Abstract
Background
Ineffective health maintenance behaviors (00292) is an important nursing diagnosis in the context of chronic conditions. However, it is observed that the etiology of this phenomenon is not well defined for this population. For nurses to infer this diagnosis early and, consequently, develop effective care plans, further studies are needed to facilitate the understanding of the factors related to the phenomenon.
Objective
To analyze the factors related to the ineffective health maintenance behaviors nursing diagnosis in people with chronic conditions.
Methods
A systematic review of related factors conducted in Scopus (Elsevier), Web of Science, Science Direct (Elsevier), Medical Literature Analysis and Retrieval System Online (MEDLINE/PubMed), CINAHL with Full Text (EBSCO), EMBASE (Elsevier) and Google Scholar. The last access date in the data sources was August 31, 2023. For the critical assessment of eligible studies, the checklists for quantitative studies from the JBI Manual for Evidence Synthesis were adopted. PROSPERO: CRD42022378870.
Results
A total of 21 studies were included and 18 related factors were retrieved. Regarding study characterization, the majority were published in 2022 (33.3 %), North America was the continent with the highest number of studies (42.8 %) and 85.7 % of studies were cross-sectional. Cardiovascular diseases was the most prevalent chronic condition in the studies at 76.1 %. The five main related factors identified were low self-efficacy, individuals with a low level of education, multimorbidity, economically disadvantaged individuals and inadequate health literacy. Of the 18 related factors identified, 11 are not included in the NANDA-International taxonomy classification.
Conclusion
A total of 18 factors related to ineffective health maintenance behaviors in people with chronic conditions were identified in the studies. This study may assist nursing professionals’ clinical practice by providing support in relation to the early detection of the phenomenon through the identification of new related factors.
Keywords: Chronic disease, Causality, Health behavior, Nursing diagnosis, Systematic review
1. Introduction
Chronic conditions led the causes of mortality and premature disabilities in the population [1]. Cardiovascular diseases, diabetes mellitus, cancer and chronic respiratory diseases are the conditions with the highest mortality rates. According to the World Health Organization (WHO), it is estimated that 74 % of all deaths worldwide are caused by chronic conditions [2]. Following a healthy diet, regular physical activity, adherence to pharmacological treatment and health maintenance behaviors are essential factors in preventing and controlling chronic diseases. However, studies note that these strategies do not have good adherence among these individuals, which can lead to complications, such as stroke, acute myocardial infarction, coronary artery disease, kidney disease, diabetic foot and limb amputation [3,4].
Nursing practice is essential for the progression of health indicators through strategies to improve patient therapeutic adherence. To achieve this, nurses must have a clinical judgment about individuals' human responses based on scientific knowledge. Standardized Language Systems (SLP) help organize the nursing process, providing support for clinical reasoning based on scientific evidence [5,6]. Among the SLP, the NANDA-International taxonomy (NANDA-I) stands out, which constitutes an international system for classifying nursing diagnoses. By identifying potential diagnoses presented by patients with chronic conditions, the possibility of designing care plans that are more reliable to patients’ needs increases and, consequently, nursing outcomes can be achieved [7]; [8]. Ineffective health maintenance behaviors (00292) is included in the health promotion domain and the health control class [7]. It is an important diagnosis in the context of chronic conditions, but new studies are needed to facilitate the understanding of related factors in order to be able to assess the diagnosis early. Only one study that explicitly addresses this phenomenon was identified in the literature. Santos et al. [9] addresses nursing diagnoses in adult patients with cardiovascular conditions, where they mention ineffective health maintenance behaviors as a finding.
It is observed that the published studies are more focused on the consequences of a diagnosis. It is expected that the development of this study can contribute to a greater understanding of the etiology of this phenomenon. This helps nursing professionals to act in the prevention of complications and health promotion, focusing on aspects that precede chronic conditions. Related factors are one of the elements that make up the nursing diagnosis, characterized by preceding the development of the phenomenon and leading to increased susceptibility to the diagnosis [7]. Studies addressing this diagnosis are scarce and new studies are recommended to update nursing SLP taxonomies. Considering the above, the present study is justified by the pressing need for research to determine which related factors lead to ineffective health maintenance behaviors (00292) in people with chronic conditions. Thus, the present study aims to analyze the factors related to the nursing diagnosis of ineffective health maintenance behaviors in people with chronic conditions. As subsequent objectives, we seek to characterize a sample of studies identified in the literature and to identify gaps in the existing scientific literature on the topic.
2. Methods
Desing This is a systematic review of etiology and risk developed in accordance with the methodological aspects recommended in Chapter 7 of the JBI Manual for Evidence Synthesis [10]. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) was used to guide the reporting of this study [11].
Protocol and registration Since this study uses secondary data from the public domain, ethics committee approval was not required. The review was guided by a previously developed research protocol, which was submitted to the International Prospective Register of Ongoing Systematic Reviews (PROSPERO) on November 24, 2022. Approval was given on December 5, 2022, with the following registration number: CRD42022378870.
Type of participants The population of interest for this review was people with chronic conditions. For chronic conditions, the four main ones, such as chronic cardiovascular diseases, diabetes mellitus, cancer and chronic respiratory diseases, were considered according to the WHO.
2.1. Eligibility criteria
To conduct the study, the following inclusion criteria were listed: studies that present related factors consistent with behaviors/signs of the diagnosis under study, studies on the identification, definition and association of related factors in people with chronic conditions and studies that identified the ineffective health maintenance behaviors nursing diagnosis. The following exclusion criteria were considered: letters to the editor, editorials, protocols, books, dissertations, theses, review articles and reflection articles, studies not retrieved as full text and that, after assessing the methodological quality, did not obtain sufficient scores to remain in the sample, were excluded. It should be noted that no time frame and language restrictions were carried out to identify the largest number of studies available.
2.2. Information sources
A prior literature review was developed in May 2022 as a precursor to the systematic review, with the aim of surveying what had already been published in the scientific literature. After this process, seven data sources were consulted to select studies for the systematic review, such as Scopus (Elsevier), Web of Science, Science Direct (Elsevier), Medical Literature Analysis and Retrieval System Online (MEDLINE/PubMed), CINAHL with Full Text (EBSCO), EMBASE (Elsevier) and Google Scholar. The last access date in the data sources was August 31, 2023.
Furthermore, a manual search was carried out in the reference lists of studies that were selected for the final sample.
2.3. Search strategy
The PEO mnemonic strategy was considered to develop the review's research question, namely: P (Population); E (Etiology); and O (Outcome) [10]. The elements adopted were P (people with chronic conditions), E (related factors) and O (ineffective health maintenance behaviors). Thus, the following question was delimited: What are the factors related to the ineffective health maintenance behaviors nursing diagnosis in people with chronic conditions? The descriptors were selected using Medical Subject Headings (MeSH). Furthermore, descriptor synonyms were used for greater comprehensiveness of results. The crossing was carried out using the Boolean operators AND and OR, combining descriptors with each other. The same search strategy was used in the seven data sources, being adapted to each source according to its particularities. The descriptors and synonyms used as well as the search strategy are presented in Table 1.
Table 1.
Descriptors and synonyms used according to the PEO strategy for etiology and risk reviews and search strategy applied to data sources.
| PEO strategy | Descriptors | Synonyms |
|---|---|---|
| P: People with chronic conditions |
MeSH “Chronic Disease” |
Not identified |
| E: Related factors |
MeSH “Causality” OR “Etiology” |
“Causalities” OR “Multifactorial causality” OR “Multifactorial causalities” OR “Reinforcing factor” OR “Causation” OR “Causations” |
| O: Ineffective health maintenance behaviors |
MeSH “Health Behavior” |
“Behavior, Health” OR “Behavior, Health-Related” OR “Health Behaviors” |
| Search strategy: ("Chronic Disease") AND (“Causality” OR “Etiology” OR “Causalities” OR “Multifactorial causality” OR “Multifactorial causalities” OR “Reinforcing factor” OR “Causation” OR “Causations”) AND ("Health Behavior” OR "Behavior, Health" OR "Behavior, Health-Related" OR "Health Behaviors") | ||
Selection process For the sampling method of the study, the selection process was carried out in pairs, with active blinding, using the Rayyan – Intelligent Systematic Review software (https://rayyan.ai/). The studies were initially analyzed by dynamic reading of titles and abstracts. Studies that met the eligibility criteria and that reached consensus between the two reviewers were read in full. Disagreements among reviewers were solved by a third reviewer. Studies that did not meet the eligibility criteria were excluded and duplicates were counted only once. The organization of citations and list of references were managed by Mendeley reference manager software (https://www.mendeley.com/).
Data collection process Data collection and mapping was carried out in pairs, independently, in an instrument structured in Microsoft Excel 2019®. At this stage, disagreements among reviewers were decided through consensus.
Data items The instrument was structured with the following items: identification of studies (study title, authors, year, journal, country of publication and language); information about the method (study design, sample size, instruments used for measurement – operational definition and type of chronic condition); and main variables under study (related factors and conceptual definition).
Assessment of risk of bias of studies The checklists for quantitative studies from the JBI Manual for Evidence Synthesis were adopted to assess the methodological quality of studies, according to each type of study present in the final sample, as a critical assessment checklist for cohort, case-control studies, case series, case reports and cross-sectional analytical studies [10].
Thus, two reviewers independently assessed the included studies. A discussion was held for the final assessment of studies and disagreements. Studies were characterized as low risk of bias if they obtained more than 70 % “yes” answers, as moderate risk of bias, if they obtained between 50 % and 69 “yes” answers, and as high risk of bias, if they received less than 49 % of “yes” answers [10]. The final score obtained from the cut-off point and critical analysis regarding the outcome of studies, based on researchers’ opinion, were the criteria that indicated whether or not studies were removed from the sample.
2.4. Data synthesis methods
From the analysis of data collected in Microsoft Excel 2019®, it was possible to tabulate the results of studies. Data were synthesized in charts to allow better visualization of results.
Reporting bias assessment If, during data collection and mapping, a lack of results was identified due to reporting biases that would harm the analysis of review findings, the study would be removed from the sample to minimize the problem.
3. Results
In the previous review carried out, it was possible to retrieve five studies relevant to the systematic review's main interest. During data source selection, 14 studies were included. Furthermore, two studies were identified during the manual search in the reference lists. Thus, 21 studies made up the final review sample. Fig. 1 presents the stages of identification, screening and inclusion of studies.
Fig. 1.
Synthesis of the study selection process according to the PRISMA flowchart.
Regarding the characterization of the studies, the majority were published in 2022 (33.3 %), followed by 2023 and 2020 with 14.2 % each and 2017 and 2014 with 9.5 % each. The years 2021, 2019, 2018 and 2015 were present in 4.7 % of the sample each. North America was the continent with the largest number of studies (42.8 %), followed by Asia with 28.5 % and Europe with 23.8 %. Africa appeared in 4.7 % of the sample.
Regarding the study design, 85.7 % of the studies were cross-sectional, followed by 14.2 % cohort studies. Cardiovascular diseases was the most prevalent chronic condition in the studies, with 76.1 %. Diabetes mellitus was present in 71.4 %, while cancer was present in 38.0 % and chronic respiratory diseases were present in 23.8 %. English was the most common language in the studies (100.0 %) and multidisciplinary journals obtained most studies (69.2 %).
A total of 18 related factors were identified, and the most frequent were low self-efficacy, individuals with a low level of education, multimorbidity, economically disadvantaged individuals and inadequate health literacy. The absolute and relative frequencies of related factors are described in Table 2.
Table 2.
Related factors identified in studies.
| Related factors | N (%) |
|---|---|
| Low self-efficacy | 04 (19.0) |
| Individuals with low level of education | 04 (19.0) |
| Multimorbidity | 03 (14.2) |
| Economically disadvantaged individuals | 03 (14.2) |
| Inadequate health literacy | 02 (9.5) |
| Depressive symptoms | 02 (9.5) |
| Inadequate social support | 02 (9.5) |
| Lack of perceived susceptibility | 02 (9.5) |
| Older adults | 02 (9.5) |
| Limited knowledge about their health condition | 01 (4.7) |
| Inadequate digital health literacy | 01 (4.7) |
| Greater impulsivity | 01 (4.7) |
| Lack of motivation to engage in health-promoting behaviors | 01 (4.7) |
| Spiritual distress | 01 (4.7) |
| Chronic stress | 01 (4.7) |
| Erroneous beliefs about the multifactorial etiology of health conditions | 01 (4.7) |
| Adverse childhood experiences | 01 (4.7) |
| Low satisfaction with life | 01 (4.7) |
Fig. 2 presents a synthesis of results identified in studies according to authors, year, country, study design, quality (JBI), type of chronic condition and related factors. The factors were coded as F1, F2, F3, F4, F5, F6, F7, F8, F9, F10, F11, F12, F13, F14, F15, F16, F17 and F18, and their descriptions are in the caption of the chart as follows.
Fig. 2.
Synthesis of studies identified in the systematic review.
Caption: (FR1) Multimorbidity, (FR2) Economically disadvantaged individuals, (FR3) Limited knowledge about their health condition, (FR4) Inadequate social support, (FR5) Depressive symptoms, (FR6) Inadequate health literacy, (FR7) Inadequate digital health literacy, (FR8) Greater impulsivity, (FR9) Low self-efficacy, (FR10) Lack of motivation to engage in health-promoting behaviors, (FR11) Lack of perceived susceptibility, (FR12) Spiritual distress, (FR13) Older adults, (FR14) Individuals with low level of education, (FR15) Chronic stress, (FR16) Erroneous beliefs about the multifactorial etiology of health conditions, (FR17) Adverse childhood experiences, (FR18) Low satisfaction with life.
The related factors were conceptually defined for readers to understand in detail their relationship with ineffective health maintenance behaviors (00292) according to the literature. Moreover, the operational definitions, i.e., the instruments used to measure the factor, were also presented (Fig. 3).
Fig. 3.
Conceptual and operational definitions of related factors.
Source: prepared by the authors.
Of the 18 related factors identified, 11 are not included in the NANDA-I taxonomy classification, such as individuals with a low level of education, multimorbidity, inadequate health literacy, limited knowledge about their health condition, lack of perceived susceptibility, literacy inadequate digital health, greater impulsivity, lack of motivation to engage in health-promoting behaviors, chronic stress, erroneous beliefs about the multifactorial etiology of health conditions and low satisfaction with life.
4. Discussion
To accurately diagnose a phenomenon, it is essential that nurses know the key concepts of nursing diagnoses [7]. The development of this review made it possible to understand a theoretical gradient, through the identification of 21 studies, which determined the related factors of ineffective health maintenance behaviors (00292) in people with chronic conditions, as well as their conceptual and operational definitions. Among the 18 related factors identified, low self-efficacy, individuals with low education and multimorbidity prevailed in the sample.
Even though no time frame was used in the study search and selection process, it was found that most studies included in this review were published in the last five years, with emphasis on the year 2022. This demonstrates the relevance of the topic today and presents new evidence for NANDA-I taxonomy updates.
In scientific literature, a study analyzed the phenomenon of ineffective health maintenance in patients with diabetes mellitus and patients living with HIV [[12], [13]]. In the present study, cardiovascular diseases were more prevalent in the sample compared to other chronic diseases. This may suggest the development of more in-depth studies in this population.
Among the related factors, low self-efficacy was one of the most prevalent factors in the sample. Patients’ low self-efficacy in controlling their chronic condition reflects their low confidence in maintaining active management of health actions [[14], [15], [16], [17]]. A study carried out with diabetic patients linked low self-efficacy to ineffective health behaviors associated with dietary control, blood glucose monitoring, physical activity, foot care and medication adherence [18]. Ineffective health maintenance behaviors (00292) have a high prevalence in people with chronic conditions, being identified in 65 % of patients with stable heart disease [19]. Multimorbidity, i.e., the presence of one or more chronic conditions, can make it difficult to adopt effective health-related behaviors due to limiting symptoms or side effects of medications in use [[20], [21], [22]].
The element of inadequate health literacy is included in the current edition of NANDA-I as a defining characteristic of ineffective health maintenance behaviors (00292). However, studies mentioned it as a related factor, since this element precedes the development of the phenomenon, which leads to increased susceptibility to diagnosis [3,21,23].
A variant of the element, inadequate digital health literacy, was identified in the studies. Corroborating this finding, participants in one study mentioned that when they found information online, they were anxious about the information available about complications of their disease. Furthermore, several individuals mentioned that they contacted their children or grandchildren due to difficulties with technical problems on computers or cell phones [[24], [25]]. Erroneous beliefs about the multifactorial etiology of health conditions were an identified factor. Individuals who believe that a disease is caused solely by genetic factors and cannot be changed may not be motivated to change their health behaviors. On the other hand, people who believe that a disease is caused solely by environmental and behavioral factors and do not consider the possibility of genetic factors may not seek medical attention or undergo appropriate treatment [[26], [27]]. In the same vein, limited knowledge about one's health condition may motivate ineffective health maintenance behaviors (00292). Studies show that patients with diabetes mellitus and/or cardiovascular disease report that they would like to have been better informed about the risk factors and consequences of their condition at the time of diagnosis, so they could have been more aware of the consequences of their lifestyle at that time, avoiding other possible complications [[25], [28], [29]]. Inadequate social support was identified in the study sample [[30], [31]]. Research carried out with patients with diabetes mellitus corroborates the results of this study, where it was observed that inadequate social support, such as a lack of resilience resources and lack of attitudes such as reminders to take medication and change the family's diet, can influence patients' negative behavior [32]. In relation to the lack of perceived susceptibility, it is important that nurses consider the perceived susceptibility when setting goals in relation to making health decisions with patients, as this can help minimize the risk of worsening their health condition in the future long term [33].
The lack of motivation to engage in health-promoting behaviors was described in studies but was not necessarily associated with depressive symptoms [33]. A study shows that individuals who live without identified psychological problems, such as depression or anxiety, may present a lack of motivation only linked to engaging in health-promoting behaviors and being motivated in other areas of life [[28], [34], [35]]. On the other hand, studies show that people with greater impulsivity have greater difficulty adhering to the diet and poor adherence to drug therapy [[36], [37]]. Spiritual distress, depressive symptoms, and low life satisfaction were also cited as factors related to ineffective health maintenance behaviors (00292). Research with patients with chronic conditions confirms this finding, where patients with these factors generally have low optimism, do not have clear health goals defined and feel low confidence in the future and unhappiness in daily health actions, directly impacting the management of their chronic condition and performance of their health behaviors [[3], [34], [38]]. Chronic stress is associated with reduced sleep duration and quality. It is worth mentioning that this factor influences negative health behaviors, just as negative health behaviors reinforce chronic stress, since healthy attitude practice can alleviate stressful situations [[39], [40]]. Social support may be a protective factor against chronic stress [41].
Older adults, individuals with a low level of education, economically disadvantaged individuals, adverse childhood experiences and men were determined in the present review as related factors. However, following the NANDA-I taxonomy structure, it is believed that these elements should be transferred to populations at risk of ineffective health maintenance behaviors (00292), as they cannot be modified nurses independently [[42], [43], [44], [45]].
Of these five populations at risk, individuals with a low level of education are not included in ineffective health maintenance behaviors (00292) in the NANDA-I taxonomy. Individuals with a low level of education was present in a greater number of studies in the review of etiology and risk, demonstrating the evidence of this population at diagnosis.
This finding is in line with other published studies in which individuals with less education were less likely to prioritize long-term health benefits. Furthermore, individuals with less education may not clearly understand what public health campaigns or advice from health professionals represent, demonstrating low health promotion efforts [28].
4.1. Study strengths and limitations
The strengths of this study are related to efforts to minimize possible biases, through a rigorous search strategy and PRISMA checklist use to prepare the report.
The limitations of this study may be related to data sources selected to identify studies, which may have hidden some studies that could have contributed to the findings of this research, in addition to non-inclusion of studies that were not retrieved as full text. Another limitation of the study is related to the sample, which was mostly composed of cross-sectional studies. These studies have low power to establish causal relationships between the variables investigated, which may limit the strength of the evidence found.
4.2. Implications for clinical practice
Considering the findings evidenced in the present study, it was observed that the structure of ineffective health maintenance behaviors (00292) of NANDA-I taxonomy presents inconsistencies in its composition. Therefore, this review can help improve the diagnosis through the inclusion of new related factors and refine nurses’ diagnostic accuracy during their clinical practice with people with chronic conditions.
5. Conclusion
A total of 21 factors related to ineffective health maintenance behaviors (00292) in people with chronic conditions were identified in the studies. This study can support the clinical practice of nursing professionals by aiding the early detection of the phenomenon through the identification of new related factors, along with their conceptual and operational definitions. Such support can contribute to the prevention of chronic diseases and the mitigation of complications when these diseases are already present.
It is suggested that observational studies be carried out to validate the elements identified in this study, thereby completing the validation process of the nursing diagnosis and elevating its level of evidence to 2.3. For future research, expanding the study to encompass different cultural and social contexts would be beneficial, with this study serving as a foundational point. Furthermore, the continuous development of studies is recommended to facilitate the ongoing updating and refinement of nursing taxonomies.
CRediT authorship contribution statement
Ana Clara Dantas: Writing – review & editing, Writing – original draft, Visualization, Validation, Software, Resources, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Barbara Ebilizarda Coutinho Borges: Writing – review & editing, Visualization, Validation, Methodology, Investigation, Formal analysis. Jéssica Naiara de Medeiros Araújo: Writing – review & editing, Visualization, Validation, Supervision, Methodology, Conceptualization. Marcos Venícios de Oliveira Lopes: Writing – review & editing, Visualization, Validation, Supervision, Methodology, Conceptualization. Amanda Barbosa da Silva: Writing – review & editing, Visualization. Allyne Fortes Vitor: Writing – review & editing, Visualization, Validation, Supervision, Project administration, Methodology, Conceptualization.
Data availability
The data that support the findings of this study are available from the corresponding author upon reasonable request.
Funding
This work was carried out with the support of the Coordination for the Improvement of Higher Education Personnel – Brazil (CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior) – Financing Code 001.
Declaration of competing interest
The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Ana Clara Dantas reports financial support was provided by Coordination of Higher Education Personnel Improvement. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Contributor Information
Ana Clara Dantas, Email: anaclaradaantas@yahoo.com.br.
Barbara Ebilizarda Coutinho Borges, Email: barbara_ebilizarda@hotmail.com.
Jéssica Naiara de Medeiros Araújo, Email: jessicanaiarama@gmail.com.
Marcos Venícios de Oliveira Lopes, Email: marcos@ufc.br.
Amanda Barbosa da Silva, Email: amandab641@hotmail.com.
References
- 1.Martins T.C.F., Silva J.H.C.M., Máximo G.C., Guimarães R.M. Transição da morbimortalidade no Brasil: um desafio aos 30 anos de SUS. Ciência Saúde Coletiva. 2021;26(10):4483–4496. doi: 10.1590/1413-812320212610.10852021. [DOI] [PubMed] [Google Scholar]
- 2.World Health Organization . 2019. Global Health Estimates. [Google Scholar]
- 3.Chen L., Gong Y., Yuan L. Health behaviour and its determinants in elderly patients with chronic diseases: evidence from Jiangsu Province, China. BMC Geriatr. 2022;22(1):291. doi: 10.1186/s12877-022-03010-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Tan T.W., Armstrong D.G., Concha-Moore K.C., Marrero D.G., Zhou W., Calhoun E., Chang C., Lo-Ciganic Association between race/ethnicity and the risk of amputation of lower extremities among medicare beneficiaries with diabetic foot ulcers and diabetic foot infections. BMJ Open Diab Res Care. 2020;8 doi: 10.1136/bmjdrc-2020-001328. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Barbosa H.C., Oliveira J.A.Q., Costa J.M., Santos R.P.M., Miranda L.G., Torres H.C., Pagano A.S., Parreiras Martins M.A. Empowerment-oriented strategies to identify behavior change in patients with chronic diseases: an integrative review of the literature. Patient Educ. Counsel. 2021;104(4):689–702. doi: 10.1016/j.pec.2021.01.011. [DOI] [PubMed] [Google Scholar]
- 6.Marcomini E.K., Paula N.V.K., Raimandi D.C. Nursing care systematization: applicability to primary care. Acta Sci. 2020;42(1):1–10. doi: 10.4025/actascihealthsci.v42i1.48465. [DOI] [Google Scholar]
- 7.Herdman T.H., Kamitsuru S., Lopes C.T., editors. Diagnósticos de enfermagem da NANDA-I: Definições e classificação 2021-2023. 12 ed. Artmed; 2021. [Google Scholar]
- 8.Sampaio F.C., Oliveira P.P., Mata L.R.F., Moraes J.T., Fonseca D.F., Vieira V.A.S. Profile of nursing diagnoses in people with hypertension and diabetes. Invest. Educ. Enfermería. 2017;35(2):139–153. doi: 10.17533/udea.iee.v35n2a03. [DOI] [PubMed] [Google Scholar]
- 9.Santos A.C.M., Silva J.K., Albuquerque S.C., Nunes S.S., Santos V.M.F., Costa C.R.B. Nursing diagnosis in adult patients with cardiovascular conditions: an integrative literature review. Rev. Enferm. UFPI. 2022;11(1) doi: 10.26694/reufpi.v11i1.943. [DOI] [Google Scholar]
- 10.Moola S., Munn Z., Tufanaru C., Aromataris E., Sears K., Sfetcu R., Currie M., Lisy K., Qureshi R., Mattis P., Mu P. In: Chapter 7: Systematic Reviews of Etiology and Risk. Aromataris E., Munn Z., editors. JBI Manual for Evidence Synthesis; 2020. [DOI] [Google Scholar]
- 11.Page M.J., McKenzie J.E., Bossuyt P.M., Boutron I., Hoffmann T.C., Mulrow C.D., Shamseer L., Tetzlaff J.M., Aki E.A., Brennan S.E., Chou R., Glanville J., Grimshaw J.M., Hróbjartsson A., Lalu M.M., Li T., Loder E.W., Mayo-Wilson E., McDonald S.…Moher D. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372(71):1–9. doi: 10.1136/bmj.n71. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Dzerounian, J., Pirrie, M., AlShenaiber, L., Angeles, R., Marzanek, F., & Agarwal, G. Health knowledge and self-efficacy to make health behaviour changes: a survey of older adults living in Ontario social housing. BMC Geriatr., 22(1), 473. 10.1186/s12877-022-03116-1. [DOI] [PMC free article] [PubMed]
- 13.Wang B., Xia L., Yu J., Feng Y., Hong J., Wang W. The multiple mediating effects of health literacy and self-care confidence between depression and self-care behaviors in patients with heart failure. Heart Lung. 2020;49(6):842–847. doi: 10.1016/j.hrtlng.2020.09.011. [DOI] [PubMed] [Google Scholar]
- 14.Wainwright K., Romanowich P., Crabtree M.A. Associations between impulsivity and self-care adherence in individuals diagnosed with Type 2 or prediabetes. PLoS One. 2022;17(3) doi: 10.1371/journal.pone.0263961. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Yao J., Wang H., Yin J., Shao D., Guo X., Sun W., Yin X. Factors associated with the utilization of community-based diabetes management care: a cross-sectional study in Shandong Province, China. BMC Health Serv. Res. 2020;20(1):407. doi: 10.1186/s12913-020-05292-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Tharek Z., Ramli A.S., Whitford D.L., Ismail Z., Mohd Zulkifli M., Ahmad Sharoni S.K., Shafie A.A., Jayaraman T. Relationship between self-efficacy, self-care behaviour and glycaemic control among patients with type 2 diabetes mellitus in the Malaysian primary care setting. BMC Fam. Pract. 2018;19(1):39. doi: 10.1186/s12875-018-0725-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Cardoso P.C., Gussatschenko Caballero L., Brasil Ruschel K., Pereira de Moraes M.A., Rabelo da Silva E.R. Profile of the nursing diagnoses in stable heart disease patients. Invest. Educ. Enfermería. 2019;37(2) doi: 10.17533/udea.iee.v37n2e08. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Fanelli S.M., Jonnalagadda S.S., Pisegna J.L., Kelly O.J., Krok-Schoen J.L., Taylor C.A. Poorer diet quality observed among US adults with a greater number of clinical chronic disease risk factors. J Prim Care Community Health. 2020;11 doi: 10.1177/2150132720945898. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Tian W.H., Tien J.J. Health behaviors and health status among middle-aged and older adults with chronic diseases in Taiwan. Int. J. Environ. Res. Publ. Health. 2020;17(19):7196. doi: 10.3390/ijerph17197196. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Zwierczyk U., Sowada C., Duplaga M. Eating choices-the roles of motivation and health literacy: a cross-sectional study. Nutrients. 2022;14(19):4026. doi: 10.3390/nu14194026. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Cramm J.M., Adams S.A., Walters B.H., Tsiachristas A., Bal R., Huijsman R., Rutten-Van Mölken M.P., Nieboer A.P. The role of disease management programs in the health behavior of chronically ill patients. Patient Educ. Counsel. 2014;95(1):137–142. doi: 10.1016/j.pec.2013.12.017. [DOI] [PubMed] [Google Scholar]
- 22.Deol R.M., Thompson L.M., Chun K.M., Chesla C. Managing type 2 diabetes: beliefs and daily practices in first generation Asian Indians in the United States. SAGE Open Nurs. 2022;8 doi: 10.1177/23779608211054814. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Rappaport S.M. Genetic factors are not the major causes of chronic diseases. PLoS One. 2016;11(4) doi: 10.1371/journal.pone.0154387. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Buková A., Chovanová E., Küchelová Z., Junger J., Horbacz A., Majherová M., Duranková S. Association between educational level and physical activity in chronic disease patients of eastern Slovakia. Healthcare (Basel) 2021;9(11):1447. doi: 10.3390/healthcare9111447. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Lindström, M., Pirouzifard, M., & Rosvall, M. Social capital, the miniaturization of community, traditionalism and mortality: A population-based prospective cohort study in southern Sweden. SSM Popul Health, 16, 100956. 10.1016/j.ssmph.2021.100956. [DOI] [PMC free article] [PubMed]
- 26.Park J.W., Howe C.J., Dionne L.A., Scarpaci M.M., Needham B.L., Sims M., et al. Social support, psychosocial risks, and cardiovascular health: using harmonized data from the jackson heart study, mediators of atherosclerosis in South Asians living in America study, and multi-ethnic study of atherosclerosis. SSM Popul Health. 2022;20 doi: 10.1016/j.ssmph.2022.101284. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Mulligan K., McBain H., Lamontagne-Godwin F., Chapman J., Haddad M., Jones J., Flood C., Thomas D., Simpson A. Barriers and enablers of type 2 diabetes self-management in people with severe mental illness. Health Expect. 2017;20(5):1020–1030. doi: 10.1111/hex.12543. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Huang Z., Ho J.S., Ven Yap Q., Chan Y.H., Tan S.Y., Ya N.K.S., Low L.P., Tan H.C., Koh W.P., Chua T.S.J., Yoon S. Patterns of motivators and barriers to heart health behaviors among adults with behavior-modifiable cardiovascular risk factors: a population-based survey in Singapore. PLoS One. 2022;17(1) doi: 10.1371/journal.pone.0262752. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Gómez-Martínez C., Babio N., Júlvez J., Nishi S.K., Fernández-Aranda F., Martínez-González M.Á., Cuenca-Royo A., Fernández R., Jiménez-Murcia S., de la Torre R., Pintó X., Bloemendaal M., Fitó M., Corella D., Arias A., Salas-Salvadó J. Impulsivity is longitudinally associated with healthy and unhealthy dietary patterns in individuals with overweight or obesity and metabolic syndrome within the framework of the PREDIMED-Plus trial. Int. J. Behav. Nutr. Phys. Activ. 2022;19(1):101. doi: 10.1186/s12966-022-01335-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Bellis M.A., Lowey H., Leckenby N., Hughes K., Harrison D. Adverse childhood experiences: retrospective study to determine their impact on adult health behaviours and health outcomes in a UK population. J. Public Health. 2014;36(1):81–91. doi: 10.1093/pubmed/fdt038. [DOI] [PubMed] [Google Scholar]
- 31.Nordberg H., Kroll J.L., Rosenfield D., Chmielewski M., Ritz T. Chronic stress experience, sleep, and physical activity: relations with change in negative affect and acute stress response to a naturalistic stressor. Br. J. Health Psychol. 2022;27(2):449–467. doi: 10.1111/bjhp.12554. [DOI] [PubMed] [Google Scholar]
- 32.Inagaki T.K., Maccormack J.K., Muscatell K.A. Prosocial and positive health behaviors during a period of chronic stress protect socioemotional well-being. Affec Sci. 2022;3:160–167. doi: 10.1007/s42761-021-00095-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Ashley L., Robb K.A., O'Connor D.B., Platt R., Price M., Robinson O., Travis E., Lipscombe L., Ajjan R., Birch R. Increased breast and colorectal cancer risk in type 2 diabetes: awareness among adults with and without diabetes and information provision on diabetes websites. Ann. Behav. Med. 2023;57(5):386–398. doi: 10.1093/abm/kaac068. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Cavalcante T.F., Oliveira L.R., Moreira R.P., Costa E.C., Ferreira J.E.S.M. Ineffective health management in people with type 2 diabetes. Int J Nurs Knowl. 2022;33(1):64–71. doi: 10.1111/2047-3095.12331. [DOI] [PubMed] [Google Scholar]
- 35.Fonseca N.K.O.D., Molle R.D., Costa M.A., Gonçalves F.G., Silva A.C., Rodrigues Y., Price M., Silveira P.P., Manfro G.G. Impulsivity influences food intake in women with generalized anxiety disorder. Braz J Psychiatry. 2020;42(4):382–388. doi: 10.1590/1516-4446-2019-0556. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Hu P., Wang S., Lee J. Socioeconomic gradients of cardiovascular risk factors in China and India: results from the China health and retirement longitudinal study and longitudinal aging study in India. Int. J. Publ. Health. 2017;62(7):763–773. doi: 10.1007/s00038-017-0968-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Hu W., Lu J. Associations of chronic conditions, APOE4 allele, stress factors, and health behaviors with self-rated health. BMC Geriatr. 2015;15:137. doi: 10.1186/s12877-015-0132-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Júnior A.D., Rabêlo P.P.C., Lopes M.V.O., Rodrigues L.D.S., Lopes C.T., Silva R.A.R.D. Clinical validation of the nursing diagnosis "Ineffective health self-management" in people living with HIV. Int J Nurs Knowl. 2023;34(1):13–20. doi: 10.1111/2047-3095.12367. [DOI] [PubMed] [Google Scholar]
- 39.Mira R., Newton T., Sabbah W. Socioeconomic and ethnic inequalities in the progress of multimorbidity and the role of health behaviors. J. Am. Med. Dir. Assoc. 2023;24(6):811–815. doi: 10.1016/j.jamda.2023.01.009. [DOI] [PubMed] [Google Scholar]
- 40.Oates G.R., Jackson B.E., Partridge E.E., Singh K.P., Fouad M.N., Bae S. Sociodemographic patterns of chronic disease: how the mid-south region compares to the rest of the country. Am. J. Prev. Med. 2017;52(1S1):S31–S39. doi: 10.1016/j.amepre.2016.09.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Otten D., Ernst M., Werner A.M., Tibubos A.N., Reiner I., Brahler E., Wiltink J., Michal M., Nagler M., Wild P.S., Munzel T., Koing J., Lackner K.J., Peiffer N., Beutel M.E. Depressive symptoms predict the incidence of common chronic diseases in women and men in a representative community sample. Psychol. Med. 2023;53(9):4172–4180. doi: 10.1017/S0033291722000861. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Riley K.E., Hay J.L., Waters E.A., Biddle C., Schofield E., Li Y., Orom H., Kiviniemi M.T. Lay beliefs about risk: relation to risk behaviors and to probabilistic risk perceptions. J. Behav. Med. 2019;42(6):1062–1072. doi: 10.1007/s10865-019-00036-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Rwegerera G.M., Moshomo T., Gaenamong M., Oyewo T.A., Gollakota S., Rivera Y.P., Masaka A., Godman B., Shimwela M., Habte D. Health-related quality of life and associated factors among patients with diabetes mellitus in Botswana. Alexandria J Med. 2018;54(2):111–118. doi: 10.1016/j.ajme.2017.05.010. [DOI] [Google Scholar]
- 44.Silva L.H.A., Carmona E.V., Beck A.R.M., Lima M.H.M., Araújo E.P. Nursing diagnoses of diabetic patient medical charts: a descriptive study. Online Braz. J. Nurs. 2013;12(1):62–72. [Google Scholar]
- 45.Walters J.A., Cameron-Tucker H., Courtney-Pratt H., Nelson M., Robinson A., Scott J., Turner P., Walters E.H., Wood-Baker R. Supporting health behaviour change in chronic obstructive pulmonary disease with telephone health-mentoring: insights from a qualitative study. BMC Fam. Pract. 2012;13:55. doi: 10.1186/1471-2296-13-55. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.