Optimising outputs from a validated online instrument to measure health-related quality of life (HRQL) in dogs
Autoři:
Vinny Davies aff001; Jacqueline Reid aff003; M. Lesley Wiseman-Orr aff002; E. Marian Scott aff002
Působiště autorů:
School of Computing Science, University of Glasgow, Glasgow, Scotland, United Kingdom
aff001; School of Mathematics and Statistics, University of Glasgow, Glasgow, Scotland, United Kingdom
aff002; NewMetrica Ltd, Glasgow, Scotland, United Kingdom
aff003
Vyšlo v časopise:
PLoS ONE 14(9)
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0221869
Souhrn
Measurement of health-related quality of life (HRQL) is becoming increasingly valuable within veterinary preventative health care and chronic disease management, as well as in outcomes research. Initial reliability and validation of a 22 item shortened version of VetMetrica (VM), structured questionnaire instrument to measure HRQL in dogs via a mobile application was reported previously. Meaningful interpretation and presentation of the 4 domain scores comprising the HRQL profile generated by VM is key to its successful use in clinical practice and research. Study one describes transformation of domain scores from 0–6 to 0–100 and normalisation of these based on the healthy canine population in two age ranges, such that a score of 50 on a 0–100 scale represents the score for the age-related average healthy dog, and establishment of a threshold to assess domain-specific health status for individual dogs. This provides the clinician with a simple method of ascertaining the health status of an individual dog relative to the average healthy population in the same age group (norm-based scoring). Study two determines the minimum important difference (MID) in domain scores which represents the smallest improvement in score that is meaningful to the dog owner, thus providing the clinician with a means of recognising what is likely to be a significant improvement in scores for an individual dog over time. Visual representation of these guidelines for the purpose of interpreting VM profile scores is presented using case studies.
Klíčová slova:
Biology and life sciences – Organisms – Eukaryota – Animals – Vertebrates – Amniotes – Mammals – Dogs – Veterinary science – Veterinary diseases – People and places – Population groupings – Age groups – Medicine and health sciences – Rheumatology – Arthritis – Osteoarthritis – Gastroenterology and hepatology – Inflammatory bowel disease – Health care – Quality of life – Engineering and technology – Equipment – Measurement equipment – Physical sciences – Mathematics – Probability theory – Probability distribution – Normal distribution
Zdroje
1. Gyatt G.H., Naylor C.D., Juniper E., Heyland D.K., Jaeschke R. & Cook D.J. (2007). User’s guides to the medical literature. XII. How to use articles about health-related quality of life. The Journal of the American Medical Association, 277(15):1232–1237.
2. Budke C.M., Levine J.M., Kerwin S.C., Levine G.J., Hettlich B.F. & Slater M.R. (2008). Evaluation of a questionnaire for obtaining owner-perceived, weighted quality- of-life assessments for dogs with spinal cord injuries. Journal of the American Veterinary Medical Association, 223, 925–930.
3. Favrot C., Linek M., Mueller R., Zini E. (2010). International Task Force on Canine Atopic Dermatitis. Development of a questionnaire to assess the impact of atopic dermatitis on health-related quality of life of affected dogs and their owners. Veterinary Dermatology, 21(1), 64–70.
4. Freeman L.M., Rush J.E., Farabaugh A.E. & Must A. (2005). Development and evaluation of a questionnaire for assessing health-related quality of life in dogs with cardiac disease. Journal of the American Veterinary Medical Association, 226(11), 1864–1868. doi: 10.2460/javma.2005.226.1864 15934254
5. Lynch S., Savary-Bataille K., Leeuw B. & Argyle D.J. (2011). Development of a questionnaire assessing health-related quality-of-life in dogs and cats with cancer. Veterinary and Comparative Oncology, 9(3), 172–182. doi: 10.1111/j.1476-5829.2010.00244.x 21848620
6. Niessen S.J.M., Powney S., Guitian J., Niessen A.P.M., Pion P.D., Shaw J.A.M. at al. Evaluation of a quality-of-life tool for dogs with diabetes mellitus. Journal of Veterinary Internal Medicine, 26(4), 953–961 doi: 10.1111/j.1939-1676.2012.00947.x 22646241
7. Noli C., Minafò G. & Galzerano M. (2011). Quality of life of dogs with skin diseases and their owners. Part 1: development and validation of a questionnaire. Veterinary Dermatology, 22(4), 335–343. doi: 10.1111/j.1365-3164.2010.00954.x 21410569
8. Schünemann H.J., Akl E.A. & Guyatt G.H. (2006). Interpreting the results of patient reported outcome measures in clinical trials: the clinician's perspective. Health and Quality of Life Outcomes, 4(1), 62.
9. Reid J., Wiseman‐Orr L. & Scott E.M. (2018). Shortening of an existing generic online health‐related quality of life instrument for dogs. Journal of Small Animal Practice, 59(6), 334–342. doi: 10.1111/jsap.12772 29023735
10. Wiseman-Orr M.L., Nolan A.M., Reid J. & Scott E.M. (2004). Development of a questionnaire to measure the effects of chronic pain on health-related quality of life in dogs. American Journal of Veterinary Research, 65(8), 1077–1084. 15334841
11. Wiseman-Orr M.L., Scott E.M., Reid J. & Nolan A.M. (2006). Validation of a structured questionnaire as an instrument to measure chronic pain in dogs on the basis of effects on health-related quality of life. American Journal of Veterinary Research, 67(11), 1826–1836. doi: 10.2460/ajvr.67.11.1826 17078742
12. Reid J., Wiseman‐Orr M.L., Scott E.M. & Nolan A.M. (2013). Development, validation and reliability of a web‐based questionnaire to measure health‐related quality of life in dogs. Journal of Small Animal Practice, 54(5), 227–233. doi: 10.1111/jsap.12059 23557412
13. Wojciechowska J.I., Hewson C.J., Stryhn H., Guy N.C., Patronek G.J. & Timmons V. (2005). Development of a discriminative questionnaire to assess nonphysical aspects of quality of life of dogs. American Journal of Veterinary Research, 66(8), 1453–1460. 16173493
14. Wojciechowska J.I., Hewson C.J., Stryhn H., Guy N.C., Patronek G.J. & Timmons V. (2005). Development of a discriminative questionnaire to assess nonphysical aspects of quality of life of dogs. American Journal of Veterinary Research, 66(8), 1461–1467. 16173494
15. Lavan R.P. (2013). Development and validation of a survey for quality of life assessment by owners of healthy dogs. The Veterinary Journal, 197(3), 578–582. doi: 10.1016/j.tvjl.2013.03.021 23639368
16. Streiner D.L., Norman G.R. & Cairney J. (2015). Health measurement scales: a practical guide to their development and use. Oxford University Press, USA.
17. Carey J.J. & Delaney M.F. (2010). T-scores and Z-scores. Clinical Reviews in Bone and Mineral Metabolism, 8(3), 113–121.
18. Lam C.L., Lauder I.J., Lam T.P. & Gandek B. (1999). Population based norming of the Chinese (HK) version of the SF-36 health survey. Hong Kong Practitioner.
19. Schünemann H.J., Puhan M., Goldstein R., Jaeschke R. & Guyatt G.H. (2005). Measurement properties and interpretability of the Chronic respiratory disease questionnaire (CRQ). Journal of Chronic Obstructive Pulmonary Disease, 2(1), 81–89. 17136967
20. Kazis L.E., Anderson J.J. & Meenan R.F. (1989). Effect sizes for interpreting changes in health status. Medical care, S178–S189. doi: 10.1097/00005650-198903001-00015 2646488
21. Liang M.H., Fossel A.H. & Larson M.G. (1990). Comparisons of five health status instruments for orthopedic evaluation. Medical care, 632–642. doi: 10.1097/00005650-199007000-00008 2366602
22. Guyatt G., Walter S. & Norman G (1987). Measuring change over time: assessing the usefulness of evaluative instruments. Journal of Chronic Diseases, 40(2), 171–178. doi: 10.1016/0021-9681(87)90069-5 3818871
23. Lydick E. & Epstein R.S. (1993). Interpretation of quality of life changes. Quality of life Research, 2(3), 221–6. 8401458
24. Zweig M.H. & Campbell G. (1993). Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. Clinical chemistry, 39(4), 561–577. 8472349
25. Deyo R.A. & Centor R.M. (1986). Assessing the responsiveness of functional scales to clinical change: an analogy to diagnostic test performance. Journal of Chronic Diseases, 39(11), 897–906. doi: 10.1016/0021-9681(86)90038-x 2947907
26. Lesaffre E., Rizopoulos D., & Tsonaka R. (2006). The logistic transform for bounded outcome scores. Biostatistics, 8(1), 72–85. doi: 10.1093/biostatistics/kxj034 16597671
27. Huang I. C., Frangakis C., Atkinson M. J., Willke R. J., Leite W. L., Vogel et al. (2008). Addressing ceiling effects in health status measures: a comparison of techniques applied to measures for people with HIV disease. Health services research, 43, 327–339. doi: 10.1111/j.1475-6773.2007.00745.x 18211533
28. French B., Sycamore N. J., McGlashan H. L., Blanchard C. C., & Holmes N. P. (2018). Ceiling effects in the Movement Assessment Battery for Children-2 (MABC-2) suggest that non-parametric scoring methods are required. PLOS ONE, 13(6), e0198426. doi: 10.1371/journal.pone.0198426 29856879
29. Ware J., Kosinski M., Bjorner J., Turner-Bowker D., Gandek B., & Maruish M. (2007) User's Manual for the SF-36v2® Health Survey. Lincoln (RI): QualityMetric Incorporated.
30. Kołtowska-Häggström M., Hennessy S., Mattsson A.F., Monson J.P. & Kind P. (2005). Quality of life assessment of growth hormone deficiency in adults (QoL-AGHDA): comparison of normative reference data for the general population of England and Wales with results for adult hypopituitary patients with growth hormone deficiency. Hormone Research in Paediatrics, 64(1), 46–54.
31. Ware J.E., Kosinski M. & Dewey J.E. (2000). How to score version two of the SF-36 health survey.
32. Gandek, B (2002). How to score version 2 of the SF-12 Health Survey (with a supplement documenting Version 1).
33. Hawthorne G., Osborne R.H., Taylor A. & Sansoni J. (2007). The SF36 Version 2: critical analyses of population weights, scoring algorithms and population norms. Quality of Life Research, 16(4), 661–73. doi: 10.1007/s11136-006-9154-4 17268926
34. de Vet H.C., Ostelo R.W., Terwee C.B., van der Roer N., Knol D.L., Beckerman H. et al. (2007). Minimally important change determined by a visual method integrating an anchor-based and a distribution-based approach. Quality of Life Research, 16(1), 131. doi: 10.1007/s11136-006-9109-9 17033901
35. Farrar J.T., Young J.P. Jr, LaMoreaux L., Werth J.L. & Poole R.M. (2001). Clinical importance of changes in chronic pain intensity measured on an 11-point numerical pain rating scale. Pain, 94(2), 149–158. doi: 10.1016/s0304-3959(01)00349-9 11690728
36. Ostelo R.W. & de Vet H.C. (2005). Clinically important outcomes in low back pain. Best Practice & Research Clinical Rheumatology, 19(4), 593–607.
37. Coteur G., Feagan B., Keininger D.L. & Kosinski M. (2009). Evaluation of the meaningfulness of health‐related quality of life improvements as assessed by the SF‐36 and the EQ‐5D VAS in patients with active Crohn’s disease. Alimentary pharmacology & therapeutics, 29(9), 1032–1041.
38. Hawker G.A., Mian S., Kendzerska T. & French M. (2011). Measures of adult pain: Visual analog scale for pain (vas pain), numeric rating scale for pain (nrs pain), mcgill pain questionnaire (mpq), short‐form mcgill pain questionnaire (sf‐mpq), chronic pain grade scale (cpgs), short form‐36 bodily pain scale (sf‐36 bps), and measure of intermittent and constant osteoarthritis pain (icoap). Arthritis Care & Research, 63(S11), S240–252.
39. Jette D.U. & Downing J. (1994). Health status of individuals entering a cardiac rehabilitation program as measured by the medical outcomes study 36-item short-form survey (SF-36). Physical Therapy, 74(6), 521–527. doi: 10.1093/ptj/74.6.521 8197238
40. Leynaert B., Neukirch C., Liard R., Bousquet J. & Neukirch F. (2000). Quality of life in allergic rhinitis and asthma: a population-based study of young adults. American Journal of Respiratory and Critical Care Medicine, 162(4), 1391–1396.
Článek vyšel v časopise
PLOS One
2019 Číslo 9
- S diagnostikou Parkinsonovy nemoci může nově pomoci AI nástroj pro hodnocení mrkacího reflexu
- Je libo čepici místo mozkového implantátu?
- Pomůže v budoucnu s triáží na pohotovostech umělá inteligence?
- AI může chirurgům poskytnout cenná data i zpětnou vazbu v reálném čase
- Nová metoda odlišení nádorové tkáně může zpřesnit resekci glioblastomů
Nejčtenější v tomto čísle
- Graviola (Annona muricata) attenuates behavioural alterations and testicular oxidative stress induced by streptozotocin in diabetic rats
- CH(II), a cerebroprotein hydrolysate, exhibits potential neuro-protective effect on Alzheimer’s disease
- Comparison between Aptima Assays (Hologic) and the Allplex STI Essential Assay (Seegene) for the diagnosis of Sexually transmitted infections
- Assessment of glucose-6-phosphate dehydrogenase activity using CareStart G6PD rapid diagnostic test and associated genetic variants in Plasmodium vivax malaria endemic setting in Mauritania
Zvyšte si kvalifikaci online z pohodlí domova
Všechny kurzy