Acta Scientific Neurology (ASNE) (ISSN: 2582-1121)

Research Article Volume 7 Issue 2

Better aggregation of Pain scores and Quality of Life

Chakrabartty Satyendra Nath*

Indian Statistical Institute, Indian Maritime University, Indian Ports Association, India

*Corresponding Author: Chakrabartty Satyendra Nath, Indian Statistical Institute, Indian Maritime University, Indian Ports Association, India

Received: November 01, 2023; Published: January 16, 2024

Abstract

Background: Assessment of pain intensity, factors of pain after surgery and their effects on Quality of Life (QoL) by tools using Likert items or Numerical rating scales, etc. are not comparable and may give different results. No instrument performed uniformly as "best" or "worst”.

Method: A method of transforming raw scores to normally distributed scores (P-scores) is described. Based on proposed P-scores, the paper proposes, an overall pain status (OPS) by arithmetic aggregation of component variables. Similarly, P-scores of items of QoL are combined to get overall QoL scores (〖QoL〗_Total). Empirical relationship can be established between OPS and 〖QoL〗_Total to predict the later with knowledge of the former. In addition, ratios of P-scores of each factor, measure of pain intensity and QoL at the current period and the base period may be combined by multiplicative aggregation to find composites index of overall pain status (OPSI) by OPSI= (P_1c.P_2c……….P_nc)/(P_10.P_20..… P_n0 ) *100

Results: Scores of OPS and QoLTotal are monotonic following normal distributions meaningful comparisons and classification of patients and assessing progress/deterioration of a patient or a group of patients and drawing path of improvement/decline. Cut-off scores of different scales can be integrated by considering equivalent scores (x_(0,) y_0) of two scales. In addition, P-scores help to find reliability as per theoretical definition and factorial validity to reflect validity of the main factor for which the scale was developed. For the index OPSI, aggregation of dimensions = OPSI as aggregation of components variables giving minimum trade-off among the dimensions or components. Dimensions or components where P_ic/P_i0 <0 are critical requiring attention of the physicians and care givers.

Conclusions: Proposed method of transforming ordinal scores of K-point items to continuous, monotonic scores following normal distribution helps to avoid major limitations of existing summative scores and facilitate undertaking analysis under parametric set up. From the angle of distribution, OPS may be preferred than OPSI. Future studies with multi-data sets involving more than one QoL scales are suggested to investigate characteristics of OPS and index of overall pain status (OPSI) along with clinically relevant issues and psychometric properties of the proposed transformations.

Keywords: Pain Intensity; Quality of Life; Normal Distribution; Responsiveness; Equivalent Scores; Reliability; Validity

References

  1. Schug SA., et al. “The IASP classification of chronic pain for ICD-11: chronic postsurgical or posttraumatic pain”. Pain 160 (2019): 45-52.
  2. Rosenberger DC., et al. “Chronic post-surgical pain - update on incidence, risk factors and preventive treatment options”. BJA Education5 (2022): 190-196.
  3. Pogatzki-Zahn EM., et al. “Postoperative pain-from mechanisms to treatment”. PAIN Reports 2 (2017): e588.
  4. Martinez V., et al. “Risk factors predictive of chronic postsurgical neuropathic pain: the value of the iliac crest bone harvest model”. Pain7 (2012): 1478- 1483.
  5. Lavand’homme P. “Transition from acute to chronic pain after surgery”. Pain1 (2017): S50-S54.
  6. Giusti EM., et al. “Psychological and psychosocial predictors of chronic postsurgical pain: a systematic review and meta-analysis”. Pain 1 (2021): 10-30.
  7. Glare P., et al. “Transition from acute to chronic pain after surgery”. Lancet 393.10180 (2019): 1537-1546.
  8. Schnabel A., et al. “Predicting poor postoperative acute pain outcome in adults: an international, multicentre database analysis of risk factors in 50,005 patients”. PAIN Reports 4 (2020): e831.
  9. Schug SA and Bruce J. “Risk stratification for the development of chronic postsurgical pain”. PAIN Reports 6 (2017): e627.
  10. Robinson A., et al. “The effectiveness of physiotherapy interventions on pain and quality of life in adults with persistent post-surgical pain compared to usual care: A systematic review”. PLoS One12 (2019): e0226227.
  11. Meretoja TJ., et al. “Clinical prediction model and tool for assessing risk of persistent pain after breast cancer surgery”. Journal of Clinical Oncology 35 (2017):
  12. Althaus A., et al. “Development of a risk index for the prediction of chronic post-surgical pain”. European Journal of Pain 16 (2012): 901-910.
  13. Montes A., et al. “Presurgical risk model for chronic postsurgical pain based on 6 clinical predictors: a prospective external validation”. Pain11 (2020): 2611-2618.
  14. Silva PA., et al. “Cut-off point for WHOQOL-bref as a measure of quality of life of older adults”. Revista de Saúde Pública 3 (2014): 390-397.
  15. Lidington E., et al. “Identifying health-related quality of life cut-off scores that indicate the need for supportive care in young adults with cancer”. Quality of Life Research 31 (2022): 2717-2727.
  16. Obuchowski “Receiver operating characteristic curves and their use in radiology”. Radiology 229 (2003): 3-8.
  17. Gagliese Lucia., et al. “The measurement of postoperative pain: A comparison of intensity scales in younger and older surgical patients”. Pain 3 (2005): 412-420.
  18. Aun C., et al. “Evaluation of the use of visual analogue scale in Chinese patients”. Pain 25 (1986): 215-221.
  19. Williamson A and Hoggart B. “Pain: a review of three commonly used pain rating scales”. Journal of Clinical Nursing 14 (2005): 798-804.
  20. Myles PS., et al. “Measuring acute postoperative pain using the visual analog scale: the minimal clinically important difference and patient acceptable symptom state”. British Journal of Anaesthesia3 (2017): 424-429.
  21. Jensen Mark P., et al. “The measurement of clinical pain intensity: a comparison of six methods”. Pain1 (1986): 117-126.
  22. Kwong WJ and Pathak DS. “Validation of the eleven-point pain scale in the measurement of migraine headache pain”. Cephalalgia 27 (2007): 336-342.
  23. Le Resche L., et al. “Reliability of Visual Analog and Verbal Descriptor Scales for “Objective” Measurement of Temporomandibular Disorder Pain”. Journal of Dental Research1 (1988): 33-36.
  24. Jensen MP and Karoly P. “Self-Report Scales and Procedures for Assessing Pain in Adults”. In: Turk, D.C. and Melzack, R., Eds., Handbook of Pain Assessment, 3rd Edition, Guilford Press, New York (2011): 15-34.
  25. Rosier EM., et al. “Reproducibility of pain measurement and pain perception”. Pain 98 (2002): 205-216.
  26. van Dijk JF., et al. “The relation between patients' NRS pain scores and their desire for additional opioids after surgery”. Pain Practice 15.7 (2015): 604-609.
  27. Coll AM., et al. “Postoperative pain assessment tools in day surgery: literature review”. Journal of Advanced Nursing2 (2004): 124-133.
  28. Laycock HC and Harrop-Griffiths W. “Assessing pain: how and why?” Anaesthesia 76 (2021): 559-562.
  29. Baamer RM., et al. “Utility of unidimensional and functional pain assessment tools in adult postoperative patients: a systematic review”. British Journal of Anaesthesia 5 (2022): 874-888.
  30. van Boekel RLM., et al. “Moving beyond pain scores: Multidimensional pain assessment is essential for adequate pain management after surgery”. PLoS ONE5 (2017): e0177345.
  31. Melzack R. “The McGill Pain Questionnaire: major properties and scoring methods”. Pain 3 (1975): 277-299.
  32. Graham C., et al. “Use of the McGill Pain Questionnaire in the assessment of cancer pain: replicability and consistency”. Pain3 (1980): 377-387.
  33. Cleeland C and Ryan K. “Pain assessment: global use of the Brief Pain Inventory”. Annals of the Academy of Medicine of Singapore 2 (1994): 129-138.
  34. Barber MD. “Validation of the Surgical Pain Scales in women undergoing pelvic reconstructive 215 surgery”. Female Pelvic Medicine and Reconstructive Surgery 4 (2012): 198-204.
  35. Closs SJ., et al. “Towards improved decision support in the assessment and management of pain for people with dementia in hospital: a systematic meta-review and observational study”. Health Services and Delivery Research 4.30 (2016): 1-162.
  36. Costardi D., et al. “The Italian version of the pain assessment in advanced dementia (PAINAD) scale. Arch Gerontol Geriatrics 44.2 (2017): 175-180.
  37. Cella DF. “Quality of life: concepts and definition”. Journal of Pain and Symptom Management 3 (1994): 186- 192.
  38. Chaichana KL., et al. “Correlation of preoperative depression and somatic perception scales with postoperative disability and quality of life after lumbar discectomy”. Journal of Neurosurgery: Spine 2 (2011): 261-267.
  39. Ware J., et al. “A 12-item short-form health survey: construction of scales and preliminary tests of reliability and validity”. Medical Care 34 (1996): 220-233.
  40. Maillard J., et al. “Preoperative and early postoperative quality of life after major surgery - a prospective observational study”. Health Qual Life Outcomes13 (2015): 12.
  41. Odom SL Boyd B., et al. “Evaluation of comprehensive treatment models for individuals with autism spectrum disorders”. Journal of Autism and Developmental Disabilities 40 (2010): 425-437.
  42. NHS Quality Improvement Scotland. “The Impact of Nursing on Patient Clinical Outcomes”. Edinburgh: NHSQIS (2005).
  43. Essink-Bot ML., et al. “An empirical comparison of four generic health status measures. The Nottingham Health Profile, the Medical Outcomes Study 36-item Short-Form Health Survey, the COOP/WONCA charts, and the EuroQol instrument”. Medical Care 5 (1997): 522-537.
  44. Clason DL and Dormody TJ. “Analyzing data measured by individual Likert-type items”. Journal of Agricultural Education 4 (1994): 31-35.
  45. Harwell MR and Gatti GG. “Rescaling ordinal data to interval data in educational research”. Review of Educational Research 71 (2001): 105-131.
  46. Šimkovic M and Träuble B. “Robustness of statistical methods when measure is affected by ceiling and/or floor effect”. PloS One8 (2019): e0220889.
  47. Yusoff Rohana and Janor RM. “Generation of an Interval Metric Scale to Measure Attitude”. SAGE Open (2014): 1-16.
  48. Chakrabartty SN. “Optimum number of Response categories”. Current Psychology 42 (2023): 5590-5598 (2023).
  49. Chakrabartty SN. “Equidistant Likert as weighted sum of Response Categories”. Cultura, Educación y Sociedad1 (2023): 75-92.
  50. Joardar AH and Omar MH. “On Statistical Characteristics of the Product of two correlated Chi-square variables”. Journal of Applied Statistical Science 9.4 (2013): 1067-5817.
  51. Chakrabartty and Satyendra Nath. “Disability and Quality of Life”. Health Science Journal12 (2022): 1-6.
  52. Chakrabartty and Satyendra Nath. “Reliability of Test Battery, Methodological Innovations2 (2020): 1-8. DOI: 10.1177/2059799120918340
  53. Parkerson HA., et al. “Factorial Validity of the English-Language Version of the Pain Catastrophizing Scale-Child Version”. The Journal of Pain 11 (2013): 1383-1389, https://doi.org/10.1016/j.jpain.2013.06.004

Citation

Citation: Chakrabartty Satyendra Nath. “Better aggregation of Pain scores and Quality of Life". Acta Scientific Neurology 7.2 (2024): 19-28.

Copyright

Copyright: © 2024 Chakrabartty Satyendra Nath. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.




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