant terms, Environmental Barrier, Risk Factor and Fragility, for instance, emerged. These terms are closely related to the approach of falls in the elderly by professionals in PHC settings, with an emphasis on comprehensive assessment and identification of predisposing factors for falls, including aspects of mobility, functionality, and environmental characteristics(²⁷).

The Action Axis was the second that stood out in constant terms, with Accompanying (10042609), Identifying (10009631), and Promoting (10015801) being some examples. The terms of this Axis already compose the statements of nursing interventions contained in ICNP®(²⁶); therefore, they have the potential to improve the description of nurses’ actions in the prevention of falls in the elderly.

The Means Axis was the third with the highest number of repetitions in constant terms, in which terms such as Nurse (10013333), Fall Prevention (10040187) and Assessment Tool (10002832) appeared. Moreover, it was the second axis with the highest number of appearances in the non-constant terms, with examples such as Educational Action, Matrix Support and Service. Consistency was observed among the terms, covering important aspects of the nurses’ role in preventing falls, such as the use of instruments to identify risk factors and the implementation of educational actions(²⁸).

Still on the Means Axis, it should be noted that terms related to health professionals appeared, such as Nurse (10013333), Physiotherapist (10024003) and Pharmacist (10023992). It should be noted that falls are events with multifactorial causes; therefore, a multidisciplinary approach(²⁹) is essential, which is a characteristic of the work developed in PHC settings.

As for the Judgment Axis, in the constant terms, the terms Effective (10014956), Impaired (10012938), and Risk (10015007) were identified, which are commonly used in the composition of pre-coordinated ICNP^® concepts, proving to be essential in the composition of the proposed terminology. In addition, the Judgment Axis stood out in the grouping of non-constant terms, presenting terms such as Stable, Inadequate, and Slippery, which are related to the prevention of falls in the elderly and can be used by nurses to express their clinical opinions or determinations regarding the focus of nursing practice (represented by the Focus Axis), especially in primary care settings.

A prominence of the Location Axis was observed in non-constant terms, such as Restroom, Household, and Surface. The terms describing environments are essential for the prevention of falls, since in the context of PHC one must look carefully at the environmental risk factors contributing to the occurrence of these accidents, including the home environment(³⁰).

A limitation of this study is the identification of relevant terms having been carried out exclusively in official documents, since scientific articles in the field of knowledge could also increase the text corpus. However, this did not hinder the achievement of the objective, as the analysed documents allowed the identification of terms that certainly represent the topic of interest in the study.

As for advances in the field of nursing/health, the research contributed to bridge a knowledge gap regarding specialized nursing terminology to be incorporated into the practice of nurses working in PHC with the elderly, in the context of preventing falls; and identified a significant number of terms that are not included in the ICNP^® and have the potential to be included in the next versions of the Classification and in health information systems.

CONCLUSION

The research achieved the proposed objective of building a specialized nursing terminology for the prevention of falls in the elderly in PHC settings, based on the ICNP^®, consisting of 391 terms, of which 283 were constant and 108 non-constant terms. The constant terms showed that the ICNP^® already includes terms characterizing the prevention of falls in the elderly; as for non-constant terms, these are relevant to the studied population/health priority; therefore, they have the potential to be included in future versions of that classification.

It should be noted that this terminology will subsidize studies aimed at the elaboration of ND, NO, and NI statements, allowing the structuring of a terminological subset of the ICNP^® to be incorporated into the clinical practice of nurses focused on the prevention of falls in the elderly in PHC settings.

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Publication Dates

• Publication in this collection
  18 Oct 2021
• Date of issue
  2021

History

• Received
  10 June 2021
• Accepted
  31 Aug 2021