Perceived Health Outcomes of Recreation Scale: Measurement Invariance over Gender
-
Elif Köse
,
Tennur Yerlisu Lapa
,
Nezaket Bilge Uzun
,
Evren Tercan Kaas
,
Emrah Serdar
,
Gökşen Aras
Abstract
Background: Research handling structural differences among groups presume that the measurement tool works similarly among the groups and the results of measurements provide similar psychometric properties. Therefore, the aim of the study is to provide evidence for measurement invariance of the construct validity Perceived Health Outcomes of Recreation Scale (PHORS).
Methods: The research sample consisted of a total of 1984 adults who exercise, including 864 women and 1120 men during 2021- 2022 in Antalya City, Turkey. The MI of the PHORS was tested by multigroup confirmatory factor analyses, which test the invariance of the covariance structures within the scope of structural equation modelling. Invariance tests were gradually conducted for the implicit variables in the model, CFI (comparative fit index criteria) and AIC (Akaike information criterion) were inquired between structural invariance, where no restriction was applied on the analyses and the other invariance tests (metric invariance, scalar invariance and string invariance respectively) where more restraints are applied.
Results: The study yielded evidence showing that the measurement model defined for the factor structure of the scale provided measurement invariance by gender. ∆CFI values were ≤0.010 in all subscales for metric and scalar invariance.
Conclusion: The items of PHORS represented the same psychological structure, different groups responded to the items in the same way, the constant values in regression equations generated for the items in regression equations were equal/invariable between the groups.
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12. Temel AS, Tukel Y (2021). Examining the health outcomes and happiness levels that result from engaging in physical recreation: A study on university students. International Journal of Research in Education and Science, 7(2): 545-61.
13. Hill E, Gómez E. (2020). Perceived health outcomes of mountain bikers: A national demographic inquiry. J Park Recreat Admi, 38(2): 31-44.
14. Korkmaz M, Somer O, Güngör D (2013). Measurement equivalence across gender with mean and covariance structure of five factor personality inventory for adolescent sample. Education and Science, 38(170): 121-134.
15. Mark BA, Wan TT (2005). Testing measurement equivalence in a patient satisfaction instrument. West. J. Nurs. Res, 27(6): 772–787.
16. Yerlisu Lapa T, Serdar E, Tercan Kaas E, et al (2020). Psychometric properties of perceived health outcomes of recreation scale-Turkish version. Hacettepe Journal of Sport Sciences, 31(2): 83-95.
17. Haladyna TM, Rodriguez MC (2013). Developing and validating test items. Routledge: Taylor & Francis. London.
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20. Fornell C, Larcker DF (1981). Evaluating structural equation models with unobservable variables and measurement error. J Mark Res, 18(1): 39-50.
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24. Kline P (1994). An easy guide to factor analysis. Routledge: Taylor & Francis. London.
25. Salkind NJ (2006). Encyclopedia of measurement and statistics. SAGE Publications: Road Thousand Oaks. California.
26. Craney TA, Surles JG (2002). Model-dependent variance inflation factor cut off values. Qual Eng, 14(3): 391-403.
27. Paulson DS (2006). Handbook of regression and modeling: Applications for the clinical and pharmaceutical industries. Chapman and Hall/CRC. New York.
28. De Boer MR, Moll AC, De Vet HCW et al (2004). Psychometric properties of vision-related quality of life questionnaires: A systematic review. Ophthalmic Physiol Opt, 24(4): 257-73.
29. Veenhof C, Bijlsma JW, Van den Ende CH, et al (2006). Psychometric evaluation of osteoarthritis questionnaires: A systematic review of the literature. Arthritis Rheum, 55(3): 480–92.
30. Kline RB (2005). Principles and practice of structural equation modeling. 2nd ed. Guilford Press. New York.
31. Baumgartner H, Homburg C (1996). Applications of structural equation modeling in marketing and consumer research: A review. Int J Res Mark, 13(2): 139-61.
32. Bentler PM, Bonett DG (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychol Bull, 88(3): 588-606.
33. Marsh HW, Hau K-T, Artelt C (2006). OECD's brief self-report measure of educational psychology's most useful affective constructs: Cross-cultural, psychometric comparisons across 25 countries. Int J Test, 6(4): 311-60.
34. Browne MW, Cudeck R (1992). Alternative ways of assessing model fit. Social Methods Res, 21(2): 230-58.
35. Prinsen CAC, Mokkink LB, Bouter LM et al (2018). COSMIN guideline for systematic reviews of patient-reported outcome measures. Qual Life Res, 27(5): 1147-57.
36. Horn JL, McArdle JJ, Mason R. (1983). When is invariance not invariant: A practical scientist’s look at the ethereal concept of factor invariance. The Southern Psychologist, 1(4): 179-88.
37. Başusta B (2010). Measurement invariance. J Meas Eval Educ Psychol, 1(2): 58-64.
38. Chen FF, Sousa KH, West SG (2005). Testing measurement invariance of second-order factor models. Struct Equ Modeling, 12(3): 471-92.
39. Steenkamp J-BEM, Baumgartner H (1998). Assessing measurement invariance in cross-national consumer research. J Consum Res, 25(1): 78-90.
40. Tucker KL, Ozer DJ, Lyubomirsky S, et al (2006). Testing for measurement invariance in the satisfaction with life scale: A comparison of Russians and North Americans. Soc Indic Res, 78(2), 341-60.
41. Önen E. Examination of measurement invariance with structural equation modelling techniques [PhD thesis]. Ankara University, Türkiye; 2009.
42. Dimitrov D (2010). Testing for factorial invariance in the context of construct validation. Meas Eval Couns Dev, 43(2): 121-49.
43. Cheung GW, Rensvold RB (2000). Assessing extreme and acquiescence response sets in cross-cultural research using structural equations modeling. J Cross-Cult Psychol, 31(2): 187-212.
44. Cheung GW, Rensvold RB (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Struct Equ Modeling, 9(2): 233-55.
45. Chen FF (2007). Sensitivity of goodness of fit indices to lack of measurement invariance. Struct Equ Modeling, 14(3): 464-504.
46. Wu AD, Li Z, Zumbo, BD (2007). Decoding the meaning of factorial invariance and updating the practice of multi-group confirmatory factor analysis: A demonstration with TIMSS data. Pract Assess Res Evaluation, 12(3): 1-26.
47. Quintana SM, Maxwell SE (1999). Implications of recent developments in structural equation modeling for counseling psychology. Couns Psychol, 27(4): 485-527.
48. Meade AW, Michels LC, Lautenschlager GJ (2007). Are internet and paper-and-pencil personality tests truly comparable? An experimental design measurement invariance study. Organ Res Methods, 10(2): 322-45.
49. Vandenberg RJ, Lance CE (2000). A review and synthesis of the measurement invariance literature: suggestions, practices, and recommendations for organizational research. Organ Res Methods, 3(1): 4-70.
50. Lin YJ, Tzeng WN (2009). Modelling the growth of Japanese eel Anguilla Japonica in the lower reach of the Kao-Ping River, Southern Taiwan: An information theory approach. J Fish Biol, 75(1): 100-12.
51. Zhu L, Li L, Liang Z (2009). Comparison of six statistical approaches in the selection of appropriate fish growth models. Chin J Ocean Limnol, 27: 457.
52. Burnham KP, Anderson DR (2002). Model selection and multimodel inference: A practical information-theoretic approach. Springer-Verlag. New York.
53. Vandenberg RJ, Lance CE (1998). A summary of the issues underlying measurement equivalence and their implications for interpreting group differences. In 1998 Research Methods Forum, (3): 1-10.
54. Bryne BM, Watkins D (2003). The issue of measurement invariance revisited. J Cross-Cult Psychol, 34(2): 155-75.
55. Cheung GW (2007). Testing equivalence in the structure, means, and variances of higher-order constructs with structural equation modeling. Organ Res Methods, 11(3): 593-613.
56. Hill E, Ahl P, Gabriele C, et al (2018). Perceived health outcomes of college climbers: Exploring why they climb. Journal of Outdoor Recreation, Education, and Leadership, 10(3): 259-62.
57. Beşikçi T, Emir E, Özdemir E, et al (2021). Investigation of psychological resilience levels of individuals and perceived health outcomes of recreation during the covid-19 pandemic process. Journal of Sport Sciences Researches, 6(2): 447-58.
2. Eskiler E, Yıldız Y, Ayhan C (2019). The effect of leisure benefits on leisure satisfaction: Extreme sports. Turkish Journal of Sport and Exercise, 21(1): 16-20.
3. Kao, CH (1995). A three-factor model of leisure benefits. Journal of Outdoor Recreation Study, 8(1): 67-78.
4. Gómez E, Hill E, Zhu X, et al (2016). Perceived health outcomes of recreation scale (PHORS): reliability, validity and invariance. Meas Phys Educ Exerc Sci, 20(1): 27-37.
5. Gómez E, Hill, E (2016). First landing state park: Participation patterns and perceived health outcomes of recreation at an urban-proximate park. J Park Recreat Admi, 34(1): 68-83.
6. Wu I-C (N), Liu, H-L(S), Cox, MA (2018). An exploration of perceived health outcomes of state park visitors in Oklahoma. Recreation, Parks, and Tourism in Public Health, 2, 57-64.
7. Hill E, Morgan T, Hooper B (2018). Hosting triathlons on a college campus: Perceived health outcomes and satisfaction. Journal of Outdoor Recreation, Education, and Leadership, 10(3): 256-8.
8. McIntosh T, Hill E, Morgan T (2019). Hosting triathlons on a college campus: Perceived health outcomes and values. Journal of Outdoor Recreation, Education, and Leadership, 11(3): 262-4.
9. Berry C, Ahl P, Hill E, et al (2019). Examining the health outcomes of college climbers: Applying the perceived health outcomes of recreation scale. Journal of Outdoor Recreation, Education, and Leadership, 11(3): 258–61.
10. Elçi G, Doğan M, Gürbüz B (2019). Investigation the level of individuals’ perceived health outcomes of recreation and life satisfaction. International Journal of Sport Exercise and Training Sciences, 5(3): 93-106.
11. Serdar E (2021). Perceived health outcomes of recreation, exercise dependence, and life satisfaction, Balt J Health Phys Act, 13(5): 43-50.
12. Temel AS, Tukel Y (2021). Examining the health outcomes and happiness levels that result from engaging in physical recreation: A study on university students. International Journal of Research in Education and Science, 7(2): 545-61.
13. Hill E, Gómez E. (2020). Perceived health outcomes of mountain bikers: A national demographic inquiry. J Park Recreat Admi, 38(2): 31-44.
14. Korkmaz M, Somer O, Güngör D (2013). Measurement equivalence across gender with mean and covariance structure of five factor personality inventory for adolescent sample. Education and Science, 38(170): 121-134.
15. Mark BA, Wan TT (2005). Testing measurement equivalence in a patient satisfaction instrument. West. J. Nurs. Res, 27(6): 772–787.
16. Yerlisu Lapa T, Serdar E, Tercan Kaas E, et al (2020). Psychometric properties of perceived health outcomes of recreation scale-Turkish version. Hacettepe Journal of Sport Sciences, 31(2): 83-95.
17. Haladyna TM, Rodriguez MC (2013). Developing and validating test items. Routledge: Taylor & Francis. London.
18. Hair JF, Black W, Babin BJ, et al (2006). Multivariate data analysis. 6th ed. Upper Saddle River: Prentice Hall. New Jersey.
19. Raykov T (1998). Coefficient Alpha and composite reliability with interrelated nonhomogeneous items. Appl Psychol Meas, 22(4): 375-85.
20. Fornell C, Larcker DF (1981). Evaluating structural equation models with unobservable variables and measurement error. J Mark Res, 18(1): 39-50.
21. Mertler CA, Vannatta RA (2016). Advanced and multivariate statistical methods: Practical application and interpretation. Routledge: Taylor & Francis. London.
22. Rosenthal R, Rosnow RL (2008). Essentials of behavioral research: Methods and data analysis. 3rd ed. McGraw-Hill. New York.
23. Comrey A, Lee H (1992). A first course in factor analysis. Hillsdale, NJ: Erlbaum.
24. Kline P (1994). An easy guide to factor analysis. Routledge: Taylor & Francis. London.
25. Salkind NJ (2006). Encyclopedia of measurement and statistics. SAGE Publications: Road Thousand Oaks. California.
26. Craney TA, Surles JG (2002). Model-dependent variance inflation factor cut off values. Qual Eng, 14(3): 391-403.
27. Paulson DS (2006). Handbook of regression and modeling: Applications for the clinical and pharmaceutical industries. Chapman and Hall/CRC. New York.
28. De Boer MR, Moll AC, De Vet HCW et al (2004). Psychometric properties of vision-related quality of life questionnaires: A systematic review. Ophthalmic Physiol Opt, 24(4): 257-73.
29. Veenhof C, Bijlsma JW, Van den Ende CH, et al (2006). Psychometric evaluation of osteoarthritis questionnaires: A systematic review of the literature. Arthritis Rheum, 55(3): 480–92.
30. Kline RB (2005). Principles and practice of structural equation modeling. 2nd ed. Guilford Press. New York.
31. Baumgartner H, Homburg C (1996). Applications of structural equation modeling in marketing and consumer research: A review. Int J Res Mark, 13(2): 139-61.
32. Bentler PM, Bonett DG (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychol Bull, 88(3): 588-606.
33. Marsh HW, Hau K-T, Artelt C (2006). OECD's brief self-report measure of educational psychology's most useful affective constructs: Cross-cultural, psychometric comparisons across 25 countries. Int J Test, 6(4): 311-60.
34. Browne MW, Cudeck R (1992). Alternative ways of assessing model fit. Social Methods Res, 21(2): 230-58.
35. Prinsen CAC, Mokkink LB, Bouter LM et al (2018). COSMIN guideline for systematic reviews of patient-reported outcome measures. Qual Life Res, 27(5): 1147-57.
36. Horn JL, McArdle JJ, Mason R. (1983). When is invariance not invariant: A practical scientist’s look at the ethereal concept of factor invariance. The Southern Psychologist, 1(4): 179-88.
37. Başusta B (2010). Measurement invariance. J Meas Eval Educ Psychol, 1(2): 58-64.
38. Chen FF, Sousa KH, West SG (2005). Testing measurement invariance of second-order factor models. Struct Equ Modeling, 12(3): 471-92.
39. Steenkamp J-BEM, Baumgartner H (1998). Assessing measurement invariance in cross-national consumer research. J Consum Res, 25(1): 78-90.
40. Tucker KL, Ozer DJ, Lyubomirsky S, et al (2006). Testing for measurement invariance in the satisfaction with life scale: A comparison of Russians and North Americans. Soc Indic Res, 78(2), 341-60.
41. Önen E. Examination of measurement invariance with structural equation modelling techniques [PhD thesis]. Ankara University, Türkiye; 2009.
42. Dimitrov D (2010). Testing for factorial invariance in the context of construct validation. Meas Eval Couns Dev, 43(2): 121-49.
43. Cheung GW, Rensvold RB (2000). Assessing extreme and acquiescence response sets in cross-cultural research using structural equations modeling. J Cross-Cult Psychol, 31(2): 187-212.
44. Cheung GW, Rensvold RB (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Struct Equ Modeling, 9(2): 233-55.
45. Chen FF (2007). Sensitivity of goodness of fit indices to lack of measurement invariance. Struct Equ Modeling, 14(3): 464-504.
46. Wu AD, Li Z, Zumbo, BD (2007). Decoding the meaning of factorial invariance and updating the practice of multi-group confirmatory factor analysis: A demonstration with TIMSS data. Pract Assess Res Evaluation, 12(3): 1-26.
47. Quintana SM, Maxwell SE (1999). Implications of recent developments in structural equation modeling for counseling psychology. Couns Psychol, 27(4): 485-527.
48. Meade AW, Michels LC, Lautenschlager GJ (2007). Are internet and paper-and-pencil personality tests truly comparable? An experimental design measurement invariance study. Organ Res Methods, 10(2): 322-45.
49. Vandenberg RJ, Lance CE (2000). A review and synthesis of the measurement invariance literature: suggestions, practices, and recommendations for organizational research. Organ Res Methods, 3(1): 4-70.
50. Lin YJ, Tzeng WN (2009). Modelling the growth of Japanese eel Anguilla Japonica in the lower reach of the Kao-Ping River, Southern Taiwan: An information theory approach. J Fish Biol, 75(1): 100-12.
51. Zhu L, Li L, Liang Z (2009). Comparison of six statistical approaches in the selection of appropriate fish growth models. Chin J Ocean Limnol, 27: 457.
52. Burnham KP, Anderson DR (2002). Model selection and multimodel inference: A practical information-theoretic approach. Springer-Verlag. New York.
53. Vandenberg RJ, Lance CE (1998). A summary of the issues underlying measurement equivalence and their implications for interpreting group differences. In 1998 Research Methods Forum, (3): 1-10.
54. Bryne BM, Watkins D (2003). The issue of measurement invariance revisited. J Cross-Cult Psychol, 34(2): 155-75.
55. Cheung GW (2007). Testing equivalence in the structure, means, and variances of higher-order constructs with structural equation modeling. Organ Res Methods, 11(3): 593-613.
56. Hill E, Ahl P, Gabriele C, et al (2018). Perceived health outcomes of college climbers: Exploring why they climb. Journal of Outdoor Recreation, Education, and Leadership, 10(3): 259-62.
57. Beşikçi T, Emir E, Özdemir E, et al (2021). Investigation of psychological resilience levels of individuals and perceived health outcomes of recreation during the covid-19 pandemic process. Journal of Sport Sciences Researches, 6(2): 447-58.
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| Issue | Vol 51 No 11 (2022) | |
| Section | Original Article(s) | |
| DOI | https://doi.org/10.18502/ijph.v51i11.11173 | |
| Keywords | ||
| Perceived health outcomes Measurement invariance Gender | ||
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How to Cite
1.
Köse E, Yerlisu Lapa T, Uzun NB, Tercan Kaas E, Serdar E, Aras G. Perceived Health Outcomes of Recreation Scale: Measurement Invariance over Gender. Iran J Public Health. 2022;51(11):2555-2563.
