The impact of decision models on self-perceived quality of life: A study on brain cancer patients

C. Lucchiari, A. Botturi, G. Pravettoni

Research output: Contribution to journalArticlepeer-review


Quality of life (QoL) is an increasingly important outcome measure in medicine. Health, in fact, is not only based on functional status but also on psychological and social well being. Since QoL is related to the patient's perception of their position in life in relation to their goals, expectations, standards and concerns, the way in which the medical context is experienced may be critical. We then hypothesised that self-perceived QoL may be linked to unmet needs in information management and decision involvement. To analyse this hypothesis, we conducted a quantitative study on 84 consecutive patients with a diagnosis of primary high-grade glioma. The functional assessment of cancer therapy-Brain (FACT-Br) scales, the hospital anxiety and depression (HAD) scale and the need evaluation questionnaire (NEQ) questionnaire were used, in order to measure quality-of-life dimension, mood and unmet needs. Patients were classified as having no need (cluster 1), a moderate need (cluster 2) or a high need (cluster 3) to be more involved in the clinical process. Our data confirmed previous studies in other clinical areas, showing that shared decision might contribute to a better adaptation process to the illness [1]. In fact, patients in cluster 1 showed a significant better self-perceived QoL, despite the lack of clinical differences between clusters. The study showed that patients satisfied with respect to decisional involvement seem to be able to better cope with their disease. Finally, the study suggests the need for a more attuned decision-making process in approaching clinical decisions. Physicians need to better understand patient preferences related to information and decision sharing.

Original languageEnglish
Article number187
Issue number1
Publication statusPublished - Aug 20 2010

ASJC Scopus subject areas

  • Cancer Research
  • Oncology


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