Development and validation of a revised trauma-specific quality of life instrument.
Adult
Aged
Female
Follow-Up Studies
Health Surveys
Humans
Injury Severity Score
Male
Middle Aged
Prospective Studies
Psychometrics
/ methods
Quality of Life
Registries
/ statistics & numerical data
Reproducibility of Results
Stress Disorders, Post-Traumatic
/ diagnosis
Time Factors
Wounds and Injuries
/ complications
Journal
The journal of trauma and acute care surgery
ISSN: 2163-0763
Titre abrégé: J Trauma Acute Care Surg
Pays: United States
ID NLM: 101570622
Informations de publication
Date de publication:
04 2020
04 2020
Historique:
pubmed:
19
10
2019
medline:
28
8
2020
entrez:
19
10
2019
Statut:
ppublish
Résumé
The National Academies of Science has called for routine collection of long-term outcomes after injury. One of the main barriers for this is the lack of practical trauma-specific tools to collect such outcomes. The only trauma-specific long-term outcomes measure that applies a biopsychosocial view of patient care, the Trauma Quality-of-Life (T-QoL), has not been adopted because of its length, lack of composite scores, and unknown validity. Our objective was to develop a shorter version of the T-QoL measure that is reliable, valid, specific, and generalizable to all trauma populations. We used two random samples selected from a prospective registry developed to follow long-term outcomes of adult trauma survivors (Injury Severity Score ≥9) admitted to three level I trauma centers. First, we validated the original T-QoL instrument using the 12-Item Short-Form Health Survey (SF-12) version 2.0 and Breslau post-traumatic stress disorder screening (B-PTSD) tools. Second, we conducted a confirmatory factor analysis to reduce the length of the original T-QoL instrument, and using a different sample, we scored and performed internal consistency and validity assessments of the revised T-QoL (RT-QoL) components. All components of the original T-QoL were significantly correlated negatively with the B-PTSD and positively with the SF-12 mental and physical composite scores. After confirmatory factor analysis, a three-component structure using 18 items (six items/component) most appropriately represented the data. Each component in the revised instrument demonstrated a high level of internal consistency (Cronbach's α ≥0.8) and correlated negatively with the B-PTSD and positively with the SF-12, demonstrating concurrent validity. In addition, each of the RT-QoL components was able to distinguish between individuals based on their work status, with those who have returned to work reporting better health. This more practical RT-QoL measure greatly increases the ability to evaluate long-term outcomes in trauma more efficiently and meaningfully, without sacrificing the validity and psychometric properties of the original instrument. Prognostic and epidemiological, level III.
Sections du résumé
BACKGROUND
The National Academies of Science has called for routine collection of long-term outcomes after injury. One of the main barriers for this is the lack of practical trauma-specific tools to collect such outcomes. The only trauma-specific long-term outcomes measure that applies a biopsychosocial view of patient care, the Trauma Quality-of-Life (T-QoL), has not been adopted because of its length, lack of composite scores, and unknown validity. Our objective was to develop a shorter version of the T-QoL measure that is reliable, valid, specific, and generalizable to all trauma populations.
METHODS
We used two random samples selected from a prospective registry developed to follow long-term outcomes of adult trauma survivors (Injury Severity Score ≥9) admitted to three level I trauma centers. First, we validated the original T-QoL instrument using the 12-Item Short-Form Health Survey (SF-12) version 2.0 and Breslau post-traumatic stress disorder screening (B-PTSD) tools. Second, we conducted a confirmatory factor analysis to reduce the length of the original T-QoL instrument, and using a different sample, we scored and performed internal consistency and validity assessments of the revised T-QoL (RT-QoL) components.
RESULTS
All components of the original T-QoL were significantly correlated negatively with the B-PTSD and positively with the SF-12 mental and physical composite scores. After confirmatory factor analysis, a three-component structure using 18 items (six items/component) most appropriately represented the data. Each component in the revised instrument demonstrated a high level of internal consistency (Cronbach's α ≥0.8) and correlated negatively with the B-PTSD and positively with the SF-12, demonstrating concurrent validity. In addition, each of the RT-QoL components was able to distinguish between individuals based on their work status, with those who have returned to work reporting better health.
CONCLUSION
This more practical RT-QoL measure greatly increases the ability to evaluate long-term outcomes in trauma more efficiently and meaningfully, without sacrificing the validity and psychometric properties of the original instrument.
LEVEL OF EVIDENCE
Prognostic and epidemiological, level III.
Identifiants
pubmed: 31626032
doi: 10.1097/TA.0000000000002505
pii: 01586154-202004000-00005
doi:
Types de publication
Journal Article
Multicenter Study
Research Support, Non-U.S. Gov't
Validation Study
Langues
eng
Sous-ensembles de citation
IM
Pagination
501-507Références
Durham R, Pracht E, Orban B, Lottenburg L, Tepas J, Flint L. Evaluation of a mature trauma system. Ann Surg. 2006;243(6):775–785.
Dutton RP, Stansbury LG, Leone S, Kramer E, Hess JR, Scalea TM. Trauma mortality in mature trauma systems: are we doing better? An analysis of trauma mortality patterns, 1997–2008. J Trauma. 2010;69(3):620–626.
Egol KA, Tolisano AM, Spratt KF, Koval KJ. Mortality rates following trauma: The difference is night and day. J Emerg Trauma Shock. 2011;4(2):178–183.
Rios-Diaz AJ, Herrera-Escobar JP, Lilley EJ, et al. Routine inclusion of long-term functional and patient-reported outcomes into trauma registries: the FORTE project. J Trauma Acute Care Surg. 2017;83(1).
National Academies of Sciences, Engineering and M. Berwick D, Downey A, Cornett E, eds. In: A National Trauma Care System: Integrating Military and Civilian Trauma Systems to Achieve Zero Preventable Deaths After Injury. Washington, DC: National Academies Press; 2016.
Wanner JP, deRoon-Cassini T, Kodadek L, Brasel K. Development of a trauma-specific quality-of-life measurement. J Trauma Acute Care Surg. 2015;79(2):275–281.
Maly M, Vondra V. Generic versus disease-specific instruments in quality-of-life assessment of chronic obstructive pulmonary disease. Methods Inf Med. 2006;45:211–215.
Patrick DL, Deyo RA. Generic and disease-specific measures in assessing health status and quality of life. Med Care. 1989;27:S217–S232.
Bland J, Altman DJ. Cronbach's alpha. BMJ. 1997;314(7080):572.
Ware J, Kosinski M, Keller SD. A 12-item short-form health survey: construction of scales and preliminary tests of reliability and validity. Med Care. 1996;34(3):220–233.
Breslau N, Peterson EL, Kessler RC, Schultz LR. Short screening scale for DSM-IV posttraumatic stress disorder. Am J Psychiatry. 1999;156:908–911.
Jamali J, Ayatollahi SMT, Jafari P. The effect of cross-loading on measurement equivalence of psychometric multidimensional questionnaires in MIMIC model: a simulation study. Mater Sociomed. 2018;30(2):121–126.
U.S. Department of Health and Human Services FDA Center for Drug Evaluation and Research; U.S. Department of Health and Human Services FDA Center for Biologics Evaluation and Research; U.S. Department of Health and Human Services FDA Center for Devices and Radiological Health. Guidance for industry: patient-reported outcome measures: use in medical product development to support labeling claims: draft guidance. Health Qual Life Outcomes. 2006;4(1):79.
Guyatt GH, Berman LB, Townsend M, Pugsley SO, Chambers LW. A measure of quality of life for clinical trials in chronic lung disease. Thorax. 1987;42(10):773–778.
Wiebe S, Guyatt G, Weaver B, Matijevic S, Sidwell C. Comparative responsiveness of generic and specific quality-of-life instruments. J Clin Epidemiol. 2003;56(1):52–60.
MacKenzie CR, Charlson ME. Standards for the use of ordinal scales in clinical trials. Br Med J (Clin Res Ed). 1986;292(6512):40–43.
Ware JE Jr., Gandek B, Guyer R, Deng N. Standardizing disease-specific quality of life measures across multiple chronic conditions: development and initial evaluation of the QOL Disease Impact Scale (QDIS®). Health Qual Life Outcomes. 2016;14:84.
Klaassen RJ, Barrowman N, Merelles-Pulcini M, et al. Validation and reliability of a disease-specific quality of life measure (the TranQol) in adults and children with thalassaemia major. Br J Haematol. 2014;164(3):431–437.
Gold SM, Heesen C, Schulz H, Guder U, Mönch A, Gbadamosi J, Buhmann C, Schulz KH. Disease specific quality of life instruments in multiple sclerosis: validation of the Hamburg Quality of Life Questionnaire in Multiple Sclerosis (HAQUAMS). Mult Scler J. 2001;7(2):119–130.
Mayou R, Bryant B. Quality of life in cardiovascular disease. Br Heart J. 1993;69(5):460–466.
Higginson IJ, Carr AJ. Measuring quality of life: Using quality of life measures in the clinical setting. BMJ. 2001;322(7297):1297 LP–1300.
Ware JE, Sherbourne CD. The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Med Care. 1992;30(6):473–483.
Li L, Wang HM, Shen Y. Chinese SF-36 Health Survey: translation, cultural adaptation, validation, and normalisation. J Epidemiol Community Health. 2003;57(4):259–263.
Sullivan M, Karlsson J, Ware JE. The Swedish SF-36 Health Survey—I. Evaluation of data quality, scaling assumptions, reliability and construct validity across general populations in Sweden. Soc Sci Med. 1995;41(10):1349–1358.
Bullinger M. German translation and psychometric testing of the SF-36 Health Survey: preliminary results from the IQOLA Project. International Quality of Life Assessment. Soc Sci Med. 1995;41(10):1359–1366.
Stewart A, Ware J. Measuring Functioning and Well-Being: The Medical Outcomes Study Approach. Durham, NC: Duke University Press; 1992.
Gandek B, Ware JE, Aaronson NK, et al. Cross-validation of item selection and scoring for the SF-12 Health Survey in nine countries: results from the IQOLA Project. International Quality of Life Assessment. J Clin Epidemiol. 1998;51(11):1171–1178.
National Committee for Quality Assurance. NCQA, Annual Member Health Care Survey Manual. Washington, DC, National Committee for Quality Assurance: 1995.
Agency for Healthcare Research and Quality. Combining Measures Into Composites or Summary Scores. Published 2016. Available at: http://www.ahrq.gov/professionals/quality-patient-safety/talkingquality/create/scores/combinemeasures.html. Accessed August 11, 2018.
Hunsley J, Meyer GJ. The incremental validity of psychological testing and assessment: conceptual, methodological, and statistical issues. Psychol Assess. 2003;15(4):446–455.
John OP, Benet-Martínez V. Measurement: reliability, construct validation, and scale construction. In: Reis HT, Judd CM, eds. Handbook of Research Methods in Social and Personality Psychology. 2nd ed. New York, NY: Cambridge University Press; 2000:339–369.
Epstein S. The self-concept revisited: or a theory of a theory. Am Psychol. 1973;28(5):404–416.
Waters E, Sroufe LA. Social competence as a developmental construct. Dev Rev. 1983;3(1):79–97.
Epstein S. The stability of behavior: II. Implications for psychological research. Am Psychol. 1980;35(9):790–806.
Rushton JP, Brainerd CJ, Pressley M. Behavioral development and construct validity: the principle of aggregation. Psychol Bull. 1983;94(1):18–38.
Watkins MW, Glutting JJ, Lei P-W. Validity of the full-scale IQ when there is significant variability among WISC-III and WISC-IV factor scores. Appl Neuropsychol. 2007;14(1):13–20.
Schumacker RE, Lomax RG. A Beginner's Guide to Structural Equation Modeling. 2nd ed. New York, NY: Routledge Academic; 2004.
Boomsma A, Hoogland JJ. The robustness of LISREL modeling revisited. In: Structural Equation Modeling: Present and Future: A Festschrift in Honor of Karl Jöreskog. Chicago, IL: Scientific Software International; 2001:139–168.
Hoogland JJ, Boomsma A. Robustness studies in covariance structure modeling: An overview and a meta-analysis. Sociol Methods Res. 1998;26(3):329–367.