AI Summary & Key Takeaways
AI InsightStatistical analysis was performed by t-test, one-wayanalysis of variance, Tukey analysis, and Pearson’s correlation coefficient.RESULTSIt was found that 80.1% of the participants were married, 60.8% graduated from primary school, 38.9%were housewives, 62.9% had an average income, 79% had been diagnosed for 6–24 months, 34.3% hadadequate information related to illness, and 81.46% had never taken any psychological help.
📌 3 Key Takeaways
Abstract
OBJECTIVEThe aim of the present study was to evaluate the factors affecting fatigue impact, severity, and anxietylevels in patients with cancer.METHODSData were collected by applying the information form, Beck Anxiety Scale, Fatigue Impact Scale, andFatigue Severity Scale to 286 patients with cancer. Statistical analysis was performed by t-test, one-wayanalysis of variance, Tukey analysis, and Pearson’s correlation coefficient.RESULTSIt was found that 80.1% of the participants were married, 60.8% graduated from primary school, 38.9%were housewives, 62.9% had an average income, 79% had been diagnosed for 6–24 months, 34.3% hadadequate information related to illness, and 81.46% had never taken any psychological help. In the study,it was observed that patients who were in the age group of 65-89 age, illiterate, poor economic status,non-working, and those who think that fatigue and anxiety symptoms are the result of treatment sufferfrom fatigue more severely in their daily live. At the same time, patients who were female, illiterate,tradesmen, had bad economic status, non-working, and with fatigue and anxiety symptoms dependenton treatment had more intense level of fatigue (p