Nursing research generates evidence that ensures the effectiveness of nursing interventions. The strength of the evidence relies on the quality of the data collection procedure and the validity and reliability of the instruments. In addition, utilizing the results of studies in clinical practice requires consideration of applicability. As such, it is important to determine if the research conclusions can be generalized to the setting and patient demographics of one’s practice. These points are illustrated in the following description of a randomized controlled trial of a nurse-led intervention seeking to enhance patient enrollment in cardiac rehabilitation.
Sample, Demographics, and Study Setting
The sample consisted of 242 patients admitted to a critical care unit and medical ward, the setting being a cardiac specialty hospital in Canada (Cossette et al., 2012). Power analysis was used to derive the sample size. The patients were adults diagnosed with acute coronary syndrome (ACS). Purposive sampling was employed wherein patients with suspected ACS were followed and recruited once the diagnosis was established. Nearly 40% of the sample was aged 65 years or older and more than 90% were male. Three-quarters were employed and more than half had a high school diploma or less. None of the sample had any physical, psychological, or cognitive problems. They were fluent in either English or French. None had attended any rehabilitation programs before. At most 92% drove a car and lived within 50 miles from the site of the cardiac rehabilitation program. Up to a quarter of the sample lived alone, and more than 70% lived in Montreal where the hospital is located.
Data Collection Process and Instrument Used
One of the outcomes investigated by Cossette et al. (2012) was the patients’ illness perceptions measured before and after implementation of the intervention protocol. Baseline data was obtained with participants answering a questionnaire following informed consent. Follow-up measurement was done by telephone after the patient enrolled in the program. Illness perceptions were ascertained using the Moss-Morris Illness Perception Questionnaire Revised (IPQ-R). The tool consisted of 38 items covering the different aspects of illness perception identified in Leventhal’s theory of self-regulation including control over prescribed treatment, negative consequences on daily functioning, and understanding of the illness (Cossette et al., 2012).
Instrument Validity and Reliability
Equivalence reliability was acceptable because the Cronbach’s alpha coefficients ranging from .79 to .89 were above the accepted value of .70 (Cossette et al., 2012). Cronbach’s alpha is a measure of the fit or consistency among the different items in the scale (Devon et al., 2007). Meanwhile, test-retest reliability was established within three weeks. The acceptable interval prior to retest is 2-4 weeks allowing participants to forget their initial responses but not their attitudes and knowledge (Devon et al., 2007). Correlations indicative of instrument stability ranged from .63 to .88, and over time the value was .46 which is acceptable. However, the ideal correlation between test and retest scores is .70 or higher (Devon et al., 2007).
Conclusions
References
Cossette, S., Frasure-Smith, N., Dupuis, J., Juneau, M., & Guertin, M. (2012). Randomized controlled trial of tailored nursing interventions to improve cardiac rehabilitation enrollment. Nursing Research, 61(2), 111-120. doi: 10.1097/NNR.0b013e318240dc6b.
Devon, H.A., Block, M.E., Moyle-Wright, P., Ernst, D.M., Hayden, S.J., Lazzara, D.J., Kostas-Polston, E. (2007). A psychometric toolbox for testing validity and reliability. Journal of Nursing Scholarship, 39(2), 155-164. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/17535316
