ArticleQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation2015
Taking into account the impact of attrition on the assessment of response shift and true change: a multigroup structural equation modeling approach.
Article in Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.
- The Role of Response-Shift in Studies Assessing Quality of Life Outcomes Among Cancer Patients: A Systematic Review.Frontiers in oncology · 2019Pooled it
- Postoperative quality of life and therapy-related impairments of oral cancer in relation to time-distance since treatment.Journal of cancer survivorship : research and practice · 2022Article
- Investigation of measurement invariance in longitudinal health-related quality of life in preemptive or previously dialyzed kidney transplant recipients.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2022Article
- Using structural equation modeling to investigate change and response shift in patient-reported outcomes: practical considerations and recommendations.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2021Article
- Advancing quality-of-life research by deepening our understanding of response shift: a unifying theory of appraisal.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2019Article
- Scoping review of response shift methods: current reporting practices and recommendations.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2018Article
- Method variation in the impact of missing data on response shift detection.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2015Article
- Response shift in the presence of missing data.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2015Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeMissing data due to attrition present a challenge for the assessment and interpretation of change and response shift in HRQL outcomes. The objective was to handle such missingness and to assess response shift and 'true change' with the use of an attrition-based multigroup structural equation modeling (SEM) approach.
methodFunctional limitations and health impairments were measured in 1,157 cancer patients, who were treated with palliative radiotherapy for painful bone metastases, before [time (T) 0], every week after treatment (T1 through T12), and then monthly for up to 2 years (T13 through T24). To handle missing data due to attrition, the SEM procedure was extended to a multigroup approach, in which we distinguished three groups: short survival (3-5 measurements), medium survival (6-12 measurements), and long survival (>12 measurements).
resultsAttrition after third, sixth, and 13th measurement occasions was 11, 24, and 41 %, respectively. Results show that patterns of change in functional limitations and health impairments differ between patients with short, medium, or long survival. Moreover, three response-shift effects were detected: recalibration of 'pain' and 'sickness' and reprioritization of 'physical functioning.' If response-shift effects would not have been taken into account, functional limitations and health impairments would generally be underestimated across measurements.
conclusionsThe multigroup SEM approach enables the analysis of data from patients with different patterns of missing data due to attrition. This approach does not only allow for detection of response shift and assessment of true change across measurements, but also allow for detection of differences in response shift and true change across groups of patients with different attrition rates.
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