Over the past few decades, health care administration has achieved significant progress in ensuring a smooth and risk-free life for the patients. There are various nursing approaches identified to date in this regard that focus on evaluating the quality of life (QOL) following a major health problem. The present description is concerned with an article in a similar context.
Generally, patients may encounter mental distress during their stay in the hospitals. Some would be longing for a speedy recovery or others would be aspiring for a life that is filled with achievements. It is timely that appropriate intervention programs are recommended to evaluate such situations and overcome inadequacy in that area. So, this issue might have appeared as the driving force or motivation in prompting the researchers to conduct a study on ‘Modeling Women’s Quality of Life After Cardiac Events’.
Here, the main objective was to examine the impact of perceived health status, dispositional optimism, and hopefulness on subjective QOL in women following an acute cardiac event. The research question was whether or not the employed indicators are reliable in determining the QOL from the patient perspective.
According to this article, there is still ambiguity over the characterization and execution of planned treatments. Therefore, a study was designed by selecting 93 women participants who had suffered an acute cardiac event during admission in two hospitals in west-central Florida.
The investigators considered the criteria that recommend the selection of only those suffering from a myocardial infarction (MI), unstable angina, or undergoing surgery for coronary revascularization (CABG); valve replacement or a percutaneous coronary intervention (PCI), oriented to time, place, and person; able to read, write, and speak English; and willingness to participate in the study. After obtaining the informed consent, QOL instruments such as the SF-36 Health Survey, the hearth hope index (HHI), and the Life Orientation Test (LOT) were administered.
The study participants were initially measured by the QOL’s Life 3 Scale to ask respondents to evaluate their life as a whole on a Terrible-Delighted Scale. The Faces Scale elicits QOL assessments without verbal labels for the scale categories. Here, seven faces with expressions ranging from very positive to very negative would be shown to the respondent who selects the face that most closely expresses how they feel about their life as a whole; and the Self-Anchoring Striving Scale (SASS) depicted as a 10-step ladder that uses only numbers as descriptors of the rungs of the ladder. The participants were asked to indicate where on the ladder they would place themselves presently in terms of their life satisfaction, like, “best possible life imaginable,” and the “worst possible life”.
Next, the SF-36 Health Survey measurement for perceived health is comprised of 36 questions that measure eight concepts. They are physical functioning (PF), role functioning–physical problems (RP), bodily pain (BP), general health perceptions (GH), vitality (VT), social functioning (SF), role functioning–emotional problems (RE), and mental health (MH). The Herth Hope Scale (HHS) was designed to measure a global, non-time-oriented sense of hope and the HHI was used to assess the level of hope. Finally, the patients measured by the LOT, a 10-item self-report measure, were asked to indicate their degree of agreement with statements such as “In uncertain times, I usually expect the best,” using a 5-point response scale ranging from 0 (strongly disagree) to 4 (strongly agree).
The research findings have revealed that there was no statistically significant difference on any of the SF-36 subscales by primary diagnosis. The distribution of the QOL, hope, and dispositional optimism indicators was found to display a clustering of cases nearer the more positive end of the scales, with a thinner tail extending off toward the negative values.
Life 3 Scale indicator was not reported to function as the other three measures of QOL.
However, according to the article, QOL measures were consistent with the conceptualization of QOL as a “global personal assessment of a single dimension which may be causally responsive to a variety of other distinct dimensions. Secondly, SF-36 analysis revealed two major orthogonal factors of health such as mental and physical and mental health. In LOT, of the six scored items, three were worded positively and three were worded negatively.
In view of the above information, the article could be evaluated as follows. Firstly, the administration of various measures helped in obtaining only satisfactory data. This may partially address previous ambiguity and confusion in the health care literature regarding the meanings assigned to QOL. The study could have considered a good sample size of men subjects to make the data more sounding and reliable.
In order to improve QOL, there is also a need to evaluate the lifestyle which the article did not address. In a recent study, it was reported that patients who have undergone CABG, especially female patients older than 60 years would benefit from the increased physical activity. Similarly, male patients older than 50, years would benefit from the dietary education. (Vachenauer et al., 2008). Therefore, these strategies if incorporated in the study may have better implications for the perceived health status of patients and may also facilitate smooth management of advancing coronary heart diseases by nurse care.
The research literature indicates that there is a need for psychosocial constructs not captured by the SF-36 to predict patients’ QOL more effectively. This is a worth fitting description and can be connected to the ‘waiting time’. Earlier workers studied the influence of waiting time on the quality of life of patients awaiting CABG (Sampalis et al., 2001). Their findings revealed that a significant decrease in physical and social functioning, both before and after surgery, for patients waiting more than 3 months for CABG is an important observation. The workers further reported that decreasing waiting times for CABG
may improve patient’s quality of life and decrease the psychological morbidity associated with CABG. This would also support the statement of the present article that ‘researchers must embark on the task of determining factors, both physical and psychosocial, that affect QOL’. Further, it is not clear whether the study has considered the severity of angina as the predictor of QOL in addition to the others; due to narrow literature support.
This is because it was reported that patients with preoperative higher Canadian Cardiovascular Society (CCS) angina class had greater improvement in sections of physical mobility, energy, and pain, thus indicating high CCS angina class before CABG as the independent predictor of quality of life improvement six months after CABG (Peric et al., 2008). Next, the study did not provide clear information on whether their findings were in agreement or disagreement statistically with other populations that could have strengthened their data. Colak et al. (2008) explored the differences in the health-related quality of life (HRQOL) of patients before and after cardiac surgery, and compared the results with norms of the Croatian population, and correlated the results with values of Euro SCORE.
Their findings revealed a statistically significant improvement in half of the domains of physical and mental health compared with the presurgery status of patients one year after hospital discharge. Finally, relying on hope and optimism as the indicators may not be sufficient for patients with poor recovery. This may require another source. Fukoka et al. (2007) described that a technique known as Cluster analysis was useful to identify the patient subgroups, based on cardiac symptoms after cardiac events, with poorer recovery.
In conclusion, the above research findings could strengthen the statement of the present article, that ‘The model made no attempt to explain the sources of, or connections between these concepts… ’. and appear to weaken the research question on the indicators. On the whole, it can be inferred that the article has furnished possible clues to focus on unexplored or unaddressed areas and refine the QOL concept with the health and psychosocial concepts as potential causes or predictors.
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