Development and assessment of a verbal response scale for the Patient-Specific Functional Scale (PSFS) in a low-literacy, non-western population



The Patient-Specific Functional Scale (PSFS) is a routinely used measure of physical function with a 0–10 response scale. We aimed to develop verbal response options for the PSFS, pre-test it for use in a multilingual, low-literacy country— Nepal, and compare preference and error rates between numeric and verbal scale. We hypothesized that a verbal scale would be preferred by respondents and yield fewer errors.


We interviewed 42 individuals with musculoskeletal, neurological, and cardiopulmonary conditions to understand how people describe varying levels of physical ability. Transcripts were thematically analyzed, and through consensus, we developed two sets of verbal responses for the PSFS. Next, we pre-tested the scales on an additional 119 respondents following which participants were asked to specify their preferred scale. Error rates were analyzed retrospectively using pre-specified criteria.


Participants described their ability in terms of the quality (95%) and the quantity of task performance (88%). Although the verbal scales were preferred over the numeric scale (50% versus 12%), there was no significant difference in error rates between numeric (34%) and verbal scales (32% and 36%). Higher error rates were associated with greater age, fewer years of education, and inexperience with numeric scales.


Despite a higher preference for verbal scale, 1 out of 3 patients made errors in using the PSFS, even with an interview format. The error rates were higher among participants with low literacy. The findings raise questions about the utility of PROMs in countries with low literacy rates.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 6
Fig. 7
Fig. 8

Data Availability

Data supporting the results can be obtained on request from the corresponding author.


  1. 1.

    De Vet HC, Terwee CB, Mokkink LB, Knol DL: Measurement in medicine: a practical guide: Cambridge University Press; 2011.

  2. 2.

    Reeve, B. B., Wyrwich, K. W., Wu, A. W., Velikova, G., Terwee, C. B., Snyder, C. F., et al. (2013). ISOQOL recommends minimum standards for patient-reported outcome measures used in patient-centered outcomes and comparative effectiveness research. Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation, 22(8), 1889–1905.

    Article  Google Scholar 

  3. 3.

    Aiyegbusi, O. L., Kyte, D., Cockwell, P., Anderson, N., & Calvert, M. (2017). A patient-centred approach to measuring quality in kidney care: patient-reported outcome measures and patient-reported experience measures. Current Opinion in Nephrology and Hypertension, 26(6), 442–449.

    PubMed  Article  Google Scholar 

  4. 4.

    Dudgeon, D. (2018). The Impact of Measuring Patient-Reported Outcome Measures on Quality of and Access to Palliative Care. Journal of Palliative Medicine, 21(S1), S76–S80.

    PubMed  Article  Google Scholar 

  5. 5.

    Bottomley, A., Reijneveld, J. C., Koller, M., Flechtner, H., Tomaszewski, K. A., Greimel, E., et al. (2019). Current state of quality of life and patient-reported outcomes research. European Journal of Cancer, 121, 55–63.

    PubMed  Article  Google Scholar 

  6. 6.

    Anker, S. D., Agewall, S., Borggrefe, M., Calvert, M., Jaime Caro, J., Cowie, M. R., et al. (2014). The importance of patient-reported outcomes: a call for their comprehensive integration in cardiovascular clinical trials. European Heart Journal, 35(30), 2001–2009.

    PubMed  Article  Google Scholar 

  7. 7.

    Maher, C., Latimer, J., & Costa, L. (2007). The relevance of cross-cultural adaptation and clinimetrics for physical therapy instruments. Brazilian Journal of Physical Therapy, 11, 245–252.

    Article  Google Scholar 

  8. 8.

    Kandula, N. R., Lauderdale, D. S., & Baker, D. W. (2007). Differences in self-reported health among Asians, Latinos, and non-Hispanic whites: the role of language and nativity. Annals of Epidemiology, 17(3), 191–198.

    PubMed  Article  Google Scholar 

  9. 9.

    Summers, R., Wang, S., Abd-El-Khalick, F., & Said, Z. (2019). Comparing Likert Scale Functionality Across Culturally and Linguistically Diverse Groups in Science Education Research: an Illustration Using Qatari Students’ Responses to an Attitude Toward Science Survey. International Journal of Science and Mathematics Education, 17(5), 885–903.

    Article  Google Scholar 

  10. 10.

    Hahn, E. A., & Cella, D. (2003). Health outcomes assessment in vulnerable populations: Measurement challenges and recommendations. Archives of Physical Medicine and Rehabilitation, 84(4 SUPPL. 2), S35–S42.

    PubMed  Article  Google Scholar 

  11. 11.

    Samuel, A. J., & Kanimozhi, D. (2019). Outcome measures used in patient with knee osteoarthritis: With special importance on functional outcome measures. International Journal Health Science (Qassim), 13(1), 52–60.

    Google Scholar 

  12. 12.

    Klokkerud, M., Dagfinrud, H., Uhlig, T., Dager, T. N., Furunes, K. A., Klokkeide, Å., et al. (2018). Developing and testing a consensus-based core set of outcome measures for rehabilitation in musculoskeletal diseases. Scandinavian Journal Of Rheumatology, 47(3), 225–234.

    CAS  PubMed  Article  Google Scholar 

  13. 13.

    Agans, R. P., Deeb-Sossa, N., & Kalsbeek, W. D. (2006). Mexican Immigrants and the Use of Cognitive Assessment Techniques in Questionnaire Development. Hispanic Journal of Behavioral Sciences, 28(2), 209–230.

    Article  Google Scholar 

  14. 14.

    Amery, R. (2017). Recognising the communication gap in Indigenous health care. Medical Journal of Australia, 207(1), 13–15.

    Article  Google Scholar 

  15. 15.

    Jull, J., & Giles, A. (2015). Minwaashin Lodge TAWsSC, Boyer Y, Stacey D: Cultural adaptation of a shared decision making tool with Aboriginal women: a qualitative study. BMC Medical Informatics and Decision Making, 15, 1–1.

    PubMed  PubMed Central  Article  Google Scholar 

  16. 16.

    Stapleton, H., Murphy, R., & Kildea, S. (2013). Lost in translation: staff and interpreters' experiences of the edinburgh postnatal depression scale with women from refugee backgrounds. Issues in Mental Health Nursing, 34(9), 648–657.

    PubMed  Article  Google Scholar 

  17. 17.

    Stasiak, K., Parkin, A., Seymour, F., Lambie, I., Crengle, S., Pasene-Mizziebo, E., et al. (2012). Measuring outcome in child and adolescent mental health services: Consumers’ views of measures. Clinical Child Psychology and Psychiatry, 18(4), 519–535.

    PubMed  Article  Google Scholar 

  18. 18.

    Nakigudde, J., Musisi, S., Ehnvall, A., Airaksinen, E., & Agren, H. (2009). Adaptation of the multidimensional scale of perceived social support in a Ugandan setting. Afr Health Sci, 9(1), S35–S41.

    PubMed  PubMed Central  Google Scholar 

  19. 19.

    Cremers, A. H. M., Welbie, M., Kranenborg, K., & Wittink, H. (2017). Deriving guidelines for designing interactive questionnaires for low-literate persons: development of a health assessment questionnaire. Universal Access in the Information Society, 16(1), 161–172.

    Article  Google Scholar 

  20. 20.

    El-Daly, I., Ibraheim, H., Rajakulendran, K., Culpan, P., & Bates, P. (2016). Are Patient-reported Outcome Measures in Orthopaedics Easily Read by Patients? Clinical Orthopaedics and Related Research, 474(1), 246–255.

    PubMed  Article  Google Scholar 

  21. 21.

    Bonevski, B., Randell, M., Paul, C., Chapman, K., Twyman, L., Bryant, J., et al. (2014). Reaching the hard-to-reach A systematic review of strategies for improving health and medical research with socially disadvantaged groups. BMC Medical Research Methodology.

    Article  PubMed  PubMed Central  Google Scholar 

  22. 22.

    Dambi, J. M., Jelsma, J., Mambo, T., & Chiwaridzo, M. (2017). Use of patient-reported outcomes in low-resource settings — lessons from the development and validation of the Zimbabwean Caregiver Burden Scale. European Journal of Physiotherapy, 19(sup1), 47–50.

    Article  Google Scholar 

  23. 23.

    Welbie, M., Wittink, H., Westerman, M. J., Topper, I., Snoei, J., & Devillé, W. L. (2018). Using Plain Language and Adding Communication Technology to an Existing Health-Related Questionnaire to Help Generate Accurate Information: Qualitative Study. Journal of Medical Internet Research, 20(4), e140–e140.

    PubMed  PubMed Central  Article  Google Scholar 

  24. 24.

    Fleischmann, M., & Vaughan, B. (2018). The challenges and opportunities of using patient reported outcome measures (PROMs) in clinical practice. International Journal of Osteopathic Medicine, 28, 56–61.

    Article  Google Scholar 

  25. 25.

    D'Aprano, A., Silburn, S., Johnston, V., Robinson, G., Oberklaid, F., & Squires, J. (2016). Adaptation of the Ages and Stages Questionnaire for Remote Aboriginal Australia. Qualitative Health Research, 26(5), 613–625.

    PubMed  Article  Google Scholar 

  26. 26.

    Stewart, A. L., Thrasher, A. D., Goldberg, J., & Shea, J. A. (2012). A framework for understanding modifications to measures for diverse populations. J Aging Health, 24(6), 992–1017.

    PubMed  PubMed Central  Article  Google Scholar 

  27. 27.

    Jahagirdar, D., Kroll, T., Ritchie, K., & Wyke, S. (2013). Patient-reported outcome measures for chronic obstructive pulmonary disease : the exclusion of people with low literacy skills and learning disabilities. Patient, 6(1), 11–21.

    PubMed  PubMed Central  Article  Google Scholar 

  28. 28.

    More Than One-Half of Children and Adolescents Are Not Learning Worldwide []

  29. 29.

    International Migration Report []

  30. 30.

    World Population Dashboard

  31. 31.

    Sharma S, Jensen MP: Cross-cultural adaptations of patient-reported outcome measures can be very useful. Annals of physical and rehabilitation medicine 2019.

  32. 32.

    Beaton, D. E., Bombardier, C., Guillemin, F., & Ferraz, M. B. (2000). Guidelines for the process of cross-cultural adaptation of self-report measures. Spine, 25(24), 3186–3191.

    CAS  PubMed  Article  Google Scholar 

  33. 33.

    Eremenco, S. L., Cella, D., & Arnold, B. J. (2005). A comprehensive method for the translation and cross-cultural validation of health status questionnaires. Evaluation & The Health Professions, 28(2), 212–232.

    Article  Google Scholar 

  34. 34.

    Weijters, B., Geuens, M., & Baumgartner, H. (2013). The Effect of Familiarity with the Response Category Labels on Item Response to Likert Scales. Journal of Consumer Research, 40(2), 368–381.

    Article  Google Scholar 

  35. 35.

    Flaskerud, J. H. (2012). Cultural Bias and Likert-Type Scales Revisited. Issues in Mental Health Nursing, 33(2), 130–132.

    PubMed  Article  Google Scholar 

  36. 36.

    Beckstead, J. W. (2014). On measurements and their quality Paper 4 Verbal anchors and the number of response options in rating scales. International Journal of Nursing Studies, 51(5), 807–814.

    PubMed  Article  Google Scholar 

  37. 37.

    Pathak, A., Sharma, S., & Jensen, M. P. (2018). The utility and validity of pain intensity rating scales for use in developing countries. Pain Rep, 3(5), e672.

    PubMed  PubMed Central  Article  Google Scholar 

  38. 38.

    Chang, E. M., Gillespie, E. F., & Shaverdian, N. (2019). Truthfulness in patient-reported outcomes: factors affecting patients' responses and impact on data quality. Patient Relat Outcome Meas, 10, 171–186.

    PubMed  PubMed Central  Article  Google Scholar 

  39. 39.

    Streiner DL, Norman GR, Cairney J: Health measurement scales: a practical guide to their development and use: Oxford University Press, USA; 2015.

  40. 40.

    Herr, K. A., Spratt, K., Mobily, P. R., & Richardson, G. (2004). Pain intensity assessment in older adults: use of experimental pain to compare psychometric properties and usability of selected pain scales with younger adults. Clinical Journal of Pain, 20(4), 207–219.

    Article  Google Scholar 

  41. 41.

    Mandysová P, Kadlečková Z: The performance of three pain intensity scales and their preferences among Czech women with acute postoperative pain. 2014.

  42. 42.

    Zhou, Y., Petpichetchian, W., & Kitrungrote, L. (2011). Psychometric properties of pain intensity scales comparing among postoperative adult patients, elderly patients without and with mild cognitive impairment in China. International Journal of Nursing Studies, 48(4), 449–457.

    PubMed  Article  Google Scholar 

  43. 43.

    Pathak, A., Sharma, S., & Jensen, M. P. (2018). The utility and validity of pain intensity rating scales for use in developing countries. Pain Reports, 3(5), e672.

    PubMed  PubMed Central  Article  Google Scholar 

  44. 44.

    Stratford, P., Gill, C., Westaway, M., & Binkley, J. (1995). Assessing Disability and Change on Individual Patients: A Report of a Patient Specific Measure. Physiotherapy Canada, 47(4), 258–263.

    Article  Google Scholar 

  45. 45.

    Horn, K. K., Jennings, S., Richardson, G., Vliet, D. V., Hefford, C., & Abbott, J. H. (2012). The patient-specific functional scale: psychometrics, clinimetrics, and application as a clinical outcome measure. Journal of Orthopaedic and Sports Physical Therapy, 42(1), 30–42.

    Article  Google Scholar 

  46. 46.

    Sharma, S., Palanchoke, J., & Abbott, J. H. (2018). Cross-cultural Adaptation and Validation of the Nepali Translation of the Patient-Specific Functional Scale. Journal of Orthopaedic and Sports Physical Therapy, 48(8), 659–664.

    Article  Google Scholar 

  47. 47.

    Yalcinkaya, G., & Kara, B. (2017). Arda M AB1201-HPR The validity and test-retest reliability of the turkish patient specific functional scale in chronic neck pain patients a preliminary report. Annals of the Rheumatic Diseases, 76(2), 1532–1532.

    Google Scholar 

  48. 48.

    Lehtola, V., Kaksonen, A., Luomajoki, H., Leinonen, V., Gibbons, S., & Airaksinen, O. (2013). Content validity and responsiveness of a Finnish version of the Patient-Specific Functional Scale. European Journal of Physiotherapy, 15(3), 134–138.

    Article  Google Scholar 

  49. 49.

    Abbott, J. H., & Schmitt, J. S. (2014). The Patient-Specific Functional Scale was valid for group-level change comparisons and between-group discrimination. Journal of Clinical Epidemiology, 67(6), 681–688.

    PubMed  Article  Google Scholar 

  50. 50.

    O'Shea, S. D., Taylor, N. F., & Paratz, J. D. (2005). Measuring changes in activity limitation and participation restriction in people with COPD. International Journal of Therapy & Rehabilitation, 12(6), 264–268.

    Article  Google Scholar 

  51. 51.

    Berghuis-Kelley, D., & Scherer, S. (2007). Research CornerOutcome Measures in Cardiopulmonary Physical Therapy: Use of the Patient Specific Functional Scale. Cardiopulmonary Physical Therapy Journal, 18(3), 21–23.

    Article  Google Scholar 

  52. 52.

    Wittboldt, S., Cider, A., & Back, M. (2016). Reliability of two questionnaires on physical function in patients with stable coronary artery disease. Eur J Cardiovasc Nurs, 15(2), 142–149.

    PubMed  Article  Google Scholar 

  53. 53.

    Siebers, A., Öberg, U., & Skargren, E. (2009). Improvement and impact of initial motor skill after intensive rehabilitation – CI-therapy in patients with chronic hemiplegia. A follow-up study. Advances in Physiotherapy, 8(4), 146–153.

    Article  Google Scholar 

  54. 54.

    Bohannon RW, Nair P, Green M: Feasibility and informativeness of the Patient-Specific Functional Scale with patients with Parkinson’s disease. Physiotherapy theory and practice 2019.

  55. 55.

    Statistics NCBo: Nepal - National Population & Housing Census 2011.

  56. 56.

    Creswell, J. W., & Plano Clark, V. L. (2011). Choosing a mixed methods design. Designing and conducting mixed methods research, 2, 53–106.

    Google Scholar 

  57. 57.

    Zhou, Y. A. (2019). mixed methods model of scale development and validation analysis. Measurement Interdisciplinary Research and Perspectives, 17(1), 38–47.

    Article  Google Scholar 

  58. 58.

    Biglan, A. (1991). Distressed behavior and its context. The Behavior Analyst, 14(2), 157–169.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  59. 59.

    Saunders, B., Sim, J., Kingstone, T., Baker, S., Waterfield, J., Bartlam, B., et al. (2018). Saturation in qualitative research: exploring its conceptualization and operationalization. Quality and Quantity, 52(4), 1893–1907.

    PubMed  Article  Google Scholar 

  60. 60.

    Perneger, T. V., Courvoisier, D. S., Hudelson, P. M., & Gayet-Ageron, A. (2015). Sample size for pre-tests of questionnaires. Quality of life research, 24(1), 147–151.

    PubMed  Article  Google Scholar 

  61. 61.

    Mokkink, L. B., Terwee, C. B., Patrick, D. L., Alonso, J., Stratford, P. W., Knol, D. L., et al. (2010). The COSMIN checklist for assessing the methodological quality of studies on measurement properties of health status measurement instruments: an international Delphi study. Quality of Life Research, 19(4), 539–549.

    PubMed  PubMed Central  Article  Google Scholar 

  62. 62.

    Van Der Veer, K., Ommundsen, R., Hak, T., & Larsen, K. S. (2003). Meaning Shift of Items in Different Language Versions A Cross-National Validation Study of the Illegal Aliens Scale. Quality and Quantity, 37(2), 193–206.

    Article  Google Scholar 

  63. 63.

    Pool, J. J. M., Hiralal, S., Ostelo, R. W. J. G., van der Veer, K., Vlaeyen, J. W. S., Bouter, L. M., et al. (2009). The applicability of the Tampa Scale of Kinesiophobia for patients with sub-acute neck pain: a qualitative study. Quality and Quantity, 43(5), 773–780.

    Article  Google Scholar 

  64. 64.

    1000minds software (, implementing the PAPRIKA method (Hansen & Ombler 2008).

  65. 65.

    Hansen, P., & Ombler, F. (2008). A new method for scoring additive multi-attribute value models using pairwise rankings of alternatives. Journal of Multi-Criteria Decision Analysis, 15(3–4), 87–107.

    Article  Google Scholar 

  66. 66.

    Lavrakas PJ: Paired Comparison Technique. In: Encyclopedia of Survey Research Methods. Thousand Oaks, CA: SAGE Publications Ltd; 2008.

  67. 67.

    Chandra Y, Shang L: Inductive Coding. In: Qualitative Research Using R: A Systematic Approach. edn. Edited by Chandra Y, Shang L. Singapore: Springer Singapore; 2019: 91–106.

  68. 68.

    Adedokun, O. A., & Burgess, W. D. (2012). Analysis of paired dichotomous data: A gentle introduction to the McNemar test in SPSS. Journal of MultiDisciplinary Evaluation, 8(17), 125–131.

    Google Scholar 

  69. 69.

    Zalmay, P. (2017). de CWAC: How do medical students use and understand pain rating scales? Scand J Pain, 15, 68–72.

    PubMed  Article  Google Scholar 

  70. 70.

    Yazici Sayin, Y., & Akyolcu, N. (2014). Comparison of pain scale preferences and pain intensity according to pain scales among Turkish Patients: a descriptive study. Pain Manag Nurs, 15(1), 156–164.

    PubMed  Article  Google Scholar 

  71. 71.

    Li, L., Herr, K., & Chen, P. (2009). Postoperative pain assessment with three intensity scales in Chinese elders. Journal of Nursing Scholarship, 41(3), 241–249.

    PubMed  Article  Google Scholar 

  72. 72.

    Li, L., Liu, X., & Herr, K. (2007). Postoperative pain intensity assessment: a comparison of four scales in Chinese adults. Pain Med, 8(3), 223–234.

    PubMed  Article  Google Scholar 

  73. 73.

    Herr, K., Spratt, K. F., Garand, L., & Li, L. (2007). Evaluation of the Iowa pain thermometer and other selected pain intensity scales in younger and older adult cohorts using controlled clinical pain: a preliminary study. Pain Med, 8(7), 585–600.

    PubMed  PubMed Central  Article  Google Scholar 

  74. 74.

    Amtmann, D., Liljenquist, K., Bamer, A., Bocell, F., Jensen, M., Wilson, R., et al. (2018). Measuring Pain Catastrophizing and Pain-Related Self-Efficacy: Expert Panels, Focus Groups, and Cognitive Interviews. The Patient - Patient-Centered Outcomes Research, 11(1), 107–117.

    PubMed  Article  Google Scholar 

  75. 75.

    Sharma, S., Pathak, A., Maharjan, R., Abbott, J. H., Correia, H., & Jensen, M. (2018). Psychometric properties of nepali versions of PROMIS short from measures of pain intensity, pain interference, pain behaviour, depressions, and sleep disturbance. The Journal of Pain, 19(3), S59.

    Google Scholar 

  76. 76.

    PROMIS® Instrument Development and Validation Scientific Standards Version 2.0 []

  77. 77.

    Hoopman, R., Terwee, C. B., Muller, M. J., Öry, F. G., & Aaronson, N. K. (2009). Methodological challenges in quality of life research among Turkish and Moroccan ethnic minority cancer patients: translation, recruitment and ethical issues. Ethnicity and Health, 14(3), 237–253.

    PubMed  Article  Google Scholar 

  78. 78.

    Chaves, F. F., Reis, I. A., & Pagano, A. S. (2017). Torres HdC: Translation, cross-cultural adaptation and validation of the Diabetes Empowerment Scale-Short Form. Revista de saude publica, 51, 16.

    PubMed  PubMed Central  Google Scholar 

  79. 79.

    Chachamovich, E., Fleck, M. P., & Power, M. (2009). Literacy affected ability to adequately discriminate among categories in multipoint Likert Scales. Journal of Clinical Epidemiology, 62(1), 37–46.

    PubMed  Article  Google Scholar 

  80. 80.

    Fang, J., Fleck, M. P., Green, A., McVilly, K., Hao, Y., Tan, W., et al. (2011). The response scale for the intellectual disability module of the WHOQOL: 5-point or 3-point? Journal of Intellectual Disability Research, 55(6), 537–549.

    CAS  PubMed  Article  Google Scholar 

  81. 81.

    Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological review, 63(2), 81.

    CAS  PubMed  Article  Google Scholar 

  82. 82.

    Gries, K., Berry, P., Harrington, M., Crescioni, M., Patel, M., Rudell, K., et al. (2018). Literature review to assemble the evidence for response scales used in patient-reported outcome measures. J Patient Rep Outcomes, 2(1), 41.

    PubMed  PubMed Central  Article  Google Scholar 

  83. 83.

    Vandenbosch, J., Van den Broucke, S., Vancorenland, S., Avalosse, H., Verniest, R., & Callens, M. (2016). Health literacy and the use of healthcare services in Belgium. Journal of Epidemiology and Community Health, 70(10), 1032–1038.

    PubMed  Article  Google Scholar 

  84. 84.

    Marcus, E. N. (2006). The Silent Epidemic — The Health Effects of Illiteracy. New England Journal of Medicine, 355(4), 339–341.

    CAS  Article  Google Scholar 

  85. 85.

    Cook, A., Roberts, D., Nelson, K., Clark, B. R., & Parker, B. E., Jr. (2018). Development of a pictorial scale for assessing functional interference with chronic pain: the Pictorial Pain Interference Questionnaire. Journal of Pain Research, 11, 1343–1354.

    PubMed  PubMed Central  Article  Google Scholar 

  86. 86.

    Sternberg, R. M., Nápoles, A. M., Gregorich, S., Paul, S., Lee, K. A., & Stewart, A. L. (2016). Development of the Stress of Immigration Survey: A Field Test Among Mexican Immigrant Women. Fam Community Health, 39(1), 40–52.

    PubMed  PubMed Central  Article  Google Scholar 

  87. 87.

    Ramos, S. R., Paintsil, E., Ofori-Atta, A., Kusah, J. T., Amissah, K. A., Alhassan, A., et al. (2020). Prototype Development, Usability, and Preference of a Culturally-relevant Pictorial Aid to Facilitate Comprehension of Likert-type Levels of Agreement in Caregivers of Children Living With HIV in Ghana. Computers, informatics, nursing : CIN, 38(1), 45–52.

    PubMed  Article  Google Scholar 

  88. 88.

    Shea, J. A., Guerra, C. E., Weiner, J., Aguirre, A. C., Ravenell, K. L., & Asch, D. A. (2008). Adapting a patient satisfaction instrument for low literate and Spanish-speaking populations: Comparison of three formats. Patient Education and Counseling, 73(1), 132–140.

    PubMed  Article  Google Scholar 

  89. 89.

    Hopkins D, King G: Improving Anchoring Vignettes: Designing Surveys to Correct Interpersonal Incomparability. Public Opinion Quarterly 2010:1–22.

  90. 90.

    Halstead, P., Arbuckle, R., Marshall, C., Zimmerman, B., Bolton, K., & Gelotte, C. (2020). Development and Content Validity Testing of Patient-Reported Outcome Items for Children to Self-Assess Symptoms of the Common Cold. The Patient—Patient-Centered Outcomes Research, 13(2), 235–250.

    PubMed  Article  Google Scholar 

  91. 91.

    Hicks, C. L., von Baeyer, C. L., Spafford, P. A., van Korlaar, I., & Goodenough, B. (2001). The Faces Pain Scale-Revised: toward a common metric in pediatric pain measurement. Pain, 93(2), 173–183.

    PubMed  Article  Google Scholar 

  92. 92.

    Guyatt, G. H., Townsend, M., Berman, L. B., & Keller, J. L. (1987). A comparison of Likert and visual analogue scales for measuring change in function. J Chronic Dis, 40(12), 1129–1133.

    CAS  PubMed  Article  Google Scholar 

  93. 93.

    Carod-Artal, F. J., Ferreira Coral, L., Stieven Trizotto, D., & Menezes Moreira, C. (2009). Self- and proxy-report agreement on the Stroke Impact Scale. Stroke, 40(10), 3308–3314.

    PubMed  Article  Google Scholar 

  94. 94.

    Haley, K. L., Womack, J. L., Harmon, T. G., McCulloch, K. L., & Faldowski, R. A. (2019). Life activity choices by people with aphasia: repeated interviews and proxy agreement. Aphasiology, 33(6), 710–730.

    Article  Google Scholar 

  95. 95.

    Schulte, F., Wurz, A., Reynolds, K., Strother, D., & Dewey, D. (2016). Quality of life in survivors of pediatric cancer and their siblings: the consensus between parent-proxy and self-reports. Pediatric Blood and Cancer, 63(4), 677–683.

    PubMed  Article  Google Scholar 

  96. 96.

    Griffiths, A. W., Smith, S. J., Martin, A., Meads, D., Kelley, R., & Surr, C. A. (2020). Exploring self-report and proxy-report quality-of-life measures for people living with dementia in care homes. Quality of Life Research, 29(2), 463–472.

    PubMed  Article  Google Scholar 

  97. 97.

    Laura N: An Exploration of Proxy- and Self-Reported Adolescent Health in Low-Resource Settings. Survey Research Methods 2016, 10(2).

  98. 98.

    Wurz, A., & Burnet, J. (2017). Evaluating Questionnaires Used to Assess Self-Reported Physical Activity and Psychosocial Outcomes Among Survivors of Adolescent and Young Adult Cancer: A Cognitive Interview Study. Journal of Adolescent and Young Adult Oncology, 6(3), 482–488.

    PubMed  Article  Google Scholar 

  99. 99.

    Thoomes-de Graaf, M., Fernández-De-Las-Peñas, C., & Cleland, J. A. (2019). The content and construct validity of the modified patient specific functional scale (PSFS 20) in individuals with neck pain. J Man Manip Ther, 28(1), 49–59.

    PubMed  PubMed Central  Article  Google Scholar 

  100. 100.

    Stevens, A., Moser, A., Köke, A., van der Weijden, T., & Beurskens, A. (2016). The patient's perspective of the feasibility of a patient-specific instrument in physiotherapy goal setting: a qualitative study. Patient Prefer Adherence, 10, 425–434.

    PubMed  PubMed Central  Article  Google Scholar 

  101. 101.

    Sharma, S., Palanchoke, J., Reed, D., & Haxby Abbott, J. (2017). Translation, cross-cultural adaptation and psychometric properties of the Nepali versions of numerical pain rating scale and global rating of change. Health Qual Life Outcomes, 15(1), 236.

    PubMed  PubMed Central  Article  Google Scholar 

  102. 102.

    Wright J, Moghaddam N, Dawson D: Cognitive Interviewing in Patient-Reported Outcome Measures: A Systematic Review of Methodological Processes. 2019.

  103. 103.

    Brod, M., Tesler, L. E., & Christensen, T. L. (2009). Qualitative research and content validity: developing best practices based on science and experience. Quality of Life Research, 18(9), 1263–1278.

    PubMed  Article  Google Scholar 

  104. 104.

    Patrick DL, Guyatt GH, Acquadro C: Patient‐reported outcomes. In: Cochrane Handbook for Systematic Reviews of Interventions: Version 510 [updated March 2011]. edn. Edited by Higgins JPT, Green S: The Cochrane Collaboration; 2011: 531–545.

  105. 105.

    Staniszewska, S., Haywood, K. L., Brett, J., & Tutton, L. (2012). Patient and Public Involvement in Patient-Reported Outcome Measures. The Patient - Patient-Centered Outcomes Research, 5(2), 79–87.

    PubMed  Article  Google Scholar 

  106. 106.

    Kosmidis, M. H., Zafiri, M., & Politimou, N. (2011). Literacy Versus Formal Schooling: Influence on Working Memory. Archives of Clinical Neuropsychology, 26(7), 575–582.

    PubMed  Article  Google Scholar 

  107. 107.

    Matteson, S. M., & Lincoln, Y. S. (2009). Using Multiple Interviewers in Qualitative Research Studies: The Influence of Ethic of Care Behaviors in Research Interview Settings. Qualitative Inquiry, 15(4), 659–674.

    Article  Google Scholar 

Download references


We would like to thank Miss. Natasha Shrestha, our research assistant, for her help in data collection and transcription. We would also like to the team members of the research committees and the physiotherapy departments at Annapurna Neurological Institute and Allied Health Sciences, Dhulikhel Hospital, and Nepal Mediciti Hospital, and Mr. Keshav Thapa and Rishi Dhakal for their support in participant recruitment. We would also like to thank Dr. Ross Wilson and Dr. Yana Pryymachenko at CMOR for their valuable feedback on the manuscript.


The primary author, Anupa Pathak, was supported in her capacity as a Ph.D. student by the University of Otago Doctoral scholarship. Daniel Cury Ribeiro is supported by The Sir Charles Hercus Health Research Fellowship (18/111) – Health Research Council of New Zealand.

Author information




AP and SS were involved in the conception of the study; all authors were involved in the study design and planning. AP conducted the data collection and AP, SS, and JHA were involved in data analysis. AP drafted the manuscript and all authors contributed to data interpretation and manuscript revisions.

Corresponding author

Correspondence to Anupa Pathak.

Ethics declarations

Conflict of interest

The authors declare no conflict of interest.

Ethical approval

We followed the ethical standard outlined by the 1964 Declaration of Helsinki and its later amendments while conducting the study. The University of Otago Human Ethics Committee-Health (H18/146), Nepal Health Research Council (Reg. No. 791/2018), and Kathmandu University School of Medical Sciences Institutional Review Committee (44/19) have approved this study.

Consent to participate

Consent forms were read aloud to the participants and written consent was obtained when possible. If a participant was unable to write, a witness signed on their behalf.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary file1 (PDF 1375 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Pathak, A., Sharma, S., Heinemann, A.W. et al. Development and assessment of a verbal response scale for the Patient-Specific Functional Scale (PSFS) in a low-literacy, non-western population. Qual Life Res 30, 613–628 (2021).

Download citation


  • Cross-cultural adaptation
  • Patient-specific functional scale
  • Patient-reported outcome
  • Functional assessment
  • Developing countries