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. 2025 Jun 18;14(12):4356.
doi: 10.3390/jcm14124356.

The Degree of Acceptance of the Disease by Patients After a Diagnosis of Lung Cancer and Their Hope

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The Degree of Acceptance of the Disease by Patients After a Diagnosis of Lung Cancer and Their Hope

Agnieszka Waleczko et al. J Clin Med. .

Abstract

Background/Objectives: The aim of this study was twofold: first, to assess the extent to which patients diagnosed with lung cancer accept their condition and, second, to characterize the profiles and dimensions of the hope experienced by these patients. Methods: In order to achieve the aforementioned goals, the following research tools were utilized: the NCN-36 scale to examine hope, the AIS to ascertain the acceptance of one's condition, and the KI scale to present socio-demographic-temperamental variables. Results: The patients exhibited an average level of acceptance of their disease while simultaneously demonstrating a high level of hope. Cluster analysis identified four groups of patients that differed significantly in terms of disease acceptance and felt hope (p < 0.001). Significantly higher acceptance of the disease was found in urban patients (p = 0.038) and those with higher education (p = 0.011), while lower acceptance was noted in those aged over 75 (p = 0.006). In turn, the experienced hope was influenced by variables such as age, place of residence, education, housing situation (living alone or with family), overall pace of activity, basic mood, and social and professional status. Conclusions: The researchers identified four distinct attitudes among the patients based on their disease-related experiences. These attitudes were categorized as follows: non-accepting-fearful, indifferent-desperate, non-accepting-fighting, and accepting-trusting.

Keywords: attitudes and acceptance of the disease; diagnosis; hope; lung cancer.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
The cluster analysis of the results of the AIS and the NCN-36 test (standardized data and medians).

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