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Clinical Predictors of Engagement in Inpatient Rehabilitation Among Stroke Survivors With Cognitive Deficits: An Exploratory Study

Published online by Cambridge University Press:  19 March 2018

Emily A. Kringle Open the ORCID record for Emily A. Kringle [Opens in a new window] ,
Lauren Terhorst ,
Meryl A. Butters  and
Elizabeth R. Skidmore
Emily A. Kringle*
Affiliation:
Department of Occupational Therapy, School of Health and Rehabilitation Science, University of Pittsburgh, Pittsburgh, Pennsylvania
Lauren Terhorst
Affiliation:
Department of Occupational Therapy, School of Health and Rehabilitation Science, University of Pittsburgh, Pittsburgh, Pennsylvania Clinical and Translational Science Institute, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania Department of Health and Community Systems, School of Nursing, University of Pittsburgh, Pittsburgh, Pennsylvania
Meryl A. Butters
Affiliation:
Clinical and Translational Science Institute, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
Elizabeth R. Skidmore
Affiliation:
Department of Occupational Therapy, School of Health and Rehabilitation Science, University of Pittsburgh, Pittsburgh, Pennsylvania Clinical and Translational Science Institute, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania Department of Physical Medicine and Rehabilitation, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
*
Correspondence and reprint requests to: Emily A. Kringle, Department of Occupational Therapy, University of Pittsburgh, 5012 Forbes Tower, Pittsburgh, PA 15260. E-mail: eak60@pitt.edu
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Abstract

Objectives: The purpose of this exploratory study was to identify clinical predictors that could distinguish clients’ level of engagement in inpatient rehabilitation following stroke. Methods: This is a secondary analysis of pooled data from three randomized controlled trials that examined the effects of a behavioral intervention. The sample (n=208) consisted of clients with stroke who had cognitive deficits (Quick-EXIT≥3) and were admitted to inpatient rehabilitation facilities associated with a university medical center. Individuals with pre-morbid dementia, aphasia and mood disorders were excluded. The Pittsburgh Rehabilitation Participation Scale was used to measure engagement. Clinical predictors were measured using the Functional Independence Measure, National Institutes of Health Stroke Scale, Repeatable Battery for the Assessment of Neuropsychological Status, selected subtests of the Delis-Kaplan Executive Function System, Patient Health Questionnaire-9, and Chedoke McMaster Stroke Assessment. Simple logistic regression identified individual clinical predictors associated with engagement. Hierarchical logistic regression identified the strongest predictors of engagement. Results: Impairments in executive functions [mean D-KEFS, odds ratio (OR)=4.062; 95% confidence interval (CI)=.866, 19.051], impairments in visuospatial skills (RBANS Visuospatial Index Score, OR=3.940; 95% CI=1.317, 11.785), impairments in mood (Patient Health Questionnaire-9, OR=2.059, 95% CI=.953, 4.449), and male gender (OR=2.474; 95% CI=1.145, 5.374) predicted levels of engagement in inpatient rehabilitation after controlling for study intervention group, baseline stroke severity, and baseline disability. Conclusions: Executive functions, visuospatial skills, mood, and gender distinguished individuals with high or low engagement in inpatient rehabilitation following stroke. Further studies should examine additional factors that may influence engagement (therapist-client relationship, treatment expectancy). (JINS, 2018, 24, 572–583)

Keywords

Patient participationStrokeNeurological rehabilitationStroke rehabilitationOccupational therapyPhysical therapy
Type
Regular Research
Information
Journal of the International Neuropsychological Society , Volume 24 , Issue 6 , July 2018 , pp. 572 - 583
Copyright
Copyright © The International Neuropsychological Society 2018 

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References

REFERENCES

Behrmann, M., & Shomstein, S. (2015). Hemispatial neglect, neural basis of. In D.J. Wright (Ed.), International encyclopedia of the social and behavioral sciences (pp. 766–772). Oxford: Elsevier.Google Scholar
Birn, R.M., Kenworthy, L., Case, L., Caravella, R., Jones, T.B., Bandettini, P.A., && Martin, A. (2010). Neural systems supporting lexical search guided by letter and semantic category cues: A self-paced overt response fMRI study of verbal fluency. Neuroimage, 49(1), 1099–1107.CrossRefGoogle ScholarPubMed
Borod, J.C., Goodglass, H., & Kaplan, E. (1980). Normative data on the Boston Diagnostic Aphasia Examination, Parietal Lobe Battery, and the Boston Naming Test. Journal of Clinical Neuropsychology, 2(3), 209–215. doi: 10.1080/01688638008403793 Google Scholar
Boukrina, O., & Barrett, A.M. (2017). Disruption of the ascending arousal system and cortical attention networks in post-stroke delirium and spatial neglect. Neuroscience & Biobehavioral Reviews, 83, 1–10.CrossRefGoogle ScholarPubMed
Bright, F.A.S., Kayes, N.M., Worrall, L., & McPherson, K.M. (2015). A conceptual review of engagement in healthcare and rehabilitation. Disability and Rehabilitation, 37(8), 643–654. doi: 10.3109/09638288.2014.933899 Google Scholar
Chen, H., Cohen, P., & Chen, S. (2010). How big is a big odds ratio? Interpreting the magnitudes of odds ratios in epidemiological studies. Communications in Statistics – Simulation and Computation, 39, 860–864. doi: 10.1080/03610911003650383 Google Scholar
Cott, C.A., Wiles, R., & Devitt, R. (2007). Continuity, transition and participation: Preparing clients for life in the community post-stroke. Disability and Rehabilitation, 29(20-21), 1566–1574.CrossRefGoogle ScholarPubMed
Delis, D.C., Kramer, J.H., Kaplan, E., & Holdnack., J. (2004). Reliability and validity of the Delis-Kaplan Executive Function System: An update. Journal of the International Neuropsychological Society, 10, 301–303. doi: 10.1017/S1355617704102191 Google Scholar
Elias, M.F., Elias, P.K., D’Agostino, R.B., Silbershatz, H., & Wolf, P.A. (1997). Role of age, education and gender on cognitive performance in the Framingham Heart Study: Community-based norms. Experimental Aging Research, 23, 201–235.CrossRefGoogle ScholarPubMed
Faul, F., Erdfelder, E., Buchner, A., & Lang, A.G. (2009). Statistical power analysis using G*Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41(4), 1149–1160.Google Scholar
Field, A. (2013). Discovering statistics using IBM SPSS Statistics (4th ed.), London: Sage.Google Scholar
Gilbody, S., Richards, D., Brealey, S., & Hewitt, C. (2007). Screening for depression in medical settings with the Patient Health Questionnaire (PHQ): A diagnostic meta-analysis. Journal of General Internal Medicine, 22, 1596–1602. doi: 10.1007/s11606-007-0333-y Google Scholar
Goldstein, L.B., Bertels, C., & Davis, J.N. (1989). Interrater reliability of the NIH Stroke Scale. Archives of Neurology, 46, 660–662. doi: 10.1001/archneur.1989.00520420080026 CrossRefGoogle ScholarPubMed
Goldstein, L.B., & Samsa, G.P. (1997). Reliability of the National Institutes of Health Stroke Scale: Extension to non-neurologists in the context of a clinical trial. Stroke, 28, 307–310. doi: 10.1161/01.str.28.2.307 Google Scholar
Gowland, C., Stratford, P., Ward, M., Moreland, J., Torresin, W., Van Hullenaar, S., & Plews, N. (1993). Measuring physical impairment and disability with the Chedoke-McMaster Stroke Assessment. Stroke, 24, 58–63. doi: 10.1161/01.str.24.1.58 Google Scholar
Hackett, M.L., Yapa, C., Parag, V., & Anderson, C.S. (2005). Frequency of depression after stroke: A systematic review of observational studies. Stroke, 36, 1330–1340. doi: 10.1161/01.STR.0000183622.75135.a4.Google Scholar
Holliday, R.C., Cano, S., Freeman, J.A., & Playford, E.D. (2007). Should patients participate in clinical decision making? An optimized balance block design controlled study of goal setting in a rehabilitation unit. Journal of Neurology, Neurosurgery, and Psychiatry, 78, 576–580.Google Scholar
Homack, S., Lee, D., & Riccio, C.A. (2005). Test review: Delis-Kaplan Executive Function System. Journal of Clinical and Experimental Neuropsychology, 27, 599–609. doi: 10.1080/13803390490918444 CrossRefGoogle ScholarPubMed
Hsueh, I.P., Lin, J.H., Jeng, J.S., & Hsieh, C.L. (2002). Comparison of the psychometric characteristics of the Functional Independence Measure, 5 item Barthel Index, and 10 item Barthel Index in patients with stroke. Journal of Neurology, Neurosurgery, and Psychiatry, 73, 188–190. doi: 10.1136/jnnp.73.2.188 CrossRefGoogle ScholarPubMed
Jaeger, R.G., & Halliday, T.R. (1998). On confirmatory versus exploratory research. Herpetologica, 54(Suppl J), S64–S66.Google Scholar
Jorgensen, H.S., Nakayama, H., Raaschou, H.O., Vive-Larsen, J., Stoier, M., & Olsen, T.S. (1995). Outcome and time course recovery in stroke. Part I: Outcome. The Copenhagen stroke study. Archives of Physical Medicine and Rehabilitation, 76(5), 399–405.Google Scholar
Kortte, K.B., Falk, L.D., Castillo, R.C., Johnson-Greene, D., & Wegener, S.T. (2007). The Hopkins Rehabilitation Engagement Rating Scale: Development and psychometric properties. Archives of Physical Medicine and Rehabilitation, 88, 877–884. doi: 10.1016/j.apmr.2007.03.030 Google Scholar
Larson, E., Kirschner, K., Bode, R., Heinemann, A., & Goodman, R. (2005). Construct and predictive validity of the Repeatable Battery for the Assessment of Neuropsychological Status in the evaluation of stroke patients. Journal of Clinical and Experimental Neuropsychology, 27, 16–32. doi: 10.1080/138033990513564 Google Scholar
Larson, E.B., & Heinemann, A.W. (2009). Rasch analysis of The Executive Interview (The EXIT-25) and introduction of an Abridged Version (The Quick EXIT). Archives of Physical Medicine and Rehabilitation, 91(3), 389–394. doi: 10.1016/j.apmr.2009.11.015 Google Scholar
Latzman, R.D., & Markon, K.E. (2010). The factor structure and age-related factorial invariance of the Delis-Kaplan Executive Function System (D-KEFS). Assessment, 17(2), 172–184.Google Scholar
Lenze, E.J., Munin, M.C., Quear, T., Dew, M.A., Rogers, J.C., Begley, A.E., && Reynolds, C.F. (2004a). Significance of poor participation in physical and occupational therapy for functional outcome and length of stay. Archives of Physical Medicine and Rehabilitation, 85, 1599–1601. doi: 10.1016/j.apmr.2004.03.027 Google Scholar
Lenze, E.J., Munin, M.C., Quear, T., Dew, M.A., Rogers, J.C., Begley, A.E., && Reynolds, C.F. (2004b). The Pittsburgh Rehabilitation Participation Scale: Reliability and validity of a clinician-rated measure of participation in acute rehabilitation. Archives of Physical Medicine and Rehabilitation, 85, 380–384. doi: 10.1016/j.apmr.2003.06.001 Google Scholar
Lequerica, A.H., Donnell, C.S., & Tate, D.G. (2009). Patient engagement in rehabilitation therapy: Physical and occupational therapists perspectives. Disability and Rehabilitation, 39(9), 753–760. doi: 10.1080/09638280802309095 Google Scholar
Levack, W.M.M., Taylor, K., Siegert, R.J., Dean, S.G., McPherson, K.M., & Weatherall, M. (2006). Is goal planning in rehabilitation effective? A systematic review. Clinical Rehabilitation, 20, 739–755.Google Scholar
Levack, W.M.M., Dean, S.G., Siegert, R.J., & McPherson, K.M. (2011). Navigating patient-centered goal setting in inpatient stroke rehabilitation: How clinicians control the process to meet perceived professional responsibilities. Patient Education and Counseling, 85, 206–213. doi: 10.1016/j.pec.2011.01.011 Google Scholar
Lincoln, N.B., Willis, D., Philips, S.A., Juby, L.C., & Berman, P. (1996). Comparison of rehabilitation practice on hospital wards for stroke patients. Stroke, 27, 18–23. doi: 10.1161/01.STR.27.1.18 Google Scholar
Lyden, P., Lu, M., Jackson, C., Marler, J., Kothari, R., Brott, T., &&Zivin, J. (1999). Underlying structure of the National Institutes of Health Stroke Scale: Results of a factor analysis. Stroke, 30, 2347–2354. doi: 10.1161/01.str.30.11.2347 Google Scholar
Matthews, G., Campbell, S.E., Falconer, S., Joyner, L.A., Huggins, J., Gilliland, K., & Warm, J.S. (2002). Fundamental dimensions of subjective state in performance settings: Task engagement, distress, and worry. Emotion, 2(4), 315–340. doi: 10.1037/1528-3542.2.4.315 Google Scholar
Moore, C.G., Carter, R.E., Nietert, P.J., & Stewart, P.W. (2011). Recommendations for planning pilot studies in clinical and translational research. Clinical and Translational Science, 4(5), 332–337.Google Scholar
Mozaffarian, D., Benjamin, E.J., Go, A.S., Arnett, D.K., Blaha, M.J., Cushman, M., & Turner, M.B. (2016). Heart disease and stroke statistics-2016 update: A report from the American Heart Association. Circulation, 133(4), e38.Google Scholar
Nys, G.M.S., Van Zandvoort, M.J.E., Van der Worp, H.B., De Haan, E.H.F., De Kort, P.L.M., & Kappelle, L.J. (2005). Early depressive symptoms after stroke: Neuropsychological correlates and lesion characteristics. Journal of the Neurological Sciences, 228(1), 27–33.Google Scholar
Nys, G.M.S., van Zandvoort, M.J.E., de Kort, P.L.M., Jansen, B.P.W., de Haan, E.H.F., & Kappelle, L.J. (2007). Cognitive disorders in acute stroke: Prevalence and clinical determinants. Cerebrovascular Disease, 23, 408–416. doi: 10.1159/000101464 CrossRefGoogle ScholarPubMed
Ottenbacher, K.J., Hsu, Y., Granger, C.V., & Fiedler, R.C. (1996). The reliability of the Functional Independence Measure: A quantitative review. Archives of Physical Medicine and Rehabilitation, 77, 1226–1232. doi: 10.1016/s0003-9993(96)90184-7 Google Scholar
Paolucci, S., Di Vita, A., Massicci, R., Traballesi, M., Bureca, I., Matano, A., & Guariglia, C. (2012). Impact of participation on rehabilitation results: A multivariate study. European Journal of Physical Medicine and Rehabilitation, 48, 455–466.Google Scholar
Randolph, C., Tierney, M.C., Mohr, E., & Chase, T.N. (1998). The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS): Preliminary clinical validity. Journal of Clinical and Experimental Neuropsychology, 20, 310–319. doi: 10.1076/jcen.20.3.310.823 Google Scholar
Rosen, V.M., & Engle, R.W. (1997). The role of working memory capacity in retrieval. Journal of Experimental Psychology: General, 126, 211–227.Google Scholar
Rosewilliam, S., Roskell, C.A., & Pandyan, A.D. (2011). A systematic review and synthesis of the quantitative and qualitative evidence behind patient-centered goal setting in stroke rehabilitation. Clinical Rehabilitation, 25(6), 501–514.Google Scholar
SAS® (Version 9.4, 2012). SAS Institute, Inc.: Cary, NC.Google Scholar
Skidmore, E.R., Whyte, E.M., Holm, M.B., Becker, J.T., Butters, M.A., Dew, M.A., & Lenze, E.J. (2010). Cognitive and affective predictors of rehabilitation participation after stroke. Archives of Physical Medicine Rehabilitation, 91, 203–207. doi: 0.1016/j.apmr.2009.10.026 Google Scholar
Skidmore, E.R., Dawson, D.R., Butters, M.A., Grattan, E.S., Juengst, S.B., Whyte, E.M., & Becker, J.T. (2015). Strategy training shows promise for addressing disability in the first 6 months after stroke. Neurorehabilitation and Neural Repair, 29, 668–676. doi: 10.1177/1545968314562113 Google Scholar
Skidmore, E., Butters, M., Whyte, E., Grattan, E.S., Shen, J., & Terhorst, L. (2017). Guided training relative to direct skill training for individuals with cognitive impairments after stroke: A pilot randomized trial. Archives of Physical Medicine and Rehabilitation, 98, 673–680.Google Scholar
Spitzer, R.L., Williams, J.B.W., Kroenke, K., Linzer, M., deGruy, F.V., Hahn, S.R., & Johnson, J.G. (1994). Utility of a new procedure for diagnosing mental disorders in primary care: The PRIME-MD 1000 Study. JAMA, 272(22), 1749–1756.Google Scholar
Spitzer, R.L., Kroenke, K., & Williams, J.B. (1999). Validation and utility of a self-report version of PRIME-MD: The PHQ Primary Care Study. JAMA, 282, 1737–1744. doi: 10.1001/jama.282.18.1737 Google Scholar
Stevens, A., Beurskens, A., Koke, A., & van der Weijden, T. (2013). The use of patient-specific measurement instruments in the process of goal-setting: A systematic review of available instruments and their feasibility. Clinical Rehabilitation, 27(11), 1005–1019.Google Scholar
Stineman, M.G., Shea, J.A., Jette., A., Tassoni, C.J., Ottenbacher, K.J., Fiedler, R., &&Granger, C.V. (1996). The Functional Independence Measure: Tests of scaling assumptions, structure, and reliability across 20 diverse impairment categories. Archives of Physical Medicine and Rehabilitation, 77, 1101–1108. doi: 10.1016/s0003-9993(96)90130-6 Google Scholar
Stuss, D.T., Alexander, M.P., Hamer, L., Palumbo, C., Dempster, R., Binns, M., & Izukawa, D. (1998). The effects of focal anterior and posterior brain lesions on verbal fluency. Journal of the International Neuropsychological Society, 4, 265–278.Google Scholar
Sugavanam, T., Mead, G., Bulley, C., Donaghy, M., & van Wijck, F. (2013). The effects and experiences of goal setting in stroke rehabilitation – A systematic review. Disability and Rehabilitation, 35(3), 177–190.Google Scholar
Troyer, A.K., Moscovitch, M., & Winocur, G. (1997). Clustering and switching as two components of verbal fluency: Evidence from younger and older healthy adults. Neuropsychology, 11(1), 138–146.Google Scholar
Watkins, C.L., Auton, M.F., Deans, C.F., Dickinson, H.A., Jack, C.I.A., Lightbody, E., & Leathley, M.J. (2007). Motivational interviewing early after acute stroke: A randomized, controlled trial. Stroke, 38, 1004–1009.Google Scholar
Ween, J.E., Alexander, M.P., D’Esposito, M., & Roberts, M. (1996). Factors predictive of stroke outcome in a rehabilitation setting. Neurology, 47, 388–392. doi: 10.1212/wnl.47.2.388 Google Scholar
Whiteside, D.M., Kealey, T., Semla, M., Luu, H., Rice, L., Basso, M.R., && Roper, B. (2016). Verbal fluency: Language or executive function measure? Applied Neuropsychology: Adult, 23(1), 29–34.Google Scholar
Wressle, E., Oberg, B., & Henriksson, C. (1999). The rehabilitation process for the geriatric stroke patient: An exploratory study of goal setting and interventions. Disability and Rehabilitation, 21(2), 80–87. doi: 10.1080/096382899298016 Google Scholar
Zinn, S., Bosworth, H.B., Hoenig, H.M., & Swartzwelder, H.S. (2007). Executive function deficits in acute stroke. Archives of Physical Medicine and Rehabilitation, 88, 173–180. doi: 10.1016/j.apmr.2006.11.015 Google Scholar