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Mediating effect of post-stroke depression between activities of daily living and health-related quality of life: meta-analytic structural equation modeling

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Abstract

Background

Stroke survivors face various problems that affect their health-related quality of life (HRQoL). Reduced activities of daily living (ADL) may contribute to post-stroke depression (PSD) and low HRQoL, and depression might be associated with low HRQoL. However, these relationships are not well known. This study aimed to analyze correlations among ADL, PSD, and HRQoL in stroke survivors and further explore the mediating role of PSD between ADL and HRQoL.

Methods

This study utilized meta-analytic structural equation modeling (MASEM) on systematically searched articles from six electronic databases, namely PubMed, Embase, the Cochrane Library, China National Knowledge Infrastructure (China), Wanfang database (China), and SinoMed (China), from inception up to July 31, 2021. Two researchers independently assessed study eligibility, and data from the eligible studies were encoded and assessed for quality. MASEM was utilized to examine correlations among ADL, PSD, and HRQoL, with an estimation of a pooled correlation matrix under a random-effects model. The matrix was directly fitted to a structural equation model using webMASEM.

Results

In total, 8580 articles were screened, and data from 27 studies involving 33 effect sizes were used in the MASEM analysis. Correlations among the three variables were significant (both P < 0.01). Furthermore, PSD partially mediated the correlation between ADL and HRQoL (β = 0.24, 95% confidence interval 0.15–0.30).

Conclusions

The findings suggest that both decreased ADL and PSD may reduce HRQoL, while a decrease in ADL tends to cause depression after stroke. Therefore, ADL and PSD reductions should be improved to achieve better HRQoL of stroke survivors. Future studies should continue to discuss other factors affecting HRQoL to achieve optimal recovery in stroke survivors.

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Abbreviations

MASEM:

Meta-analytic structural equation modeling

ADL:

Activities of daily living

PSD:

Post-stroke depression

QoL:

Quality of life

HRQoL:

Health-related quality of life

CMV:

Common method variance

References

  1. Johnson, W., Onuma, O., Owolabi, M., & Sachdev, S. (2016). Stroke: A global response is needed. Bulletin of the World Health Organization, 94(9), 634-634A. https://doi.org/10.2471/BLT.16.181636

    Article  PubMed  PubMed Central  Google Scholar 

  2. GBD. (2021). Global, regional, and national burden of stroke and its risk factors, 1990–2019: A systematic analysis for the Global Burden of Disease Study 2019. The Lancet Neurology, 20(10), 795–820. https://doi.org/10.1016/s1474-4422(21)00252-0

    Article  CAS  Google Scholar 

  3. Wan, X., Chau, J. P. C., Mou, H., & Liu, X. (2021). Effects of peer support interventions on physical and psychosocial outcomes among stroke survivors: A systematic review and meta-analysis. International Journal of Nursing Studies, 121, 104001. https://doi.org/10.1016/j.ijnurstu.2021.104001

    Article  PubMed  Google Scholar 

  4. Ahmed, T., Kumar, R., & Bahurupi, Y. (2020). Factors affecting quality of life among post-stroke patients in the sub-Himalayan region. Journal of Neurosciences in Rural Practice, 11(4), 616–622. https://doi.org/10.1055/s-0040-1716927

    Article  PubMed  PubMed Central  Google Scholar 

  5. Oliveira, C., de Silva, N. T., Ungar, W. J., Bayoumi, A. M., Avitzur, Y., Hoch, J. S., et al. (2020). Health-related quality of life in neonates and infants: A conceptual framework. Quality of Life Research: An International Journal of Quality of Life Aspects of Treatment, Care and Rehabilitation, 29(5), 1159–1168. https://doi.org/10.1007/s11136-020-02432-6

    Article  PubMed  Google Scholar 

  6. Zhu, W., & Jiang, Y. (2019). Determinants of quality of life in patients with hemorrhagic stroke; A path analysis. Medicine (United States). https://doi.org/10.1097/MD.0000000000013928

    Article  PubMed Central  Google Scholar 

  7. Wilson, I. B., & Cleary, P. D. (1995). Linking clinical variables with health-related quality of life. A conceptual model of patient outcomes. JAMA, 273(1), 59–65.

    Article  CAS  PubMed  Google Scholar 

  8. Mlinac, M. E., & Feng, M. C. (2016). Assessment of activities of daily living, self-care, and independence. Archives of Clinical Neuropsychology, 31(6), 506–516. https://doi.org/10.1093/arclin/acw049

    Article  PubMed  Google Scholar 

  9. Zhang, Q., Schwade, M., Smith, Y., Wood, R., & Young, L. (2020). Exercise-based interventions for post-stroke social participation: A systematic review and network meta-analysis. International Journal of Nursing Studies, 111, 103738. https://doi.org/10.1016/j.ijnurstu.2020.103738

    Article  PubMed  Google Scholar 

  10. Medeiros, G. C., Roy, D., Kontos, N., & Beach, S. R. (2020). Post-stroke depression: A 2020 updated review. General Hospital Psychiatry, 66, 70–80. https://doi.org/10.1016/j.genhosppsych.2020.06.011

    Article  PubMed  Google Scholar 

  11. Mitchell, A. J., Sheth, B., Gill, J., Yadegarfar, M., Stubbs, B., Yadegarfar, M., et al. (2017). Prevalence and predictors of post-stroke mood disorders: A meta-analysis and meta-regression of depression, anxiety and adjustment disorder. General Hospital Psychiatry, 47, 48–60. https://doi.org/10.1016/j.genhosppsych.2017.04.001

    Article  PubMed  Google Scholar 

  12. Kirkevold, M., Bronken, B. A., Martinsen, R., & Kvigne, K. (2012). Promoting psychosocial well-being following a stroke: Developing a theoretically and empirically sound complex intervention. International Journal of Nursing Studies, 49(4), 386–397. https://doi.org/10.1016/j.ijnurstu.2011.10.006

    Article  PubMed  Google Scholar 

  13. He, M., Ma, J., Ren, Z., Zhou, G., Gong, P., Liu, M., et al. (2019). Association between activities of daily living disability and depression symptoms of middle-aged and older Chinese adults and their spouses: A community based study. Journal of Affective Disorders, 242, 135–142. https://doi.org/10.1016/j.jad.2018.08.060

    Article  PubMed  Google Scholar 

  14. De Ryck, A., Brouns, R., Fransen, E., Geurden, M., Van Gestel, G., Wilssens, I., et al. (2013). A prospective study on the prevalence and risk factors of poststroke depression. Cerebrovascular Diseases Extra, 3(1), 1–13. https://doi.org/10.1159/000345557

    Article  PubMed  PubMed Central  Google Scholar 

  15. Kawada, S., & Goto, R. (2017). Relationship between psychophysiological factors and prognosis for activities of daily living in patients with stroke in a recovery rehabilitation unit: A preliminary study. Journal of Physical Therapy Science, 29(12), 2206–2209. https://doi.org/10.1589/jpts.29.2206

    Article  PubMed  PubMed Central  Google Scholar 

  16. Vojtikiv-Samoilovska, D., & Arsovska, A. (2018). Prevalence and predictors of depression after stroke—Results from a prospective study. Open Access Macedonian Journal of Medical Sciences, 6(5), 824–828. https://doi.org/10.3889/oamjms.2018.182

    Article  PubMed  PubMed Central  Google Scholar 

  17. Souza, A. C., Rocha, M. O., Teixeira, A. L., Dias Júnior, J. O., Sousa, L. A., & Nunes, M. C. (2013). Depressive symptoms and disability in chagasic stroke patients: Impact on functionality and quality of life. Journal of the Neurological Sciences, 324(1–2), 34–37. https://doi.org/10.1016/j.jns.2012.09.022

    Article  PubMed  Google Scholar 

  18. Hunter, J., & Schmidt, F. (2004). Methods of meta-analysis corrected error and bias in research findings. SAGE Publications Inc.

    Google Scholar 

  19. Langhammer, B., Stanghelle, J. K., & Lindmark, B. (2008). Exercise and health-related quality of life during the first year following acute stroke. A randomized controlled trial. Brain Injury, 22(2), 135–145. https://doi.org/10.1080/02699050801895423

    Article  PubMed  Google Scholar 

  20. Kim, J. S., Choi-Kwon, S., Kwon, S. U., Lee, H. J., Park, K. A., & Seo, Y. S. (2005). Factors affecting the quality of life after ischemic stroke: Young versus old patients. Journal of Clinical Neurology (Seoul, Korea), 1(1), 59–68. https://doi.org/10.3988/jcn.2005.1.1.59

    Article  CAS  PubMed  Google Scholar 

  21. Hartley, T., Burger, M., & Inglis-Jassiem, G. (2022). Post stroke health-related quality of life, stroke severity and function: A longitudinal cohort study. African Journal of Disability, 11, 947. https://doi.org/10.4102/ajod.v11i0.947

    Article  PubMed  PubMed Central  Google Scholar 

  22. Naess, H., Lunde, L., & Brogger, J. (2012). The effects of fatigue, pain, and depression on quality of life in ischemic stroke patients: The Bergen Stroke Study. Vascular Health and Risk Management, 8, 407–413. https://doi.org/10.2147/vhrm.S32780

    Article  PubMed  PubMed Central  Google Scholar 

  23. Bello, U. M., Chutiyami, M., Salihu, D., Abdu, S. I., Tafida, B. A., Jabbo, A. A., et al. (2021). Quality of life of stroke survivors in Africa: A systematic review and meta-analysis. Quality of Life Research: An International Journal of Quality of Life Aspects of Treatment, Care and Rehabilitation, 30(1), 1–19. https://doi.org/10.1007/s11136-020-02591-6

    Article  PubMed  Google Scholar 

  24. Kim, E. S., Kim, J. W., Kang, H. J., Bae, K. Y., Kim, S. W., Kim, J. T., et al. (2018). Longitudinal impact of depression on quality of life in stroke patients. Psychiatry Investigation, 15(2), 141–146. https://doi.org/10.30773/pi.2017.10.11

    Article  PubMed  Google Scholar 

  25. Haghgoo, H. A., Pazuki, E. S., Hosseini, A. S., & Rassafiani, M. (2013). Depression, activities of daily living and quality of life in patients with stroke. Journal of the Neurological Sciences, 328(1–2), 87–91. https://doi.org/10.1016/j.jns.2013.02.027

    Article  PubMed  Google Scholar 

  26. Chan, S. H., Pan, Y., Xu, Y., & Yeung, K. C. (2021). Life satisfaction of 511 elderly Chinese stroke survivors: Moderating roles of social functioning and depression in a quality of life model. Clinical Rehabilitation, 35(2), 302–313. https://doi.org/10.1177/0269215520956908

    Article  PubMed  Google Scholar 

  27. Ayerbe, L., Ayis, S., Wolfe, C. D., & Rudd, A. G. (2013). Natural history, predictors and outcomes of depression after stroke: Systematic review and meta-analysis. The British Journal of Psychiatry: The Journal of Mental Science, 202(1), 14–21. https://doi.org/10.1192/bjp.bp.111.107664

    Article  PubMed  Google Scholar 

  28. Jak, S., & Cheung, M. W. (2020). Meta-analytic structural equation modeling with moderating effects on SEM parameters. Psychological Methods, 25(4), 430–455. https://doi.org/10.1037/met0000245

    Article  PubMed  Google Scholar 

  29. Kraft, P., & Bausch, A. (2016). How do transformational leaders promote exploratory and exploitative innovation? Examining the black box through MASEM. Journal of Product Innovation Management, 33(6), 687–707. https://doi.org/10.1111/jpim.12335

    Article  Google Scholar 

  30. Gómez-Gallego, M., Gómez-García, J., & Ato-Lozano, E. (2017). The mediating role of depression in the association between disability and quality of life in Alzheimer’s disease. Aging & Mental Health, 21(2), 163–172. https://doi.org/10.1080/13607863.2015.1093603

    Article  Google Scholar 

  31. Schwarzer, R. (1988). Meta-analysis programs. Behavior Research Methods, Instruments, & Computers, 20(3), 338–338. https://doi.org/10.3758/BF03203853

    Article  Google Scholar 

  32. Peterson, R. A., & Brown, S. P. (2005). On the use of beta coefficients in meta-analysis. The Journal of Applied Psychology, 90(1), 175–181. https://doi.org/10.1037/0021-9010.90.1.175

    Article  PubMed  Google Scholar 

  33. Rupinski, M. T., & Dunlap, W. P. (2016). Approximating Pearson product-moment correlations from Kendall’s tau and Spearman’s rho. Educational and Psychological Measurement, 56(3), 419–429. https://doi.org/10.1177/0013164496056003004

    Article  Google Scholar 

  34. Yonker, J. E., Schnabelrauch, C. A., & Dehaan, L. G. (2012). The relationship between spirituality and religiosity on psychological outcomes in adolescents and emerging adults: A meta-analytic review. Journal of Adolescence, 35(2), 299–314. https://doi.org/10.1016/j.adolescence.2011.08.010

    Article  PubMed  Google Scholar 

  35. Tehrani, H. D., & Yamini, S. (2020). Dataset of parenting practices, self-control and anti-social behaviors: Meta-analytic structural equation modeling. Data in Brief, 32, 106114. https://doi.org/10.1016/j.dib.2020.106114

    Article  PubMed  PubMed Central  Google Scholar 

  36. Cicolini, G., Comparcini, D., & Simonetti, V. (2014). Workplace empowerment and nurses’ job satisfaction: A systematic literature review. Journal of Nursing Management, 22(7), 855–871. https://doi.org/10.1111/jonm.12028

    Article  PubMed  Google Scholar 

  37. Hunter, J., & Hamilton, M. (2006). The advantages of using standardized scores in causal analysis. Human Communication Research, 28, 552–561. https://doi.org/10.1111/j.1468-2958.2002.tb00823.x

    Article  Google Scholar 

  38. Cheung, M. W., & Cheung, S. F. (2016). Random-effects models for meta-analytic structural equation modeling: Review, issues, and illustrations. Research Synthesis Methods, 7(2), 140–155. https://doi.org/10.1002/jrsm.1166

    Article  PubMed  Google Scholar 

  39. Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. R. (2009). Introduction to meta-analysis. Wiley.

    Book  Google Scholar 

  40. Viswesvaran, C., & Ones, D. (1995). Theory testing: Combining psychometric meta-analysis and structural equations modeling. Personnel Psychology, 48, 865–885. https://doi.org/10.1111/j.1744-6570.1995.tb01784.x

    Article  Google Scholar 

  41. Jak, S., Li, H., Kolbe, L., de Jonge, H., & Cheung, M. W. (2021). Meta-analytic structural equation modeling made easy: A tutorial and web application for one-stage MASEM. Research Synthesis Methods, 12(5), 590–606. https://doi.org/10.1002/jrsm.1498

    Article  PubMed  PubMed Central  Google Scholar 

  42. Morris, J. H., van Wijck, F., Joice, S., & Donaghy, M. (2013). Predicting health related quality of life 6 months after stroke: The role of anxiety and upper limb dysfunction. Disability and Rehabilitation, 35(4), 291–299. https://doi.org/10.3109/09638288.2012.691942

    Article  PubMed  Google Scholar 

  43. Gunaydin, R., Karatepe, A. G., Kaya, T., & Ulutas, O. (2011). Determinants of quality of life (QoL) in elderly stroke patients: A short-term follow-up study. Archives of Gerontology and Geriatrics, 53(1), 19–23. https://doi.org/10.1016/j.archger.2010.06.004

    Article  PubMed  Google Scholar 

  44. Mou, H., Wong, M. S., & Chien, W. T. P. (2021). Effectiveness of dyadic psychoeducational intervention for stroke survivors and family caregivers on functional and psychosocial health: A systematic review and meta-analysis. International Journal of Nursing Studies, 120, 103969. https://doi.org/10.1016/j.ijnurstu.2021.103969

    Article  PubMed  Google Scholar 

  45. Wang, H., Wen, Q., Chen, X., Chen, L., & Li, H. (2016). Analysis of depression status and influencing factors in senile stroke patients. Chinese Journal of Rehabilitation Medicine, 27(4), 339–343. https://doi.org/10.16460/j.issn1008-9969.2016.23.048

    Article  Google Scholar 

  46. Byeon, H., & Koh, H. W. (2016). The relationship between communication activities of daily living and quality of life among the elderly suffering from stroke. Journal of Physical Therapy Science, 28(5), 1450–1453. https://doi.org/10.1589/jpts.28.1450

    Article  PubMed  PubMed Central  Google Scholar 

  47. Žikić, T. R., Mirjana, J., Semnic, M., Slankamenac, P., Žarkov, M., & Žikić, M. (2014). The effect of post stroke depression on functional outcome and quality of life. Acta Clinica Croatica, 53(3), 294–301.

    PubMed  Google Scholar 

  48. Pan, J. H., Song, X. Y., Lee, S. Y., & Kwok, T. (2008). Longitudinal analysis of quality of life for stroke survivors using latent curve models. Stroke, 39(10), 2795–2802. https://doi.org/10.1161/strokeaha.108.515460

    Article  PubMed  Google Scholar 

  49. Perna, R., & Harik, L. (2020). The role of rehabilitation psychology in stroke care described through case examples. NeuroRehabilitation, 46(2), 195–204. https://doi.org/10.3233/nre-192970

    Article  PubMed  Google Scholar 

  50. Ahlsiö, B., Britton, M., Murray, V., & Theorell, T. (1984). Disablement and quality of life after stroke. Stroke, 15(5), 886–890. https://doi.org/10.1161/01.str.15.5.886

    Article  PubMed  Google Scholar 

  51. Salter, K., Foley, N., & Teasell, R. (2010). Social support interventions and mood status post stroke: A review. International Journal of Nursing Studies, 47(5), 616–625. https://doi.org/10.1016/j.ijnurstu.2009.12.002

    Article  PubMed  Google Scholar 

  52. Jak, S. (2015). Introduction to meta-analysis and structural equation modeling. In S. Jak (Ed.), Meta-analytic structural equation modelling. SpringerBriefs in research synthesis and meta-analysis. Springer. https://doi.org/10.1007/978-3-319-27174-3_1

    Chapter  Google Scholar 

  53. Lo Buono, V., Corallo, F., Bramanti, P., & Marino, S. (2017). Coping strategies and health-related quality of life after stroke. Journal of Health Psychology, 22(1), 16–28. https://doi.org/10.1177/1359105315595117

    Article  PubMed  Google Scholar 

  54. da Rocha, N. S., Power, M. J., Bushnell, D. M., & Fleck, M. P. (2009). Is there a measurement overlap between depressive symptoms and quality of life? Comprehensive Psychiatry, 50(6), 549–555. https://doi.org/10.1016/j.comppsych.2008.11.015

    Article  PubMed  Google Scholar 

  55. Jakobsen, M., & Jensen, R. (2015). Common method bias in public management studies. International Public Management Journal. https://doi.org/10.1080/10967494.2014.997906

    Article  Google Scholar 

  56. George, B., & Pandey, S. K. (2017). We know the Yin-But where is the Yang? Toward a balanced approach on common source bias in public administration scholarship. Review of Public Personnel Administration, 37(2), 245–270. https://doi.org/10.1177/0734371x17698189

    Article  PubMed  PubMed Central  Google Scholar 

  57. Conway, J. M., & Lance, C. E. (2010). What reviewers should expect from authors regarding common method bias in organizational research. Journal of Business and Psychology, 25(3), 325–334. https://doi.org/10.1007/s10869-010-9181-6

    Article  Google Scholar 

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Funding

This work was supported by the Natural Science Foundation of Shandong province (Grant No. ZR2021MG031).

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Li, J., Yang, L., Lv, R. et al. Mediating effect of post-stroke depression between activities of daily living and health-related quality of life: meta-analytic structural equation modeling. Qual Life Res 32, 331–338 (2023). https://doi.org/10.1007/s11136-022-03225-9

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