Achtergrondinformatie (Engelstalig)

The problem/challenge

Standard quality of life (QoL) questionnaires typically rely on global retrospective self-reports (using a timeframe of one week or more) (e.g. “My QoL is very good taking everything into consideration”). They obtain psychological constructions of QoL, either in the past or in general. However, despite apparent changes in health, patients may report surprisingly stable quality of life (QoL). Two key causes are addressed that are generally ignored in QoL research: (1) standard QoL questionnaires predominantly tap stable (trait) rather than changeable (state) components of QoL; and (2) they do not take changes in internal standards, values and conceptualisation of QoL (so called response shifts) into account.

Therefore, this project aims to improve the conceptualisation of QoL and to enhance the sensitivity and comprehensiveness of its measurement by taking the trait-state distinction and response shift into account. We will also investigate how co-morbidities (i.e., number and type) impact QoL.

We focus on patients with cardiac disease having multiple co-morbidities (i.e. diabetes, lung disease, joint problems and / or overweight (BMI ≥ 30)), because of their high prevalence, patient burden and societal costs. Moreover, prevalence rates are expected to increase due to the aging population


Description of trait-state distinction

There is increasing evidence to suggest that quality of life is partly heritable1-6. Studies of twins have indicated that heritability estimates for QoL-related domains such as mood and self-reported health range from 20 to 50%1,7-8 which is comparable or even higher than that of most diseases. Biological pathways have been associated with domains such as pain, fatigue, mood, and overall well-being4-6,9. Thus, QoL cannot be seen as the exclusive result of health care interventions because it is in part a person characteristic. This intrinsic nature is frequently ignored, or treated as noise. Consequently, we treat QoL as a concept that has trait and state components10-11.

To measure trait and state components of QoL we use standard QoL questionnaires and QoL questions administered via an iPod, respectively. By using questionnaires via smartphones we can apply Ecological Momentary Assessment (EMA) (also called Experience Sampling Method19-20). EMA involves repeated sampling of subjects’ current QoL in real-time and natural environment. Standard QoL questionnaires predominantly capture generic trait judgments whereas EMA taps specific episodic state reports (e.g. “Now I feel miserable”). Thereby, EMA allows the assessment of fluctuations in QoL across time, such as the diurnal rhythm of fatigue21-23. Since EMA assesses symptoms and side effects as experienced in daily life, unaffected by reconstruction bias, it is the best method for obtaining state-level data11.


Description of Response Shift

Response shift refers to a change in what (specific) constructs mean to a person. People confronted with a chronic disease may change their internal standards (recalibration), values (reprioritization) and conceptualisation of QoL12. Whereas these response shifts are adaptive from the patients’ perspective, they may obfuscate treatment effects and estimates of change over time13-14. For example, patients who have learned to adapt to deteriorating health, may report stable QoL, which is also referred to as the disability paradox15. Changes in QoL are more sensitively assessed when response shifts are taken into account13,14,16-18.


Conceptualisation: towards a narrative understanding
of quality of life

We conceptualize the trait-state distinction and response shift in relation to QoL, using a biographical/narrative and identity-based perspective on the meaning of the ‘good life’26, and a theory of contingency and life goals24-25.

Falling ill often has a large impact on people’s quality of life. For many people, falling ill is a ‘contingent life event’: something unexpected that ruptures our life course and causes conflict with our expectations and life goals.
In the medical sciences, quality-of-life-research usually focuses on ‘health-related quality of life’: the way a disease influences physical, psychological and social functioning. Previous theoretical and empirical research suggests that the way people make meaning of their disease influences their experienced quality of life. However, little research has been done on the way people make meaning of illness and other contingent life events in the context of their personal life narrative and worldview, and how this relates to quality of life. To understand this type of meaning making and its relationship with quality of life, we need a humanities-approach.

In this part of our interdisciplinary project, we develop a narrative perspective on quality of life, connecting contingency theory and theories on narrative identity with theories on quality of life in medical psychology. Taking contingency theory and motivation theory as a starting point, we focus on the role of worldview, ultimate life goals, the experience of contingency and ‘relating to contingency’ in people’s interpretation of contingent life events.
One of our hypotheses is that confronted with a contingent life event, people ‘relate to contingency’ in different ways, some being more able than others to integrate negative contingent life events in their life story. In this project we aim to elucidate how this aspect of a person’s identity is related to the self-evaluation of quality of life.

This part of the Impact study consists of three sub projects

  1. a theoretical project: literature study on quality of life, life goals and narrative identity;
  2. an empirical qualitative project: in-depth interviews with respondents having cardiac disease about the way their illness and other contingent life events impacts their life goals and influences their quality of life;
  3. an empirical quantitative project: developing a quantitative questionnaire about meaning making of contingent life events, to be tested in a large-scale study on quality of life amongst 400 patients having cardiac disease.

This project is the first that aims to empirically examine QoL from a trait and state perspective and to explicitly measure and control for response-shift effects. Moreover, the innovative and fundamental conceptualisation and measurement of QoL is, in principle, applicable to other disease groups and care innovations, and will enhance the evidence base for care provision, allocation and reimbursement.

Reference list
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  2. Sprangers MAG et al. The establishment of the GENEQOL Consortium to investigate the genetic disposition of patient-reported quality-of-life outcomes. Twin Research and Human Genetics 2009; 12: 301-311.
  3. Sprangers MAG et al. Scientific imperatives, clinical implications, and theoretical underpinnings for the investigation of the relationship between genetic variables and patient-reported quality-of-life outcomes. Quality of Life Research 2010a; 19: 1395-1403.
  4. Shi Q et al. Biological pathways and genetic variables involved in pain. Qual Life Res 2010; 19: 1407-1417.
  5. Barsevick A et al. I’m so tired: biological and genetic mechanisms of cancer-related fatigue. Qual Life Res 2010; 19: 1419-1427.
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