Sample Case Study on Application of a Health Behavior Theory

Introduction and Overview

People engage in multiple behaviors that significantly affect their health and wellness. Such activities may include physical exercise, smoking, stress mitigation, and diet orientations. Healthcare professionals and promoters need to design the best programs to help patients engage in activities that promote healthy living and reduce related risks. To achieve this, it is critical to apply health behavior theories and models. Application of a health behavior model as portrayed in a chosen study relating to smoking cessation among cardiac patients.

Purpose of the study

For cardiac patients who smoke, cessation is the most effective intervention for increasing prognosis. However, most patients continue to smoke even after hospital admission. Studies have shown that smoking cessation reduces the mortality rates of these patients when compared to all other intervention or treatment mechanisms. Additionally, cardiac patients who quit smoking significantly reduce the risk of future diseases, thus improving their general health and wellness. In the light of this, de Hoog et al. (2016) undertook a study whose purpose was to examine the influence of self-efficacy, action plans, and coping plans on the intention to quit smoking among patients suffering from cardiac complications.

The study applied the social cognitive theory (SCT) to study the health behavior of the selected population. According to the SCT, human behavior can be explained by a three-way reciprocal and dynamic model in which environmental influences, practice, and personal factors interact continuously (Hagger et al., 2016). According to the study, different factors contribute to smoking cessation among cardiac patients. However, this specific study only focused on the social cognitive factors, the reason being that such considerations are the most proximal to bringing about an actual change in behavior. Notably, the study analyzed the post-motivational social-cognitive factors that may facilitate smoking cessation among the identified population. These determinants included self-efficacy, and action and coping plans.

Sample Size

Eight cardiac nursing units in the Netherlands based hospitals took part in the study. For hospitals to be considered in the research, the following criteria needed to be met; the presence of a cardiology ward, willingness to participate, and not currently offering any smoking interventions.  A total of 245 patients took place in the study. Out of the participants considered, 184 completed a telephone follow-up interview, representing a 77% response rate (de Hoog et al.,2016). The follow-up interview was conducted by an external company and took six months after completing the baseline questionnaires.

Description of the Sample

Patients admitted to the cardiology units as a result of heart-related diseases were invited to take part in the study. However, only patients who indicated physical stability and smoked at least five cigarettes a day before admission were included in the study. Before engaging in the research, patients were asked to sign a consent form after receiving information on the procedure and content of the investigation. The nurses administered the baseline questionnaire. Only respondents from the control group were included in the study. The original research was a randomized, controlled trial and consisted of three groups; two receiving intensive smoking cessation counseling and one acting as a control group.

Health Behavior Measurement

Measurement of the health behavior of the participants was two-fold; the baseline questionnaire (t0) and the six months follow-up (t1). At the baseline questionnaire level, 5-point rating scale ranging from 0-4 otherwise stated. Some personality traits such as gender, age, Type D personality and social, economic status (SES) were assessed (de Hoog et al.,2016). All these characteristics affect smoking cessation among cardiac patients.  Social, economic status was based on both income and education level. DS14 was used to measure Type D personality. Smoking behavior was assessed using 7-day prevalence abstinence (PPA).

Self-efficacy to quit smoking was assessed with questions such as ‘will you be able to continue quitting smoking even when stressed’? The Intention to stop was determined using two questions-one touching on the likelihood of continuing to quit smoking and the other relating to the strength of quitting after leaving the hospital. Questions were asked with the intention of assessing the Action and coping plans. Concerning the six-month follow-ups, respondents were asked if they had succeeded in abstaining from smoking, and if affirmative, since when (de Hoog et al.,2016). The quit date was subtracted from the day of the interview to obtain the number of days refrained from smoking. Patients were labeled quitters (CA=1) if smoking abstained from more than five months. In all other cases, patients were regarded as smokers (CA=0).

Research Findings

A total of 245 patients completed the baseline (t0) questionnaire. However, the results of 11 respondents were not considered since 20% of their data was missing. 37% of the respondents had tried to quit smoking previously. Additionally, it was found out that their intention to stop was high (M=3.77). The mean scores on relapse self-efficacy, self-efficacy, coping plans, and making actions were around the middle of the scale. On the six-month follow-ups, it was noted that a total of 31% of the respondents had not smoked in the past five months (de Hoog et al.,2016). 43% of the patients had not smoked in the past seven days.

Correlation analysis between the main variables was done. It was noted that self-efficacy indicated a positive correlation with the other significant variables. The correlation for the relapse self-efficacy was weaker. Action plans had strong relationships with intention. Furthermore, attrition analyses were performed to determine the differences noted in the background features between non-responders and those who responded to the follow-ups. Results indicated that patients who lived with a partner and or children were more likely to complete the follow-up interview. About action and coping plans, no plan was found to be more popular than the other.

The implication for Nursing Practice

This study examined the effects of self-efficacy, action and coping planning on smoking cessation and the intention to quit smoking among cardiac patients. The findings of these study have a significant implication on the nursing profession, especially in the management of related cardiac conditions. Some of the critical impacts of the survey of the practice include the following;

First, the study plays an important role in highlighting the role of patients’ social life in action and coping plans. For instance, the research found out that patients with partners and children portrayed a higher rate of smoking cessation. Healthcare professionals can, therefore, focus on educating patients’ close relatives on the importance of supporting the patients to aid recovery (Smith et al., 2017).

Second, the results of the study can aid health care professionals to predict the intention to quit smoking among patients. This emanates from the consequence of self-efficacy and relapse self-efficacy as seen from the research. For instance, self-efficacy was shown to have a positive effect on smoking cessation.

Third, the study provides an essential guideline concerning intervention planning concerning cardiac patients. In smoking cessation, action planning is crucial. This study has highlighted the need to analyze the importance of considering other factors that may affect the patient’s ability to cope, action, and eventually quit smoking. In all this, nurses will be promoting patient health and well-being.

 

 

References

de Hoog, N., Bolman, C., Berndt, N., Kers, E., Mudde, A., de Vries, H., & Lechner, L. (2016). Smoking cessation in cardiac patients: the influence of action plans, coping plans and self-efficacy on quitting smoking. Health education research31(3), 350-362.

Hagger, M. S., Chan, D. K., Protogerou, C., & Chatzisarantis, N. L. (2016). Using meta-analytic path analysis to test theoretical predictions in health behavior: An illustration based on meta-analyses of the theory of planned behavior. Preventive Medicine89, 154-161.

Smith, A. J., Felix, E. D., Benight, C. C., & Jones, R. T. (2017). Protective factors, coping appraisals, and social barriers predict mental health following community violence: A prospective test of social cognitive theory. Journal of traumatic stress30(3), 245-253.