2.5 CE Credits - JINS Special Issue on Rehabilitation (JINS 26:1, 2020) CE Bundle 2

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Educational Objectives
  1. List three types of memory strategies that people with MCI may use to compensate for their cognitive difficulties.
  2. Explain how these memory strategies relate to cognitive functioning as well as how they impact on close family/friends.
  3. Describe how the use of memory strategies may be tailored to an individual’s cognitive and psychosocial profile for maximal benefit.
  4. Explain key issues regarding the use of group treatment as a service delivery model for aphasia treatment.
  5. Describe some of the challenges of assessing language in conversation.
  6. List key approaches to assessment and rehabilitation of memory.
  7. Critique the effectiveness of a telehealth application of a memory rehabilitation program for stroke participants compared to face-to-face methods.
  8. List two factors that differentiate individuals with schizophrenia who were classified as responders and nonresponders to cognitive remediation.
  9. Assess the relationship of near learning and far transfer of learning in response to cognitive remediation in schizophrenia.
  10. Explain the mechanism of tDCS.
  11. List the tDCS applications that can be made for language disorders following an acquired brain injury.
  12. Discuss the use of a language measure to evaluate speech improvement in an aphasic patient.

Course Information
Target Audience:Intermediate
Availability:Date Available: 2020-05-04
You may obtain CE for this JINS package at any time.
Offered for CEYes
CostMembers $10
Non-Members $15
Refund PolicyThis JINS package is not eligible for refunds
CE Credits2.5
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Introduction

Cognitive and behavioral impairments arguably represent the greatest impediment to independence and participation in work, study, social, and leisure activities for individuals with brain injury. Despite this, research on remediation of cognitive, behavioral, and emotional consequences still lags far behind that on physical functions in rehabilitation of individuals with neurological dysfunction. Nevertheless, in the last few decades, there has been exponential growth both in practice and research on the rehabilitation of these disorders.

There are many definitions, but Wilson (1989, p. 117) defined cognitive rehabilitation as “any intervention strategy or technique which intends to enable clients or patients, and their families, to live with, manage, by-pass, reduce or come to terms with cognitive deficits precipitated by injury to the brain.” We prefer the broader term neuropsychological rehabilitation, which, according to Shany-Ur et al. in this issue, may be conceived as interventions aimed at mitigating or compensating for cognitive, behavioral, and psychosocial deficits, and enhancing independence and integration into employment and society.

Creating the science to underpin these practices represents a significant challenge. Guidelines have been developed for the treatment of specific acquired cognitive impairments in domains including attention, language, memory, visuo-spatial, and executive functions, as a result of traumatic brain injury or stroke (Bayley et al.,2014; Cicerone,2000,2005,2011; Ponsford et al.,2014; Tate et al.,2014; Togher et al.,2014; Velikonja et al.,2014). Although there is evidence in support of interventions across each of these domains of impairment, these guidelines have identified very few rigorous controlled trials and, as a consequence, guidelines for clinical practice are limited. Most outcomes have been assessed on neuropsychological measures, with limited assessment of generalization to meaningful everyday activities. This criticism is equally applicable to cognitive rehabilitation efforts in individuals with psychiatric disorders, specifically schizophrenia (Bryce, Sloan, Lee, Ponsford, & Rossell,2016). There has also been limited evaluation of psychotherapeutic interventions in these groups.

A survey of international practice in cognitive rehabilitation (Nowell, Downing, Bragge, & Ponsford, in press) recently reported that clinicians don’t just want to know whether an intervention works, but how it works and in what contexts. Clearly, brain injuries are complex and not everyone responds in the same way. There is a need to identify the factors that impact an individual’s capacity to respond to treatment. There has been limited comparison of modes of therapy delivery – for example, individualversusgroup; in person orviatelehealth. There is growing use of exciting new technologies in a rehabilitation context, but limited evaluation of the functional impacts of these.

This JINS Special Edition on Rehabilitation takes some steps toward addressing many of these issues. It includes papers representing the application of specific rehabilitation treatments to impairments in a broad range of domains, including language and communication, memory, attention, and challenging behavior, as well as depression, anxiety, and posttraumatic stress disorder (PTSD). These interventions have been applied across diverse populations, including groups with stroke, traumatic brain injury, mild cognitive impairment, and schizophrenia. The papers in this issue can be categorised into four thematic areas: application of technology to cognitive rehabilitation; comparison of modes of treatment delivery; factors impacting response to treatment; and maintenance of treatment gains.


Individual Titles, Authors, and Articles:

Memory Compensation Strategies in Older People with Mild Cognitive Impairment
Author(s)
  • Pinghsiu Lin | Healthy Brain Ageing Program, Brain and Mind Centre, The University of Sydney, NSW, Australia
  • Haley M. LaMonica | Healthy Brain Ageing Program, Brain and Mind Centre, The University of Sydney, NSW, Australia | Central Clinical School, The University of Sydney, NSW, Australia
  • Sharon L. Naismith | Healthy Brain Ageing Program, Brain and Mind Centre, The University of Sydney, NSW, Australia | School of Psychology, The University of Sydney, NSW, Australia | Charles Perkins Centre, The University of Sydney, NSW, Australia
  • Loren Mowszowski | Healthy Brain Ageing Program, Brain and Mind Centre, The University of Sydney, NSW, Australia | School of Psychology, The University of Sydney, NSW, Australia

Correspondence
E-mail address: | loren.mowszowski@sydney.edu.au

Disclosures
There are no financial relationships with commercial interests and no conflicts of interest to report.

Abstract
Objectives:

With the rapid growth of the older population worldwide, understanding how older adults with mild cognitive impairment (MCI) use memory strategies to mitigate cognitive decline is important. This study investigates differences between amnestic and nonamnestic MCI subtypes in memory strategy use in daily life, and how factors associated with cognition, general health, and psychological well-being might relate to strategy use.

Methods:

One hundred forty-eight participants with MCI (mean age = 67.9 years, SD = 8.9) completed comprehensive neuropsychological, medical, and psychological assessments, and the self-report ‘Memory Compensation Questionnaire’. Correlational and linear regression analyses were used to explore relationships between memory strategy use and cognition, general health, and psychological well-being.

Results:

Memory strategy use does not differ between MCI subtypes (p > .007) despite higher subjective everyday memory complaints in those with amnestic MCI (p = .03). The most marked finding showed that increased reliance-type strategy use was significantly correlated with more subjective memory complaints and poorer verbal learning and memory (p < .01) in individuals with MCI. Moreover, fewer subjective memory complaints and better working memory significantly predicted (p < .05) less reliance strategy use, respectively, accounting for 10.6% and 5.3% of the variance in the model.

Conclusions:

In general, the type of strategy use in older adults with MCI is related to cognitive functioning. By examining an individual’s profile of cognitive dysfunction, a clinician can provide more personalized clinical recommendations regarding strategy use to individuals with MCI, with the aim of maintaining their day-to-day functioning and self-efficacy in daily life.

Bibliography
  1. Australian Bureau of Statistics (ABS) (2013). Population projections, Australia, 2012 (base) to 2101 . ABS cat. no. 3222.0. Canberra: ABS. Google Scholar 
  2. Australian Institute of Health and Welfare (AIHW) (2017). Older Australia at a glance . ABS cat. no. WEB 194. Canberra: AIHW. Google Scholar 
  3. Aronov, A., Rabin, L.A., Fogel, J., Chi, S.Y., Kann, S.J., Abdelhak, N., & Zimmerman, M.E. (2015). Relationship of cognitive strategy use to prospective memory performance in a diverse sample of nondemented older adults with varying degrees of cognitive complaints and impairment. Aging, Neuropsychology, and Cognition, 22(4), 486–501. doi:10.1080/13825585.2014.984653  CrossRef  Google Scholar 
  4. Baddeley, A. (1998). Recent developments in working memory. Current Opinion in Neurobiology, 8(2), 234–238. CrossRef  Google Scholar 
  5. Bouazzaoui, B., Isingrini, M., Fay, S., Angel, L., Vanneste, S., Clarys, D., & Taconnat, L. (2010). Aging and self-reported internal and external memory strategy uses: the role of executive functioning. Acta Psychologica (Amst), 135(1), 59–66. doi:10.1016/j.actpsy.2010.05.007  CrossRef  Google Scholar 
  6. Busse, A., Hensel, A., Guhne, U., Angermeyer, M.C., & Riedel-Heller, S.G. (2006). Mild cognitive impairment: long-term course of four clinical subtypes. Neurology, 67(12), 2176–2185. doi:10.1212/01.wnl.0000249117.23318.e1  CrossRef  Google Scholar 
  7. Buysse, D.J., Reynolds, III, , C.F., Monk, T.H., Berman, S.R., & Kupfer, D.J. (1989). The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Research, 28(2), 193–213. CrossRef  Google Scholar 
  8. Coe, A., Martin, M., & Stapleton, T. (2019). Effects of an occupational therapy memory strategy education group intervention on Irish older adults’ self-management of everyday memory difficulties. Occupational Therapy in Health Care, 33(1), 37–63. doi:10.1080/07380577.2018.1543911  CrossRef  Google Scholar 
  9. de Frias, C.M. & Dixon, R.A. (2005). Confirmatory factor structure and measurement invariance of the Memory Compensation Questionnaire. Psychological Assessment, 17(2), 168–178. doi:10.1037/1040-3590.17.2.168  CrossRef  Google Scholar 
  10. de Frias, C.M., Dixon, R.A., & Backman, L. (2003). Use of memory compensation strategies is related to psychosocial and health indicators. The Journals of Gerontology: Series B, 58(1), P12–P22. doi:10.1093/geronb/58.1.P12  CrossRef  Google Scholar 
  11. Deary, I.J., Corley, J., Gow, A.J., Harris, S.E., Houlihan, L.M., Marioni, R.E., Penke, L., Rafnsson, S.B., & Starr, J.M. (2009). Age-associated cognitive decline. British Medical Bulletin, 92(1), 135–152. doi:10.1093/bmb/ldp033  CrossRef  Google Scholar 
  12. Delis, D.C., Kaplan, E., & Kramer, J.H. (2001). Delis-Kaplan Executive function system: examiners manual. San Antonio, TX: Psychological Corporation. Google Scholar 
  13. Dewar, B.K., Kapur, N., & Kopelman, M. (2018). Do memory aids help everyday memory? A controlled trial of a Memory Aids Service. Neuropsychological Rehabilitation, 28(4), 614–632. CrossRef  Google Scholar 
  14. Diamond, K., Mowszowski, L., Cockayne, N., Norrie, L., Paradise, M., Hermens, D., Lewis, S.J.G., Hickie, I.B., & Naismith, S. (2015). Randomized controlled trial of a healthy brain aging cognitive training program: effects on memory, mood, and sleep. Journal of Alzheimer's Disease, 44(4), 1181–1191. CrossRef  Google Scholar 
  15. Dixon, R. & Hultsch, D. (1983). Structure and development of metamemory in adulthood. Journal of Gerontology, 38(6), 682–688. doi:10.1093/geronj/38.6.682  CrossRef  Google Scholar 
  16. Dixon, R.A., de Frias, C.M., & Backman, L. (2001). Characteristics of self-reported memory compensation in older adults. Journal of Clinical and Experimental Neuropsychology, 23(5), 650–661. doi:10.1076/jcen.23.5.650.1242  CrossRef  Google Scholar 
  17. Fekete, C., Tough, H., Siegrist, J., & Brinkhof, M.W. (2017). Health impact of objective burden, subjective burden and positive aspects of caregiving: an observational study among caregivers in Switzerland. BMJ Open, 7(12), e017369. CrossRef  Google Scholar 
  18. Folstein, M.F., Folstein, S.E., & McHugh, P.R. (1975). “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12(3), 189–198. CrossRef  Google Scholar 
  19. Gauthier, S., Reisberg, B., Zaudig, M., Petersen, R.C., Ritchie, K., Broich, K., Belleville, S., Brodaty, H., Bennett, D., Chertkow, H., Cummings, J.L., de Leon, M., Feldman, H., Ganguli, M., Hampel, H., Scheltens, P., Tierney, M.C., Whitehouse, P., Winblad, B. (2006). Mild cognitive impairment. Lancet, 367(9518), 1262–1270. doi:10.1016/s0140-6736(06)68542-5  CrossRef  Google Scholar 
  20. Hamilton, M. (1960). A rating scale for depression. Journal of Neurology, Neurosurgery, and Psychiatry, 23(1), 56. CrossRef  Google Scholar 
  21. IBM Corporation (2016). SPSS for windows, version 24. Chicago: IBM Corp. Google Scholar 
  22. Kennedy, M.R.T., Coelho, C., Turkstra, L., Ylvisaker, M., Moore Sohlberg, M., Yorkston, K., Chiou, H.H., & Kan, P.-F. (2008). Intervention for executive functions after traumatic brain injury: a systematic review, meta-analysis and clinical recommendations. Neuropsychological Rehabilitation, 18(3), 257–299. doi:10.1080/09602010701748644  CrossRef  Google Scholar 
  23. Kinsella, G. J., Ames, D., Storey, E., Ong, B., Pike, K.E., Saling, M.M., Clare, L., Mullaly, E., & Rand, E. (2016). Strategies for improving memory: a randomized trial of memory groups for older people, including those with mild cognitive impairment. Journal of Alzheimer's Disease, 49(1), 31–43. doi:10.1097/00004583-200502000-00010  CrossRef  Google Scholar 
  24. Klingberg, T., Fernell, E., Olesen, P.J., Johnson, M., Gustafsson, P., Dahlstrom, K., Gillberg, C.G., Forssberg, H., & Westerberg, H. (2005). Computerized training of working memory in children with ADHD - A randomized, controlled trial. Journal of the American Academy of Child and Adolescent Psychiatry, 44(2), 177–186. doi:10.1097/00004583-200502000-00010  CrossRef  Google Scholar 
  25. Lezak, M.D. (1995). Neuropsychological assessment (3rd ed.). New York, NY: Oxford University Press. Google Scholar 
  26. Lobo, A., Launer, L.J., Fratiglioni, L., Andersen, K., Di Carlo, A., Breteler, M.M., Copeland, J.R., Dartigues, J.F., Jagger, C., Martinez-Lage, J., Soininen, H., & Hofman, A. (2000). Prevalence of dementia and major subtypes in Europe: a collaborative study of population-based cohorts. Neurologic Diseases in the Elderly Research Group. Neurology, 54(11 Suppl 5), S4–S9. Google Scholar 
  27. Miller, M. & Towers, A. (1991). A Manual for the Cumulative Illness Rating Scale. Pittsburgh, PA: Western Psychiatric Institute. Google Scholar 
  28. Mitchell, A.J. & Shiri-Feshki, M. (2009). Rate of progression of mild cognitive impairment to dementia--meta-analysis of 41 robust inception cohort studies. Acta Psychiatrica Scandinavica, 119(4), 252–265. doi:10.1111/j.1600-0447.2008.01326.x  CrossRef  Google Scholar 
  29. Mowszowski, L., Batchelor, J., & Naismith, S.L. (2010). Early intervention for cognitive decline: can cognitive training be used as a selective prevention technique? International Psychogeriatrics, 22(4), 537–548. doi:10.1017/s1041610209991748  CrossRef  Google Scholar 
  30. Okonkwo, O.C., Wadley, V.G., Griffith, H.R., Belue, K., Lanza, S., Zamrini, E.Y., Harrell, L.E., Brockington, J.C., Clark, D., Raman, R., & Marson, D.C. (2008). Awareness of deficits in financial abilities in patients with mild cognitive impairment: going beyond self-informant discrepancy. The American Journal of Geriatric Psychiatry, 16(8), 650–659. doi:10.1097/JGP.0b013e31817e8a9d  CrossRef  Google Scholar 
  31. Petersen, R.C. (2004). Mild cognitive impairment as a diagnostic entity. Journal of Internal Medicine, 256(3), 183–194. doi:10.1111/j.1365-2796.2004.01388.x  CrossRef  Google Scholar 
  32. Petersen, R.C., Doody, R., Kurz, A., Mohs, R.C., Morris, J.C., Rabins, P.V., Ritchie, K., Rossor, M., Thal, L., & Winblad, B. (2001). Current concepts in mild cognitive impairment. Archives of Neurology, 58(12), 1985–1992. doi:10.1001/archneur.58.12.1985  CrossRef  Google Scholar 
  33. Reijnders, J., van Heugten, C., & van Boxtel, M. (2013). Cognitive interventions in healthy older adults and people with mild cognitive impairment: a systematic review. Ageing Research Reviews, 12(1), 263–275. doi:10.1016/j.arr.2012.07.003  CrossRef  Google Scholar 
  34. Reitan, R.M. (1979). Manual for administration of neuro-psycholgical test batteries for adults and children. Tucson, AZ: Neuropsychology Laboratory. Google Scholar 
  35. Royle, J. & Lincoln, N.B. (2008). The Everyday Memory Questionnaire–revised: development of a 13-item scale. Disability and Rehabilitation, 30(2), 114–121. CrossRef  Google Scholar 
  36. Saczynski, J.S., Willis, S.L., & Warner Schaie, K. (2002). Strategy use in reasoning training with older adults. Aging, Neuropsychology, and Cognition, 9(1), 48–60. doi:10.1076/anec.9.1.48.836  CrossRef  Google Scholar 
  37. Samuels, M.H. (2014). Psychiatric and cognitive manifestations of hypothyroidism. Current Opinion in Endocrinology, Diabetes, and Obesity, 21(5), 377–383. doi:10.1097/MED.0000000000000089  CrossRef  Google Scholar 
  38. Schmitter-Edgecombe, M., Parsey, C., & Lamb, R. (2014). Development and psychometric properties of the instrumental activities of daily living: compensation scale. Archives of Clinical Neuropsychology, 29(8), 776–792. CrossRef  Google Scholar 
  39. Teri, L., Truax, P., Logsdon, R., Uomoto, J., Zarit, S., & Vitaliano, P.P. (1992). Assessment of behavioral problems in dementia: the revised memory and behavior problems checklist. Psychology and Aging, 7(4), 622. CrossRef  Google Scholar 
  40. Tomaszewski, F.S., Schmitter-Edgecombe, M., Weakley, A., Harvey, D., Denny, K.G., Barba, C., Gravano, J.T., Giovannetti, T., & Willis, S. (2018). Compensation strategies in older adults: association with cognition and everyday function. American Journal of Alzheimer’s Disease & Other Dementias, 33(3), 184–191. doi:10.1177/1533317517753361  CrossRef  Google Scholar 
  41. Wear, H.J., Wedderburn, C.J., Mioshi, E., Williams-Gray, C.H., Mason, S.L., Barker, R.A., & Hodges, J.R. (2008). The Cambridge Behavioural Inventory revised. Dementia & Neuropsychologia, 2(2), 102–107. doi:10.1590/S1980-57642009DN20200005  CrossRef  Google Scholar 
  42. Wechsler (1997a). Wechsler adult intelligence scale–Third edition. San Antonio, TX: Harcourt Assessment. Google Scholar 
  43. Wechsler (1997b). Wechsler memory scale (WMS-III), Vol. 14. San Antonio, TX: Psychological corporation. Google Scholar 
  44. Wechsler (2001). The Wechsler test of adult reading (WTAR). San Antonio, TX: Psychological corporation. Google Scholar 
  45. Winblad, B., Palmer, K., Kivipelto, M., Jelic, V., Fratiglioni, L., Wahlund, L.-O., Nordberg, A., Bäckman, L., Albert, M., Almkvist, O., Arai, H., Basun, H., Blennow, K., De Leon, M., DeCarli, C., Erkinjuntti, T., Giacobini, E., Graff, C., Hardy, J., Jack, C., Jorm, A., Ritchie, K., Van Duijn, C., Visser, P., & Petersen, R.C. (2004). Mild cognitive impairment – beyond controversies, towards a consensus: report of the International Working Group on Mild Cognitive Impairment. Journal of Internal Medicine, 256(3), 240–246. doi:10.1111/j.1365-2796.2004.01380.x  CrossRef  Google Scholar 
  46. World Health Organization (1996). WHOQOL-BREF: introduction, administration, scoring and generic version of the assessment: field trial version, December 1996. Geneva: World Health Organization. Google Scholar 
  47. World Health Organization (2000). World Health Organization disability assessment schedule: WHODAS II. Phase 2 field trials. Geneva: World Health Organization. Google Scholar 
  48. Zigmond, A.S. & Snaith, R.P. (1983). The hospital anxiety and depression scale. Acta Psychiatrica Scandinavica, 67(6), 361–370. CrossRef  Google Scholar 
An Exploration of the Impact of Group Treatment for Aphasia on Connected Speech
Author(s)
  • Catherine Mason | Department of Cognitive Science, ARC Centre of Excellence in Cognition and its Disorders, Macquarie University, Sydney 2113, Australia
  • Lyndsey Nickels | Department of Cognitive Science, ARC Centre of Excellence in Cognition and its Disorders, Macquarie University, Sydney 2113, Australia
  • Belinda McDonald | St. Vincent’s Health, Sydney 2010, Australia

Correspondence
E-mail address | catherine.mason@mq.edu.au

Disclosures
The authors have nothing to disclose.

Abstract
Objective:

Group treatment enables people with aphasia to practise communication skills outside the typical clinician–patient dyad. While there is evidence that this treatment format can improve participation in everyday communication, there is little evidence it impacts linguistic abilities. This project aimed to investigate the effects of ‘typical’ group treatment on the communication skills of people with aphasia with a focus on word retrieval in discourse.

Methods:

Three people with aphasia took part in a 6-week group therapy programme. Each week focused on a different topic, and three topics also received a home programme targeting word retrieval. The six treated topics were compared with two control topics, with regard to language production in connected speech. Semistructured interviews were collected twice prior to treatment and twice following the treatment and analysed using (a) word counts; (b) the profile of word errors and retrieval in speech; (c) a measure of propositional idea density, and (d) perceptual discourse ratings.

Results:

Two participants showed no significant improvements; one participant showed significant improvement on discourse ratings.

Conclusions:

This study provides limited support for group treatment, leading to improved communication as measured by semistructured interviews, even when supplemented with a home programme. We suggest that either group treatment, as implemented here, was not an effective approach for improving communication for our participants and/or that outcome measurement was limited by difficulty assessing changes in connected speech.

Bibliography
  1. ABC TV (producer). (2004–2012). Australian story [television series]. Australia: Australian Broadcasting Corporation. Google Scholar 
  2. Antonucci, S.M. (2009). Use of semantic feature analysis in group aphasia treatment. Aphasiology, 23(7–8), 854–866. DOI: 10.1080/02687030802634405  CrossRef  Google Scholar 
  3. Aten, J.L., Caligiuri, M.P., & Holland, A.L. (1982). The efficacy of functional communication therapy for chronic aphasic patients. Journal of Speech and Hearing Disorders, 47(1), 93–96. DOI: 10.1044/jshd.4701.93  CrossRef  Google Scholar 
  4. Berarducci, M.A. (2008). The stability of discourse measures. (Unpublished Master’s Thesis) Macquarie University, Australia. Google Scholar 
  5. Best, W., Grassly, J., Greenwood, A., Herbert, R., Hickin, J., & Howard, D. (2011). A controlled study of changes in conversation following aphasia therapy for anomia. Disability and rehabilitation, 33(3), 229–242. DOI: 10.3109/09638288.2010.534230  CrossRef  Google Scholar 
  6. Best, W., Howard, D., Bruce, C., & Gatehouse, C. (1997). Cueing the words: A single case study of treatments for anomia. Neuropsychological Rehabilitation, 7(2), 105–141. DOI: 10.1080/096020197390211  Google Scholar 
  7. Bollinger, R.L., Musson, N.D., & Holland, A.L. (1993). A study of group communication intervention with chronically aphasic persons. Aphasiology, 7(3), 301–313. DOI: 10.1080/02687039308249512  CrossRef  Google Scholar 
  8. Boyle, M. (2011). Discourse treatment for word retrieval impairment in aphasia: The story so far. Aphasiology, 25(11), 1308–1326. DOI: 10.1080/02687038.2011.596185  CrossRef  Google Scholar 
  9. Boyle, M. (2014). Test–retest stability of word retrieval in aphasic discourse. Journal of Speech, Language, and Hearing Research, 57(3), 966–978. DOI: 10.1044/2014_JSLHR-L-13-0171  CrossRef  Google Scholar 
  10. Brown, C.S. & Cullinan, W.L. (1981). Word-retrieval difficulty and disfluent speech in adult anomic speakers. Journal of Speech, Language, and Hearing Research, 24(3), 358–365. DOI: 10.1044/jshr.2403.358  CrossRef  Google Scholar 
  11. Brown, C., Snodgrass, T., & Covington, M. (2007). Computerized propositional idea density rater 3 (CPIDR 3), CASPR Project, Artificial Intelligence Centre, University of Georgia. Google Scholar 
  12. Bryant, L., Spencer, E., Ferguson, A., Craig, H., Colyvas, K., & Worrall, L. (2013). Propositional Idea Density in aphasic discourse. Aphasiology, 27(8), 992–1009. DOI: 10.1080/02687038.2013.803514  CrossRef  Google Scholar 
  13. Carragher, M., Conroy, P., Sage, K., & Wilkinson, R. (2012). Can impairment-focused therapy change the everyday conversations of people with aphasia? A review of the literature and future directions. Aphasiology, 26(7), 895–916. DOI: 10.1080/02687038.2012.676164  CrossRef  Google Scholar 
  14. Cartwright, J. & Elliott, K. (2009). Promoting strategic television viewing in the context of progressive language impairment. Aphasiology, 23(2), 266–285. DOI:10.1080/02687030801942932  CrossRef  Google Scholar 
  15. Croot, K., Taylor, C., Abel, S., Jones, K., Krein, L., Hameister, I., Ruggero, L., & Nickels, L. (2015). Measuring gains in connected speech following treatment for word retrieval: A study with two participants with primary progressive aphasia. Aphasiology, 29(11), 1265–1288. DOI: 10.1080/02687038.2014.975181  CrossRef  Google Scholar 
  16. Dietz, A. & Boyle, M. (2018). Discourse measurement in aphasia research: Have we reached the tipping point? Aphasiology, 32(4), 459–464. DOI: 10.1080/02687038.2017.1398803  CrossRef  Google Scholar 
  17. Eales, C. & Pring, T. (1998). Using individual and group therapy to remediate word finding difficulties. Aphasiology, 12(10), 913–918. DOI: 10.1080/02687039808249459  CrossRef  Google Scholar 
  18. Elman, R.J. (2007). The importance of aphasia group treatment for rebuilding community and health. Topics in Language Disorders, 27(4), 300–308. DOI: 10.1097/01.TLD.0000299884.31864.99  CrossRef  Google Scholar 
  19. Elman, R.J. & Bernstein-Ellis, E. (1999). The efficacy of group communication treatment in adults with chronic aphasia. Journal of Speech, Language, and Hearing Research, 42(2), 411–419. DOI: 10.1044/jslhr.4202.411  CrossRef  Google Scholar 
  20. Falconer, C. & Antonucci, S.M. (2012). Use of semantic feature analysis in group discourse treatment for aphasia: Extension and expansion. Aphasiology, 26(1), 64–82. DOI: 10.1080/02687038.2011.602390  CrossRef  Google Scholar 
  21. Fama, M.E., Baron, C.R., Hatfield, B., & Turkeltaub, P.E. (2016). Group therapy as a social context for aphasia recovery: A pilot, observational study in an acute rehabilitation hospital. Topics in Stroke Rehabilitation, 23(4), 276–283. DOI: 10.1080/10749357.2016.1155277  CrossRef  Google Scholar 
  22. Fergadiotis, G. & Wright, H.H. (2011). Lexical diversity for adults with and without aphasia across discourse elicitation tasks. Aphasiology, 25(11), 1414–1430. DOI: 10.1080/02687038.2011.603898  CrossRef  Google Scholar 
  23. Goodglass, H. & Wingfield, A. (Eds.). (1997). Anomia: Neuroanatomical and cognitive correlates. San Diego, CA: Academic Press. Google Scholar 
  24. Herbert, R., Best, W., Hickin, J., Howard, D., & Osborne, F. (Eds.). (2012), POWERS: Profile of word errors and retrieval in speech. Albury, UK: J & R Press. Google Scholar 
  25. Herbert, R., Hickin, J., Howard, D., Osborne, F., & Best, W. (2008). Do picture-naming tests provide a valid assessment of lexical retrieval in conversation in aphasia? Aphasiology, 22(2), 184–203. DOI: 10.1080/02687030701262613  CrossRef  Google Scholar 
  26. Hickin, J., Best, W., Herbert, R., Howard, D., & Osborne, F. (2001). Treatment of word retrieval in aphasia: Generalisation to conversational speech. International Journal of Language & Communication Disorders, 36(S1), 13–18. DOI:10.3109/13682820109177851  CrossRef  Google Scholar 
  27. Howard, D., Best, W., & Nickels, L. (2015). Optimising the design of intervention studies: Critiques and ways forward. Aphasiology, 29(5), 526–562. DOI: 10.1080/02687038.2014.985884  CrossRef  Google Scholar 
  28. Kearns, K.P. & Elman, R.J. (2001). Group therapy for aphasia: Theoretical and practical considerations, In Chapey, R. (Ed.), Language intervention strategies in aphasia and related neurogenic communication disorders (4th ed., pp. 316–337). Philadelphia: Lippincott Williams & Wilkins. Google Scholar 
  29. Kemper, S. & Sumner, A. (2001). The structure of verbal abilities in young and older adults. Psychology and Aging, 16(2), 312–322. DOI: 10.1037/0882-7974.16.2.312  CrossRef  Google Scholar 
  30. Lanyon, L.E., Rose, M.L. & Worrall, L. (2013). The efficacy of outpatient and community-based aphasia group interventions: A systematic review. International Journal of Speech-Language Pathology, 15(4), 359–374. DOI: 10.3109/17549507.2012.752865  CrossRef  Google Scholar 
  31. Le Dorze, G., Boulay, N., Gaudreau, J., & Brassard, C. (1994). The contrasting effects of a semantic versus a formal—semantic technique for the facilitation of naming in a case of anomia. Aphasiology, 8(2), 127–141. DOI: 10.1080/02687039408248646  CrossRef  Google Scholar 
  32. Maher, L.M., Kendall, D., Swearengin, J.A., Rodriguez, A., Leon, S.A., Pingel, K., Holland, A., & Rothi, L.J. G. (2006). A pilot study of use-dependent learning in the context of constraint induced language therapy. Journal of the international Neuropsychological Society, 12(6), 843–852. DOI: 10.1017/S1355617706061029  CrossRef  Google Scholar 
  33. Mason, C., Nickels, L., McDonald, B., Moses, M., Makin, K., & Taylor, C. (2011). Treatment of word retrieval impairments in aphasia: Evaluation of a self-administered home programme using personally chosen words. Aphasiology, 25(2), 245–268. DOI: 10.1080/02687038.2010.489258  CrossRef  Google Scholar 
  34. Meinzer, M., Djundja, D., Barthel, G., Elbert, T., & Rockstroh, B. 2005. Long-term stability of improved language functions in chronic aphasia after constraint-induced aphasia therapy. Stroke, 36(7), 1462–1466. DOI: 10.1161/01.STR.0000169941.29831.2a  CrossRef  Google Scholar 
  35. Nicholas, L.E. & Brookshire, R.H. (1993). A system for quantifying the informativeness and efficiency of the connected speech of adults with aphasia. Journal of Speech, Language, and Hearing Research, 36(2), 338–350. DOI: 10.1044/jshr.3602.338  CrossRef  Google Scholar 
  36. Nickels, L. (2002). Therapy for naming disorders: Revisiting, revising, and reviewing, Aphasiology, 16(10–11), 935–979. DOI: 10.1080/02687030244000563  CrossRef  Google Scholar 
  37. Nickels, L. & Best, W. (1996). Therapy for naming disorders (part I): Principles, puzzles and progress. Aphasiology, 10(1), 21–47. DOI: 10.1080/02687039608248397  CrossRef  Google Scholar 
  38. Nickels, L., McDonald, B., & Mason, C. (2016). The impact of group therapy on word retrieval in people with chronic aphasia. NeuroRehabilitation, 39(1), 81–95. DOI: 10.3233/NRE-161340  CrossRef  Google Scholar 
  39. Pulvermüller, F., Neininger, B., Elbert, T., Mohr, B., Rockstroh, B., Koebbel, P., & Taub, E. (2001). Constraint-induced therapy of chronic aphasia after stroke. Stroke, 32(7), 1621–1626. DOI: 10.1161/01.str.32.7.1621  CrossRef  Google Scholar 
  40. Renvall, K., Nickels, L., & Davidson, B. (2013). Functionally relevant items in the treatment of aphasia (part I): Challenges for current practice. Aphasiology, 27(6), 636–650. DOI: 10.1080/02687038.2013.786804  CrossRef  Google Scholar 
  41. Swinburn, K., Porter, G., & Howard, D. 2005. Comprehensive aphasia test, Hove, UK: Psychology Press. Google Scholar 
  42. Verna, A., Davidson, B., & Rose, T. (2009). Speech-language pathology services for people with aphasia: A survey of current practice in Australia. International Journal of Speech-Language Pathology, 11(3), 191–205. DOI: 10.1080/17549500902726059  CrossRef  Google Scholar 
  43. Wallace, S.J., Worrall, L., Rose, T., & Le Dorze, G. (2014). Measuring outcomes in aphasia research: A review of current practice and an agenda for standardisation. Aphasiology, 28(11), 1364–1384. DOI: 10.1080/02687038.2014.930262  CrossRef  Google Scholar 
  44. Wallace, S.J., Worrall, L., Rose, T., & Le Dorze, G. (2016). Core outcomes in aphasia treatment research: An e-Delphi consensus study of international aphasia researchers. American Journal of Speech-Language Pathology, 25(4S), 729–742. DOI: 10.1044/2016_AJSLP-15-0150  CrossRef  Google Scholar 
  45. Webster, J., Whitworth, A., & Morris, J. (2015). Is it time to stop “fishing”? A review of generalisation following aphasia intervention. Aphasiology, 29(11), 1240–1264. DOI:10.1080/02687038.2015.1027169  CrossRef  Google Scholar 
  46. Wertz, R.T., Collins, M.J., Weiss, D., Kurtzke, J.F., Friden, T., Brookshire, R.H., & West, J.A. (1981). Veterans Administration cooperative study on aphasia: A comparison of individual and group treatment. Journal of Speech and Hearing Research, 24(4), 580–594. DOI:10.1044/jshr.2404.580  CrossRef  Google Scholar 
Telehealth Delivery of Memory Rehabilitation Following Stroke
Author(s)
  • David W. Lawson | Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Australia | Monash-Epworth Rehabilitation Research Centre, Epworth HealthCare, Melbourne, Australia | School of Psychology and Public Health, La Trobe University, Melbourne, Australia
  • Renerus J. Stolwyk | Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Australia | Monash-Epworth Rehabilitation Research Centre, Epworth HealthCare, Melbourne, Australia
  • Jennie L. Ponsford | Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Australia | Monash-Epworth Rehabilitation Research Centre, Epworth HealthCare, Melbourne, Australia
  • Dean P. McKenzie | Monash-Epworth Rehabilitation Research Centre, Epworth HealthCare, Melbourne, Australia | Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia
  • Marina G. Downing | Monash-Epworth Rehabilitation Research Centre, Epworth HealthCare, Melbourne, Australia
  • Dana Wong | Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Australia | Monash-Epworth Rehabilitation Research Centre, Epworth HealthCare, Melbourne, Australia | School of Psychology and Public Health, La Trobe University, Melbourne, Australia

Correspondence
E-mail address | d.wong@latrobe.edu.au

Disclosures
The authors have nothing to disclose.

Abstract
Objective:

Rehabilitation of memory after stroke remains an unmet need. Telehealth delivery may overcome barriers to accessing rehabilitation services.

Method:

We conducted a non-randomized intervention trial to investigate feasibility and effectiveness of individual telehealth (internet videoconferencing) and face-to-face delivery methods for a six-week compensatory memory rehabilitation program. Supplementary analyses investigated non-inferiority to an existing group-based intervention, and the role of booster sessions in maintaining functional gains. The primary outcome measure was functional attainment of participants’ goals. Secondary measures included subjective reports of lapses in everyday memory and prospective memory, reported use of internal and external memory strategies, and objective measures of memory functioning.

Results:

Forty-six stroke survivors were allocated to telehealth and face-to-face intervention delivery conditions. Feasibility of delivery methods was supported, and participants in both conditions demonstrated treatment-related improvements in goal attainment, and key subjective outcomes of everyday memory, and prospective memory. Gains on these measures were maintained at six-week follow-up. Short-term gains in use of internal strategies were also seen. Non-inferiority to group-based delivery was established only on the primary measure for the telehealth delivery condition. Booster sessions were associated with greater maintenance of gains on subjective measures of everyday memory and prospective memory.

Conclusions:

This exploratory study supports the feasibility and potential effectiveness of telehealth options for remote delivery of compensatory memory skills training after a stroke. These results are also encouraging of a role for booster sessions in prolonging functional gains over time.

Bibliography
  1. Aben, L., Heijenbrok-Kal, M.H., van Loon, E.M.P., Groet, E., Ponds, R.W.H.M., Busschbach, J.J.V., & Ribbers, G.M. (2013). Training memory self-efficacy in the chronic stage after stroke: A randomized controlled trial. Neurorehabilitation and Neural Repair, 27(2), 110–117. doi: 10.1177/1545968312455222  CrossRef  Google Scholar 
  2. Allott, K. & Lloyd, S. (2009). The provision of neuropsychological services in rural/regional settings: Professional and ethical issues. Applied Neuropsychology, 16(3), 193–206. doi: 10.1080/09084280903098760  CrossRef  Google Scholar 
  3. Armfield, N.R., Gray, L.C., & Smith, A.C. (2012). Clinical use of Skype: A review of the evidence base. Journal of Telemedicine and Telecare, 18(3), 125–127. doi: 10.1258/jtt.2012.SFT101  CrossRef  Google Scholar 
  4. Armfield, N.R., Bradford, M., & Bradford, N.K. (2015). The clinical use of Skype – For which patients, with which problems and in which settings? A snapshot review of the literature. International Journal of Medical Informatics, 84(10), 737–742. doi: 10.1016/j.ijmedinf.2015.06.006  CrossRef  Google Scholar 
  5. Bergquist, T.F., Thompson, K., Gehl, C., & Pineda, J.M. (2010). Satisfaction ratings after receiving internet-based cognitive rehabilitation in persons with memory impairments after severe acquired brain injury. Telemedicine and e-Health, 16(4), 417–423. doi: 10.1089/tmj.2009.0118  CrossRef  Google Scholar 
  6. Boot, W.R., Charness, N., Czaja, S.J., Sharit, J., Rogers, W.A., Fisk, A.D., Mitzner, T., Lee, C.C., & Nair, S. (2015). Computer proficiency questionnaire: Assessing low and high computer proficient seniors. Gerontologist, 55(3), 404–411. doi: 10.1093/geront /gnt117  CrossRef  Google Scholar 
  7. Brearly, T.W., Shura, R.D., Martindale, S.L., Lazowski, R.A., Luxton, D.D., Shenal, B.V., & Rowland, J.A. (2017). Neuropsychological test administration by videoconference: A systematic review and meta-analysis. Neuropsychology Review, 27, 174–186. doi: 10.1007/s11065-017-9349-1  CrossRef  Google Scholar 
  8. Brown, T., Mapleston, J., Nairn, A., & Molloy, A. (2013). Relationship of cognitive and perceptual abilities to functional independence in adults who have had a stroke. Occupational Therapy International, 20(1), 11–22. doi: 10.1002/oti.1334  CrossRef  Google Scholar 
  9. Carson, N., Leach, L., & Murphy, K.J. (2017). A re-examination of Montreal Cognitive Assessment (MoCA) cutoff scores. International Journal of Geriatric Psychiatry, 33, 379–388. doi: 10.1002/gps.4756  CrossRef  Google Scholar 
  10. Chen, S.-Z., Jiang, Q., Liu, P., Huang, D.-F., & Ding, J.-X. (2006). Effect of the cognitive rehabilitation on the functional independence of hemiplegic patients with stroke. Chinese Journal of Clinical Rehabilitation, 10(18), 14–16. Google Scholar 
  11. Cohen, J. (1988). Statistical power analysis for the behavioral sciences, 2nd ed. Hillsdale, NJ: Lawremce Erlbaum Associates. Google Scholar 
  12. das Nair, R., Cogger, H., Worthington, E., & Lincoln, N.B. (2016). Cognitive rehabilitation for memory deficits after stroke. Cochrane Database of Systematic Reviews, 2016(9), CD002293. doi: 10.1002/14651858.CD002293.pub3  Google Scholar 
  13. das Nair, R., Cogger, H., Worthington, E., & Lincoln, N.B. (2017). Cognitive rehabilitation for memory deficits after stroke: An updated review. Stroke, 48, e28–e29. doi: 10.1161/STROKEAHA.116.015377. CrossRef  Google Scholar 
  14. das Nair, R. & Lincoln, N.B. (2007). Cognitive rehabilitation for memory deficits following stroke. Cochrane Database of Systematic Reviews, (3), CD002293. doi: 10.1002/14651858.CD002293.pub2  CrossRef  Google Scholar 
  15. Doornhein, K. & de Haan, E.H. (1998). Cognitive training for memory deficits in stroke patients. Neuropsychological Rehabilitation, 8(4), 393–400. doi: 10.1080/713755579  CrossRef  Google Scholar 
  16. Egbewale, B.E., Lewis, M., & Sim, J. (2014). Bias, precision and statistical power of analysis of covariance in the analysis of randomized trials with baseline imbalance: A simulation study. BMC Medical Research Methodology, 14(1), 1–12. doi: 10.1186/1471-2288-14-49  CrossRef  Google Scholar 
  17. Elliott, M. & Parente, F. (2014). Efficacy of memory rehabilitation therapy: A meta-analysis of TBI and stroke cognitive rehabilitation literature. Brain Injury, 28(12), 1610–1616. doi: 10.3109/02699052.2014.934921  CrossRef  Google Scholar 
  18. Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175–191. doi: 10.3758/BF03193146  CrossRef  Google Scholar 
  19. Fleming, J., Kennedy, S., Fisher, R., Gill, H., Gullo, M., & Shum, D. (2012). Validity of the Comprehensive Assessment of Prospective Memory (CAPM) for use with adults with traumatic brain injury. Brain Impairment, 10(1), 34–44. doi: 10.1375/brim.10.1.34  CrossRef  Google Scholar 
  20. Hill, A. & Theodoros, D. (2002). Research into telehealth applications in speech-language pathology. Journal of Telemedicine and Telecare, 8, 187–196. doi: 10.1258/135763302320272158  CrossRef  Google Scholar 
  21. House, G., Burdea, G., Grampurohit, N., Polistico, K., Roll, D., Damiani, F., Keeler, S., Hundal, J., & Pollack, S. (2016). Longitudinal study of integrative virtual rehabilitation use in skilled nursing facility maintenance programs for residents with chronic stroke. Paper presented at the International Conference on Virtual Rehabilitation, Los Angeles, California. Google Scholar 
  22. Howell, D.C. (2012). Statistical methods for psychology, 8th ed. Belmont, CA: Cengage. Google Scholar 
  23. IBM Corp. (2017). IBM SPSS Statistics for Windows, Version 25. Armonk, NY: IBM Corp. Google Scholar 
  24. Jager, K.J., Zoccali, C., MacLeod, A., & Dekker, F.W. (2008). Confounding: What it is and how to deal with it. Kidney International, 73(3), 256–260. doi: 10.1038/sj.ki.5002650  CrossRef  Google Scholar 
  25. Jia, H., Cowper, D.C., Tang, Y., Litt, E., & Wilson, L. (2012). Postacute stroke rehabilitation utilization: Are there differences between rural-urban patients and taxonomies? Journal of Rural Health, 28(3), 242–247. doi: 10.1111/j.1748-0361.2011.00397.x  CrossRef  Google Scholar 
  26. Joubert, J., Prentice, L.F., Moulin, T., Liaw, S.-T., Joubert, L.B., Preux, P.M., Ware, D. Medeiros de Bustos, E., & McLean, A. (2008). Stroke in rural areas and small communities. Stroke, 39(6), 1920–1928. doi: 10.1161/STROKEAHA.107.501643  CrossRef  Google Scholar 
  27. Lamb, F., Anderson, J., Saling, M., & Dewey, H. (2013). Predictors of subjective cognitive complaint in postacute older adult stroke patients. Archives of Physical Medicine and Rehabilitation, 94(9), 177–1752. doi: 10.1016/j.apmr.2013.02.026. CrossRef  Google Scholar 
  28. Lockwood, C. (2017). Cognitive rehabilitation for memory deficits after stroke: A Cochrane review summary. International Journal of Nursing Studies, 76, 131–132. CrossRef  Google Scholar 
  29. Miller, L.A. & Radford, K. (2014). Testing the effectiveness of group-based memory rehabilitation in chronic stroke patients. Neuropsychological Rehabilitation, 24(5), 721–737. doi: 10.1080/09602011.2014.894479  CrossRef  Google Scholar 
  30. Nasreddine, Z.S., Phillips, N.A., Bedirian, V., Charbonneau, S., Whitehead, V., Collin, I., Cummings, J.L., & Chertkow, H. (2005). The Montreal Cognitive Assessment, MoCA: A brief screening tool for mild cognitive impairment. Journal of the American Geriatrics Society, 53(4), 695–699. CrossRef  Google Scholar 
  31. Nouri, F.M. & Lincoln, N.B. (1987). An extended activities of daily living scale for stroke patients. Clinical Rehabilitation, 1(4), 301–305. doi: 10.1177/026921558700100409  CrossRef  Google Scholar 
  32. Optale, G., Urgesi, C., Busato, V., Marin, S., Piron, L., Priftis, K., Gamberini, L. Capodieci, S., & Bordin, A. (2010). Controlling memory impairment in elderly adults: A randomised controlled pilot study. Neurorehabilitation and Neural Repair, 24(4), 348–357. doi: 10.1177/1545968309353328  CrossRef  Google Scholar 
  33. Ownsworth, T., Arnautovska, U., Beadle, E., Shum, D.H.K., & Moyle, W. (2018). Efficacy of telerehabilitation for adults with traumatic brain injury. Journal of Head Trauma Rehabilitation, 33(4), E33–E46. doi: 10.1097/htr.0000000000000350  CrossRef  Google Scholar 
  34. Radford, K., Say, M., Thayer, Z., & Miller, L. (2010). Making the Most of Your Memory: An Everyday Memory Skills Program. Sydney, Australia: ASSBI Resources, Sydney. Google Scholar 
  35. Radford, K., Lah, S., Say, M.J., & Miller, L.A. (2011). Validation of a new measure of prospective memory: The Royal Prince Alfred prospective memory test. Clinical Neuropsychologist, 25(1), 127–140. doi: 10.1080/13854046.2010.529463  CrossRef  Google Scholar 
  36. Radford, K., Lah, S., Thayer, Z., Say, M.J., & Miller, L.A. (2012). Improving memory in outpatients with neurological disorders using a group-based training program. Journal of the International Neuropsychological Society, 18(4), 738–748. doi: 10.1017/S1355617712000379  CrossRef  Google Scholar 
  37. Rothman, M.D. & Tsou, H.-H. (2003). On non-inferiority analysis based on delta-method confidence intervals. Journal of Biopharmaceutical Statistics, 13(3), 565–583. doi: 10.1081/BIP-120022775  CrossRef  Google Scholar 
  38. Royle, J. & Lincoln, N. (2008). The Everyday Memory Questionnaire-revised: Development of a 13-item scale. Disability and Rehabilitation, 30(2), 114–121. doi: 10.1080/09638280701223876  CrossRef  Google Scholar 
  39. Russell, T.G. (2009). Telerehabilitation: A coming of age. Australian Journal of Physiotherapy, 55(1), 5–6. doi: 10.1016/S0004-9514(09)70054-6  CrossRef  Google Scholar 
  40. Schumi, J. & Wittes, J.T. (2011). Through the looking glass: Understanding non-inferiority. Trials, 12, 1–12. doi: 10.1186/1745-6215-12-106  CrossRef  Google Scholar 
  41. Schmidt, M. (1996). Rey auditory verbal learning test: A handbook. Los Angeles, CA: Western Psychological Services. Google Scholar 
  42. Sheldon, S. & Winocur, G. (2014). Memory loss after stroke, In Schweizer, T.A. and Loch Macdonald, R. (Eds.), The behavioral consequences of stroke (pp. 151–176). New York, NY: Springer. CrossRef  Google Scholar 
  43. Taylor, G.H. & Broomfield, N.M. (2013). Cognitive assessment and rehabilitation pathway for stroke (CARPS). Topics in Stroke Rehabilitation, 20(3), 270–282. doi: 10.1310/tsr2003-270  CrossRef  Google Scholar 
  44. Turner-Stokes, L. (2009). Goal attainment scaling (GAS) in rehabilitation: A practical guide. Clinical Rehabilitation, 23(4), 362–370. doi: 10.1177/0269215508101742  CrossRef  Google Scholar 
  45. Turner-Stokes, L., Williams, H., & Johnson, J. (2009). Goal attainment scaling: Does it provide added value as a person-centred measure for evaluation of outcome in neurorehabilitation following acquired brain injury? Journal of Rehabilitation Medicine, 41(7), 528–535. doi: 10.2340/16501977-0383  CrossRef  Google Scholar 
  46. Weakliem, D.L. (2016). Hypothesis testing and model selection in the social sciences. New York: Guilford Press. Google Scholar 
  47. Wechsler, D. (2009). Test of premorbid functioning. San Antonio, TX: The Psychological Corporation. Google Scholar 
  48. Westerberg, H., Jacobaeus, H., Hirvikoski, T., Clevberger, P., Ostensson, M.-L., Bartfai, A., & Klingberg, T. (2007). Computerised working memory training after stroke: A pilot study. Brain Injury, 21(1), 21–29. doi: 10.1080/02699050601148726  CrossRef  Google Scholar 
  49. Withiel, T.D., Sharp, V.L., Wong, D., Ponsford, J.L., Warren, N., & Stolwyk, R.J. (2018). Understanding the experience of compensatory and restorative memory rehabilitation: A qualitative study of stroke survivors. Neuropsychological Rehabilitation. Advance online publication. doi: 10.1080/09602011.2018.1479275  CrossRef  Google Scholar 
  50. Withiel, T.D., Stolwyk, R.J., Ponsford, J.L., Cadilhac, D.A., & Wong, D. (2019). Effectiveness of a manualised group training intervention for memory dysfunction following stroke: A series of single case studies. Disability and Rehabilitation. Advance online publication. doi: 10.1080/09638288.2019.1579260  CrossRef  Google Scholar 
  51. Withiel, T.D., Wong, D., Ponsford, J.L., Cadilhac, D.A., New, P., Mihaljcic, T., & Stolwyk, R.J. (2019). Comparing compensatory and restorative memory rehabilitation following stroke: A phase II randomised controlled trial. Journal of Rehabilitation Medicine, 51(5), 343–351. doi: 10.2340/16501977-2540  CrossRef  Google Scholar 
Individual Alpha Peak Frequency Moderates Transfer of Learning in Cognitive Remediation of Schizophrenia
Author(s)
  • B.C. Castelluccio | Department of Psychiatry and Human Behavior, Brown University Alpert Medical School, Providence, RI 02903, USA
  • J.G. Kenney | Psychology Service, VA Connecticut Healthcare System, West Haven, CT 06516, USA | Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06510, USA
  • J.K. Johannesen | Psychology Service, VA Connecticut Healthcare System, West Haven, CT 06516, USA | Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06510, USA

Correspondence
E-mail address | jason.johannesen@yale.edu

Disclosures
There are no conflicts of interest for any of the authors of this paper.

Abstract
Objective:

Meta-analyses report moderate effects across cognitive remediation (CR) trials in schizophrenia. However, individual responses are variable, with some participants showing no appreciable gain in cognitive performance. Furthermore, reasons for heterogeneous outcome are undetermined. We examine the extent to which CR outcome is attributable to near learning—direct gains in trained cognitive tasks—while also exploring factors influencing far transfer of gains during training to external cognitive measures.

Method:

Thirty-seven schizophrenia outpatients were classified as CR responders and non-responders according to change in MATRICS Consensus Cognitive Battery composite score following 20 sessions of computer-based training. Metrics of near learning during training, as well as baseline demographic, clinical, cognitive, and electroencephalographic (EEG) measures, were examined as predictors of responder status.

Results:

Significant post-training improvement in cognitive composite score (Cohen’s d = .41) was observed across the sample, with n = 21 and n = 16 classified as responders and non-responders, respectively. Near learning was evidenced by significant improvement on each training exercise with practice; however, learning did not directly predict responder status. Group-wise comparison of responders and non-responders identified two factors favoring responders: higher EEG individual alpha frequency (IAF) and lower antipsychotic dosing. Tested in moderation analyses, IAF interacted with learning to predict improvement in cognitive outcome.

Conclusion:

CR outcome in schizophrenia is not directly explained by learning during training and appears to depend on latent factors influencing far transfer of trained abilities. Further understanding of factors influencing transfer of learning is needed to optimize CR efficacy.

Bibliography
  1. Aben, L., Heijenbrok-Kal, M.H., van Loon, E.M.P., Groet, E., Ponds, R.W.H.M., Busschbach, J.J.V., & Ribbers, G.M. (2013). Training memory self-efficacy in the chronic stage after stroke: A randomized controlled trial. Neurorehabilitation and Neural Repair, 27(2), 110–117. doi: 10.1177/1545968312455222  CrossRef  Google Scholar 
  2. Allott, K. & Lloyd, S. (2009). The provision of neuropsychological services in rural/regional settings: Professional and ethical issues. Applied Neuropsychology, 16(3), 193–206. doi: 10.1080/09084280903098760  CrossRef  Google Scholar 
  3. Armfield, N.R., Gray, L.C., & Smith, A.C. (2012). Clinical use of Skype: A review of the evidence base. Journal of Telemedicine and Telecare, 18(3), 125–127. doi: 10.1258/jtt.2012.SFT101  CrossRef  Google Scholar 
  4. Armfield, N.R., Bradford, M., & Bradford, N.K. (2015). The clinical use of Skype – For which patients, with which problems and in which settings? A snapshot review of the literature. International Journal of Medical Informatics, 84(10), 737–742. doi: 10.1016/j.ijmedinf.2015.06.006  CrossRef  Google Scholar 
  5. Bergquist, T.F., Thompson, K., Gehl, C., & Pineda, J.M. (2010). Satisfaction ratings after receiving internet-based cognitive rehabilitation in persons with memory impairments after severe acquired brain injury. Telemedicine and e-Health, 16(4), 417–423. doi: 10.1089/tmj.2009.0118  CrossRef  Google Scholar 
  6. Boot, W.R., Charness, N., Czaja, S.J., Sharit, J., Rogers, W.A., Fisk, A.D., Mitzner, T., Lee, C.C., & Nair, S. (2015). Computer proficiency questionnaire: Assessing low and high computer proficient seniors. Gerontologist, 55(3), 404–411. doi: 10.1093/geront /gnt117  CrossRef  Google Scholar 
  7. Brearly, T.W., Shura, R.D., Martindale, S.L., Lazowski, R.A., Luxton, D.D., Shenal, B.V., & Rowland, J.A. (2017). Neuropsychological test administration by videoconference: A systematic review and meta-analysis. Neuropsychology Review, 27, 174–186. doi: 10.1007/s11065-017-9349-1  CrossRef  Google Scholar 
  8. Brown, T., Mapleston, J., Nairn, A., & Molloy, A. (2013). Relationship of cognitive and perceptual abilities to functional independence in adults who have had a stroke. Occupational Therapy International, 20(1), 11–22. doi: 10.1002/oti.1334  CrossRef  Google Scholar 
  9. Carson, N., Leach, L., & Murphy, K.J. (2017). A re-examination of Montreal Cognitive Assessment (MoCA) cutoff scores. International Journal of Geriatric Psychiatry, 33, 379–388. doi: 10.1002/gps.4756  CrossRef  Google Scholar 
  10. Chen, S.-Z., Jiang, Q., Liu, P., Huang, D.-F., & Ding, J.-X. (2006). Effect of the cognitive rehabilitation on the functional independence of hemiplegic patients with stroke. Chinese Journal of Clinical Rehabilitation, 10(18), 14–16. Google Scholar 
  11. Cohen, J. (1988). Statistical power analysis for the behavioral sciences, 2nd ed. Hillsdale, NJ: Lawremce Erlbaum Associates. Google Scholar 
  12. das Nair, R., Cogger, H., Worthington, E., & Lincoln, N.B. (2016). Cognitive rehabilitation for memory deficits after stroke. Cochrane Database of Systematic Reviews, 2016(9), CD002293. doi: 10.1002/14651858.CD002293.pub3  Google Scholar 
  13. das Nair, R., Cogger, H., Worthington, E., & Lincoln, N.B. (2017). Cognitive rehabilitation for memory deficits after stroke: An updated review. Stroke, 48, e28–e29. doi: 10.1161/STROKEAHA.116.015377. CrossRef  Google Scholar 
  14. das Nair, R. & Lincoln, N.B. (2007). Cognitive rehabilitation for memory deficits following stroke. Cochrane Database of Systematic Reviews, (3), CD002293. doi: 10.1002/14651858.CD002293.pub2  CrossRef  Google Scholar 
  15. Doornhein, K. & de Haan, E.H. (1998). Cognitive training for memory deficits in stroke patients. Neuropsychological Rehabilitation, 8(4), 393–400. doi: 10.1080/713755579  CrossRef  Google Scholar 
  16. Egbewale, B.E., Lewis, M., & Sim, J. (2014). Bias, precision and statistical power of analysis of covariance in the analysis of randomized trials with baseline imbalance: A simulation study. BMC Medical Research Methodology, 14(1), 1–12. doi: 10.1186/1471-2288-14-49  CrossRef  Google Scholar 
  17. Elliott, M. & Parente, F. (2014). Efficacy of memory rehabilitation therapy: A meta-analysis of TBI and stroke cognitive rehabilitation literature. Brain Injury, 28(12), 1610–1616. doi: 10.3109/02699052.2014.934921  CrossRef  Google Scholar 
  18. Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175–191. doi: 10.3758/BF03193146  CrossRef  Google Scholar 
  19. Fleming, J., Kennedy, S., Fisher, R., Gill, H., Gullo, M., & Shum, D. (2012). Validity of the Comprehensive Assessment of Prospective Memory (CAPM) for use with adults with traumatic brain injury. Brain Impairment, 10(1), 34–44. doi: 10.1375/brim.10.1.34  CrossRef  Google Scholar 
  20. Hill, A. & Theodoros, D. (2002). Research into telehealth applications in speech-language pathology. Journal of Telemedicine and Telecare, 8, 187–196. doi: 10.1258/135763302320272158  CrossRef  Google Scholar 
  21. House, G., Burdea, G., Grampurohit, N., Polistico, K., Roll, D., Damiani, F., Keeler, S., Hundal, J., & Pollack, S. (2016). Longitudinal study of integrative virtual rehabilitation use in skilled nursing facility maintenance programs for residents with chronic stroke. Paper presented at the International Conference on Virtual Rehabilitation, Los Angeles, California. Google Scholar 
  22. Howell, D.C. (2012). Statistical methods for psychology, 8th ed. Belmont, CA: Cengage. Google Scholar 
  23. IBM Corp. (2017). IBM SPSS Statistics for Windows, Version 25. Armonk, NY: IBM Corp. Google Scholar 
  24. Jager, K.J., Zoccali, C., MacLeod, A., & Dekker, F.W. (2008). Confounding: What it is and how to deal with it. Kidney International, 73(3), 256–260. doi: 10.1038/sj.ki.5002650  CrossRef  Google Scholar 
  25. Jia, H., Cowper, D.C., Tang, Y., Litt, E., & Wilson, L. (2012). Postacute stroke rehabilitation utilization: Are there differences between rural-urban patients and taxonomies? Journal of Rural Health, 28(3), 242–247. doi: 10.1111/j.1748-0361.2011.00397.x  CrossRef  Google Scholar 
  26. Joubert, J., Prentice, L.F., Moulin, T., Liaw, S.-T., Joubert, L.B., Preux, P.M., Ware, D. Medeiros de Bustos, E., & McLean, A. (2008). Stroke in rural areas and small communities. Stroke, 39(6), 1920–1928. doi: 10.1161/STROKEAHA.107.501643  CrossRef  Google Scholar 
  27. Lamb, F., Anderson, J., Saling, M., & Dewey, H. (2013). Predictors of subjective cognitive complaint in postacute older adult stroke patients. Archives of Physical Medicine and Rehabilitation, 94(9), 177–1752. doi: 10.1016/j.apmr.2013.02.026. CrossRef  Google Scholar 
  28. Lockwood, C. (2017). Cognitive rehabilitation for memory deficits after stroke: A Cochrane review summary. International Journal of Nursing Studies, 76, 131–132. CrossRef  Google Scholar 
  29. Miller, L.A. & Radford, K. (2014). Testing the effectiveness of group-based memory rehabilitation in chronic stroke patients. Neuropsychological Rehabilitation, 24(5), 721–737. doi: 10.1080/09602011.2014.894479  CrossRef  Google Scholar 
  30. Nasreddine, Z.S., Phillips, N.A., Bedirian, V., Charbonneau, S., Whitehead, V., Collin, I., Cummings, J.L., & Chertkow, H. (2005). The Montreal Cognitive Assessment, MoCA: A brief screening tool for mild cognitive impairment. Journal of the American Geriatrics Society, 53(4), 695–699. CrossRef  Google Scholar 
  31. Nouri, F.M. & Lincoln, N.B. (1987). An extended activities of daily living scale for stroke patients. Clinical Rehabilitation, 1(4), 301–305. doi: 10.1177/026921558700100409  CrossRef  Google Scholar 
  32. Optale, G., Urgesi, C., Busato, V., Marin, S., Piron, L., Priftis, K., Gamberini, L. Capodieci, S., & Bordin, A. (2010). Controlling memory impairment in elderly adults: A randomised controlled pilot study. Neurorehabilitation and Neural Repair, 24(4), 348–357. doi: 10.1177/1545968309353328  CrossRef  Google Scholar 
  33. Ownsworth, T., Arnautovska, U., Beadle, E., Shum, D.H.K., & Moyle, W. (2018). Efficacy of telerehabilitation for adults with traumatic brain injury. Journal of Head Trauma Rehabilitation, 33(4), E33–E46. doi: 10.1097/htr.0000000000000350  CrossRef  Google Scholar 
  34. Radford, K., Say, M., Thayer, Z., & Miller, L. (2010). Making the Most of Your Memory: An Everyday Memory Skills Program. Sydney, Australia: ASSBI Resources, Sydney. Google Scholar 
  35. Radford, K., Lah, S., Say, M.J., & Miller, L.A. (2011). Validation of a new measure of prospective memory: The Royal Prince Alfred prospective memory test. Clinical Neuropsychologist, 25(1), 127–140. doi: 10.1080/13854046.2010.529463  CrossRef  Google Scholar 
  36. Radford, K., Lah, S., Thayer, Z., Say, M.J., & Miller, L.A. (2012). Improving memory in outpatients with neurological disorders using a group-based training program. Journal of the International Neuropsychological Society, 18(4), 738–748. doi: 10.1017/S1355617712000379  CrossRef  Google Scholar 
  37. Rothman, M.D. & Tsou, H.-H. (2003). On non-inferiority analysis based on delta-method confidence intervals. Journal of Biopharmaceutical Statistics, 13(3), 565–583. doi: 10.1081/BIP-120022775  CrossRef  Google Scholar 
  38. Royle, J. & Lincoln, N. (2008). The Everyday Memory Questionnaire-revised: Development of a 13-item scale. Disability and Rehabilitation, 30(2), 114–121. doi: 10.1080/09638280701223876  CrossRef  Google Scholar 
  39. Russell, T.G. (2009). Telerehabilitation: A coming of age. Australian Journal of Physiotherapy, 55(1), 5–6. doi: 10.1016/S0004-9514(09)70054-6  CrossRef  Google Scholar 
  40. Schumi, J. & Wittes, J.T. (2011). Through the looking glass: Understanding non-inferiority. Trials, 12, 1–12. doi: 10.1186/1745-6215-12-106  CrossRef  Google Scholar 
  41. Schmidt, M. (1996). Rey auditory verbal learning test: A handbook. Los Angeles, CA: Western Psychological Services. Google Scholar 
  42. Sheldon, S. & Winocur, G. (2014). Memory loss after stroke, In Schweizer, T.A. and Loch Macdonald, R. (Eds.), The behavioral consequences of stroke (pp. 151–176). New York, NY: Springer. CrossRef  Google Scholar 
  43. Taylor, G.H. & Broomfield, N.M. (2013). Cognitive assessment and rehabilitation pathway for stroke (CARPS). Topics in Stroke Rehabilitation, 20(3), 270–282. doi: 10.1310/tsr2003-270  CrossRef  Google Scholar 
  44. Turner-Stokes, L. (2009). Goal attainment scaling (GAS) in rehabilitation: A practical guide. Clinical Rehabilitation, 23(4), 362–370. doi: 10.1177/0269215508101742  CrossRef  Google Scholar 
  45. Turner-Stokes, L., Williams, H., & Johnson, J. (2009). Goal attainment scaling: Does it provide added value as a person-centred measure for evaluation of outcome in neurorehabilitation following acquired brain injury? Journal of Rehabilitation Medicine, 41(7), 528–535. doi: 10.2340/16501977-0383  CrossRef  Google Scholar 
  46. Weakliem, D.L. (2016). Hypothesis testing and model selection in the social sciences. New York: Guilford Press. Google Scholar 
  47. Wechsler, D. (2009). Test of premorbid functioning. San Antonio, TX: The Psychological Corporation. Google Scholar 
  48. Westerberg, H., Jacobaeus, H., Hirvikoski, T., Clevberger, P., Ostensson, M.-L., Bartfai, A., & Klingberg, T. (2007). Computerised working memory training after stroke: A pilot study. Brain Injury, 21(1), 21–29. doi: 10.1080/02699050601148726  CrossRef  Google Scholar 
  49. Withiel, T.D., Sharp, V.L., Wong, D., Ponsford, J.L., Warren, N., & Stolwyk, R.J. (2018). Understanding the experience of compensatory and restorative memory rehabilitation: A qualitative study of stroke survivors. Neuropsychological Rehabilitation. Advance online publication. doi: 10.1080/09602011.2018.1479275  CrossRef  Google Scholar 
  50. Withiel, T.D., Stolwyk, R.J., Ponsford, J.L., Cadilhac, D.A., & Wong, D. (2019). Effectiveness of a manualised group training intervention for memory dysfunction following stroke: A series of single case studies. Disability and Rehabilitation. Advance online publication. doi: 10.1080/09638288.2019.1579260  CrossRef  Google Scholar 
  51. Withiel, T.D., Wong, D., Ponsford, J.L., Cadilhac, D.A., New, P., Mihaljcic, T., & Stolwyk, R.J. (2019). Comparing compensatory and restorative memory rehabilitation following stroke: A phase II randomised controlled trial. Journal of Rehabilitation Medicine, 51(5), 343–351. doi: 10.2340/16501977-2540  CrossRef  Google Scholar 
Impact of Combined Transcranial Direct Current Stimulation and Speech-language Therapy on Spontaneous Speech in Aphasia: A Randomized Controlled Double-blind Study
Author(s)
  • Elodie Guillouët | Rehabilitation Unit, Raymond Poincaré Hospital, Garches 92380, France | EA4047, HANDIReSP, Versailles Saint-Quentin University, Versailles 78180, France
  • Mélanie Cogné | Rehabilitation Unit, University Hospital, Rennes 35000, France
  • Elisabeth Saverot | Rehabilitation Unit, MGEN, Maisons-Laffitte 78600, France
  • Nicolas Roche | Rehabilitation Unit, Raymond Poincaré Hospital, Garches 92380, France | INSERM Unit 1179, Team 3, Technologies and Innovative Therapies Applied to Neuromuscular Diseases, UVSQ, CIC 429, Physiology-Functional Testing Ward, AP-HP, Raymond Poincaré Teaching Hospital, Garches 92380, France
  • Pascale Pradat-Diehl | Rehabilitation Unit, hôpital Pitié-Salpêtrière, AP–HP, Paris 75013, France
  • Agnès Weill-Chounlamountry | Rehabilitation Unit, hôpital Pitié-Salpêtrière, AP–HP, Paris 75013, France
  • Vanessa Ramel | Rehabilitation Unit, hôpital Pitié-Salpêtrière, AP–HP, Paris 75013, France
  • Catherine Taratte | Rehabilitation Unit, MGEN, Maisons-Laffitte 78600, France
  • Anne-Gaëlle Lachasse | Rehabilitation Unit, MGEN, Maisons-Laffitte 78600, France
  • Jean-Arthur Haulot | Rehabilitation Unit, MGEN, Maisons-Laffitte 78600, France
  • Isabelle | Inserm, Centre d’Investigation Clinique 1429, AP-HP, Raymond Poincaré hospital, Garches 92380, France
  • Frédéric Barbot | Inserm, Centre d’Investigation Clinique 1429, AP-HP, Raymond Poincaré hospital, Garches 92380, France
  • Philippe Azouvi | Rehabilitation Unit, Raymond Poincaré Hospital, Garches 92380, France | EA4047, HANDIReSP, Versailles Saint-Quentin University, Versailles 78180, France
  • Sophie Charveriat | Rehabilitation Unit, Raymond Poincaré Hospital, Garches 92380, France | EA4047, HANDIReSP, Versailles Saint-Quentin University, Versailles 78180, France

Correspondence
E-mail address | philippe.azouvi@aphp.fr

Disclosures
There are no conflicts of interest for any of the authors of this paper.

Abstract
Objective:

Aphasia recovery depends on neural reorganization, which can be enhanced by speech-language therapy and noninvasive brain stimulation. Several studies suggested that transcranial direct current stimulation (tDCS) associated with speech-language therapy may improve verbal performance evaluated by analytic tests, but none focused on spontaneous speech. We explored the effect of bihemispheric tDCS on spontaneous speech in patients with poststroke aphasia.

Methods:

In this multicentric controlled randomized cross-over double-blind study, we included 10 patients with poststroke aphasia (4 had aphasia >6 months and 6 with aphasia <6 months). We combined the sessions of speech-language therapy and bihemispheric tDCS (2 mA, 20 min). After three baseline speech evaluations (1/week), two different conditions were randomly consecutively proposed: active and sham tDCS over 3 weeks with 1 week of washout in between. The main outcome measure was the number of different nouns used in 2 min to answer the question “what is your job.”

Results:

There was no significant difference between conditions concerning the main outcome measure (p = .47) nor in the number of verbs, adjectives, adverbs, pronouns, repetitions, blank ideas, ideas, utterances with grammatical errors or paraphasias used. Other cognitive functions (verbal working memory, neglect, or verbal fluency) were not significantly improved in the tDCS group. No adverse events occurred.

Conclusion:

Our results differed from previous studies using tDCS to improve naming in patients with poststroke aphasia possibly due to bihemispheric stimulation, rarely used previously. The duration of the rehabilitation period was short given the linguistic complexity of the measure. This negative result should be confirmed by larger studies with ecological measures.

Bibliography
  1. Anokhin, A. & Vogel, F. (1996). EEG Alpha rhythm frequency and intelligence in normal adults. Intelligence, 23(1), 1–14. doi:10.1016/S0160-2896(96)80002-X  CrossRef  Google Scholar 
  2. Best, M.W. & Bowie, C.R. (2017). A review of cognitive remediation approaches for schizophrenia: From top-down to bottom-up, brain training to psychotherapy. Expert Review of Neurotherapeutics, 17(7), 713–723. doi:10.1080/14737175.2017.1331128  CrossRef  Google Scholar 
  3. Buchanan, R.W., Freedman, R., Javitt, D.C., Abi-Dargham, A., & Lieberman, J.A. (2007). Recent advances in the development of novel pharmacological agents for the treatment of cognitive impairments in schizophrenia. Schizophrenia Bulletin, 33(5), 1120–1130. doi:10.1093/schbul/sbm083  CrossRef  Google Scholar 
  4. Clark, C.R., Veltmeyer, M.D., Hamilton, R.J., Simms, E., Paul, R., Hermens, D., & Gordon, E. (2004). Spontaneous alpha peak frequency predicts working memory performance across the age span. International Journal of Psychophysiology, 53(1), 1–9. doi:10.1016/J.IJPSYCHO.2003.12.011  CrossRef  Google Scholar 
  5. Davidson, C.A., Johannesen, J.K., & Fiszdon, J.M. (2016). Role of learning potential in cognitive remediation: Construct and predictive validity. Schizophrenia Research, 171(1–3), 117–124. doi:10.1016/j.schres.2016.01.044  CrossRef  Google Scholar 
  6. DeTore, N.R., Mueser, K.T., Byrd, J.A., & McGurk, S.R. (2019). Cognitive functioning as a predictor of response to comprehensive cognitive remediation. Journal of Psychiatric Research, 113(March), 117–124. doi:10.1016/j.jpsychires.2019.03.012  CrossRef  Google Scholar 
  7. Doppelmayr, M., Klimesch, W., Sauseng, P., Hödlmoser, K., Stadler, W., & Hanslmayr, S. (2005). Intelligence related differences in EEG-bandpower. Neuroscience Letters, 381(3), 309–313. doi:10.1016/J.NEULET.2005.02.037  CrossRef  Google Scholar 
  8. D’Souza, D.C., Carson, R.E., Driesen, N., Johannesen, J., Ranganathan, M., Krystal, J.H., Ahn, K.H., Bielen, K., Carbuto, M., Deaso, E. Naganawa, M., & Pittman, B. (2018). Dose-related target occupancy and effects on circuitry, behavior, and neuroplasticity of the glycine transporter-1 inhibitor PF-03463275 in healthy and schizophrenia subjects. Biological Psychiatry, 84(6), 413–421. doi:10.1016/j.biopsych.2017.12.019  CrossRef  Google Scholar 
  9. Élie, D., Poirier, M., Chianetta, J., Durand, M., Grégoire, C., & Grignon, S. (2010). Cognitive effects of antipsychotic dosage and polypharmacy: A study with the BACS in patients with schizophrenia and schizoaffective disorder. Journal of Psychopharmacology, 24(7), 1037–1044. doi:10.1177/0269881108100777  CrossRef  Google Scholar 
  10. First, M.B., Spitzer, R.L., Gibbon, M., & Williams, J.B.W. (2002). Structured Clinical Interview for DSM-IV-TR Axis I Disorders (Research Version, Patient Edition (SCID-I/P)). New York: Biometrics Research: New York State Psychiatric Institute. Google Scholar 
  11. Fisher, M., Loewy, R., Carter, C., Lee, A., Ragland, J.D., Niendam, T., Schlosser, D., Pham, L., Miskovich, T., & Vinogradov, S. (2015). Neuroplasticity-based auditory training via laptop computer improves cognition in young individuals with recent onset schizophrenia. Schizophrenia Bulletin, 41(1), 250–258. doi:10.1093/schbul/sbt232  CrossRef  Google Scholar 
  12. Fiszdon, J.M. & Johannesen, J.K. (2010). Comparison of computational methods for the evaluation of learning potential in schizophrenia. Journal of the International Neuropsychological Society, 16(4), 613–620. doi:10.1017/S1355617710000317  CrossRef  Google Scholar 
  13. Fiszdon, J.M., McClough, J.F., Silverstein, S.M., Bell, M.D., Jaramillo, J.R., & Smith, T.E. (2006). Learning potential as a predictor of readiness for psychosocial rehabilitation in schizophrenia. Psychiatry Research, 143(2–3), 159–166. doi:10.1016/j.psychres.2005.09.012  CrossRef  Google Scholar 
  14. Foxe, J.J. & Snyder, A.C. (2011). The role of alpha-band brain oscillations as a sensory suppression mechanism during selective attention. Frontiers in Psychology, 2, 1–13. doi:10.3389/fpsyg.2011.00154  CrossRef  Google Scholar 
  15. Giannitrapani, D. & Kayton, L. (1974). Schizophrenia and EEG spectral analysis. Electroencephalography and Clinical Neurophysiology, 36, 377–386. doi:10.1016/0013-4694(74)90187-4  CrossRef  Google Scholar 
  16. Grandy, T.H., Werkle-Bergner, M., Chicherio, C., Lövdén, M., Schmiedek, F., & Lindenberger, U. (2013). Individual alpha peak frequency is related to latent factors of general cognitive abilities. NeuroImage, 79, 10–18. doi:10.1016/J.NEUROIMAGE.2013.04.059  CrossRef  Google Scholar 
  17. Grandy, T.H., Werkle-Bergner, M., Chicherio, C., Schmiedek, F., Lövdén, M., & Lindenberger, U. (2013). Peak individual alpha frequency qualifies as a stable neurophysiological trait marker in healthy younger and older adults. Psychophysiology, 50(6), 570–582. doi:10.1111/psyp.12043  CrossRef  Google Scholar 
  18. Gratton, G., Coles, M.G., & Donchin, E. (1983). A new method for off-line removal of ocular artifact. Electroencephalography and Clinical Neurophysiology, 55(4), 468–84. CrossRef  Google Scholar 
  19. Green, M.F., Kern, R.S., Braff, D.L., & Mintz, J. (2000). Neurocognitive deficits and functional outcome in schizophrenia: Are we measuring the “Right Stuff”? Schizophrenia Bulletin, 26(1), 119–136. doi:10.1093/oxfordjournals.schbul.a033430  CrossRef  Google Scholar 
  20. Grynszpan, O., Perbal, S., Pelissolo, A., Fossati, P., Jouvent, R., Dubal, S., & Perez-Diaz, F. (2011). Efficacy and specificity of computer-assisted cognitive remediation in schizophrenia: A meta-analytical study. Psychological Medicine, 41(1), 163–173. doi:10.1017/S0033291710000607  CrossRef  Google Scholar 
  21. Harris, A., Melkonian, D., Williams, L., & Gordon, E. (2006). Dynamic spectral analysis findings in first episode and chronic schizophrenia. International Journal of Neuroscience, 116(3), 223–246. doi:10.1080/00207450500402977  CrossRef  Google Scholar 
  22. Hayes, A.F. (2013). Methodology in the Social Sciences. Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach. New York, NY: Guilford Press. Google Scholar 
  23. Hegerl, U., Sander, C., Ulke, C., Böttger, D., Hensch, T., Huang, J., Mauche, N., & Olbrich, S. (2016). Vigilance Algorithm Leipzig (VIGALL) Version 2.1 Manual. Google Scholar 
  24. Hill, S.K., Bishop, J.R., Palumbo, D., & Sweeney, J.A. (2010). Effect of second-generation antipsychotics on cognition: Current issues and future challenges. Expert Review of Neurotherapeutics, 10(1), 43–57. doi:10.1586/ern.09.143  CrossRef  Google Scholar 
  25. Ho, B.-C., Andreasen, N.C., Ziebell, S., Pierson, R., & Magnotta, V. (2011). Long-term antipsychotic treatment and brain volumes: A longitudinal study of first-episode schizophrenia. Archives of General Psychiatry, 68(2), 128–37. doi:10.1001/archgenpsychiatry.2010.199  CrossRef  Google Scholar 
  26. Hochberger, W.C., Joshi, Y.B., Thomas, M.L., Zhang, W., Bismark, A.W., Treichler, E.B.H., Tarasenko, M, Nungaray, J, Sprock, J, Cardoso, L, Swerdlow, N, & Light, G.A. (2018). Neurophysiologic measures of target engagement predict response to auditory-based cognitive training in treatment refractory schizophrenia. Neuropsychopharmacology, 44, 606–612. (October 2018). doi:10.1038/s41386-018-0256-9  CrossRef  Google Scholar 
  27. Hori, H., Noguchi, H., Hashimoto, R., Nakabayashi, T., Omori, M., Takahashi, S., Tsukue, R., Anami, K., Hirabayashi, N., Harada, S., Saitoh, O., & Kunugi, H. (2006). Antipsychotic medication and cognitive function in schizophrenia. Schizophrenia Research, 86(1–3), 138–146. doi:10.1016/j.schres.2006.05.004  CrossRef  Google Scholar 
  28. Joshi, Y.B., Thomas, M.L., Hochberger, W.C., Bismark, A.W., Treichler, E.B.H., Molina, J., Nungaray, J., Cardoso, L., Sprock, J., Swerdlow, N.R., & Light, G.A. (2019). Verbal learning deficits associated with increased anticholinergic burden are attenuated with targeted cognitive training in treatment refractory schizophrenia patients. Schizophrenia Research, 208, 384–389. doi:10.1016/j.schres.2019.01.016  CrossRef  Google Scholar 
  29. Karson, C.N., Coppola, R., & Daniel, D.G. (1988). Alpha frequency in schizophrenia: An association with enlarged cerebral ventricles. American Journal of Psychiatry, 145, 861–864. doi:10.1176/ajp.145.7.861  Google Scholar 
  30. Klimesch, W., Schimke, H., & Pfurtscheller, G. (1993). Alpha frequency, cognitive load and memory performance. Brain Topography, 5(3), 241–251. doi:10.1007/BF01128991  CrossRef  Google Scholar 
  31. Lindenmayer, J.P., Ozog, V.A., Khan, A., Ljuri, I., Fregenti, S., & McGurk, S.R. (2017). Predictors of response to cognitive remediation in service recipients with severe mental illness. Psychiatric Rehabilitation Journal, 40(1), 61–69. doi:10.1037/prj0000252  CrossRef  Google Scholar 
  32. McGurk, S.R. & Mueser, K.T. (2017). Introduction to special issue on cognitive remediation. Psychiatric Rehabilitation Journal, 40(1), 1–3. doi:10.1037/prj0000263  CrossRef  Google Scholar 
  33. McGurk, S.R., Twamley, E.W., Sitzer, D.I., McHugo, G.J., & Mueser, K.T. (2007). A meta-analysis of cognitive remediation in schizophrenia. American Journal of Psychiatry, 164, 1791–1802. CrossRef  Google Scholar 
  34. Medalia, A. & Richardson, R. (2005). What predicts a good response to cognitive remediation interventions? Schizophrenia Bulletin, 31(4), 942–953. doi:10.1093/schbul/sbi045  CrossRef  Google Scholar 
  35. Murthy, N.V., Mahncke, H., Wexler, B.E., Maruff, P., Inamdar, A., Zucchetto, M., Lund, J., Shabbir, S., Shergill, S., Keshavan, M., Kapur, S., Laruelle, M., & Alexander, R. (2012). Computerized cognitive remediation training for schizophrenia: An open label, multi-site, multinational methodology study. Schizophrenia Research, 139(1–3), 87–91. doi:10.1016/j.schres.2012.01.042  CrossRef  Google Scholar 
  36. Nuechterlein, K.H., Barch, D.M., Gold, J.M., Goldberg, T.E., Green, M.F., & Heaton, R.K. (2004). Identification of separable cognitive factors in schizophrenia. Schizophrenia Research, 72(1), 29–39. doi:10.1016/j.schres.2004.09.007  CrossRef  Google Scholar 
  37. Nuechterlein, K.H., Green, M.F., Kern, R.S., Baade, L.E., Barch, D.M., Cohen, J.D., Essock, S., Fenton, W.S., Frese, FJ 3rd, Gold, J.M., Goldberg, T., Heaton, R.K., Keefe, R.S., Kraemer, H., Mesholam-Gately, R., Seidman, L.J., Stover, E., Weinberger, D.R., Young, A.S., Zalcman, S., & Marder, S.R. (2008). The MATRICS consensus cognitive battery, Part 1: Test selection, reliability, and validity. American Journal of Psychiatry, 165(2), 203–213. doi:10.1176/appi.ajp.2007.07010042  CrossRef  Google Scholar 
  38. Perez, V.B., Tarasenko, M., Miyakoshi, M., Pianka, S.T., Makeig, S.D., Braff, D.L., Swerdlow, N.R., & Light, G.A. (2017). Mismatch negativity is a sensitive and predictive biomarker of perceptual learning during auditory cognitive training in schizophrenia. Neuropsychopharmacology, 42(11), 2206–2213. doi:10.1038/npp.2017.25  CrossRef  Google Scholar 
  39. Seidman, L.J., Cherkerzian, S., Goldstein, J.M., Agnew-Blais, J., Tsuang, M.T., & Buka, S.L. (2013). Neuropsychological performance and family history in children at age 7 who develop adult schizophrenia or bipolar psychosis in the New England Family Studies. Psychological Medicine, 43(1), 119–31. doi:10.1017/S0033291712000773  CrossRef  Google Scholar 
  40. Shamsi, S., Lau, A., Lencz, T., Burdick, K.E., DeRosse, P., Brenner, R., Lindenmayer, J.P., & Malhotra, A.K. (2011). Cognitive and symptomatic predictors of functional disability in schizophrenia. Schizophrenia Research, 126, 257–264. doi:10.1109/TMI.2012.2196707.Separate  CrossRef  Google Scholar 
  41. Simons, D.J., Boot, W.R., Charness, N., Gathercole, S.E., Chabris, C.F., Hambrick, D.Z., & Stine-Morrow, E.A.L. (2016). Do “brain-training” programs work? Psychological Science in the Public Interest, 17(3), 103–186. doi:10.1177/1529100616661983  CrossRef  Google Scholar 
  42. Smit, C.M., Wright, M.J., Hansell, N.K., Geffen, G.M., & Martin, N.G. (2006). Genetic variation of individual alpha frequency (IAF) and alpha power in a large adolescent twin sample. International Journal of Psychophysiology, 61(2), 235–243. doi:10.1016/J.IJPSYCHO.2005.10.004  CrossRef  Google Scholar 
  43. Steiger, J.H. (1980). Tests for comparing elements of a correlation matrix. Psychological Bulletin, 87(2), 245–251. doi:10.1037/0033-2909.87.2.245  CrossRef  Google Scholar 
  44. Tarasenko, M., Perez, V.B., Pianka, S.T., Vinogradov, S., Braff, D.L., Swerdlow, N.R., & Light, G.A. (2016). Measuring the capacity for auditory system plasticity: An examination of performance gains during initial exposure to auditory-targeted cognitive training in schizophrenia. Schizophrenia Research, 172(2), 123–130. doi:10.1016/j.schres.2016.01.019  CrossRef  Google Scholar 
  45. Tsang, H.W.H., Leung, A.Y., Chung, R.C.K., Bell, M., & Cheung, W.M. (2010). Review on vocational predictors: A systematic review of predictors of vocational outcomes among individuals with schizophrenia: An update since 1998. Australian and New Zealand Journal of Psychiatry, 44(6), 495–504 doi:10.3109/00048671003785716  Google Scholar 
  46. Vita, A., Deste, G., De Peri, L., Barlati, S., Poli, R., Cesana, B.M., & Sacchetti, E. (2013). Predictors of cognitive and functional improvement and normalization after cognitive remediation in patients with schizophrenia. Schizophrenia Research, 150(1), 51–7. doi:10.1016/j.schres.2013.08.011  CrossRef  Google Scholar 
  47. Watzke, S., Brieger, P., Kuss, O., Schoettke, H., & Wiedl, K.H. (2008). A longitudinal study of learning potential and rehabilitation outcome in schizophrenia. Psychiatric Services, 59(3), 248–255. doi:10.1176/ps.2008.59.3.248  CrossRef  Google Scholar 
  48. Wechsler, D. (2001). Wechsler Test of Adult Reading (WTAR). San Antonio, TX: Harcourt Assessment. Google Scholar 
  49. Wiedl, K.H. & Wienobst, J. (1999). Interindividual differences in cognitive remediation research with schizophrenic patients—indicators of rehabilitation potential? International Journal of Rehabilitation Research, 22(1), 55–59 doi:10.1097/00004356-199903000-00007  CrossRef  Google Scholar 
  50. Wright, B.A., Wilson, R.M., & Sabin, A.T. (2010). Generalization lags behind learning on an auditory perceptual task. Journal of Neuroscience, 30(35), 11635–11639. doi:10.1523/JNEUROSCI.1441-10.2010  CrossRef  Google Scholar 
  51. Wykes, T., Huddy, V., Cellard, C., McGurk, S.R., & Czobor, P. (2011). A meta-analysis of cognitive remediation for schizophrenia: Methodology and effect sizes. American Journal of Psychiatry, 168(5), 472–485. doi:10.1176/appi.ajp.2010.10060855  CrossRef  Google Scholar