Literature DB >> 27220523

Evaluation of quality of life using a tablet PC-based survey in cancer patients treated with radiotherapy: a multi-institutional prospective randomized crossover comparison of paper and tablet PC-based questionnaires (KROG 12-01).

Haeyoung Kim1, Hee Chul Park2,3, Sang Min Yoon4, Tae Hyun Kim5, Jinsung Kim6, Min Kyu Kang7, Jinhong Jung8, Sang-Won Kim7, Ji Woon Yea7, Sung Ho Park9, Young Suk Park10.   

Abstract

PURPOSE: This study compared a tablet PC questionnaire with a paper method for reliability and patient preferences in the acquisition of patient-reported outcomes (PROs) for patients treated with radiotherapy. By comparing the two modes of PRO administration, we aimed to evaluate the adequacy of using tablet PC questionnaires in future clinical use.
METHODS: Patients were randomized in a crossover study design using two different methods for PRO entry. A group of 89 patients answered a paper questionnaire followed by the tablet PC version, whereas 89 patients in another group completed the tablet PC questionnaire followed by the paper version. Surveys were performed four times per patient throughout the course of the radiotherapy. The Korean versions of the M.D. Anderson Symptom Inventory (MDASI-K) and the Brief Fatigue Inventory (BFI-K) were used. The primary endpoint of our current study was an assessment of patient preference for the survey method. The proportions of patients preferring each mode of questionnaire were evaluated.
RESULTS: The proportion of patients who preferred the tablet PC version, paper form, or who had no preference was 52.2, 22.1, and 25.7 %, respectively. More than half of the patients preferred the tablet PC to the paper version in all four surveys. Age, gender, educational status, prior experience of using a tablet PC, and the order of paper to tablet PC administration did not impact patient preferences. Inter-class correlation coefficients (ICCs) between the modes were 0.92 for MDASI-K and 0.94 for BFI-K and ranged from 0.91 to 0.96 on both instruments during the four surveys.
CONCLUSIONS: A tablet PC-based PRO is an acceptable and reliable method compared with paper-based data collection for Korean patients receiving radiotherapy.

Entities:  

Keywords:  Equivalence; Health-related quality of life; Patient-reported outcomes; Radiotherapy; Tablet PC

Mesh:

Year:  2016        PMID: 27220523     DOI: 10.1007/s00520-016-3280-5

Source DB:  PubMed          Journal:  Support Care Cancer        ISSN: 0941-4355            Impact factor:   3.603


  21 in total

1.  Validation of electronic systems to collect patient-reported outcome (PRO) data-recommendations for clinical trial teams: report of the ISPOR ePRO systems validation good research practices task force.

Authors:  Arthur Zbrozek; Joy Hebert; Gregory Gogates; Rod Thorell; Christopher Dell; Elizabeth Molsen; Gretchen Craig; Kenneth Grice; Scottie Kern; Sheldon Hines
Journal:  Value Health       Date:  2013-06       Impact factor: 5.725

2.  The rapid assessment of fatigue severity in cancer patients: use of the Brief Fatigue Inventory.

Authors:  T R Mendoza; X S Wang; C S Cleeland; M Morrissey; B A Johnson; J K Wendt; S L Huber
Journal:  Cancer       Date:  1999-03-01       Impact factor: 6.860

3.  Improving individual measurement of postoperative pain: the pain trajectory.

Authors:  C Richard Chapman; Gary W Donaldson; Jennifer J Davis; David H Bradshaw
Journal:  J Pain       Date:  2011-01-15       Impact factor: 5.820

4.  Validation study of the korean version of the brief fatigue inventory.

Authors:  Young Ho Yun; Xin Shelley Wang; Jung Suk Lee; Ju Won Roh; Chang Geol Lee; Won Sup Lee; Keun Seok Lee; Soo-Mee Bang; Tito R Mendoza; Charles S Cleeland
Journal:  J Pain Symptom Manage       Date:  2005-02       Impact factor: 3.612

5.  Assessing symptom distress in cancer patients: the M.D. Anderson Symptom Inventory.

Authors:  C S Cleeland; T R Mendoza; X S Wang; C Chou; M T Harle; M Morrissey; M C Engstrom
Journal:  Cancer       Date:  2000-10-01       Impact factor: 6.860

6.  Health-related quality of life and cancer clinical trials.

Authors:  David Osoba
Journal:  Ther Adv Med Oncol       Date:  2011-03       Impact factor: 8.168

7.  Equivalence of electronic and paper-and-pencil administration of patient-reported outcome measures: a meta-analytic review.

Authors:  Chad J Gwaltney; Alan L Shields; Saul Shiffman
Journal:  Value Health       Date:  2008 Mar-Apr       Impact factor: 5.725

Review 8.  Methods and problems in measuring quality of life.

Authors:  D F Cella
Journal:  Support Care Cancer       Date:  1995-01       Impact factor: 3.603

9.  Feasibility and acceptability to patients of a longitudinal system for evaluating cancer-related symptoms and quality of life: pilot study of an e/Tablet data-collection system in academic oncology.

Authors:  Amy P Abernethy; James E Herndon; Jane L Wheeler; Jeannette M Day; Linda Hood; Meenal Patwardhan; Heather Shaw; Herbert Kim Lyerly
Journal:  J Pain Symptom Manage       Date:  2009-04-25       Impact factor: 3.612

Review 10.  The impact of measuring patient-reported outcomes in clinical practice: a systematic review of the literature.

Authors:  J M Valderas; A Kotzeva; M Espallargues; G Guyatt; C E Ferrans; M Y Halyard; D A Revicki; T Symonds; A Parada; J Alonso
Journal:  Qual Life Res       Date:  2008-01-04       Impact factor: 4.147

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  5 in total

1.  Validation of the Chinese version of functional assessment of anorexia-cachexia therapy (FAACT) scale for measuring quality of life in cancer patients with cachexia.

Authors:  Ting Zhou; Kaixiang Yang; Sudip Thapa; Qiang Fu; Yongsheng Jiang; Shiying Yu
Journal:  Support Care Cancer       Date:  2016-11-29       Impact factor: 3.603

2.  Barriers and Enablers to Using a Patient-Facing Electronic Questionnaire: A Qualitative Theoretical Domains Framework Analysis.

Authors:  Janet Yamada; Andrew Kouri; Sarah-Nicole Simard; Stephanie A Segovia; Samir Gupta
Journal:  J Med Internet Res       Date:  2020-10-08       Impact factor: 5.428

3.  Primary Care Pre-Visit Electronic Patient Questionnaire for Asthma: Uptake Analysis and Predictor Modeling.

Authors:  Andrew Kouri; Janet Yamada; Joanna E M Sale; Sharon E Straus; Samir Gupta
Journal:  J Med Internet Res       Date:  2020-09-18       Impact factor: 5.428

4.  Regulation of Quality of Life and Immune Function in Patients with Thyroid Cancer Treated by Deep Learning Technology.

Authors:  Xiandong Fu; Xinxin Yang; Yibo Wang; Nannan Chi; Jianan Yu; Yao Feng
Journal:  Contrast Media Mol Imaging       Date:  2022-08-30       Impact factor: 3.009

5.  eHealth System for Collecting and Utilizing Patient Reported Outcome Measures for Personalized Treatment and Care (PROMPT-Care) Among Cancer Patients: Mixed Methods Approach to Evaluate Feasibility and Acceptability.

Authors:  Afaf Girgis; Ivana Durcinoska; Janelle V Levesque; Martha Gerges; Tiffany Sandell; Anthony Arnold; Geoff P Delaney
Journal:  J Med Internet Res       Date:  2017-10-02       Impact factor: 5.428

  5 in total

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