Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
Hostname: page-component-cd9895bd7-q99xh Total loading time: 0 Render date: 2024-12-23T19:31:57.516Z Has data issue: false hasContentIssue false

Part IV - Clinical Assessment in Specific Settings

Published online by Cambridge University Press:  06 December 2019

Edited by
Martin Sellbom  and
Julie A. Suhr
Martin Sellbom
Affiliation:
University of Otago, New Zealand
Julie A. Suhr
Affiliation:
Ohio University
Get access

Summary

A summary is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.
Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'

Keywords

integrated primary careprimary care behavioral healthbrief assessmentsintegrated primary care assessment competenciesprimary care screening and assessmentforensic mental health assessmentadjudicative competencecriminal responsibilityrisk assessmentpersonal injurydisability determinationchild custodyparenting capacityjuvenile waiverneuropsychologyclinical neuropsychologyneuropsychological assessmentpsychologyclinicaltrainingsettingspopulationsneuropsychological teststechnologytesting accommodationslearning disabilitieseducational assessmentspecial educationdisproportionality
Type
Chapter
Information
The Cambridge Handbook of Clinical Assessment and Diagnosis , pp. 445 - 497
Publisher: Cambridge University Press
Print publication year: 2019

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

References

Alberts, N. M., Hadjistavropoulos, H. D., Jones, S. L., & Sharpe, D. (2013). The short health anxiety inventory: A systematic review and meta-analysis. Journal of Anxiety Disorders, 27(1), 68–78. doi:10.1016/j.janxdis.2012.10.009Google Scholar
APA (American Psychological Association). (2016). A Curriculum for an Interprofessional Seminar on Integrated Primary Care. APA Interprofessional Seminar on Integrated Primary Care Work Group. www.apa.org/education/grad/curriculum-seminar.aspxGoogle Scholar
Arroll, B., Goodyear-Smith, F., Crengle, S., Gunn, J., Kerse, N., Fishman, T., … & Hatcher, S. (2010). Validation of PHQ-2 and PHQ-9 to screen for major depression in the primary care population. Annals of Family Medicine, 8(4), 348–353. doi:10.1370/afm.1139Google Scholar
Baird, M., Blount, A., Brungardt, S., Dickinson, P., Dietrich, A., Epperly, T., & deGruy, F. (2014). Joint principles: Integrating behavioral health care into the patient-centered medical home. Annals of Family Medicine, 12(2), 183–185. doi:10.1370/afm.1634Google Scholar
Bastien, C. H., Vallières, A., & Morin, C. M. (2001). Validation of the Insomnia Severity Index as an outcome measure for insomnia research. Sleep Medicine, 2(4), 297–307. doi:10.1016/S1389-9457(00)00065-4Google Scholar
Beck, A. T., Guth, D., Steer, R. A., & Ball, R. (1997). Screening for major depression disorders in medical inpatients with the beck depression inventory for primary care. Behaviour Research and Therapy, 35(8), 785–791. doi:10.1016/S0005-7967(97)00025-9Google Scholar
Berwick, D. M., Nolan, T. W., & Whittington, J. (2008). The triple aim: Care, health, and cost. Health Affairs, 27(3), 759–769. doi:10.1377/hlthaff.27.3.759Google Scholar
Blevins, C. A., Weathers, F. W., Davis, M. T., Witte, T. K., & Domino, J. L. (2015). The Posttraumatic Stress Disorder Checklist for DSM‐5 (PCL‐5): Development and initial psychometric evaluation. Journal of Traumatic Stress, 28(6), 489–498. doi:10.1002/jts.22059Google Scholar
Boardman, J. (2001). The Quick PsychoDiagnostics Panel was accurate for identifying psychiatric disorders in primary care. Evidence-Based Mental Health, 4(1), 26–26. doi:10.1136/ebmh.4.1.26CrossRefGoogle Scholar
Bodenheimer, T., & Sinsky, C. (2014). From triple to quadruple aim: Care of the patient requires care of the provider. The Annals of Family Medicine, 12(6), 573–576. doi:10.1370/afm.1713Google Scholar
Bovin, M. J., Marx, B. P., Weathers, F. W., Gallagher, M. W., Rodriguez, P., Schnurr, P. P., & Keane, T. M. (2016). Psychometric properties of the PTSD Checklist for Diagnostic and Statistical Manual of Mental Disorders–Fifth Edition (PCL-5) in veterans. Psychological Assessment, 28(11), 1379–1391. doi:10.1037/pas0000254Google Scholar
Bower, P., & Gilbody, S. (2005). Stepped care in psychological therapies: Access, effectiveness and efficiency: narrative literature review. The British Journal of Psychiatry, 186(1), 11–17. doi:10.1192/bjp.186.1.11CrossRefGoogle ScholarPubMed
Boyd, R. C., Le, H. N., & Somberg, R. (2005). Review of screening instruments for postpartum depression. Archives of Women’s Mental Health, 8(3), 141–153. doi:10.1007/s00737-005-0096-6Google Scholar
Breuer, B., Cruciani, R., & Portenoy, R. K. (2010). Pain management by primary care physicians, pain physicians, chiropractors, and acupuncturists: A national survey. Southern Medical Journal, 103(8), 738–747.CrossRefGoogle ScholarPubMed
Bridges, A. J., Andrews III, A. R., Villalobos, B. T., Pastrana, F. A., Cavell, T. A., & Gomez, D. (2014). Does integrated behavioral health care reduce mental health disparities for Latinos? Initial findings. Journal of Latina/o Psychology, 2(1), 37–53. doi:10.1037/lat0000009CrossRefGoogle ScholarPubMed
Bryan, C. J., Blount, T., Kanzler, K. A., Morrow, C. E., Corso, K. A., Corso, M. A., & Ray-Sannerud, B. (2014). Reliability and normative data for the behavioral health measure (BHM) in primary care behavioral health settings. Families, Systems and Health : The Journal of Collaborative Family Healthcare, 32(1), 89–100. doi:10.1037/fsh0000014Google Scholar
Butler, S. F., Fernandez, K., Benoit, C., Budman, S. H., & Jamison, R. N. (2008). Validation of the revised Screener and Opioid Assessment for Patients with Pain (SOAPP-R). The Journal of Pain, 9(4), 360–372.CrossRefGoogle ScholarPubMed
Carson, N., Leach, L., & Murphy, K. J. (2018). A re‐examination of Montreal Cognitive Assessment (MoCA) cutoff scores. International Journal of Geriatric Psychiatry, 33, 379–388.CrossRefGoogle ScholarPubMed
CDC (Centers for Disease Control and Prevention). (2014). Annual number and percent distribution of ambulatory care visits by setting type according to diagnosis group, United States 2009–2010. www.cdc.gov/nchs/data/ahcd/combined_tables/2009–2010_combined_web_table01.pdfGoogle Scholar
Chiu, H. Y., Chen, P. Y., Chuang, L. P., Chen, N. H., Tu, Y. K., Hsieh, Y. J., … & Guilleminault, C. (2017). Diagnostic accuracy of the Berlin Questionnaire, STOP-BANG, STOP, and Epworth Sleepiness Scale in detecting obstructive sleep apnea: A bivariate meta-analysis. Sleep Medicine Reviews, 36, 57–70. doi:10.1016/j.smrv.2016.10.004Google Scholar
Chung, F., Subramanyam, R., Liao, P., Sasaki, E., Shapiro, C., & Sun, Y. (2012). High STOP-Bang score indicates a high probability of obstructive sleep apnea. British Journal of Anesthesia, 108(5), 768–775. doi:10.1093/bja/aes022Google Scholar
Chung, F., Yegneswaran, B., Liao, P., Chung, S. A., Vairavanathan, S., Islam, S., … & Shapiro, C. M. (2008). STOP Questionnaire: A tool to screen patients for obstructive sleep apnea. Anesthesiology: The Journal of the American Society of Anesthesiologists, 108(5), 812–821. doi:10.1097/ALN.0b013e31816d83e4Google Scholar
Cox, J. L., Holden, J. M., & Sagovsky, R. (1987). Detection of postnatal depression. British Journal of Psychiatry, 150(06), 782–786. https://doi.org/10.1192/bjp.150.6.782Google Scholar
Croghan, T. W., & Brown, J. D. (2010). Integrating mental health treatment into the patient centered medical home (AHRQ Publication No. 10–0084-EF). Rockville, MD: Agency for Healthcare Research and Quality.Google Scholar
Davis, D. H., Creavin, S. T., Yip, J. L., Noel-Storr, A. H., Brayne, C., & Cullum, S. (2015). Montreal Cognitive Assessment for the diagnosis of Alzheimer’s disease and other dementias. Cochrane Database of Systematic Reviews 2015(10), 1–50. doi:10.1002/14651858.CD010775.pub2Google ScholarPubMed
Derogatis, L. R. (2017). Screening for psychiatric disorders in primary care settings. In Maruish, M. E. (Ed.), Handbook of psychological assessment in primary care settings (2nd ed., pp. 167–192). New York: Routledge.Google Scholar
Dieleman, J. L., Baral, R., Birger, M., Bui, A. L., Bulchis, A., Chapin, A., … & Murray, C. J. L. (2016). US Spending on Personal Health Care and Public Health, 1996–2013. JAMA, 316(24), 2627. https://doi.org/10.1001/jama.2016.16885CrossRefGoogle Scholar
Dobkin, P. L., & Boothroyd, L. J. (2008). Organizing health services for patients with chronic pain: When there is a will there is a way. Pain Medicine, 9(7), 881–889.Google Scholar
Eberhard-Gran, M., Eskild, A., Tambs, K., Opjordsmoen, S., & Ove Samuelsen, S. (2001). Review of validation studies of the Edinburgh Postnatal Depression Scale. Acta Psychiatrica Scandinavica, 104(4), 243–249. doi:10.1034/j.1600-0447.2001.00187.xGoogle Scholar
El-Den, S., Chen, T. F., Gan, M. Y. L., Wong, M. E., & O’Reilly, C. L. (2017). The psychometric properties of depression screening tools in primary healthcare settings: A systematic review. Journal of Affective Disorders, 225, 503–522.Google Scholar
Fairbank, J. C., Couper, J., Davies, J. B., & O’Brien, J. P. (1980). The Oswestry low back pain disability questionnaire. Physiotherapy, 66(8), 271–273.Google Scholar
Fairbank, J. C., & Pynsent, P. B. (2000). The Oswestry Disability Index. Spine, 25(22), 2940–2953.Google Scholar
Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975). Mini-mental state: A practical guide for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12, 189–198.Google Scholar
Freedy, J. R., Steenkamp, M. M., Magruder, K. M., Yeager, D. E., Zoller, J. S., Hueston, W. J., & Carek, P. J. (2010). Post-traumatic stress disorder screening test performance in civilian primary care. Family Practice, 27(6), 615–624. doi:10.1093/fampra/cmq049Google Scholar
Gagnon, C., Bélanger, L., Ivers, H., & Morin, C. M. (2013). Validation of the insomnia severity index in primary care. Journal of the American Board of Family Medicine, 26(6), 701–710. doi:10.3122/jabfm.2013.06.130064Google Scholar
Gatchel, R. J., McGeary, D. D., Peterson, A., Moore, M., LeRoy, K., Isler, W. C., & … Edell, T. (2009). Preliminary findings of a randomized controlled trial of an interdisciplinary military pain program. Military Medicine, 174(3), 270–277. doi:10.7205/MILMED-D-03-1607Google Scholar
Harvan, J. R., & Cotter, V. T. (2006). An evaluation of dementia screening in the primary care setting. Journal of the American Academy of Nurse Practitioners, 18, 351–360. doi:10.1111/j.1745-7599.2006.00137.xCrossRefGoogle ScholarPubMed
Holsinger, T., Deveau, J., Boustani, M., & Williams, J. W. (2007). Does this patient have dementia? The Journal of the American Medical Association, 297, 2391–2404. doi:10.1001/jama.297.21.2391Google Scholar
Huang, F. Y., Chung, H., Kroenke, K., Delucchi, K. L., & Spitzer, R. L. (2006). Using the patient health questionnaire‐9 to measure depression among racially and ethnically diverse primary care patients. Journal of General Internal Medicine, 21(6), 547–552.Google Scholar
Hunter, C. L., Dobmeyer, A. C., & Reiter, J. T. (2018). Integrating behavioral health services into primary care: Spotlight on the primary care behavioral health (PCBH) model of service delivery. Journal of Clinical Psychology in Medical Settings, 25, 105–108. doi:10.1007/s10880-017-9534-7Google Scholar
Hunter, C. L., Goodie, J. L., Oordt, M., & Dobmeyer, A. C. (2017). Integrated Behavioral Health in Primary Care: Step-by-Step Guidance for Assessment and Intervention (2nd ed.). Washington, DC: American Psychological Association.Google Scholar
Institute of Medicine. (2011). Relieving pain in America: A blueprint for transforming prevention, care, education, and research. Washington, DC: The National Academies Press.Google Scholar
Jones, T., Lookatch, S., & Moore, T. (2015). Validation of a new risk assessment tool: The Brief Risk Questionnaire. Journal of Opioid Management, 11(2), 171–183.CrossRefGoogle ScholarPubMed
Jordan, P., Shedden-Mora, M. C., & Löwe, B. (2017). Psychometric analysis of the generalized anxiety disorder scale (GAD-7) in primary care using modern item response theory. PLoS ONE, 12(8), e0182162. doi:10.1371/journal.pone.0182162Google Scholar
Kessler, R. C., Petukhova, M., Sampson, N. A., Zaslavsky, A. M., & Wittchen, H. U. (2012). Twelve‐month and lifetime prevalence and lifetime morbid risk of anxiety and mood disorders in the United States. International Journal of Methods in Psychiatric Research, 21(3), 169–184. doi:10.1002/mpr.1359Google Scholar
Kopta, S. M., & Lowry, J. L. (2002). Psychometric evaluation of the behavioral health questionnaire-20: A brief instrument for assessing global mental health and the three phases of psychotherapy outcome. Psychotherapy Research, 12(4), 413–426. doi:10.1093/ptr/12.4.413Google Scholar
Kopta, M., Owen, J., & Budge, S. (2015). Measuring psychotherapy outcomes with the behavioral health measure-20: Efficient and comprehensive. Psychotherapy (Chicago, Ill.), 52(4), 442–448. doi:10.1037/pst0000035Google Scholar
Krebs, E. E., Lorenz, K. A., Bair, M. J., Damush, T. M., Jingwei, W., Sutherland, J. M., … & Kroenke, K. (2009). Development and initial validation of the PEG, a three-item scale assessing pain intensity and interference. Journal of General Internal Medicine, 24(6), 733–738. doi:10.1007/s11606-009-0981-1Google Scholar
Kroenke, K., Spitzer, R. L., & Williams, J. B. W. (2001). The PHQ-9: Validity of a brief depression severity measure. Journal of General Internal Medicine, 16(9), 606–613. doi:10.1046/j.1525-1497.2001.016009606.xGoogle Scholar
Kroenke, K., Spitzer, R. L., Williams, J. B., & Löwe, B. (2009). An ultra-brief screening scale for anxiety and depression: The PHQ–4. Psychosomatics, 50(6), 613–621. doi:10.1016/S0033-3182(09)70864-3Google Scholar
Kroenke, K., Spitzer, R. L., Williams, J. B., Monahan, P. O., & Löwe, B. (2007). Anxiety disorders in primary care: Prevalence, impairment, comorbidity, and detection. Annals of Internal medicine, 146(5), 317–325.CrossRefGoogle ScholarPubMed
Lambert, M. J. (2010). Prevention of treatment failure. Washington, DC: American Psychological Association.Google Scholar
Lin, J. S., O’Connor, E., Rossom, R. C., Perdue, L. A., Burda, B. U., Thompson, M., & Eckstrom, E. (2013). Screening for cognitive impairment in older adults: An evidence update for the US Preventive Services Task Force. Rockville, MD: Agency for Healthcare Research and Quality. www.ncbi.nlm.nih.gov/books/NBK174643Google Scholar
McDaniel, S. H., Grus, C. L., Cubic, B. A., Hunter, C. L., Kearney, L. K., Schuman, C. C., … & Miller, B. F. (2014). Competencies for psychology practice in primary care. American Psychologist, 69(4), 409–429. doi:10.1037/a0036072Google Scholar
Mitchell, A. J., Rao, S., & Vaze, A. (2010). Do primary care physicians have particular difficulty identifying late-life depression? A meta-analysis stratified by age. Psychotherapy and Psychosomatics, 79(5), 285–294. doi:10.1159/000318295Google Scholar
Moraes, C., Pinto, J. A., Lopes, M. A., Litvoc, J., & Bottino, C. M. (2010). Impact of sociodemographic and health variables on mini-mental state examination in a community-based sample of older people. European Archives of Psychiatry and Clinical Neuroscience, 260(7), 535–542.Google Scholar
Moriarty, A. S., Gilbody, S., McMillan, D., & Manea, L. (2015). Screening and case finding for major depressive disorder using the Patient Health Questionnaire (PHQ-9): A meta-analysis. General Hospital Psychiatry, 37(6), 567–576. doi:10.1016/j.genhosppsych.2015.06.012CrossRefGoogle ScholarPubMed
Moyer, V. A. (2013). Screening and behavioral counseling interventions in primary care to reduce alcohol misuse: US preventive services task force recommendation statement. Annals of Internal Medicine, 159(3), 210–218. doi:10.7326/0003-4819-159-3-201308060-00652Google Scholar
Nasreddine, Z. S., Phillips, N. A., Bédirian, V., Charbonneau, S., Whitehead, V., Collin, I., … & 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. doi:10.1111/j.1532-5415.2005.53221.xGoogle Scholar
Netzer, N. C., Stoohs, R. A., Netzer, C. M., Clark, K., & Strohl, K. P. (1999). Using the Berlin questionnaire to identify patients at risk for the sleep apnea syndrome. Annals of Internal Medicine, 131(7), 485–491. doi:10.7326/0003-4819-131-7-199910050-00002Google Scholar
NIAAA (National Institute on Alcohol Abuse and Alcoholism). (2010). Rethinking drinking: Alcohol and your health. https://pubs.niaaa.nih.gov/publications/RethinkingDrinking/Rethinking_Drinking.pdfGoogle Scholar
O’Connor, E., Rossom, R. C., Henninger, M., Groom, H. C., & Burda, B. U. (2016). Primary care screening for and treatment of depression in pregnant and postpartum women: Evidence report and systematic review for the US Preventive Services Task Force. The Journal of the American Medical Association, 315, 388–406.Google Scholar
Ogbeide, S. A., Landoll, R. R., Nielsen, M. K., & Kanzler, K. E. (2018). To go or not go: Patient preference in seeking specialty mental health versus behavioral consultation within the primary care behavioral health consultation model. Families, Systems, and Health, 36(4), 513–517. https://doi.org/10.1037/fsh0000374Google Scholar
Ozer, S., Young, J., Champ, C., & Burke, M. (2016). A systematic review of the diagnostic test accuracy of brief cognitive tests to detect amnestic mild cognitive impairment. International Journal of Geriatric Psychiatry, 31(11), 1139–1150. doi:10.1002/gps.4444Google Scholar
Parkerson, G. R., Jr., Broadhead, W. E., & Tse, C. J. (1990). The Duke Health Profile: A 17-item measure of health and dysfunction. Medical Care, 28(11), 1056–1072. doi:10.1097/00005650-199011000-00007CrossRefGoogle ScholarPubMed
Peek, C. J. and the National Integration Academy Council. (2013). Lexicon for behavioral health and primary care integration: Concepts and definitions developed by expert consensus (AHRQ Publication No.13-IP001-EF). Rockville, MD: Agency for Healthcare Research and Quality. http://integrationacademy.ahrq.gov/sites/default/files/Lexicon.pdf.Google Scholar
Perret-Guillaume, C., Briancon, S., Guillemin, F., Wahl, D., Empereur, F., & Nguyen Thi, P. L. (2009). Which generic health related quality of life questionnaire should be used in older inpatients: Comparison of the duke health profile and the MOS short-form SF-36? Journal of Nutrition, Health and Aging, 14(4), 325–331. doi:10.1007/s12603-010-0074-1Google Scholar
Phelan, E., Williams, B., Meeker, K., Bonn, K., Frederick, J., LoGerfo, J., & Snowden, M. (2010). A study of the diagnostic accuracy of the PHQ-9 in primary care elderly. BMC Family Practice, 11(1), 63–63. doi:10.1186/1471-2296-11-63Google Scholar
Polen, M. R., Whitlock, E. P., Wisdom, J. P., Nygren, P., & Bougatsos, C. (2008). Screening in primary care settings for illicit drug use: Staged systematic review for the United States Preventive Services Task Force (AHRQ Publication No. 08–05108-EF-s). Rockville, MD: Agency for Healthcare Research and Quality.Google Scholar
Prins, A., Bovin, M. J., Smolenski, D. J., Marx, B. P., Kimerling, R., Jenkins-Guarnieri, M. A., Tiet, Q. Q. (2016). The primary care PTSD screen for DSM-5 (PC-PTSD-5): Development and evaluation within a veteran primary care sample. Journal of General Internal Medicine, 31(10), 1206–1211. doi:10.1007/s11606-016-3703-5Google Scholar
Public Law No: 111–148, 111th Congress: Patient Protection and Affordable Care Act. (2010). 124 STAT. 119. www.gpo.gov/fdsys/pkg/PLAW-111publ148/pdf/PLAW-111publ148.pdf.Google Scholar
Ram, S., Seirawan, H., Kumar, S. K., & Clark, G. T. (2010). Prevalence and impact of sleep disorders and sleep habits in the United States. Sleep and Breathing, 14(1), 63–70. doi:10.1007/s11325-009-0281-3Google Scholar
Ranallo, P. A., Kilbourne, A. M., Whatley, A. S., & Pincus, H. A. (2016). Behavioral health information technology: From chaos to clarity. Health Affairs, 35(6), 1106–1113. doi:10.1377/hlthaff.2016.0013Google Scholar
Reiter, J. T., Dobmeyer, A. C., & Hunter, C. (2018). The primary care behavioral health (PCBH) model: an overview and operational definition. Journal of Clinical Psychology in Medical Settings, 25, 109–126. doi:10.1007/s10880-017-9531-xGoogle Scholar
Richmond, A., & Jackson, J. (2018). Cultural considerations for psychologists in primary care. Journal of Clinical Psychology in Medical Settings, 3, 305–315.Google Scholar
Robinson, P. J., & Reiter, J. D. (2015). Behavioral consultation and primary care: A guide to integrating services (2nd ed.). New York: Springer.Google Scholar
Rutter, L. A., & Brown, T. A. (2017). Psychometric properties of the generalized anxiety disorder scale-7 (GAD-7) in outpatients with anxiety and mood disorders. Journal of Psychopathology and Behavioral Assessment, 39, 140–146.Google Scholar
Salkovskis, P. M., Rimes, K. A., Warwick, H. M. C., & Clark, D. M. (2002). The Health Anxiety Inventory: Development and validation of scales for the measurement of health anxiety and hypochondriasis. Psychological Medicine, 32(5), 843–853. doi:10.1017/S0033291702005822Google Scholar
Sanchez, K., Chapa, T., Ybarra, R., & Martienez, O. N. Jr. (2012). Eliminating disparities through the integration of behavioral health and primary care services for racial and ethnic minority populations, including individuals with limited English proficiency: A literature report. US Department of Health and Human Services Office of Minority Health and Hogg Foundation for Mental Health.Google Scholar
Saunders, J. B., Aasland, O. G., Babor, T. F., De la Fuente, J. R., & Grant, M. (1993). Development of the alcohol use disorders identification test (AUDIT): WHO collaborative project on early detection of persons with harmful alcohol consumption‐II. Addiction, 88(6), 791–804. doi:10.1111/j.1360-0443.1993.tb02093.xGoogle Scholar
Scott, E. D., Gil, K., King, B. C., & Piatt, E. (2015). Clinical outcomes in a primary care practice within a center for health equity. Journal of Primary Care and Community Health, 6, 239–242.Google Scholar
Senaratna, C. V., Perret, J. L., Matheson, M. C., Lodge, C. J., Lowe, A. J., Cassim, R., … & Dharmage, S. C. (2017). Validity of the Berlin questionnaire in detecting obstructive sleep apnea: A systematic review and meta-analysis. Sleep Medicine Reviews, 36, 116–124. doi:10.1016/j.smrv.2017.04.001Google Scholar
Sheahan, P. J., Nelson-Wong, E. J., & Fischer, S. L. (2015). A review of culturally adapted versions of the Oswestry Disability Index: The adaptation process, construct validity, test–retest reliability and internal consistency. Disability and Rehabilitation, 37, 2367–2374.Google Scholar
Shedler, J. (2017). Automated mental health assessment for integrated care. In Feinstein, R. E., Connely, J. V., & Feinstein, M. S. (Eds.) Integrating behavioral health and primary care (pp. 134–145). New York: Oxford University Press.Google Scholar
Shedler, J., Beck, A., & Bensen, S. (2000). Practical mental health assessment in primary care. Journal of Family Practice, 49(7), 614–622.Google Scholar
Shulman, K. I. (2000). Clock‐drawing: Is it the ideal cognitive screening test? International Journal of Geriatric Psychiatry, 15, 548–561. doi:10.1002/1099-1166(200006)15:6<548::aid-gps242>3.0.CO;2-UGoogle Scholar
Simon, G. E., Rutter, C. M., Peterson, D., Oliver, M., Whiteside, U., Operskalski, B., & Ludman, E. J. (2013). Does response on the PHQ-9 depression questionnaire predict subsequent suicide attempt or suicide death? Psychiatric Services, 64(12), 1195–1202. doi:10.1176/appi.ps.201200587Google Scholar
Skinner, H. A. (1982). The drug abuse screening test. Addictive Behaviors, 7, 363–371.Google Scholar
Smith, P. C., Schmidt, S. M., Allensworth-Davies, D., & Saitz, R. (2009). Primary care validation of a single-question alcohol screening test. Journal of General Internal Medicine, 24, 783–788. doi:10.1007/s11606-009-0928-6Google Scholar
Smith, P. C., Schmidt, S. M., Allensworth-Davies, D., & Saitz, R. (2010). A single-question screening test for drug use in primary care. Archives of Internal Medicine, 170(13), 1155–1160. doi:10.1001/archinternmed.2010.140Google Scholar
Spitzer, R. L., Kroenke, K., Williams, J. B., & Löwe, B. (2006). A brief measure for assessing generalized anxiety disorder: The GAD-7. Archives of Internal Medicine, 166(10), 1092–1097.Google Scholar
Steer, R. A., Cavalieri, T. A., Leonard, D. M., & Beck, A. T. (1999). Use of the Beck Depression Inventory for Primary Care to screen for major depression disorders. General Hospital Psychiatry, 21(2), 106–111. doi:10.1016/S0163-8343(98)00070-XCrossRefGoogle ScholarPubMed
Thibodeau, M. A., & Asmundson, G. J. (2014). The PHQ-9 assesses depression similarly in men and women from the general population. Personality and Individual Differences, 56(1), 149–153. doi:10.1016/j.paid.2013.08.039Google Scholar
Tran, P. L., Blizzard, C. L., Srikanth, V., Hanh, V. T., Lien, N. T., Thang, N. H., & Gall, S. L. (2015). Health-related quality of life after stroke: Reliability and validity of the Duke Health Profile for use in Vietnam. Quality of Life Research, 24(11), 2807–2814.Google Scholar
Vinson, D. C., Manning, B. K., Galliher, J. M., Dickinson, L. M., Pace, W. D., & Turner, B. J. (2010). Alcohol and sleep problems in primary care patients: A report from the AAFP National Research Network. The Annals of Family Medicine, 8(6), 484–492. doi:10.1370/afm.1175Google Scholar
Weathers, F. W., Litz, B. T., Keane, T. M., Palmieri, P. A., Marx, B. P., & Schnurr, P. P. (2013). The PTSD Checklist for DSM–5 (PCL-5). Boston, MA: National Center for PTSD.Google Scholar
Wortmann, J. H., Jordan, A. H., Weathers, F. W., Resick, P. A., Dondanville, K. A., Hall-Clark, B., … & Mintz, J. (2016). Psychometric analysis of the PTSD Checklist-5 (PCL-5) among treatment-seeking military service members. Psychological Assessment, 28(11), 1392. doi:10.1037/pas0000260Google Scholar
Wu, L. T., McNeely, J., Subramaniam, G. A., Brady, K. T., Sharma, G., VanVeldhuisen, P., … & Schwartz, R. P. (2017). DSM-5 substance use disorders among adult primary care patients: Results from a multisite study. Drug and Alcohol Dependence, 179, 42–46. doi:10.1016/j.drugalcdep.2017.05.048Google Scholar

References

Achenbach, T. M. (2001). Child behavior checklist. Burlington: University of Vermont.Google Scholar
Ackerman, M. J., & Gould, J. W. (2015). Child custody and access. In Cutler, B. L. & Zapf, P. A. (Eds.), APA handbook of forensic psychology, Vol. 1: Individual and situational influences in criminal and civil contexts (pp. 425–469). Washington, DC: American Psychological Association. doi:10.1037/14461-013Google Scholar
Ackerman, M. J., & Schoendorf, K. (1992). ASPECT Ackerman-Schoendorf Scales for Parent Evaluation of Custody. Los Angeles: Western Psychological Services.Google Scholar
APA (American Psychological Association). (2010). Guidelines for child custody evaluations in family law proceedings. American Psychologist, 65(9), 863–867. doi:10.1037/a0021250Google Scholar
APA (American Psychological Association). (2013). Specialty guidelines for forensic psychology. American Psychologist, 68, 7–19.Google Scholar
Ben-Porath, Y., & Tellegen, A. (2008). The Minnesota Multiphasic Personality Inventory – 2 – Restructured Form (MMPI-2-RF) manual for administration and scoring. Minneapolis, MN: University of Minnesota Press.Google Scholar
Bonnie, R. J., & Grisso, T. (2000). Adjudicative competence and youthful offenders. In Grisso, T. & Schwartz, R. G. (Eds.), Youth on trial: A developmental perspective on juvenile justice (pp. 73–103). Chicago: University of Chicago Press.Google Scholar
Borum, R., Bartel, P., & Forth, A. (2006). Manual for the Structured Assessment of Violence Risk in Youth (SAVRY), version 1.1. Tampa, FL: University of South-Florida.Google Scholar
Bricklin, B. (1990). Bricklin Perceptual Scales manual. Furlong, PA: Village Publishing.Google Scholar
Budd, K. S., Clark, J., & Connell, M. A. (2011). Evaluation of parenting capacity in child protection. New York: Oxford University Press.Google Scholar
Choate, P. W. (2009). Parenting capacity assessments in child protection cases. The Forensic Examiner, 18(1), 52–59.Google Scholar
Conroy, M. A., & Murrie, D. C. (2007). Forensic assessment of violence risk: A guide for risk assessment and risk management. Hoboken, NJ: Wiley.Google Scholar
DeMatteo, D.,Burl, J., Filone, S., & Heilbrun, K. (2016). Training in forensic assessment and intervention: Implications for principle-based models. In Jackson, R. & Roesch, R. (Eds.), Learning forensic assessment: Research and practice (pp. 3–31). New York: Routledge.Google Scholar
Douglas, K. S., Hart, S. D., Webster, C. D., & Belfrage, H. (2013). HCR-20V3: Assessing risk for violence – User guide. Burnaby, BC: Mental Health, Law, and Policy Institute, Simon Fraser University.Google Scholar
Drozd, L., Saini, M., & Olesen, N. (2016). Parenting plan evaluations: Applied research for the family court (2nd ed.). New York: Oxford University Press.Google Scholar
Emery, R. E., Otto, R. K., & O’Donahue, W. T. (2005). A critical assessment of child custody evaluations: Limited science and a flawed system. Psychological Science in the Public Interest, 6(1), 1–29. doi:10.1111/j.1529–1006.2005.00020.xGoogle Scholar
Foote, W. E., & Lareau, C. R. (2013). Psychological evaluation of emotional damages in tort cases. In Otto, R. K., Weiner, I. B., Otto, R. K., & Weiner, I. B. (Eds.), Handbook of psychology: Forensic psychology (pp. 172–200). Hoboken, NJ: John Wiley & Sons.Google Scholar
Forth, A. E., Kosson, D. S., & Hare, R. (2003). The Hare Psychopathy Checklist: Youth version. New York: Multi-Health Systems.Google Scholar
Fuhrmann, G. S. W., & Zibbell, R. A. (2012). Evaluation for child custody. New York: Oxford University Press.Google Scholar
Golding, S. L. (1993). Interdisciplinary Fitness Interview-Revised: Training manual. Salt Lake City: University of Utah.Google Scholar
Grisso, T. (2003). Evaluating competencies: Forensic assessments and instruments (2nd ed.). New York: Kluwer/Plenum.Google Scholar
Grisso, T. (2013). Forensic evaluation of juveniles. Sarasota, FL, US: Professional Resource Press.Google Scholar
Goldstein, A., & Goldstein, N. E. S. (2010). Evaluating capacity to waive Miranda rights. New York: Oxford.Google Scholar
Guy, L. S., Douglas, K. S., & Hart, S. D. (2015). Risk assessment and communication. In Cutler, B. L. & Zapf, P. A. (Eds.), APA handbook of forensic psychology, Vol. 1 (pp. 35–86). Washington, DC: American Psychological Association. doi:10.1037/14461-003.Google Scholar
Hart, S. D., Kropp, P. R., Laws, D. R., Klaver, J., Logan, C., & Watt, K. A. (2003). The Risk for Sexual Violence Protocol (RSVP): Structured professional guidelines for assessing risk of sexual violence. Burnaby, BC: Mental Health Law and Policy Institute, Simon Fraser University.Google Scholar
Heilbrun, K. (2001). Principles of forensic mental health assessment. New York: Kluwer Academic/Plenum.Google Scholar
Heilbrun, K. (2009). Evaluation for risk of violence in adults. New York: Oxford University Press. doi:10.1093/med:psych/9780195369816.001.0001Google Scholar
Heilbrun, K., DeMatteo, D., & Marczyk, J. (2004). Pragmatic psychology, forensic mental health assessment, and the case of Thomas Johnson: Applying principles to promote quality. Psychology, Public Policy, and Law, 10, 31–70.Google Scholar
Heilbrun, K., DeMatteo, D., Marczyk, J., & Goldstein, A. M. (2008). Standards and practice and care in forensic mental health assessment: Legal, professional, and principles-based consideration. Psychology, Public Policy, and Law, 14, 1–26.Google Scholar
Heilbrun, K., Grisso, T., & Goldstein, A. (2009). Foundations of forensic mental health assessment. New York: Oxford University Press.Google Scholar
Heilbrun, K., & LaDuke, C. (2015). Foundational aspects of forensic mental health assessment. In Cutler, B. L. & Zapf, P. A. (Eds.), APA handbook of forensic psychology (1), 3–18. Washington, DC: American Psychological Association. doi:10.1037/14461-001Google Scholar
Heilbrun, K., Rogers, R., & Otto, R. K. (2002). Forensic assessment: Current status and future directions. In Ogloff, J. R. P. (Ed.), Taking psychology and law into the 21st century. New York: Kluwer/Plenum.Google Scholar
Helmus, L., Thornton, D., Hanson, R. K., & Babchishin, K. M. (2012). Improving the predictive accuracy of Static-99 and Static-2002 with older sex offenders: Revised age weights. Sexual Abuse: A Journal of Research and Treatment, 24, 64–101. doi:10.1177/1079063211409951.Google Scholar
Kane, A. W., & Dvoskin, J. A. (2011). Evaluation for personal injury claims. New York: Oxford University Press.Google Scholar
Kropp, P. R., Belfrage, H., & Hart, S. D. (2013). Assessment of risk for honor-based violence (PATRIARCH): User manual. Vancouver: ProActive ReSolutions.Google Scholar
Kropp, P. R., & Hart, S. D. (2015). SARA-V3: User manual for Version 3 of the Spousal Assault Risk Assessment guide. Vancouver: ProActive ReSolutions.Google Scholar
Kropp, P. R., Hart, S. D., & Belfrage, H. (2005). Structuring judgments about spousal violence risk and lethality: A decision support tool for criminal justice professionals. JustResearch, 13, 22–27.Google Scholar
Kropp, P. R., Hart, S. D., & Lyon., D. R. (2008). The Stalking Assessment and Management guidelines (SAM): User manual. Vancouver: ProActive ReSolutions.Google Scholar
Kruh, I., & Grisso, T. (2009). Evaluation of juveniles’ competence to stand trial. New York: Oxford University Press.Google Scholar
Lally, S. J. (2003). What tests are acceptable for use in forensic evaluations? A survey of experts. Professional Psychology: Research and Practice, 34, 491–498.Google Scholar
Melton, G. B., Petrila, J., Poythress, N. G., & Slobogin, C. (2007). Psychological evaluations for the courts: A handbook for mental health professionals and lawyers (3rd ed.). New York: Guilford Press.Google Scholar
Mills, J. F., Kroner, D. G., & Morgan, R. D. (2007). Clinician’s guide to violence risk assessment. New York: Guilford.Google Scholar
Otto, R. K., DeMier, R. L., & Boccaccini, M. T. (2014). Forensic reports and testimony: A guide to effective communication for psychologists and psychiatrists. Hoboken, NJ: Wiley.Google Scholar
Otto, R. K., & Douglas, K. D. (2010). Handbook of violence risk assessment. New York: Routledge.Google Scholar
Otto, R., & Edens, J. (2003). Parenting capacity. In Grisso, T. (Ed.), Evaluating competencies: Forensic assessments and instruments (2nd ed., pp. 229–307). New York: Springer.Google Scholar
Packer, I. K. (2009). Evaluation of criminal responsibility. New York: Oxford University Press.Google Scholar
Piechowski, L. D. (2011). Evaluation of workplace disability. New York: Oxford University Press.Google Scholar
Poythress, N. G., Nicholson, R., Otto, R. K., Edens, J. F., Bonnie, R. J., Monahan, J., & Hoge, S. K. (1999). The MacArthur Competence Assessment Tool – Criminal Adjudication (MacCAT-CA): Professional Manual. Lutz, FL: Psychological Assessment Resources.Google Scholar
Roesch, R., Zapf, P. A., & Eaves, D. (2006). FIT-R: Fitness Interview Test-Revised. A structured interview for assessing competency to stand trial. Sarasota, FL: Professional Resource Press/Professional Resource Exchange.Google Scholar
Rice, M. E., Harris, G. T., & Lang, C. (2013). Validation of and revision to the VRAG and SORAG: The violence risk appraisal guide-revised (VRAG-R). Psychological Assessment, 25, 951–965. doi:10.1037/a0032878.Google Scholar
Rogers, R. (1984). Rogers criminal responsibility assessment scales (R-CRAS) and test manual. Odessa, FL: Psychological Assessment Resources.Google Scholar
Rogers, R., Tillbrook, C. E., & Sewell, K. W. (2004). Evaluation of Competency to Stand Trial – Revised professional manual. Lutz, FL: Psychological Assessment Resources.Google Scholar
Salekin, R. T. (2004). Risk-Sophistication-Treatment Inventory. Lutz, FL: Psychological Assessment Resources.Google Scholar
Salekin, R. T. (2015). Forensic evaluation and treatment of juveniles: Innovation and best practice. Washington, DC: American Psychological Association. doi:10.1037/14595000Google Scholar
Singh, J. P., Grann, M., & Fazel, S. (2011). A comparative study of violence risk assessment tools: A systematic review and metaregression analysis of 68 studies involving 25, 980 participants. Clinical Psychology Review, 31, 499–513. doi:10.1016/j.cpr.2010.11.009Google Scholar
Slobogin, C., Melton, G. B., & Showalter, C. R. (1984). The feasibility of a brief evaluation of mental state at the time of offense. Law and Human Behavior, 8, 305–321. doi:10.1007/BF01044698Google Scholar
Stahl, P. M. (2011). Conducting child custody evaluations: From basic to complex issues. Thousand Oaks, CA: Sage.Google Scholar
Viljoen, J. L., Nicholls, T. L., Cruise, K. R., Desmarais, S. L., & Webster, C. D. (2014). Short-Term Assessment of Risk and Treatability: Adolescent Version (START:AV) – User guide. Burnaby, BC: Mental Health, Law, and Policy Institute.Google Scholar
Webster, C. D., Douglas, K., Eaves, D., & Hart, S. (1997). HCR-20: Assessing risk for violence: Version 2. Burnaby, BC: Simon Fraser University.Google Scholar
White, S. G., & Meloy, J. R. (2010). WAVR-21: A structured professional guide for the Workplace Assessment of Violence Risk (2nd ed.). San Diego, CA: Specialized Training Services.Google Scholar
Wygant, D. B., & Lareau, C. R. (2015). Civil and criminal forensic psychological assessment: Similarities and unique challenges. Psychological injury and law, 8, 11–26. doi:10.1007/s12207-015-9220-8Google Scholar
Woolard, J. L., Vidal, S., & Fountain, E. (2015). Juvenile offenders. In Cutler, B. L. & Zapf, P. A. (Eds.), APA handbook of forensic psychology, Vol. 2: Criminal investigation, adjudication, and sentencing outcomes (pp. 33–58). Washington, DC: American Psychological Association. doi:10.1037/14462-002Google Scholar
Worling, J. R., & Curwen, T. (2001). Estimate of Risk of Adolescent Sexual Offense Recidivism (ERASOR): Version 2.0. Toronto: SAFE-T Program, Thistletown Regional Centre, Ontario Ministry of Community and Social Services.Google Scholar
Zapf, P. A., & Roesch, R. (2009). Evaluation of competence to stand trial. New York: Oxford University Press.Google Scholar

References

AACN (American Academy of Clinical Neuropsychology). (1999). American Academy of Clinical Neuropsychology policy on the use of nondoctoral personnel in conducting clinical neuropsychological evaluations. The Clinical Neuropsychologist, 13(4), 385. https://doi.org/10.1076/1385–4046(199911)13:04;1-Y;FT385.Google Scholar
Allain, P., Foloppe, D. A., Besnard, J., Yamaguchi, T., Etcharry-Bouyx, F., Le Gall, D., … & Richard, P. (2014). Detecting everyday action deficits in Alzheimer’s disease using a nonimmersive virtual reality kitchen. Journal of the International Neuropsychological Society, 20(5), 468–477.Google Scholar
Au, R., Piers, R. J., & Devine, S. (2017). How technology is reshaping cognitive assessment: Lessons from the Framingham Heart Study. Neuropsychology, 31(8), 846–861. doi:10.1037/neu0000411.Google Scholar
Aubin, G., Béliveau, M. F., & Klinger, E. (2018). An exploration of the ecological validity of the Virtual Action Planning–Supermarket (VAP-S) with people with schizophrenia. Neuropsychological rehabilitation, 28(5), 689–708.Google Scholar
Ardila, A. (2007). The impact of culture on neuropsychological test performance. In Uzzell, B. P., Ponton, M., & Ardila, A. (Eds.), International handbook of cross-cultural neuropsychology (pp. 23–44). Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
Baum, K.T., von Thomsen, C., Elam, M., Murphy, C., Gerstle, M., Austin, C.A., & Beebe, D. W. (2018). Communication is key: The utility of a revised neuropsychological report format. The Clinical Neuropsychologist, 32(3), 345–367. doi:10.1080/13854046.2017.1413208Google Scholar
Besnard, J., Richard, P., Banville, F., Nolin, P., Aubin, G., Le Gall, D., … & Allain, P. (2016). Virtual reality and neuropsychological assessment: The reliability of a virtual kitchen to assess daily-life activities in victims of traumatic brain injury. Applied Neuropsychology: Adult, 23(3), 223–235.Google Scholar
Blair, J. R., & Spreen, O. (1989). Predicting premorbid IQ: A revision of the National Adult Reading Test. The Clinical Neuropsychologist, 3, 129–136.Google Scholar
Boone, K. B. (2007). Assessment of feigned cognitive impairment: A neuropsychological perspective. New York: Guilford Press.Google Scholar
Brouillette, R. M., Foil, H., Fontenot, S., Correro, A., Allen, R., Martin, C. K., … & Keller, J. N. (2013). Feasibility, reliability, and validity of a smartphone based application for the assessment of cognitive function in the elderly. PloS ONE, 8(6), e65925.Google Scholar
Brown, E. L., Ruggiano, N., Li, J., Clarke, P. J., Kay, E. S., & Hristidis, V. (2017). Smartphone-based health technologies for dementia care: Opportunities, challenges, and current practices. Journal of Applied Gerontology, 38(1), 73–91. doi:10.1177/0733464817723088Google Scholar
Bush, S. S., Ruff, R. M., Tröster, A. I., Barth, J. T., Koffler, S. P., Pliskin, N. H., … & Silver, C. H. (2005). Symptom validity assessment: Practice issues and medical necessity NAN Policy & Planning Committee. Archives of Clinical Neuropsychology, 20(4), 419–426. http://dx.doi.org/10.1016/j.acn.2005.02.002Google Scholar
Bush, S. S., Sweet, J. J., Bianchini, K. J., Johnson-Greene, D., Dean, P. M., & Schoenberg, M. R. (2018). Deciding to adopt revised and new psychological and neuropsychological tests: An inter-organizational position paper. The Clinical Neuropsychologist, 32(3), 319–325. doi:10.1080/13854046.2017.1422277Google Scholar
Butcher, J. N., Dahlstrom, W. G., Graham, J. R., Tellegen, A., & Kaemmer, B. (1989). MMPI-2:Manual for administration and scoring. Minneapolis: University of Minnesota Press.Google Scholar
Canini, M., Battista, P., Della Rosa, P. A., Catricalà, E., Salvatore, C., Gilardi, M. C., & Castiglioni, I. (2014). Computerized neuropsychological assessment in aging: testing efficacy and clinical ecology of different interfaces. Computational and Mathematical Methods in Medicine. doi:10.1155/2014/804723Google Scholar
Collie, A., Darby, D., & Maruff, P. (2001). Computerised cognitive assessment of athletes with sports related head injury. British Journal of Sports Medicine, 35(5), 297–302. doi:10.1136/bjsm.35.5.297.Google Scholar
Cullum, C. M., Hynan, L. S., Grosch, M., Parikh, M., & Weiner, M. F. (2014). Teleneuropsychology: Evidence for video teleconference-based neuropsychological assessment. Journal of the International Neuropsychological Society, 20(10), 1028–1033. doi:10.1017/S1355617714000873CrossRefGoogle Scholar
Davis, R., & Penney, D. L. (2014). U.S. Patent No. 8,740,819. Washington, DC: U.S. Patent and Trademark Office.Google Scholar
de Frias, C. M., Dixon, R. A., Fisher, N., & Camicioli, R. (2007). Intraindividual variability in neurocognitive speed: A comparison of Parkinson’s disease and normal older adults. Neuropsychologia, 45(11), 2499–2507. doi:10.1016/j.neuropsychologia.2007.03.022Google Scholar
Delaney, R. C. (2003). The practice of clinical neuropsychology in a VA setting. In Lamberty, G. J., Courtney, J. C., & Heilbronner, R. L. (Eds.), The practice of clinical neuropsychology (pp. 267–279). Leiden: Swets & Zeitlinger.Google Scholar
Delis, D. C., Kramer, J. H., Kaplan, E., & Ober, B. A. (2000). The California Verbal Learning Test – Second Edition: Adult version manual. San Antonio, TX: The Psychological Corporation.Google Scholar
Division 40 Task Force on Education Accreditation Credentialing. (1991). Recommendations for the education and training of nondoctoral personnel in clinical neuropsychology. The Clinical Neuropsychologist, 3(1), 23–24. https://doi.org/10.1080/13854049108401838Google Scholar
Duggan, E. C., Awakon, L. M., Loaiza, C. C., & Garcia-Barrera, M. A. (2018). Contributing towards a cultural neuropsychology assessment decision-making framework: comparison of WAIS-IV norms from Colombia, Chile, Mexico, Spain, United States, and Canada. Archives of Clinical Neuropsychology, 34(5), 657–681. http://dx.doi.org/10.1093/arclin/acy074Google Scholar
Dykiert, D., Der, G., Starr, J. M., & Deary, I. J. (2012). Age differences in intra-individual variability in simple and choice reaction time: systematic review and meta-analysis. PLoS ONE, 7(10). doi:10.1371/journal.pone.0045759.Google Scholar
Elbulok-Charcape, M. M., Rabin, L. A., Spadaccini, A. T., & Barr, W. B. (2014). Trends in the neuropsychological assessment of ethnic/racial minorities: A survey of clinical neuropsychologists in the United States and Canada. Cultural Diversity and Ethnic Minority Psychology, 20(3), 353–361. doi:10.1037/a0035023.Google Scholar
Evans, J. J. (2010). Basic concepts and principles of neuropsychological assessment. In Gurd, J. M., Kischka, U., & Marshall, J. C. (Eds.), Handbook of clinical neuropsychology (pp. 15–27). New York: Oxford University Press.Google Scholar
Fellows, R. P., Dahmen, J., Cook, D., & Schmitter-Edgecombe, M. (2017). Multicomponent analysis of a digital Trail Making Test. The Clinical Neuropsychologist, 31(1), 154–167.Google Scholar
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.Google Scholar
Geurts, H. M., Grasman, R. P., Verté, S., Oosterlaan, J., Roeyers, H., van Kammen, S. M., & Sergeant, J. A. (2008). Intra-individual variability in ADHD, autism spectrum disorders and Tourette’s syndrome. Neuropsychologia, 46(13), 3030–3041. doi:10.1016/j.neuropsychologia.2008.06.013.Google Scholar
Gioia, G. A., Isquith, P. K., Guy, S. C., & Kenworthy, L. (2015). BRIEF-2: Behavior Rating Inventory of Executive Function. Lutz, FL: Psychological Assessment Resources.Google Scholar
Gorus, E., De Raedt, R., Lambert, M., Lemper, J. C., & Mets, T. (2008). Reaction times and performance variability in normal aging, mild cognitive impairment, and Alzheimer’s disease. Journal of Geriatric Psychiatry and Neurology, 21(3), 204–218. doi:10.1177/0891988708320973.Google Scholar
Grosch, M. C., Gottlieb, M. C., & Cullum, C. M. (2011). Initial practice recommendations for teleneuropsychology. The Clinical Neuropsychologist, 25(7), 1119–1133. doi:10.1080/13854046.2011.609840.Google Scholar
Groth-Marnat, G. E. (2000). Neuropsychological assessment in clinical practice: A guide to test interpretation and integration. New York: John Wiley & Sons.Google Scholar
Halliday, D. W. R., Mulligan, B. P., Garrett, D. D., Schmidt, S., Hundza, S. R., Garcia-Barrera, M. A., Stawski, R. S., & MacDonald, S. W. S. (2018). Mean and variability in functional brain activations differentially predict executive function in older adults: An investigation employing functional near-infrared spectroscopy, Neurophotonics 5(1), 011013. doi:10.1117/1.NPh.5.1.011013.Google Scholar
Hannay, J., Bieliauskas, L., Crosson, B., Hammeke, T., Hamsher, K., & Koffler, S. (1998). Proceedings of the Houston Conference on Specialty Education and Training in Clinical Neuropsychology. Archives of Clinical Neuropsychology, 13, 157–250.Google Scholar
Harris, J. G. (2002). Ethical decision making with individuals of diverse ethnic, cultural, and linguistic backgrounds. In Bush, S. S. & Drexler, M. L. (Eds.), Ethical issues in clinical neuropsychology (pp. 223–241). Leiden: Swets & Zeitlinger.Google Scholar
Heaton, R. K., Chelune, G. J., Talley, J. L., Kay, C. G., & Curtiss, G. (1993). Wisconsin Card Sorting Test manual. Odessa, FL: Psychological Assessment Resources.Google Scholar
Hebben, N & Milberg, W. (2002). Essentials of neuropsychological assessment. New York: John Wiley & Sons.Google Scholar
Hilborn, J. V., Strauss, E., Hultsch, D. F., & Hunter, M. A. (2009). Intraindividual variability across cognitive domains: Investigation of dispersion levels and performance profiles in older adults. Journal of Clinical and Experimental Neuropsychology, 31(4), 412–424.Google Scholar
Hill, B. D., & Rohling, M. L. (2011). Diagnostic utility of measures of variability in patients suffering from traumatic brain injury: Intra-individual variability as an indicator of validity and pathology. In Baker, K. S. & Edwards, N. C. (Eds.), Brain injuries: New research (pp. 159–174). Hauppauge, NY: Nova Science.Google Scholar
Kamphaus, R. W., & Reynolds, C. R. (2015). Behavior Assessment System for Children – Third Edition (BASC-3): Behavioral and emotional screening system (BESS). Bloomington, MN: Pearson.Google Scholar
Kaplan, E.F., Goodglass, H., & Weintraub, S. (1983). The Boston Naming Test – Second Edition. Philadelphia: Lea & Febiger.Google Scholar
Karr, J. E., Garcia-Barrera, M. A., Holdnack, J. A., & Iverson, G. L. (2016). Using multivariate base rates to interpret low scores on an abbreviated battery of the Delis–Kaplan Executive Function System. Archives of Clinical Neuropsychology, 32(3), 297–305. doi:10.1093/arclin/acw105.Google Scholar
Karr, J. E., Garcia-Barrera, M. A., Holdnack, J. A., & Iverson, G. L. (2017). Advanced clinical interpretation of the Delis-Kaplan Executive Function System: Multivariate base rates of low scores. The Clinical Neuropsychologist, 32(1), 1–12. doi:10.1080/13854046.2017.1334828.Google Scholar
Kløve, H. (1963). Grooved pegboard. Lafayette, IN: Lafayette Instruments.Google Scholar
Kubu, C. S., Ready, R. E., Festa, J. R., Roper, B. L., & Pliskin, N. H. (2016). The times they are a changin’: Neuropsychology and integrated care teams. The Clinical Neuropsychologist, 30(1), 51–65.Google Scholar
Larrabee, G. J. (2007). Assessment of malingered neuropsychological deficits. New York: Oxford University PressGoogle Scholar
Lezak, M. D., Howieson, D. B., Bigler, E. D., & Tranel, D. (2012). Neuropsychological assessment (5th ed.). New York: Oxford University Press.Google Scholar
MacDonald, S. W., Nyberg, L., & Bäckman, L. (2006). Intra-individual variability in behavior: Links to brain structure, neurotransmission and neuronal activity. Trends in Neurosciences, 29(8), 474–480.Google Scholar
Malek-Ahmadi, M., Erickson, T., Puente, A. E., Pliskin, N., & Rock, R. (2012). The use of psychometrists in clinical neuropsychology: History, current status, and future directions. Applied Neuropsychology: Adult, 19(1), 26–31.Google Scholar
McKinlay, W. W., McGowan, M., & Russell, J. V. (2010). Forensic issues in neuropsychology. In Gurd, J. M., Kischka, U., & Marshall, J. C. (Eds.), Handbook of clinical neuropsychology (pp. 741–761). New York: Oxford University Press.Google Scholar
Meyers, J. E., & Meyers, K. R. (1995). Rey Complex Figure Test and recognition trial: Professional manual. Odessa, TX: Psychological Assessment Resources.Google Scholar
Miller, J. B., & Barr, W. B. (2017). The technology crisis in neuropsychology. Archives of Clinical Neuropsychology, 32(5), 541–554.Google Scholar
Moore, R. C., Swendsen, J., & Depp, C. A. (2017). Applications for self‐administered mobile cognitive assessments in clinical research: A systematic review. International Journal of Methods in Psychiatric Research, 26(4), e1562.Google Scholar
Neguț, A., Matu, S. A., Sava, F. A., & David, D. (2016). Virtual reality measures in neuropsychological assessment: A meta-analytic review. The Clinical Neuropsychologist, 30(2), 165–184. https://doi.org/10.1080/13854046.2016.1144793.Google Scholar
Nelson, H. E. (1982). National Adult reading test (NART): Test manual. Windsor, UK: NFER-Nelson.Google Scholar
Nolin, P., Stipanicic, A., Henry, M., Lachapelle, Y., Lussier-Desrochers, D., & Allain, P. (2016). ClinicaVR: Classroom-CPT: A virtual reality tool for assessing attention and inhibition in children and adolescents. Computers in Human Behavior, 59, 327–333.Google Scholar
Ponsford, J. (2017). International growth of neuropsychology. Neuropsychology, 31(8), 921–933. doi:10.1037/neu0000415.Google Scholar
Poreh, A. (2002). Neuropsychological and psychological issues associated with cross-cultural and minority assessment. In Ferraro, F. R. (Ed.), Minority and cross-cultural aspects of neuropsychological assessment (pp. 329–343). Leiden: Swets & Zeitlinger.Google Scholar
Psychological Corporation. (2001). The Wechsler Test of Adult Reading (WTAR). San Antonio, TX: Psychological Corporation.Google Scholar
Puente, A. E., Adams, R., Barr, W., Bush, S. S., & NAN Policy and Planning Committee. (2006). The use, education, training, and supervision of neuropsychological test technicians (psychometrists) in clinical practice: Official statement of the National Academy of Neuropsychology. Archives of Clinical Neuropsychology, 21(8), 837–839. doi:10.1016/j.acn.2006.08.011.Google Scholar
Puente, A. E., Ojeda, C., Zink, D., Portillo Reyes, V. (2015). Neuropsychological testing of Spanish speakers. In Geisinger, K. F. (Ed.), Psychological testing of Hispanics (pp. 135–152). Washington, DC: American Psychological Association.Google Scholar
Rabin, L. A., Barr, W. B., & Burton, L. A. (2005). Assessment practices of clinical neuropsychologists in the United States and Canada: A survey of INS, NAN, and APA Division 40 members. Archives of Clinical Neuropsychology, 20(1), 33–65. doi:10.1016/j.acn.2004.02.005.Google Scholar
Rabin, L. A., Paolillo, E., & Barr, W. B. (2016). Stability in test-usage practices of clinical neuropsychologists in the United States and Canada over a 10-year period: A follow-up survey of INS and NAN members. Archives of Clinical Neuropsychology, 31(3), 206–230. doi:10.1093/arclin/acw007.Google Scholar
Rabin, L. A., Spadaccini, A. T., Brodale, D. L., Grant, K. S., Elbulok-Charcape, M. M., & Barr, W. B. (2014). Utilization rates of computerized tests and test batteries among clinical neuropsychologists in the United States and Canada. Professional Psychology: Research and Practice, 45(5), 368–377. doi:10.1037/a0037987.Google Scholar
Rabinowitz, A. R., & Arnett, P. A. (2013). Intraindividual cognitive variability before and after sports-related concussion. Neuropsychology, 27(4), 481–490. doi:10.1037/a0033023.Google Scholar
Randolph, C. (2012). RBANS update: Repeatable battery for the assessment of neuropsychological status. Bloomington, MN: NCS Pearson.Google Scholar
Reitan, R. M. (1958). Validity of the Trail Making test as an indicator of organic brain damage. Perceptual and Motor Skills, 8, 271–276.Google Scholar
Resnick, H. E., & Lathan, C. E. (2016). From battlefield to home: A mobile platform for assessing brain health. Mhealth, 2(30), 1–6.Google Scholar
Reynolds, C. R., & Kamphaus, R. W. (2015). Behavior assessment system for children—third edition (BASC-3). Bloomington, MN: Pearson.Google Scholar
Ricker, J. H. (2003). Neuropsychological practice in medical rehabilitation. In Lamberty, G. J., Courtney, J. C., and Heilbronner, R. L. (Eds.), The practice of clinical neuropsychology (pp. 305–317). Leiden: Swets & Zeitlinger.Google Scholar
Rizzo, A., & Koenig, S. T. (2017). Is clinical virtual reality ready for primetime?. Neuropsychology, 31(8), 877–899. doi:10.1037/neu0000405.Google Scholar
Schinka, J. A., & Vanderploeg, R. D (2000). Estimating premorbid level of functioning. In: Vanderploeg, R. D. (Ed.), Clinician’s guide to neuropsychological assessment (2nd ed., pp. 39–67). Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
Schopp, L., Johnstone, B., & Merrell, D. (2000). Telehealth and neuropsychological assessment: New opportunities for psychologists. Professional Psychology: Research and Practice, 31(2), 179–183. doi:10.1037//0735-7028.31.2.179,Google Scholar
Schultheis, M. T., & Rizzo, A. A. (2001). The application of virtual reality technology in rehabilitation. Rehabilitation psychology, 46(3), 296–311. doi:10.1037/0090–5550.46.3.296.Google Scholar
Schweitzer, P., Husky, M., Allard, M., Amieva, H., Pérès, K., Foubert‐Samier, A., … & Swendsen, J. (2017). Feasibility and validity of mobile cognitive testing in the investigation of age‐related cognitive decline. International Journal of Methods in Psychiatric Research, 26(3), e1521.Google Scholar
Souillard-Mandar, W., Davis, R., Rudin, C., Au, R., Libon, D. J., Swenson, R., … & Penney, D. L. (2016). Learning classification models of cognitive conditions from subtle behaviors in the digital clock drawing test. Machine learning, 102(3), 393–441. doi:10.1007/s10994-015-5529-5.Google Scholar
Stedman, J. M. (2006). What we know about predoctoral internship training: A review. Training and Education in Professional Psychology, S(2), 80–95.Google Scholar
Strauss, E., Slick, D. J., Levy-Bencheton, J., Hunter, M., MacDonald, S. W., & Hultsch, D. F. (2002). Intraindividual variability as an indicator of malingering in head injury. Archives of Clinical Neuropsychology, 17(5), 423–444. https://doi.org/10.1016/S0887–6177(01)00126–3.Google Scholar
Stringer, A. Y., & Nadolne, M. J. (2000). Neuropsychological assessment: Contexts for contemporary clinical practice. In Groth-Marnat, G. (Ed.), Neuropsychological assessment in clinical practice (pp. 26–47). John Wiley & Sons.Google Scholar
Stuss, D. T., Murphy, K. J., Binns, M. A., & Alexander, M. P. (2003). Staying on the job: The frontal lobes control individual performance variability. Brain, 126 (11), 2363–2380.Google Scholar
Stuss, D. T., Pogue, J., Buckle, L., & Bondar, J. (1994). Characterization of stability of performance in patients with traumatic brain injury: variability and consistency on reaction time tests. Neuropsychology, 8(3), 316. https://doi.org/10.1037/0894–4105.8.3.316.Google Scholar
Suzuki, L. A., & Ponterotto, J. G. (Eds.). (2007). Handbook of multicultural assessment: Clinical, psychological, and educational applications. John Wiley & Sons.Google Scholar
Sweet, J. J. (1999). Malingering: differential diagnosis. In J. J. Sweet, Forensic Neuropsychology: Fundamentals and practice (pp. 255–285). Leiden: Sets & Zeitlinger.Google Scholar
Sweet, J. J., Benson, L. M., Nelson, N. W., & Moberg, P. J. (2015). The American Academy of Clinical Neuropsychology, National Academy of Neuropsychology, and Society for Clinical Neuropsychology (APA Division 40) 2015 TCN professional practice and ‘salary survey’: Professional practices, beliefs, and incomes of US neuropsychologists. The Clinical Neuropsychologist, 29(8), 1069–1162.Google Scholar
Sweet, J. J., Ecklund-Johnson, E., & Malina, A. (2008). Forensic neuropsychology: An overview of issues and directions. In Morgan, J. E. and Ricker, J. H. (Eds.), Textbook of clinical neuropsychology (pp. 869–890). New York: Taylor & Francis Group.Google Scholar
Sweet, J. J., Lee, C., Guidotti Breting, L. M., & Benson, L. M. (2018). Gender in clinical neuropsychology: Practice survey trends and comparisons outside the specialty. The Clinical Neuropsychologist, 32(2), 186–216. doi:10.1080/13854046.2017.1365932Google Scholar
Sweet, J. J., Moberg, P. J., & Suchy, Y. (2000). Ten-year follow-up survey of clinical neuropsychologists: Part I. Practices and beliefs. The Clinical Neuropsychologist, 14(1), 18–37.Google Scholar
Torres, I. J., & Pliskin, N. H. (2003). Adult practice in a university-affiliated medical center. In Lamberty, G. J., Courtney, J. C., and Heilbronner, R. L. (Eds.), The practice of clinical neuropsychology (pp. 213–225). Leiden: Swets & Zeitlinger.Google Scholar
Vanderploeg, R. D., & Schinka, J. A. (2004). Estimation of premorbid cognitive abilities: Issues and approaches. In Ricker, J. H. (Ed.), Differential diagnosis in adult neuropsychological assessment (pp. 27–65). New York: Springer.Google Scholar
Wechsler, D. (2003). Wechsler Intelligence Scale for Children – Fourth Edition (WISC-IV). San Antonio, TX: The Psychological Corporation.Google Scholar
Wechsler, D. (2008). Wechsler Adult Intelligence Scale – Fourth Edition (WAIS–IV). San Antonio, TX: The Psychological Corporation.Google Scholar
Wechsler, D. (2009). Wechsler Memory Scale – Fourth Edition (WMS-IV). San Antonio, TX: The Psychological Corporation.Google Scholar
Wechsler, D. (2011). Wechsler Abbreviated Scale of Intelligence – Second Edition (WASI-II). San Antonio, TX: NCS Pearson.Google Scholar
Wechsler, D. (2014). Wechsler Intelligence Scale for Children – Fifth Edition (WISC-V). San Antonio, TX: NCS Pearson.Google Scholar

References

Aaron, P. G. (1997). The impending demise of the discrepancy formula. Review of Educational Research, 67(4), 461–502.Google Scholar
Adelman, H. S., Lauber, B. A., Nelson, P., & Smith, D. C. (1989). Toward a procedure for minimizing and detecting false positive diagnoses of learning disability. Journal of Learning Disabilities, 22(4), 234–244.Google Scholar
AERA (American Educational Research Association), APA (American Psychological Association), & NCME (National Council on Measurement in Education). (2014). Standards for educational and psychological testing. Washington, DC: American Educational Research Association.Google Scholar
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Publishing.Google Scholar
Ardoin, S. P., & Christ, T. J. (2009). Curriculum-based measurement of oral reading: Standard errors associated with progress monitoring outcomes from DIBELS, AIMSweb, and an experimental passage set. School Psychology Review, 38(2), 266–284.Google Scholar
Barth, A. E., Stuebing, K. K., Anthony, J. L., Denton, C. A., Mathes, P. G., Fletcher, J. M., & Francis, D. J. (2008). Agreement among response to intervention criteria for identifying responder status. Learning and Individual Differences, 18(3), 296–307.Google Scholar
Bateman, B. D. (1965). An educator’s view of a diagnostic approach to learning disorders. In Hellmuth, J. (Ed.), Learning disorders (pp. 219–239). Seattle, WA: Special Child Publications.Google Scholar
Berninger, V. W., & Abbott, R. D. (1994). Redefining learning disabilities: Moving beyond aptitude–achievement discrepancies to failure to respond to validated treatment protocols. In Lyon, G. R. (Ed.), Frames of reference for the assessment of learning disabilities (pp. 163–183). Baltimore, MD: Brookes.Google Scholar
Blanchett, W. J. (2006). Disproportionate representation of African American students in special education: Acknowledging the role of white privilege and racism. Educational Researcher, 35(6), 24–28.Google Scholar
Brooks, B. L. (2011). A study of low scores in Canadian children and adolescents on the Wechsler Intelligence Scale for Children, (WISC-IV). Child Neuropsychology, 17(3), 281–289.Google Scholar
Burns, M. K. (2007). RTI will fail, unless … NASP Communiqué, 35(5), 38–40.Google Scholar
Burns, M. K., Jimerson, S. R., VanDerHeyden, A. M., & Deno, S. L. (2016). Toward a unified response-to-intervention model: Multi-tiered systems of support. In Jimerson, S. R., Burns, M. K., & VanDerHeyden, A. M. (Eds.), Handbook of response to intervention (2nd ed., pp. 719–732). New York: Springer.Google Scholar
Carone, D. A. (2015). Clinical strategies to assess the credibility of presentations in children. In Kirkwood, M. W. (Ed.), Validity testing in child and adolescent assessment: Evaluating exaggeration, feigning, and noncredible effort (pp. 107–124). New York: Guilford.Google Scholar
Chafetz, M., & Prentkowski, E. (2011). A case of malingering by proxy in a Social Security Disability psychological consultative examination. Applied Neuropsychology, 18, 143–149. doi:10.1080/09084282.2011.570619Google Scholar
DeRight, J., & Carone, D. A. (2015). Assessment of effort in children: A systematic review. Child Neuropsychology, 21(1), 1–24. doi:10.1080/09297049.2013.864383Google Scholar
Dombrowski, S. C., Kamphaus, R. W., & Reynolds, C. R. (2004). After the demise of the discrepancy. Professional Psychology: Research and Practice, 35(4), 364–372.Google Scholar
Duckworth, A. L., Quinn, P. D., Lynam, D. R., Loeber, R., Stouthamer-Loeber, M., & Smith, E. E. (2011). Role of test motivation in intelligence testing. Proceedings of the National Academy of Sciences of the United States of America, 108(19), 7716–7720. doi:10.1073/pnas.10118601108/-/DCSupplementalGoogle Scholar
Eckert, T. L., & Lovett, B. J. (2013). Principles of behavioral assessment. In Saklofske, D. H., Reynolds, C. R., & Schwean, V. L. (Eds.), Oxford Handbook of Child Psychological Assessment (pp. 366–384). New York: Oxford University Press.Google Scholar
Flanagan, D. P., Alfonso, V. C., & Mascolo, J. T. (2011). A CHC-based operational definition of SLD: Integrating multiple data sources and multiple data-gathering methods. In Flanagan, D. P. & Alfonso, V. C. (Eds.), Essentials of specific learning disability identification (pp. 233–298). Hoboken, NJ: Wiley.Google Scholar
Fletcher, J. M., Denton, C., & Francis, D. J. (2005). Validity of alternative approaches for the identification of learning disabilities: Operationalizing unexpected underachievement. Journal of Learning Disabilities, 38(6), 545–552.Google Scholar
Fletcher-Janzen, E., & Reynolds, C. R. (Eds.). (2008). Neuropsychological perspectives on learning disabilities in the era of RTI: Recommendations for diagnosis and intervention. Hoboken, NJ: Wiley.Google Scholar
Frazier, T. W., Frazier, A. R., Busch, R. M., Kerwood, M. A., & Demaree, H. A. (2008). Detection of simulated ADHD and reading disorder using symptom validity measures. Archives of Clinical Neuropsychology, 23, 501–509. doi:10.1016/j.acn.2008.04.001Google Scholar
Fuchs, D., Fuchs, L. S., & Stecker, P. M. (2010). The “blurring” of special education in a new continuum of general education placements and services. Exceptional Children, 76(3), 301–323.Google Scholar
Gersten, R., Jayanthi, M., & Dimino, J. (2017). Too much, too soon? Unanswered questions from national Response to Intervention evaluation. Exceptional Children, 83(3), 244–254.Google Scholar
Green, P. (2003). Word Memory Test. Edmonton: Green’s Publishing.Google Scholar
Green, P. (2009). The Advanced Interpretation Program. Edmonton: Green’s Publishing.Google Scholar
Green, P., & Flaro, L. (2003). Word Memory Test performance in children. Child Neuropsychology, 9(3), 189–207. doi:10.1076/chin.9.3.189.16460Google Scholar
Gresham, F. M. (2002). Responsiveness to intervention: An alternative approach to the identification of learning disabilities. In Bradley, R., Danielson, L., & Hallahan, D. P. (Eds.), Identification of learning disabilities: Research to practice (pp. 467–519). Mahwah, NJ: Erlbaum.Google Scholar
Guilmette, T. J. (2013). The role of clinical judgment in symptom validity assessment. In Carone, D. & Bush, S. (Eds.), Mild traumatic brain injury: Symptom validity assessment and malingering (pp. 31–45). New York: Springer.Google Scholar
Hale, J. B., Wycoff, K. L., & Fiorello, C. A. (2011). RTI and cognitive hypothesis testing for identification and intervention of specific learning disabilities: The best of both worlds. In Flanagan, D. P. & Alfonso, V. C. (Eds.), Essentials of specific learning disability identification (pp. 173–202). Hoboken, NJ: Wiley.Google Scholar
Harrison, A. G., & Armstrong, I. (2014). WISC-IV unusual digit span performance in a sample of adolescents with learning disabilities. Applied Neuropsychology: Child, 3(2), 152–160. doi:10.1080/21622965.2012.753570Google Scholar
Harrison, A. G., & Edwards, M. J. (2010). Symptom exaggeration in post-secondary students: Preliminary base rates in a Canadian sample. Applied Neuropsychology, 17, 135–143. doi:10.1080/09084281003715642Google Scholar
Harrison, A. G., Edwards, M. J., Armstrong, I., & Parker, K. C. H. (2010) An investigation of methods to detect feigned reading disabilities. Archives of Clinical Neuropsychology, 25, 89–98. doi:10.1093/arclin/acp104Google Scholar
Harrison, A. G., Edwards, M. J., & Parker, K. C. H. (2008). Identifying students feigning dyslexia: Preliminary findings and strategies for detection. Dyslexia, 14, 228–246. doi:10.1002/dys.366Google Scholar
Harrison, A. G., Green, P., & Flaro, L. (2012). The importance of symptom validity testing in adolescents and young adults undergoing assessments for learning or attention difficulties. Canadian Journal of School Psychology, 27(1), 98–112. doi:10.1177/0829573512437024Google Scholar
Heward, W. L. (2013). Exceptional children (10th ed.). Boston: Pearson.Google Scholar
Hunt, E. (2011). Human intelligence. New York: Cambridge University Press.Google Scholar
Infante-Green, A. (2016). Changes in allowable testing accommodations on the Grades 3–8 New York State English Language Arts Assessments. www.p12.nysed.gov/specialed/publications/testing-accommodations-ela-grades-3–8.htmGoogle Scholar
Kirk, S. A. (1962). Educating exceptional children. Boston: Houghton Mifflin.Google Scholar
Kirkwood, M. W. (2015). Review of pediatric performance and symptoms validity tests. In Kirkwood, M. W. (Ed.), Validity testing in child and adolescent assessment: Evaluating exaggeration, feigning, and noncredible effort (pp. 79–106) New York: Guilford.Google Scholar
Kirkwood, M. W., Kirk, J. W., Blaha, R. Z., & Wilson, P. (2010). Noncredible effort during pediatric neuropsychological evaluations: A case series and literature review. Child Neuropsychology, 16, 604–618. doi:10.1080/09297049.2010.495059Google Scholar
Kovaleski, J. F., VanDerHeyden, A. M., & Shapiro, E. S. (2013). The RTI approach to evaluating learning disabilities. New York: Guilford.Google Scholar
Larochette, A., & Harrison, A. G. (2012). Word Memory Test performance in Canadian adolescents with learning disabilities: A preliminary study. Applied Neuropsychology: Child, 1, 38–47. doi:10.1080/21622965.2012.665777Google Scholar
Lewandowski, L., Gathje, R. A., Lovett, B. J., & Gordon, M. (2013). Test-taking skills in college students with and without ADHD. Journal of Psychoeducational Assessment, 31(1), 41–52.Google Scholar
Lindstrom, W. A., Lindstrom, J. H., Coleman, C., Nelson, J., & Gregg, N. (2009). The diagnostic accuracy of symptom validity tests when used with postsecondary students with learning disabilities: A preliminary investigation. Archives of Clinical Neuropsychology, 24, 659–669. doi:10.1093/arclin/acp071Google Scholar
Lovett, B. J., & Kilpatrick, D. A. (2018). Differential diagnosis of SLD versus other difficulties. In Flanagan, D. P. & Alfonso, V. C. (Eds.), Essentials of specific learning disability assessment (2nd ed., pp. 549–571). Hoboken, NJ: Wiley.Google Scholar
Lovett, B. J., & Lewandowski, L. J. (2006). Gifted students with learning disabilities: Who are they? Journal of Learning Disabilities, 39(6), 515–527.Google Scholar
Lovett, B. J., & Lewandowski, L. J. (2015). Testing accommodations for students with disabilities: Research-based practice. Washington, DC: American Psychological Association.Google Scholar
Maki, K. E., Floyd, R. G., & Roberson, T. (2015). State learning disability eligibility criteria: A comprehensive review. School Psychology Quarterly, 30(4), 457–469. doi:10.1037/spq0000109Google Scholar
Martin, P. K., Schroeder, R. W., & Odland, A. P. (2015). Neuropsychologists’ validity testing beliefs and practices: A survey of North American professionals. The Clinical Neuropsychologist, 29(6), 741–776. doi:10.1080/13854046.2015.1087597Google Scholar
McGill, R. J., Styck, K. M., Palomares, R. S., & Hass, M. R. (2016). Critical issues in specific learning disability identification: What we need to know about the PSW model. Learning Disability Quarterly, 39(3), 159–170.Google Scholar
Miciak, J., Williams, J. L., Taylor, W. P., Cirino, P. T., Fletcher, J. M., & Vaughn, S. (2016). Do processing patterns of strengths and weaknesses predict differential treatment response? Journal of Educational Psychology, 108(6), 898–909.Google Scholar
Morgan, P. L., Farkas, G., Hillemeier, M. M., & Maczuga, S. (2012). Are minority children disproportionately represented in early intervention and early childhood special education? Educational Researcher, 41(9), 339–351.Google Scholar
Morgan, P. L., Farkas, G., Hillemeier, M. M., Mattison, R., Maczuga, S., Li, H., & Cook, M. (2015). Minorities are disproportionately underrepresented in special education: Longitudinal evidence across five disability conditions. Educational Researcher, 44(5), 278–292.Google Scholar
Naglieri, J. A. (2011). The discrepancy/consistency approach to SLD identification using the PASS theory. In Flanagan, D. P. & Alfonso, V. C. (Eds.), Essentials of specific learning disability identification (pp. 145–172). Hoboken, NJ: Wiley.Google Scholar
Osmon, D. C., Plambeck, E., Klein, L., & Mano, Q. (2006). The Word Reading Test of effort in adult learning disability: A simulation study. The Clinical Neuropsycholgist, 20, 315–324. doi:10.1080/13854040590947434Google Scholar
Phillips, S. E. (1994). High-stakes testing accommodations: Validity versus disabled rights. Applied Measurement in Education, 7(2), 93–120.Google Scholar
Reschly, D. J., & Hosp, J. L. (2004). State SLD identification policies and practices. Learning Disability Quarterly, 27(4), 197–213.Google Scholar
Rutkowski, D., & Wild, J. (2015). Stakes matter: Student motivation and the validity of student assessments for teacher evaluation. Educational Assessment, 20(3), 165–179. doi:10.1080/10627197.2015.1059273Google Scholar
Scanlon, D. (2013). Specific learning disability and its newest definition: Which is comprehensive? And which is insufficient? Journal of Learning Disabilities, 46, 26–33.Google Scholar
Schneider, W.J. , & McGrew, K. S. (2012). The Cattell-Horn-Carroll model of intelligence. In Flanagan, D. & Harrison, P. (Eds.), Contemporary intellectual assessment: Theories, tests, and issues (3rd ed., pp. 99–144). New York: Guilford.Google Scholar
Sherman, E. M. S. (2015). Terminology and diagnostic concepts. In Kirkwood, M. W. (Ed.), Validity testing in child and adolescent assessment: Evaluating exaggeration, feigning, and noncredible effort (pp. 22–41). New York: Guilford.Google Scholar
Skiba, R. J., Simmons, A. B., Ritter, S., Gibb, A. C., Rausch, M. K., Cuadrado, J., & Chung, C. G. (2008). Achieving equity in special education: History, status, and current challenges. Exceptional Children, 74(3), 264–288.Google Scholar
Slick, D., Hopp, G., Strauss, E., & Thompson, G. B. (1997). Victoria Symptom Validity Test. Odessa, FL: Psychological Assessment Resources.Google Scholar
Slick, D. J., Sherman, E. M. S., & Iverson, G. L. (1999). Diagnostic criteria for malingered neurocognitive dysfunction: Proposed standards for clinical practice and research. The Clinical Neuropsychologist, 13(4), 545–561. doi:10.1076/1385-4046(199911)13:041-Y;FT545Google Scholar
Stanovich, K. E. (2005). The future of a mistake: Will discrepancy measurement continue to make the learning disabilities field a pseudoscience? Learning Disability Quarterly, 28(2), 103–106.Google Scholar
Steedle, J. T., & Grochowalkski, J. (2017). The effects of stakes on accountability test scores and pass rates. Educational Assessment, 22(2), 11–123. doi:10.1080/10627197.2017.1309276Google Scholar
Sternberg, R. J., & Grigorenko, E. L. (2002). Difference scores in the identification of children with learning disabilities: It’s time to use a different method. Journal of School Psychology, 40(1), 65–83.Google Scholar
Sullivan, A. L., & Bal, A. (2013). Disproportionality in special education: Effects of individual and school variables on disability risk. Exceptional Children, 79(4), 475–494.Google Scholar
Sullivan, B. K., May, K., & Galbally, L. (2007). Symptom exaggeration by college adults in attention-deficit hyperactivity and learning disorder assessments. Applied Neuropsychology, 14(3), 189–207. doi:10.1080/09084280701509083Google Scholar
Thurlow, M. L., Elliott, J. L., & Ysseldyke, J. E. (2003). Testing students with disabilities: Practical strategies for complying with district and state requirements. Thousand Oaks, CA: Corwin.Google Scholar
Tombaugh, T. N. (1996). Test of Memory Malingering. Toronto: Multi-Health Systems.Google Scholar
Vellutino, F. R., Scanlon, D. M., & Lyon, G. R. (2000). Differentiating between difficult-to-remediate and readily remediated poor readers: More evidence against the IQ-achievement discrepancy definition of reading disability. Journal of Learning Disabilities, 33(3), 223–238.Google Scholar
Volpe, R. J., & Fabiano, G. A. (2013). Daily behavior report cards. New York: Guilford.Google Scholar
Walker, J. S. (2011). Malingering in children: Fibs and faking. Child and Adolescent Psychiatric Clinics of North America, 20, 547–556. doi:10.1016/j.chc.2011.03.13Google Scholar
Yell, M. L., Katsiyannis, A., & Collins, J. C. (2010). Compton Unified School District v. Starvenia Addison: Child find activities and response to intervention. Journal of Disability Policy Studies, 21(2), 67–69.Google Scholar
Ysseldyke, J. (2001). Reflections on a research career: Generalizations from 25 years of research on assessment and instructional decision making. Exceptional Children, 67(3), 295–309.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×