OBJECTIVES

To develop a new questionnaire to assess well-being for chronic treatments from the perspective of social support and psychological needs.

METHODS

A scientific committee composed by seven experts in health service quality, chronic care, pharmaco-economics, psychometry, sociology, and patient-relation management, along with representatives of two national patient associations supervised the process. Bibliographic review on instruments measuring wellbeing raised a 29-item questionnaire, piloted in a sample of 7 patients. A sample of 58 chronic patients was recruited at 15 patient associations. Item measurement properties (ceiling/floor effect, response distribution, missing responses) were assessed. Questionnaire structure and item reduction were studied using Exploratory Factor Analysis (Principal components, Oblimin rotation), and reliability (Chronbach’s α & McDonald’s ω).

RESULTS

A total of 39,455 articles mentioned the term wellbeing, in the period 1990-2019, and it was possible to identify 7 different dimensions, measured by 21 questionnaires with proven psychometric properties. After content review, 29 items were produced, structured in four main dimensions (# items): Psychological-Emotional (12), labor impact (5), social impact (8), and health condition management (4). Responses covered the whole range of 0-4 point Likert scales, with means between 0.85 (SD=0.87) and 2.66 (SD=1.44). Item α were acceptable (0.75-0.84), except for the fourth dimension (α=0.41), while item-ω was high (0.90-0.92) for the unidimensional solution. Two items had to be discarded due to ill measurement behavior of responses and failing to fit the theoretical structure. Most correlations with EQ-5D dimensions were low (0.1-0.3), but some were statistically significant, like psychological/emotional dimension and EQ5D anxiety/depression (r=0.7), labor impact with EQ5D pain (r=-0.43), and social impact with EQ5D daily activities (r=‑0.56).

CONCLUSIONS

The proposed instrument showed acceptable psychometric properties to pass to the following development stage, using a larger sample and more validation instruments.