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A feasibility study on using tablet personal computers for self‐reported symptom assessment in newly diagnosed lung cancer patients
Author(s) -
Tang Fiona W.K.,
Chan Carmen W.H.,
Choy YinPing,
Loong Herbert H.F.,
Chow Ka Ming,
So Winnie K.W.
Publication year - 2018
Publication title -
international journal of nursing practice
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.62
H-Index - 55
eISSN - 1440-172X
pISSN - 1322-7114
DOI - 10.1111/ijn.12658
Subject(s) - medicine , anxiety , psychological intervention , lung cancer , physical therapy , intervention (counseling) , self assessment , nursing , psychology , psychiatry , pedagogy
Aim The study aimed to assess the feasibility and acceptability of an innovative tablet‐assisted self‐reported symptom assessment among newly diagnosed lung cancer patients. Background Routine symptom assessment for lung cancer patients in a fast‐paced clinical environment is demanding. Mobile health technology offers a potential platform for symptom assessment and paves the way for tailored self‐care intervention. Design A feasibility study using a mixed method design. Method A convenience sample of 10 newly diagnosed lung cancer patients used tablet personal computers to self‐report common symptoms: dyspnoea, fatigue, pain, and anxiety. A nurse reviewed the assessment results and provided tailored educational interventions. Acceptability was evaluated by the Electronic Self‐Report Assessment‐Cancer. Semi‐structured interviews were conducted to explore the patients' perceptions of this symptom assessment method. Data were collected from January to March 2016. Results An Electronic Self‐Report Assessment‐Cancer mean score of 23.5 (SD 2.7) showed moderate acceptance of the assessment method. Participants found this approach user‐friendly and helpful in identifying their symptoms and they gained awareness and better understanding of them. Conclusion Tablet‐assisted symptom assessment is a feasible method that can be further tested in busy clinical settings to assess symptom burden and identify individual needs for tailoring symptom management plans.