Purpose of the Study
The “Detecting Distress” study by O’Connor et al. is based on the significance of the patient distress, as well as the crucial role and positive outcomes of its timely detection. Distress covers a set of issues and is closely connected with poorer physical and psychological standards of living. The well-timed detection of distress might have beneficial impacts as it may lead to early intervention and avoid patients struggling, as well as be advantageous in the financial sector. The following research concerns the oncology field that pursues identifying the pervasiveness of distress in patients with gynecologic cancers, defining specific issues, as well as discussing the medical workers’ perception of distress screening.
Research & Design
The article is based upon the mixed-methods design. Besides, the quantitative data collection on the levels of distress and its problems was applied to examine the issue thoroughly. In addition, the number of qualitative interviews with healthcare professionals was undertaken as well.
Sixty-two women with gynecologic cancer in the pre-admission clinic were involved in the study throughout the six months. The patients were seen before the surgery. The median age was 58 years, and the age group was 25–94 years; the women younger than eighteen years were suspended. The patients were diagnosed with gynecological cancer, including cervical, endometrial, ovarian, uterine, and vulvar diagnoses. They were able to understand and complete the Distress Thermometer (DT) and Problem List (PL) that provide an “ideal way to streamline care” (p. 80). The average time since cancer diagnosis was 2-12 months. The majority of patients had whether high school education, or diploma, certificate, and trade qualification; most were a self-funded retiree. Furthermore, six oncology healthcare professionals (HCPs) were interviewed, including three nurses, two social workers, and one psychotherapist.
As mentioned above, the mixed-methods design was applied in this study. Quantitative data were collected according to the Distress Thermometer (DT) and Problem List (PL) in the intersectoral study. Qualitative interviews were held with healthcare professionals (HCPs). The procedure was conducted the following way: the research officer (RO) visited the patients in the pre-admission clinic and explained to them the research project. Those who were willing to participate signed the form and were required to complete DT and PL. The procedure was followed by a consultation with an oncology nurse. DTs and PLs results were evaluated to select the appropriate intervention treatment method according to distress and psychosocial management guiding principles. By the end of the project, HCPs were additionally interviewed by the trained individual.
The descriptive statistical approach was used to describe the DT scores and the problems detected. Pearson chi-square test for independence and one-way analysis of variance (ANOVA) were applied to study the distinctions between the groups (p. 80). To examine the linkage between the number of problems and distress records, a Pearson product-moment correlation coefficient was used. Qualitative data were analyzed with the help of directed content analysis focusing on the work of distress screening in clinical practice. Moreover, the deductive category application was applied as well; interview questions served as a guide. The study precision was provided by “employing transparency, consistency, neutrality, applicability, and credibility” (p. 81). The study was finalized by the team discussion of emerging themes to reach an agreement.
Some patients were difficult to communicate, and some were missed because of the busy conditions.
Twenty-one patients reached from 0–3 on the DT, 20 participants reached 4–6, and 21 participants reached 7–10 (p. 81). Based on the statistics of the individual problem identified on the PL, there were 207 physical, 53 practical, 24 familial, 147 emotional, and 2 spiritual problems. Pearson chi-square test indicated a crucial linkage between age group (three categories: at the age of 40 years or younger, 41–64 years old, and 65 years or older) and the three different distress score categories (0–3, 4–6, and 7–10) (p. 81). A Pearson product-moment correlation coefficient was applied to identify the correlation between distress scores (continuous) and a number of problems. A positive connection was found between the two variables with high levels of distress related to greater number of problems. Qualitative data highlighted the key topics, such as benefits to patients and staff, challenges faced, and the impact of routine screening on services. To sum up, the increase in overall referrals or referrals to the social work department was not traced, and there was no more need for consulting.
Reading and understanding research literature, specifically in the medical field, is of utmost importance due to its relevance and significance. With that said, such examination of the study provides a better understanding of the discussed issue, its impact and outcomes, and the possible ways to avoid its occurrence. With the help of a statistical approach, one may trace the dissemination and distinction of the specific problem, as well as to monitor the linkage of different groups of patients, which altogether are essential topics needed to be discussed in teamwork.
O’Connor, M., Tanner, P., Miller, L., Watts, K., & Musiello, T. (2017). Detecting distress: introducing routine screening in a gynecological cancer setting. Clinical Journal of Oncology Nursing, 21(1), 79-85. Web.