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Schwartz, Carolyn E.; Rapkin, Bruce D.

doi:10.1186/1477-7525-2-16

Cited by 177 publications

(58 citation statements)

References 30 publications

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“…Comparison to prior research is difficult as this is the first investigation to employ an adjustment for patient recall bias when utilising a then-test approach. However, empirical evidence from this investigation is in line with conceptual models surrounding the response shift phenomenon[7,8]. Results from the then test without adjustment for recall bias reported in this investigation are also congruent with previous investigations of response shift that have not adjusted for recall bias[10,11,13,17].…”

Section: Discussionsupporting

confidence: 89%

Response shift, recall bias and their effect on measuring change in health-related quality of life amongst older hospital patients

McPhail

Haines

2010

Health Qual Life Outcomes

119

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BackgroundAssessments of change in subjective patient reported outcomes such as health-related quality of life (HRQoL) are a key component of many clinical and research evaluations. However, conventional longitudinal evaluation of change may not agree with patient perceived change if patients' understanding of the subjective construct under evaluation changes over time (response shift) or if patients' have inaccurate recollection (recall bias). This study examined whether older adults' perception of change is in agreement with conventional longitudinal evaluation of change in their HRQoL over the duration of their hospital stay. It also investigated this level of agreement after adjusting patient perceived change for recall bias that patients may have experienced.MethodsA prospective longitudinal cohort design nested within a larger randomised controlled trial was implemented. 103 hospitalised older adults participated in this investigation at a tertiary hospital facility. The EQ-5D utility and Visual Analogue Scale (VAS) scores were used to evaluate HRQoL. Participants completed EQ-5D reports as soon as they were medically stable (within three days of admission) then again immediately prior to discharge. Three methods of change score calculation were used (conventional change, patient perceived change and patient perceived change adjusted for recall bias). Agreement was primarily investigated using intraclass correlation coefficients (ICC) and limits of agreement.ResultsOverall 101 (98%) participants completed both admission and discharge assessments. The mean (SD) age was 73.3 (11.2). The median (IQR) length of stay was 38 (20-60) days. For agreement between conventional longitudinal change and patient perceived change: ICCs were 0.34 and 0.40 for EQ-5D utility and VAS respectively. For agreement between conventional longitudinal change and patient perceived change adjusted for recall bias: ICCs were 0.98 and 0.90 respectively. Discrepancy between conventional longitudinal change and patient perceived change was considered clinically meaningful for 84 (83.2%) of participants, after adjusting for recall bias this reduced to 8 (7.9%).ConclusionsAgreement between conventional change and patient perceived change was not strong. A large proportion of this disagreement could be attributed to recall bias. To overcome the invalidating effect of response shift (on conventional change) and recall bias (on patient perceived change) a method of adjusting patient perceived change for recall bias has been described.

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Section: Discussionsupporting

confidence: 89%

Response shift, recall bias and their effect on measuring change in health-related quality of life amongst older hospital patients

McPhail

Haines

2010

Health Qual Life Outcomes

119

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“…The presence of discordance in HLQ scores does not necessarily mean that the patient’s perspective is wrong, nor that the clinician’s perspective is wrong. Rather, their answers may come from different reference points and they may be using different appraisal criteria [27]. To advance the field, provision of training to better detect these differences may assist clinicians to provide improved care.…”

Section: Discussionmentioning

confidence: 99%

The Health Literacy Questionnaire (HLQ) at the patient-clinician interface: a qualitative study of what patients and clinicians mean by their HLQ scores

Hawkins

Gill

Batterham

et al. 2017

BMC Health Serv Res

100

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BackgroundThe Health Literacy Questionnaire (HLQ) has nine scales that each measure an aspect of the multidimensional construct of health literacy. All scales have good psychometric properties. However, it is the interpretations of data within contexts that must be proven valid, not just the psychometric properties of a measurement instrument. The purpose of this study was to establish the extent of concordance and discordance between individual patient and clinician interpretations of HLQ data in the context of complex case management.MethodsSixteen patients with complex needs completed the HLQ and were interviewed to discuss the reasons for their answers. Also, the clinicians of each of these patients completed the HLQ about their patient, and were interviewed to discuss the reasons for their answers. Thematic analysis of HLQ scores and interview data determined the extent of concordance between patient and clinician HLQ responses, and the reasons for discordance.ResultsHighest concordance (80%) between patient and clinician item-response pairs was seen in Scale 1 and highest discordance (56%) was seen in Scale 6. Four themes were identified to explain discordance: 1) Technical or literal meaning of specific words; 2) Patients’ changing or evolving circumstances; 3) Different expectations and criteria for assigning HLQ scores; and 4) Different perspectives about a patient’s reliance on healthcare providers.ConclusionThis study shows that the HLQ can act as an adjunct to clinical practice to help clinicians understand a patient’s health literacy challenges and strengths early in a clinical encounter. Importantly, clinicians can use the HLQ to detect differences between their own perspectives about a patient’s health literacy and the patient’s perspective, and to initiate discussion to explore this. Provision of training to better detect these differences may assist clinicians to provide improved care.The outcomes of this study contribute to the growing body of international validation evidence about the use of the HLQ in different contexts. More specifically, this study has shown that the HLQ has measurement veracity at the patient and clinician level and may support clinicians to understand patients’ health literacy and enable a deeper engagement with healthcare services.

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“…Rather than selecting CDEs focused solely on narrowly defined symptoms, it will likely be necessary to include broader sets of indicators that represent the multidimensional nature of experience. This trade-off has been described as the “bandwidth-fidelity” problem in psychological assessment (Schwartz & Rapkin, 2004). …”

Section: Challenges To the Use Of Cdes For Symptom Sciencementioning

confidence: 99%

Advancing Symptom Science Through Use of Common Data Elements

Redeker¹,

Anderson

Bakken

et al. 2015

J of Nursing Scholarship

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Background Use of common data elements (CDEs), conceptually defined as variables that are operationalized and measured in identical ways across studies, enables comparison of data across studies in ways that would otherwise be impossible. Although healthcare researchers are increasingly using CDEs, there has been little systematic use of CDEs for symptom science. CDEs are especially important in symptom science because people experience common symptoms across a broad range of health and developmental states, and symptom management interventions may have common outcomes across populations. Purposes The purposes of this article are to (a) recommend best practices for the use of CDEs for symptom science within and across centers; (b) evaluate the benefits and challenges associated with the use of CDEs for symptom science; (c) propose CDEs to be used in symptom science to serve as the basis for this emerging science; and (d) suggest implications and recommendations for future research and dissemination of CDEs for symptom science. Design The National Institute of Nursing Research (NINR)-supported P20 and P30 Center directors applied published best practices, expert advice, and the literature to identify CDEs to be used across the centers to measure pain, sleep, fatigue, and affective and cognitive symptoms. Findings We generated a minimum set of CDEs to measure symptoms. Conclusions The CDEs identified through this process will be used across the NINR Centers and will facilitate comparison of symptoms across studies. We expect that additional symptom CDEs will be added and the list will be refined in future work. Clinical Relevance Journal of Nursing Scholarship, 47:5, ©2015 Sigma Theta Tau International.

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Untitled

Cited by 177 publications

References 30 publications

Response shift, recall bias and their effect on measuring change in health-related quality of life amongst older hospital patients

Response shift, recall bias and their effect on measuring change in health-related quality of life amongst older hospital patients

The Health Literacy Questionnaire (HLQ) at the patient-clinician interface: a qualitative study of what patients and clinicians mean by their HLQ scores

Advancing Symptom Science Through Use of Common Data Elements

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