Multivariate Outliers: A Conceptual and Practical Overview for the Nurse and Health Researcher

The presence of statistical outliers is a shared concern in research. If ignored or improperly handled, outliers have the potential to distort parameter estimates and possibly compromise the validity of research findings. The purpose of this paper is to provide a conceptual and practical overview of multivariate outliers with a focus on common techniques used to identify and manage multivariate outliers. Specifically, this paper discusses the use of Mahalanobis distance and residual statistics as common multivariate outlier identification techniques. It also discusses the use of leverage and Cook's distance as two common techniques to determine the influence that multivariate outliers may have on statistical models. Finally, this paper discusses techniques that are commonly used to handle influential multivariate outlier cases.

Testing a Model of Delayed Care-Seeking for Acute Myocardial Infarction

A theory-testing approach to the study of delay in seeking treatment for acute myocardial infarction (AMI) was performed using a descriptive design with 135 AMI patients. Participants provided information pertaining to history of AMI, symptom congruence, responses to symptoms, cardiac symptom attribution, and AMI care-seeking delay. Structural equation modeling fit indices suggested that the independent predictors of AMI care-seeking delay were cardiac symptom attribution and emotion-focused coping. History of AMI had a direct relationship with AMI care-seeking delay, but its total effect through symptom attribution and symptom congruence was not significant. The total effect of symptom congruence on AMI care-seeking delay was significant. In conclusion, the study findings highlight the importance of targeting cardiac symptom attribution and emotion-focused coping in interventions that are aimed at reducing AMI care-seeking delay.

Comparing the psychological stress between non-smoking patients and smoking patients who experience abrupt smoking cessation during hospitalization for acute myocardial infarction: a pilot study

BACKGROUND

Stress is an untoward condition in patients with acute myocardial infarction (AMI). Abrupt nicotine withdrawal is associated with increased symptoms of stress. However, little is known about the impact of smoking cessation on the psychological indicators of stress among hospitalized AMI patients.

PURPOSE

In this pilot study we compared the psychological stressors between non-smoking AMI patients and smoking patients who abruptly ceased smoking following admission to the CCU.

METHODS

A cross-sectional survey was piloted on a sample of 57 AMI patients (29 smokers and 28 nonsmokers) on the second day of admission to the CCU. Psychological stress was measured using the Profile of Mood States and the Insomnia Severity Index.

RESULTS

Multivariate analysis of covariance (MANCOVA) suggested that after adjusting for age, smokers experienced significantly higher overall levels of stress than non-smokers (F = 3.13; p = 0.016). Post-hoc analyses suggested that scores of depression (p = 0.033), anxiety (p = 0.007), and anger (p = 0.017) were particularly higher among smokers, as compared to non-smokers. However, the two groups were not different with regard to their scores on fatigue (p = 0.528) and insomnia (p = 0.299).

CONCLUSIONS

Abrupt smoking cessation may expose patients admitted with AMI symptoms to higher levels of psychological stress. Given the potential damaging impact of psychological stressors on the physical outcomes of these patients, these findings demonstrate the need for continued assessment and research related to the management of nicotine withdrawal following AMI.

Comparison of coping responses to symptoms between first-time sufferers and those with a previous history of acute myocardial infarction

BACKGROUND AND OBJECTIVE

Little is known about how experience with a previous acute myocardial infarction (AMI) impacts individuals' reactions to symptoms of a recurrent episode. Thus, the purpose of this study was to compare the use of coping strategies during an acute cardiac event in patients experiencing a first AMI with those experiencing a recurrent AMI.

SUBJECTS AND METHODS

Secondary data analyses were performed to examine differences in the use of coping strategies between individuals with and without a history of AMI. Mann-Whitney U test was performed to compare those with (n = 26) and without (n = 109) a previous AMI with respect to 15 coping strategies, each of which was measured on a 5-point Likert scale.

RESULTS AND CONCLUSIONS

Patients with a history of AMI were more likely to use prescribed medications to deal with their symptoms than were patients who did not have a previous AMI (M = 1.5 and 0.20; median = 2.0 and 0.0, respectively; P < .001). However, patients who had no previous AMI were more likely to respond by taking nonprescription medications (M = 0.90 and 0.60; median = 1.0 and 0.0, respectively; P = .04). The results suggest that patients with and without a history of AMI tend to respond to their symptoms with similar coping strategies. When differences occurred, patients with and without a history of AMI differed only with respect to the type of self-medication choices they made. Implications pertaining to these findings are discussed.

Methodological issues associated with using different cut-off points to categorize outcome variables

Knowledge of the factors that contribute to delay in seeking medical treatment for acute myocardial infarction (AMI) provides the basis for interventions that are intended to facilitate prompt care-seeking behaviour. However, operational definitions of delay time vary across research studies. The use of inconsistent cut-off times to distinguish between delayers and non-delayers is likely to compromise comparability and generalizability of the findings across studies. The purpose of this paper is to examine the impact of inconsistent operationalization of delay, in terms of cut-off times, on the validity of research findings pertaining to identifying its predictors. Secondary data analysis was performed using a sample of 73 patients who had recently experienced out-of-hospital AMI and concluded that their symptoms were related to the heart. Several regression models were built to examine the influence of using different cut-off times (1, 2, 3, 6, and 12 hours, median delay) on the number and nature of predictors ofAMI care-seeking delay. The impact of varying cut-off times on the explained variance, sensitivity, specificity, and predictive values associated with each regression model was examined. The use of different cut-off times produced different sets of independent predictors, which varied in number and nature. The variance explained by the different regression models as well as their classification indices varied. Use of different cut-off times for the definition of delay time led to inconsistent results. Thus, it is recommended that criteria be established among clinicians and researchers with regard to operationally defining care-seeking delay for AMI.

Nurses' roles with families: perceptions of ICU nurses

This descriptive survey examined: (a) differences between nurses' (N=47) perceptions of self-performance and that of their colleagues with regard to their roles with family members of intensive care patients, and (b) the impact of nurses' comfort on their role enactment as it relates to family focused interventions. Participants rated their self-performance higher than that of their colleagues with respect to 15 of the 19 items, suggesting that they think they perform better than their colleagues. The results also showed that nurses' comfort was positively correlated with their role enactment as it pertains to discussing patient prognosis (r=.496; p<.001), explaining patient's equipment (r=.43; p=.003), and discussing the possibility of death with family members (r=.43; p=.003).

Family perceptions of nurses' roles toward family members of critically ill patients: a descriptive study

OBJECTIVES

The purpose of this study was to examine the role of the nurse with families of critically ill patients as perceived by family members and whether meeting family expectations impact family satisfaction.

METHODS

A descriptive design was conducted with 29 family members from a 19-bed intensive care unit. Nonparametric statistics, known for their appropriateness for small samples, were used to examine the research questions.

RESULTS

Overall, the expectations that family members held regarding nurses' roles with families were not different from their perceptions of what nurses actually did (P = .087). Family members were more satisfied with care when nurses' performance either met or exceeded their expectations (P = .046).

CONCLUSION

Nurses did well with regard to meeting family members' expectations. Variations in expectations among family members reflect their diversity and highlight the importance of assessing family needs on a case-by-case basis.

Missing data: an introductory conceptual overview for the novice researcher

Missing data is a common issue in research that, if improperly handled, can lead to inaccurate conclusions about populations. A variety of statistical techniques are available to treat missing data. Some of these are simple while others are conceptually and mathematically complex. The purpose of this paper is to provide the novice researcher with an introductory conceptual overview of the issue of missing data. The authors discuss patterns of missing data, common missing-data handling techniques, and issues associated with missing data. Techniques discussed include listwise deletion, pairwise deletion, case mean substitution, sample mean substitution, group mean substitution, regression imputation, and estimation maximization.

Enhancing health-care research: an interdisciplinary collaborative approach

Many research programs tackle complex problems that cannot be comprehensively investigated by a sole researcher or a research team from a single profession. Interdisciplinary teams can develop a collective mass of common knowledge, broaden the scope of research, and produce more clinically relevant outcomes that are sensitive to the realities of practice. The authors describe the experience of a research team from the perspective of its members. The purposes of the paper are to highlight the benefits of an interdisciplinary collaborative approach to research and to describe the characteristics of a successful team. Some of the benefits discussed include increased research productivity and quality, professional development and mentorship, support and encouragement, expanded resource networks, and bridging of the gap between academia and practice. The authors also discuss the characteristics of a successful research team, associated challenges, and recommendations for enhancing research endeavours through collaboration.

Predicting Nosocomial Bloodstream Infections Using Surrogate Markers of Injury Severity

BACKGROUND

Injury severity indices are numerical scores that are utilized to predict nosocomial bloodstream infections (BSI) in critically ill patients. However, surrogate markers of injury severity (SMIS) may be more clinically meaningful than these commonly used numerical injury severity indices with respect to the control and prevention of nosocomial BSI.

OBJECTIVE

The purpose of this study was to demonstrate the clinical and research implications of using the SMIS in predicting nosocomial BSI.

METHOD

A prospective nonexperimental cohort study was conducted on 361 critically ill trauma patients. Three logistic regression models were examined for their clinical relevance and statistical parsimony. The first model included the Injury Severity Score (ISS) and 5 other independent predictors, and excluded the SMIS. The second model included all study variables. The third model excluded the ISS.

RESULTS

The analysis suggested that number of blood units transfused, number of central venous catheters inserted, and use of chest tube(s) were the SMIS. The ISS was found to be an independent predictor of nosocomial BSI only when the SMIS were not included in the model. The model that included the SMIS and excluded the ISS explained the highest variance in nosocomial BSI and had the best negative predictive value (93%).

DISCUSSION

Clinicians can use knowledge of SMIS to develop interventions that minimize the risk of nosocomial BSI. Hence, the SMIS can serve not only as a prediction tool but also as a way to enhance control and prevention strategies for BSI.

Handling missing data in self-report measures

Self-report measures are extensively used in nursing research. Data derived from such reports can be compromised by the problem of missing data. To help ensure accurate parameter estimates and valid research results, the problem of missing data needs to be appropriately addressed. However, a review of nursing research literature revealed that issues such as the extent and pattern of missingness, and the approach used to handle missing data are seldom reported. The purpose of this article is to provide researchers with a conceptual overview of the issues associated with missing data, procedures used in determining the pattern of missingness, and techniques for handling missing data. The article also highlights the advantages and disadvantages of these techniques, and makes distinctions between data that are missing at the item versus variable levels. Missing data handling techniques addressed in this article include deletion approaches, mean substitution, regression-based imputation, hot-deck imputation, multiple imputation, and maximum likelihood imputation.

Severe acute respiratory syndrome: another challenge for critical care nurses

Severe acute respiratory syndrome (SARS) is a viral disease that may be contracted by exposure to a newly recognized form of the coronavirus. It often manifests through a set of common respiratory symptoms that include fever and nonproductive cough. To date, SARS has no vaccine or definitive treatment. Approximately 20% of SARS patients develop respiratory failure, which requires mechanical ventilation and close cardiopulmonary monitoring. Intensive care unit (ICU) nurses and other healthcare workers who care for SARS patients are at risk of contracting the disease. Thus, it is important that ICU nurses be familiar with the disease and its implications for critical care. This article provides critical care nurses with an update on the first SARS outbreak, its origin, case definition, clinical manifestations, diagnosis, relevant infection control practices, management, and recommendations for the role of ICU nurses in dealing with future outbreaks.