Objectives: This study aims to (i) develop a screening tool for determining distress and supportive care needs of adolescent and young adult cancer patients (AYAs) based on the NCCN's Distress Thermometer and Problem List (DTPL), (ii) evaluate its feasibility, discriminant validity, and test-retest reliability in clinical settings, and (iii) report prevalence of distress and unmet needs.
Method: In the development phase, after translation of the Japanese version of the DTPL (DTPL-J) from English into Japanese and back translation, cognitive debriefing was performed. Items in the problem list were modified to better reflect AYAs' concerns after interviews. The modified items were reviewed and accepted unanimously by healthcare professionals. In the feasibility phase, the DTPL-J for AYAs was used in a clinical setting for 3 months. Descriptive statistics of participants' demographics, selected items, and DT scores were calculated to report prevalence of distress and unmet needs. Response and referral rates to experts were assessed to evaluate feasibility. Some items were compared with patient demographics to assess discriminant validity. Among the patients who responded at least twice, correlations between two consecutive screenings were assessed to evaluate test-retest reliability.
Results: The DTPL-J consisted of 49 items in five categories. Of 251 patients, 232 (92.4%) were provided the DTPL-J and 230 (91.6%) responded. Based on the DT cutoff of ≥4, 69 of 230 patients (30%) had high distress. Anxiety ( = 85, 36.6%) was the most commonly selected item. Primary nurses referred 45 (21.7%) patients to an attending physician or another expert. Referral rates after DTPL-J use were higher than rates before use, but the difference was not statistically significant ( = 0.06). The items compared were consistent with their social background. A positive correlation was observed between two responses for some items.
Significance Of Results: The feasibility, discriminant validity, and test-retest reliability of the tool were suggested.
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