Attitudes, Knowledge, Self-efficacy, and Behaviors of Nurses in Nutritional Care for Older People
- Conditions
- Nutrition Disorders in Old Age
- Registration Number
- NCT05691595
- Lead Sponsor
- IRCCS Policlinico S. Donato
- Brief Summary
Even if awareness among nurses regarding the importance of nutritional care for older people has increased in recent years, nurses continue to underestimate the necessary approach to prevent malnutrition. Therefore, some authors have argued the critical importance of understanding which factors can influence nurses' caring behaviors during real situations and affect the prevention and management of malnutrition under actual working conditions. Specifically, the relationship between nurses' attitudes, knowledge, and self-efficacy in nutritional care for older people has not been described yet. Understanding these relationships can provide a framework to enhance adequate caring behaviors, mitigating the negative attitudes.
Considering that self-efficacy has been previously theorized in several populations as the mediator of the relationship from knowledge and attitudes to specific behaviors, the investigators hypothesized that knowledge and attitudes in the specific area of nursing nutritional care have moderately positive effects on nursing caring behaviors in nutritional care only through the mediation of nursing self-efficacy.
The study design is a multi-phase, descriptive observational cross-sectional, multicentric study, collecting data using a web-survey.
- Detailed Description
Background and rationale
Malnutrition in older people is still an unsolved issue, affecting from 3.1% among outpatients to 29.4% in rehabilitation/sub-acute settings. To date, empirical evidence shows that malnutrition in older people cause a higher risk of disability and loss of autonomy and increase morbidity and mortality. For this reason, prevention of malnutrition should be a priority of health professionals in the care and cure of older patients, and nurses are in a strategic position to prevent malnutrition in older people because they are the only health professionals who look after the patients 24/24 and 7/7. However, several studies report that the quality of nutritional care is often under the standard in clinical settings, underlining that the major barriers to nutritional care, from the nurses' point of view, were: loneliness in nutritional care, a need for competence in nutritional care, low flexibility in foodservice practices, system failure in nutritional care and the neglect of nutritional care.
In this regard, it is possible to hypothesize several key factors underpinning the nursing nutritional competencies that could influence the quality of nutritional care delivery, such as knowledge, attitudes, and self-efficacy. Indeed, numerous authors have described that a lack of knowledge about the key elements of good nutritional care is fundamental to delivering care with high quality, as lead them to underestimate the consequences of its inadequacy. Literature explained that a lack of knowledge of the important concepts of malnutrition could lead to an underestimation of the phenomenon and to behaviors that do not prevent the onset of malnutrition. Therefore, it is crucial to measure the level of the health professional's knowledge on these matters to implement targeted training, although recent literature reported an improvement in this regard. A further factor that could influence the quality of care is the attitude of nurses toward nutritional care. Indeed, previous evidence identified that the proper screening for malnourished patients and implementing corrective strategies with the multidisciplinary team are essential aspects of the nursing competencies . Unfortunately, literature reports that nurses often have a negative attitude toward nutritional care because they often perceive nutritional care as a secondary responsibility. These negative attitudes can cause underestimating malnutrition, which can remain undetected, increasing the risk of negative health-related outcomes in older adults.
Finally, self-efficacy, defined as the beliefs that people have in their ability to successfully complete complex tasks, can be considered a proxy for nursing job performance, and its perceived level by nurses could influence the quality of nutritional care. In fact, according to Bandura, self-efficacy is a predictor of performance, which can be modified through appropriate educational and motivational interventions, mediating between the level of both knowledge and attitudes with action. In this regard, Dellafiore et al. developed a self-efficacy scale for nurses to assess the nutritional care of older adults to make it possible to measure nurses' self-efficacy in nutritional care (as a proxy assessment of nursing competencies in nutritional care) and, consequently, evaluate its improvement by specific interventions.
Data collection and sample size
The collected data will be sent into an electronic data collector, whose output will be saved as an eCRF file in REDCap. The start and end of the data collection are scheduled for June 2022 and June 2023, respectively.
Thus far, it is known that the correlation between knowledge and attitudes regarding nutritional nursing care is moderately positive (r = 0.410; p\<0.001), while the correlations between knowledge, attitude with self-efficacy, and behaviors are mainly undescribed. As per our hypothesis, knowledge and attitudes with self-efficacy and behaviors might show moderate positive correlations. Thus, the investigators hypothesize that the weakest correlation (out of the total of six in the posited model) could be approximately r = 0.25. According to Hulley et al. (2013), a total sample size required to determine whether a correlation coefficient differs from zero has to meet the following criteria: N = \[(Zα+Zβ)/C\]2 +3; where N is the sample size, α = 0.05/6 (0.0083) considering a Bonferroni correction for performing six tests of hypotheses, and therefore Zα = 2.40, β = 10% and then Zβ = 1.28, C = 0.5 \* ln\[(1 + r)/(1 - r)\] = 0.5\*ln\[(1 + 0.25)/(1 - 0.25)\] = 0.5 \* ln\[1.67\] = 0.5 \* 0.51 = 0.26. Consequently, \[(2.40+1.28)/0.26\]2 +3 = 203. Therefore, 203 nurses should be enrolled to determine whether the correlation coefficients differ from zero.
The data collection will be performed with the following questionnaires in a self-reporting format via web-survey:
* Socio-demographic variables, such as sex (male, female), age (years), and marital status (married, unmarried, other)
* Professional characteristics are: postgraduate education (yes, no), clinical setting (chronic care settings, acute care settings), work experience (years), nutritional care to older adults (routine care, infrequent care)
* Staff Attitudes to Nutritional Nursing Care Geriatric scale (SANN-G scale)
* Knowledge of Malnutrition- Geriatric (KoM-G)
* Self-efficacy Scale for Nursing Nutrition Care (SE-NNC)
Statistical analysis
All the data will be checked using the frequency distribution to assess possible missing, errors or outliers. Descriptive statistics will be used to describe the sample characteristics, where categorical data will be presented as frequencies, and continuous data will be presented as means ± standard deviation (M±SD) for normally distributed variables and as the median and interquartile range (25°-75° percentile) for continues data non-normally distributed. The study of skewness will be used to preliminary assess the normal distribution of the variables, followed by the Kolmogorov-Smirnov test. Missing data will be managed using a pairwise approach. The sample characteristics will be compared between and within groups and using Pearson's χ2 test for dichotomous variables in the univariate analysis or using The Student's t-test (or one-way ANOVA when appropriate) for parametric values.
For the preliminary Aim, the Bartlett's test will be used to assess the correlation matrix's factorability and the Kaiser-Mayer-Olkin (KMO) index will be performed before running an exploratory factor analysis (EFA). EFAs will be performed using robust maximum likelihood parameter estimates (MLR) in the case of non-normally distributed items or robust maximum likelihood (ML) in the case of normally-distributed items. A geomin oblique rotation will be used for facilitating the interpretation of the relationships between latent factors and observed variables. The selection of the number of factors to be extracted will be guided by analyzing the eigenvalues, the scree test, the interpretation of the relationships between latent factors and observed variables, and the theoretical domains conceptualized in the items' generation phase.
Structural equation modelings will be run according to the posited hypothesis to investigate the main Aim. The models will be evaluated considering the interpretation of the following indices of fit: the Satorra-Bentler χ2; the comparative fit index (CFI) (values \>0.90 indicated an acceptable fit); the root mean square error of approximation (RMSEA) (values \<0.06 indicated an acceptable fit); the weighted root mean square residual (WRMR; values 1.0 indicated an acceptable fit).
All data will be analyzed using Statistical Package for Social Science version 22 (SPSS, Chicago, IL, USA) and MPLus 8.1, and the level of significance will be set at 0.05 and two-tailed.
Expected results
This study will provide useful information to firstly understand and determine the relationship between attitudes, knowledge, self-efficacy, and behaviors of nurses in nutritional care for older people. So far, this topic has been under-investigated, and this study will provide helpful information to answer a gap in knowledge.
Data management
All data collected anonymously through the web-survey will be processed following current legislation (European Regulation 2016/679, Legislative Decree 101/2018) and the GCP, respecting the participating subjects' privacy. The data will be automatically entered into an online binder after each patient completes the questionnaire. Once the collection phase is complete, the binder will be extrapolated into an Excel sheet for analysis purposes. The Excel output will also be deposited in REDCap.
Ethical considerations
Prior to the compilation of the web-survey, the informed consent will be obtained online on the same page. The study can be described as anonymous because it is impossible to link any particular sample to a person based on the obtained data. It is not considered necessary to employ a separate written informed permission for this sort of study, according to current legislation (European Regulation 2016/679, Legislative Decree 101/2018), because it would cease to exist the study's confidentiality. On the other hand, it is thought to prioritize properly informing subjects with a clear and understandable presentation webpage that explains the survey's purpose before they complete the online questionnaire.
Recruitment & Eligibility
- Status
- RECRUITING
- Sex
- All
- Target Recruitment
- 203
- to be a nurse;
- aged ≥ 18 years;
- full-time work contract;
- work experience: more than six months of experience in the same ward;
- work experience in nutritional care for older people (people aged 60 years and older).
- not available to participate in the study;
- not compiling the informed consent (via the same web-survey);
- working in critical care settings (e.g., intensive care units, emergency demertments);
- working in outpatient settings.
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method To describe the relationship of attitudes (measured using the SANN-G scale) with knowledge and self-efficacy of nurses in delivering nutritional care for older people June 2022 - December 2023 The attitudes will be measured with the Staff Attitudes to Nutritional Nursing Care Geriatric scale (SANN-G scale). The SANN G scale consists of 18 statements, which the respondent can answer on a five-point Likert scale from 'Strongly Agree' to 'Strongly Disagree'. The SANN-G scale is based on the theory of planned behavior by Ajzen (1991). The original scale investigates the attitudes of nurses to five factors related to nutritional care, identified in the literature as critical for high-quality care. The authors of the original instrument also validated the cut-off for a positive attitude to each factor. The five factors, with their ranges and cut-offs for positive attitudes, are: norms, habits, assessment, intervention, individualization.
To describe the relationship of knowledge (measured using the KoM-G scale) with attitudes and self-efficacy of nurses in delivering nutritional care for older people June 2022 - December 2023 The knowledge will be measured with the Knowledge of Malnutrition- Geriatric (KoM-G), a questionnaire that consists of 19 multiple-choice questions about malnutrition in older people, with six possible answers, one of which is "I don't know". Each of the other five answers can be right or wrong. The question is considered correct if all the answers are correctly marked. A correct answer assigns 6 points; an incorrect answer is 1 point. The score goes from a minimum of 19 points to a maximum of 114 points; no cut-off will be specified). The Italian version of the tool showed good psychometric properties (ICC coefficient for the total scores=0.981; Kuder-Richardson 20 test=0.914).
To describe the relationship of self-efficacy (measured using the SE-NNC scale) with attitudes and knowledge of nurses in delivering nutritional care for older people. June 2022 - December 2023 The self-efficacy of nurses to assess nutritional care will be measured using the self-efficacy scale for nursing nutrition care (SE-NNC). SE-NNC is a self-report tool encompassing 27 items and measuring self-efficacy in boosting knowledge (regarding nutritional care), assessment and evidence utilization, and care delivery. Each domain requires to be computed standardizing the responses in a 0-100 score, where the higher self-efficacy scores indicate greater self-efficacy levels. A total self-efficacy score might be computed. In the validation study, the SE-NNC showed adequate internal consistency for each domain and the overall scale (Cronbach's α ranged from 0.879 to 0.963).
- Secondary Outcome Measures
Name Time Method
Trial Locations
- Locations (2)
ASST Grande Ospedale Metropolitano Niguarda
🇮🇹Milano, Italy
IRCCS Policlinico San Donato
🇮🇹San Donato Milanese, Milan, Italy