Validation of the Dutch Freiburg Mindfulness Inventory in Patients With Medical Illness

Fieke Z. Bruggeman-Everts, Marije. L. Van der Lee, Elisabeth F. M. Van ‘t Hooft and Ivan NyklÃ­Ä Ek

SAGE Open, 2017, vol. 7, issue 2, 2158244017705936

Abstract: Most validation studies of the Freiburg Mindfulness Inventory (FMI) involved healthy subjects. Validation in patients who suffer from a life-threatening medical illness is needed, to investigate the FMI’s validity in medical psychology research and practice. Psychometric properties of the Dutch FMI were examined in two patient groups of two different studies: (Sample 1) cardiac patients ( n = 114, M age = 56 ± 7 years, 18% women) and (Sample 2) severely fatigued cancer survivors ( n = 158, M age = 50 ± 10 years, 77% women). Confirmatory factor analysis (studied only in Sample 2) provided good fit for the two-factor solution (Acceptance and Presence), while the one-factor solution provided suboptimal fit indices. Internal consistency was good for the whole scale in both samples (Sample 1 α = .827 and Sample 2 α = .851). The two-factor model showed acceptable to good internal consistency in Sample 2 (Presence: α = .823; Acceptance α = .744), but poor to acceptable in Sample 1 (Presence subscale: α = .577, Acceptance subscale: α = .791). Clinical sensitivity was supported in both samples, and construct validity (studied only in Sample 1) was acceptable. The Dutch FMI is an acceptable instrument to measure mindfulness in patients who experienced a life-threatening illness in a Dutch-speaking population.

Keywords: mindfulness; Freiburg Mindfulness Inventory; cancer; validity; cardiac; psychometrics (search for similar items in EconPapers)
Date: 2017
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/2158244017705936 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:sagope:v:7:y:2017:i:2:p:2158244017705936

DOI: 10.1177/2158244017705936

Access Statistics for this article

More articles in SAGE Open
Bibliographic data for series maintained by SAGE Publications ().