Development and Validation of the Hand Assessment Tool

SCIENTIFIC/CLINICAL ARTICLE JHT READ

FOR

CREDIT ARTICLE #132.

Development and Validation of the Hand Assessment Tool Sanjiv H. Naidu, MD, PhD Pinnacle Health Hand Center, Mechanicsburg, Pennsylvania

Daniel Panchik, DSc, OTR/L Department of Occupational Therapy, Elizabethtown College, Elizabethtown, Pennsylvania

Vernon M. Chinchilli, PhD Department of Health Evaluation Sciences, Penn State College of Medicine, Hershey, Pennsylvania

The importance of outcome measures in Health care is well established.1e5 It is important to use control methods, including activity limitation measurements to document accountability, to offer costeffective service, and to improve the quality of care. Moreover, there are substantial clinical benefits to using a self-report activity limitation measure. They are used to guide clinical reasoning regarding goal setting. Measurement of functional status can also aid initiation and discharge of specific interventions and assists the clinician in discharge planning.6 Selfreported outcome measures are needed to justify the treatment regime and to account for principal concerns of the patients, which include activity and participation changes.1e3 The International Classification of Functioning, Disability, and Health (ICF), endorsed by the World Health Assembly in May 2001, aims to provide a scientific basis for understanding and studying health and health-related states, outcomes, and determinants. To accomplish this, it has established a common language for describing health—allowing Correspondence and reprint requests to Sanjiv H. Naidu, MD, PhD, Pinnacle Health Hand Center, 2015 Technology Parkway, Mechanicsburg, PA 17050; e-mail: . 0894-1130/$ e see front matter Ó 2009 Hanley & Belfus, an imprint of Elsevier Inc. All rights reserved. doi:10.1016/j.jht.2008.11.003

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ABSTRACT: The objective was to develop a self-administered activity limitation measurement tool for individuals with hand and wrist injuries, and to evaluate the reliability and validity of the new instrument, the Hand Assessment Tool (HAT). The final version of the HAT instrument, the SF12, and Disabilities of Arm, Shoulder, and Hand Questionnaire (DASH) were given to 94 consecutive new hand surgery clinic patients. Statistical analyses indicated excellent internal consistency with Cronbach’s alpha of 0.91. Testeretest reliability of the HAT showed a concordance correlation coefficient of 0.73, with 95% confidence interval ¼ (0.60, 0.83). Excellent correlation between the HAT and DASH was noted. A modest agreement with the SF12 physical score was observed. The HAT correlated well with the DASH and SF12 physical score and proved to be an internally consistent and reliable instrument for evaluation of activity limitations for individuals who sustain wrist or hand injury. J HAND THER. 2009;22:250–7.

data comparisons and providing a systematic coding scheme for health information systems.7 The ICF defines activity as ‘‘the execution of a task or action by an individual’’ and activity limitation is defined as ‘‘difficulties an individual may have in executing activities.’’ The ICF further notes that these limitations should be direct manifestations of the respondent’s health state, without assistance. This is why the Hand Assessment Tool (HAT) is classified as a measurement of activity limitation. The ICF defines assistance as the ‘‘help of another person, or assistance provided by an adapted or specially designed tool, or a form of environmental modification.’’ The level of capacity is judged relative to that which is normally expected of a person, or a person’s capacity before he or she acquired his or her health condition.7 The intent of the HAT is to measure activity limitation without assistance. The Disabilities of Arm, Shoulder, and Hand Questionnaire (DASH) evaluates upper-limb disability and it is common knowledge within hand surgery and rehabilitation communities that the DASH is the most used region-specific outcome questionnaire.8e10 The intent of the DASH is to determine how well a person can perform functional activities regardless of how these activities are performed.8e10 It allows the responding patient to take into account the benefits gained from using assistive devices to complete functional tasks. Therefore, it may very well underestimate

the actual impairment. In addition, modern day hand surgery is routinely set in surgery centers and the lengthy nature of the questionnaire poses another barrier in obtaining reliable outcome data. Although QuickDash is an abbreviated version available, critical analysis of this questionnaire shows that at least five of the 11 questions concern subjective pain with only six functional items. Our goal is to define and validate a region-specific activity limitation measure for the hand, wrist, and forearm axis, which encompasses functional tasks, neuritic and subjective pain symptoms, and aesthetics. The Michigan Hand Outcomes Questionnaire (MHQ) includes items that fall into one of six subscales for different content areas. These domains are overall hand function, activities of daily living (ADL), pain, work performance, aesthetics, and patient satisfaction with hand function.11 A notable advantage of the MHQ is that hand dominance is taken into consideration with respect to overall hand function, ADLs, pain, and satisfaction with hand function. A score is obtained for both right and left hands and if both hands are affected, the right and left hand function scores are averaged. A disadvantage of the MHQ is the complexity of the instrument and the lengthy nature of the questionnaire.11e13 Another instrument, the patient-rated wrist evaluation (PRWE),14e16 was developed and validated for evaluation of clients with wrist fractures. The PRWE was modified into the patient-rated wrist/hand evaluation (PRWHE) by changing the word wrist to wrist/hand throughout the instrument.15,16 The instrument was developed to conform to the priorities set by the clinicians and uses pain, activities of daily life, and work as subjective outcomes. The PRWHE measures wrist pain and disability and is in essence a disease-specific instrument that may not be suitable for general hand and upper extremity dysfunction. The objective of this project was to develop a selfadministered activity limitation instrument for hand and wrist injuries and to evaluate the reliability and validity of the new instrument. The HAT was developed to address a full range of activities for patients with injuries specific to the hand and wrist. The HAT seeks to assess activity in terms of a broad spectrum of health-related outcomes, including self-care, leisure, symptoms, and aesthetics. Because it seems conceivable that questions regarding the impact on work performance may be a source of error in a self-report measurement tool, work performance was not included in the content of the HAT. The HAT was designed to investigate the effects of intervention and examine the impact of disease processes specific to the hand and wrist. The instrument specifically evaluates the activity limitation impact of hand and wrist injuries on usual task performance; unlike the DASH, the HAT takes the approach of basing the comparison on performance without compensatory strategies or equipment.

MATERIALS AND METHODS Instrument Development Items for initial instrument development were generated by review and modification of established questionnaires, including the DASH,8 the Symptom Severity Scale,17 the Functional Status Scale,17 and from opinions of hand surgeons and certified hand therapists working in a clinical setting at outpatient hand clinics. Both surgeons and hand therapists responded by mail to the pilot questionnaire. Initial item reduction to 30 questions was judgment based and determined by the researchers. Factor analysis was used as an exploratory multivariate statistical technique to examine the structure within a large set of variables.18 Our intention was to reduce the HAT instrument from 30 to a smaller number of questions. Seven factors were identified and all factors were represented in selection of questions in the final instrument. Factor loadings were determined as correlations between each factor and the 30 items in the factor analysis. The higher the loading, the closer the association of the item with the group of items that makes up the factor. Identifying a cutoff point for determining whether an item’s loading is high enough for a meaningful contribution to the factor is somewhat arbitrary—we chose 0.5 as our cutoff.19 Responses from 95 consecutive hand therapy patients were used in the pilot study of the initial 30-question version of the instrument for factor analysis. Only patients with wrist and hand pathology were included in the pilot study. Institutional Review Board approval was obtained before the initiation of the pilot study.

Subject Selection and Methodology Subject recruitment occurred in an orthopedic hand clinic, and a plastic surgery hand clinic. Only new clinic patients (.18 yr) with hand and wrist problems were included in the study. Patients who were in a cast or immobilization splint new to the clinic were excluded until immobilization was removed at which time they were eligible. Patients who were non-native English speakers were excluded. The final version of the HAT, DASH, and SF12 were given to 94 consecutive patients, after obtaining signed informed consent. At the conclusion of their initial appointment, patients were given a copy of the HAT to complete and mail back, one week later in a self-addressed stamped envelope. Approval from the Institutional Review Board and human subject protection office was secured before data collection. The performance site human research protection program was awarded full accreditation by the Association for the Accreditation of Human Research Protection Programs, Inc. (AAHRPP). JulyeSeptember 2009 251

Reliability Cronbach’s alpha coefficient was used to measure internal consistency and the test statistic ranges from 0 to 1.0. Scores of $0.70 indicated that the questions in an index are measuring the same variable.18 Internal consistency was determined from analysis of the initial administration of the HAT. The concordance correlation coefficient was used to determine testeretest reliability in this study because it assesses agreement between X and Y, not just whether there are linear relationships between X and Y. To determine testeretest reliability for the HAT, subjects who had no intervention repeated the measurement one week after the initial clinic visit. This was accomplished by giving the subjects a test to mail back one week after the initial assessment. If the HAT was not received on a timely basis by mail, the HAT retest score was obtained by a telephonic interview.

Validity Two measures of construct validity were included in this study—convergent validity and discriminant validity. Convergent validity tests the hypothesis that two measures that are believed to reflect the same underlying phenomena will correlate highly. Discriminant validity estimates the ability of a measure to sort or discriminate by correctly identifying factors that are expected not to correlate with one another.18,20 Discriminant validity is measured less often compared with convergent construct validity in instrument development.18 Analyses were conducted to compare established instruments with the HAT. HAT scores were compared with the patients’ scores on the DASH and the SF12 Health Survey (physical score) to provide evidence of construct validity.8,21,22 Discriminant validity was determined by comparing HAT scores with SF12 Health Survey (mental health score) results. Pearson correlation coefficients were constructed for this study for analysis of construct validity.

RESULTS Pilot Study Results Ninety-five patients completed the 30-question pilot study. Table 1 delineates the demographic information for the pilot group and Table 2 lists the diagnostic categories in the pilot study sample. The factor analysis procedure used data from 69 of the pilot study respondents, because questionnaires with any missing questions were excluded from the analysis. Seven factors were identified by the analysis based on a factor level . 1.19 An eigenvalue in a factor analysis setting represents the variance of a factor, and the 252

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TABLE 1. Demographic Data of Subjects Characteristic Mean age, yr (mean 6 SD) Female gender (%) Right-hand dominant (%) Dominant hand injured (%) Both hands injured (%) Non-dominant hand injured (%)

95 Pilot Subjects

94 Validation Subjects

50 6 16.5 56.0 82.1 57.9

47 6 16.4 67.4 84.2 67

10.5 50.5

17 53

sum of the eigenvalues represents the total variability within the data set. Thus, the eigenvalues are ordered from largest to smallest and the objective of the scree plot is to determine the appropriate set of eigenvalues that explain the majority of the total variability. The recommendation for the scree plot is to use the first K-eigenvalues where the Kth eigenvalue appears at or after the ‘‘elbow’’ in the plot. Based on this figure, K ¼ 7 factors were selected. One of the steps in factor analysis is to rotate the factor loading matrix to optimize the interpretation. Examining loadings rotated TABLE 2. Diagnostic Categories of Subjects Pilot Study

Validation Study

Diagnostic category

N

N

Carpel tunnel syndrome Wrist fracture Finger fracture Metacarpal fracture Crush injury Finger amputation Carpometacarpal arthritis Wrist sprain Ganglion cyst Ligament injury Tendon repair Arthritis Trigger finger Dupuytren’s disease Laceration Medial epicondylitis Lateral epicondylitis Hand amputation (bilateral) Triangular fibrocartilage complex repair Degloving Nerve repair Wrist tendonitis Burn Arthrodesis Artery injury Finger dislocation Pronator syndrome TFCC repair Compartment syndrome Tumor Carpal instability Left ulnar neuropathy

24 12 8 1 6 2 5 5 4 3 2 7 2 2 2 1 1 1 1

25 2 3 2

1 1 1 1 1 1

7 8 4 4 3 12 8 1 3

4

1 1 1 1 2 1 1

from the factor pattern helped us decide which questions to include. In this study, a factor level $0.5 was used to determine which variables dominated the factor.19 A review of the identified questions determined that items in factor 1 related to ADLs involving a firm grasp; factor 2, encompassed ADLs involving fine hand skills; factor 3, pain; factor 4, ADLs involving wrist and digit extension; factor 5, neuritic symptoms; factor 6, ADLs involving gross grasp; and factor 7, aesthetics (Table 3). Question number 18, ‘‘Have you had difficulty making a bed?’’ was the only question that did not load on any factor. This question was eliminated in the final version of the instrument. Because positive signs were observed among the loadings of the rotated factor pattern, it was determined that one overall score could be calculated. No ceiling effects were observed in the pilot study data. One possible floor effect was observed in the pilot data for question number 9. ‘‘Have you had difficulty closing the refrigerator door?’’ This question was eliminated in the final version of the instrument. A total score is obtained based on a 0e100 scale with higher scores representing greater activity limitation. Scoring procedures for the HAT account for missing items; however, a score should not be calculated if there are more than two items missing.

Reliability/Validity Results Ninety-four consecutive patients who met the inclusion criteria completed the HAT (Appendix A), SF12, and DASH. Demographic information is given in Table 1 and diagnostic categories are described in Table 2. Reliability of the instrument was determined by analyses of internal consistency and testeretest

reliability. Cronbach’s alpha was 0.91, which showed excellent internal consistency. The results for testeretest reliability showed good agreement. The concordance correlation was 0.73, with 95% confidence interval ¼ (0.60, 0.83). The scatterplot of test versus retest illustrates these results (Figure 1). It was anticipated that testeretest reliability would be slightly lower than internal consistency because it includes content/item sampling and time sampling as sources of error, whereas internal consistency includes only content/sampling as a source of error. There was a one-week period of time between the two administrations of the test. Analysis of validity revealed a strong positive correlation between the DASH and the HAT. The Pearson correlation coefficient was 0.91 with 95% confidence interval ¼ (0.88, 0.95). The scatterplot of HAT versus DASH illustrates these results (Figure 2). Robustness of the instrument was evaluated by removing the data from the four functional questions that are similar on the HAT and DASH. The Pearson correlation was 0.89 still indicating a strong positive correlation. Pearson correlation coefficients were also constructed for convergent and discriminant construct validity comparing the HAT with the SF12 physical score and SF12 mental health score, respectively. For the physical score, there was a good correlation with the HAT—Pearson correlation coefficient was 0.52, with 95% confidence interval ¼ (0.34, 0.70). The predicted correlation coefficient for the physical SF12 score had been above 0.50. The correlation of the SF12 mental health score with the HAT, a test of discriminant validity showed only a weak correlation, again confirming the expectation. The Pearson correlation coefficient was 0.35, with 95% confidence interval ¼ (0.15, 0.55). The box plot

TABLE 3. Factors and Questions of the HAT Factor 1: Firm Grip

Factor 2: Fine Hand Skills

Factor 3: Pain

Have you had Have you had Does the pain in difficulty opening difficulty writing? your hand or a tight jar? wrist increase with activity? Have you had difficulty gripping a telephone and talking for 5 min? Have you had difficulty wringing out a washcloth? Have you had difficulty carrying a grocery bag?

Have you had difficulty buttoning, zippering or tying? Have you had difficulty using scissors?

Are you able to perform your normal leisure activities without difficulty?

Factor 4: Extension Have you had difficulty with personal hygiene after toileting?

Factor 5: Neuritic Symptoms

Factor 6: Gross Grasp

Do you have Have you had numbness and/or difficulty turning tingling a key? sensations in your hand and wrist? At night, does pain, tingling, or numbness wake you?

Factor 7: Aesthetics Do you dislike the appearance of your injured hand?

HAT ¼ Hand Assessment Tool.

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FIGURE 1. Scatterplot of concordance correlation coefficient. illustrates the simple statistics. The means for the tests are as follows: HAT is 35.74; DASH is 38.69; SF12 physical score is 39.03; and the SF12 mental health score is 49.92 (see Figure 3). The outlier in the retest was a participant who consistently scored poorly among all the instruments.

DISCUSSION The results of this study indicate that the HAT is a reliable and valid instrument for evaluation of activity limitation7 for individuals who sustain wrist and hand injury. The ICF notes that limitations are a direct manifestation of a respondent’s health state, without assistance.7 Administration of the HAT may be particularly useful when activity measurement relative to how one previously performed the task without compensatory strategies or equipment is indicated. A measure of this kind, an activity limitation measurement,7 can be used to investigate effects of interventions or the pathological processes affecting the

FIGURE 2. Pearson correlation between the HAT and DASH. HAT ¼ Hand Assessment Tool; DASH ¼ Disabilities of Arm, Shoulder, and Hand Questionnaire. 254

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FIGURE 3. Box plot of simple statistics. hand and wrist. The clinical applications include treatment planning, progress monitoring, and planning for change or discharge of interventions. The HAT correlates well with the DASH and SF12 physical score and as expected does not correlate well with the SF12 mental health score. There are notable differences between the HAT and DASH. The HAT does not ask the respondents to rate subjective pain or weakness nor does it ask them to rate the impact of their injury to their work. The HAT does, however, ask respondents to rate the impact of the appearance of their injured hand. Unlike the DASH, the HAT takes the approach of basing the comparison on performance without compensatory strategies or the use of adaptive equipment. The HAT may better discriminate activity limitation more than the DASH that focuses on an assessment of disability. This new instrument may be particularly useful when examining intervention or disease processes of wrist and hand pathology and its impact to activity. There are several limitations to this study. Although the sample size is statistically sound for hand and wrist patients in the aggregate, it does not permit analyses of each major diagnostic group. With 94 patients in the aggregate, the Pearson correlation coefficient has a 95% confidence interval such that the length of the interval is ,60.05, which reflects a high level of precision.23 Although the DASH and SF12 are known reliable and valid instruments, correlations between two self-report measures may inflate the estimates of correlation due to shared method variance. Future research that assesses the correlation of self-reported measurements with objective parameters, such as the JebseneTaylor Hand Function Test, or isokinetic strength testing could address this potential limitation. The HAT does not calculate a separate right hand and left hand score; however, hand dominance and location of injury are noted on the evaluation. It is important that researchers using the HAT in practice

be aware of a patient’s unique circumstance in comparison of scores. Patients are asked to compare their current performance to how they would have usually performed the task. One might question the extent to which a respondent may have motivation to exaggerate responses in either direction on a self-report measurement tool. The HAT has no specific question related to performance at work. It seems conceivable that questions regarding the impact on work performance would be a source of such an error. The HAT may serve as a useful alternative to the DASH in evaluating such patients because the DASH asks respondents to rate how they were limited in their work.

CONCLUSION The HAT correlates well with the DASH and SF12 physical score and proves to be an internally consistent and reliable region-specific outcome instrument for evaluation of activity limitations for individuals who sustain wrist or hand injury. The HAT outcome questionnaire may be used to investigate the effects of therapeutic intervention or the pathological processes affecting the hand and wrist. Acknowledgment The authors acknowledge the contributions for the clinical material from the following coworkers: Jana Underwood Poole, BS, OTR/L, CHT; Randy M Hauck, MD, FACS; and Virginia Hight, OTR/L, DrPH.

REFERENCES 1. Mullner RM, Jewell MA. The medical outcomes mandate. J Med Syst. 1999;23(3):171–3. 2. Chase RA. Costs, risks, and benefits of hand surgery. J Hand Surg. 1983;8:644–8. 3. Greenfield S, Nelson EC. Recent developments and future issues in the use of health status assessment measures in clinical settings. Med Care. 1992;30(5):MS23–41. 4. US Congress, Office of Technology Assessment. The Quality of Medical Care: Information for Consumers. Washington, DC: Government Printing Office, June 1988. 5. US Department of Health and Human Services. Healthy People 2000 DHHS Publication Number (PHS) 91-50213Washington, DC: US Government Printing Office, 1991. 6. Binkley J, Stratford P, Lott S, Riddle D. The lower extremity scale (LEFS): scale development, measurement properties, and clinical application. Phys Ther. 1999;79:371–83.

7. World Health Organization. International Classification of Functioning Disability and Health: ICF. Geneva, Switzerland: World Health Organization, 2001. 8. Solway S, Beaton DE, McConnell S, Bombardier C. The Dash Outcome Measure User’s Manual. 2nd ed. Toronto, Ontario: Institute for Work and Health, 2002. 9. Beaton DE, Davis AM, Hudak P, McConnell S. The DASH (disabilities of the arm, shoulder and hand) outcome measure: what do we know about it now? J Hand Ther [Br]. 2001;6(4): 109–18. 10. Beaton DE, Katz JN, Fossel AH, Wright JG, Tarasuk V, Bombardier C. Measuring the whole or parts? Validity, reliability, responsiveness of the disabilities of the arm, shoulder and hand outcome measure in different regions of the upper extremity. J Hand Ther. 2001;14:128–46. 11. Chung KC, Pillsbury MS, Walters MR, Hayward RA. Reliability and validity testing of the michigan hand outcomes questionnaire. J Hand Surg [Am]. 1998;23:575–87. 12. Chung KC, Hamill JB, Walters MR, Hayward RA. The Michigan hand outcomes questionnaire (MHG): assessment of responsiveness to clinical change. Ann Plas Surg. 1999;42(6): 619–22. 13. Kotsis SV, Chung KC. Responsiveness of the michigan hand outcomes questionnaire and the disabilities of the arm, shoulder, and hand questionnaire in carpal tunnel surgery. J Hand Surg. 2005;30:81–6. 14. MacDermid JC, Tottenham V. Responsiveness of the disability of the arm, shoulder, and hand (dash) and patient-related wrist/hand evaluation (PRWHE) in evaluating change after therapy. J Hand Ther. 2004;17(1):18–23. 15. MacDermid JC, Jurgeon T, Richards RS, Beadle M, Roth JH. Patient rating of wrist pain and disability: a reliable and valid measurement tool. J Orthop Trauma. 1998;12(8):577–86. 16. MacDermid JC, Richards RS, Donner A, Bellamy N, Roth JH. Responsiveness of the short form-36, disability of the arm, shoulder, and hand questionnaire, patient-rated wrist evaluation, and physical impairment measurements in evaluating recovery after a distal radius fracture. J Hand Surg. 2000;25A: 330–40. 17. Levine DW, Simmons BP, Koris MJ, et al. A self-administered questionnaire for the assessment of severity of symptoms and functional status in carpal tunnel syndrome. J Bone Joint Surg [Am]. 1993;11:1585–92. 18. Vogt WP. Dictionary of Statistics and Methodology. 2nd ed. Thousand Oaks, CA: Sage Publications, 1999. 19. Johnson RA, Wichern DW. Applied Multivariate Statistical Analysis. 5th ed. Upper Saddle River, NJ: Prentice Hall, 2002. 440e44. 20. Portney LG, Watkins MP. Foundations of Clinical Research: Applications to Practice. 2nd ed. Upper Saddle River, NJ: Prentice Hall Health, 2000. 21. Ware J, Kosinski M, Keller SD. A 12-item short form health survey, construction of scales and preliminary tests of reliability and validity. Med Care. 1996;34:220–33. 22. Ware JE, Sherbourne CD. The MOS 36-item short form health survey (SF-36) conceptual framework and item selection. Med Care. 1992;30(6):473–83. 23. Armitage P, Berry G. Statistical Methods in Medical Research. 3rd ed. London: Blackwell Scientific Publications, 1994. 163e65.

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Appendix A THE HAND ASSESSMENT TOOL (HAT) Background Information Are you male or female? What happened to your hand and where did it happen? What date did this begin? Which hand is injured? Are you right handed, left handed, or do you use both hands equally well? What is your age? Who is your doctor?

Instructions: Please circle answers to every question based on your condition over the past week. Answer all questions. If the activity has not occurred, answer the question as you would anticipate your performance. Please respond to the items as you would have usually performed the task. 1 1. Have you had difficulty No difficulty writing? 2. Have you had difficulty No difficulty buttoning, zippering, or tying? 3. Have you had difficulty No difficulty opening a tight jar? 4. Have you had difficulty No difficulty gripping a telephone and talking for 5 min? 5. Have you had difficulty No difficulty turning a key? 6. Have you had difficulty No difficulty using scissors? 7. Have you had difficulty No difficulty wringing out a washcloth? 8. Have you had difficulty No difficulty with personal hygiene after toileting? 9. Have you had difficulty No difficulty carrying a grocery bag? 10.Does the pain in your No pain hand or wrist increase with activity? 11.Do you have numbness No numbness and/or tingling nor tingling sensations in your hand and wrist? 12.At night, does pain, Never tingling, or numbness wake you? 13.Are you able to perform No difficulty your normal leisure activities without difficulty? 14.Do you dislike the No, it looks appearance of your fine injured hand?

2

3

4

5

Mild difficulty

Moderate difficulty

Severe difficulty

Unable to do

Mild difficulty

Moderate difficulty

Severe difficulty

Unable to do

Mild difficulty

Moderate difficulty

Severe difficulty

Unable to do

Mild difficulty

Moderate difficulty

Severe difficulty

Unable to do

Mild difficulty

Moderate difficulty

Severe difficulty

Unable to do

Mild difficulty

Moderate difficulty

Severe difficulty

Unable to do

Mild difficulty

Moderate difficulty

Severe difficulty

Unable to do

Mild difficulty

Moderate difficulty

Severe difficulty

Unable to do

Mild difficulty

Moderate difficulty

Severe difficulty

Unable to do

Mild pain

Moderate pain

Severe pain

Unbearable

Mild numbness and/or tingling

Moderate numbness and/or tingling

Severe numbness and/or tingling

I cannot feel my hand or wrist and/or I have profound tingling

1 or 2 times

Sometimes

Often

I can’t sleep because of it

Mild difficulty

Moderate difficulty

Severe difficulty

Unable to actively participate in leisure activities

I dislike it a little bit

I moderately dislike it I dislike it very much

I am extremely bothered by its appearance

Scoring procedures for the hand assessment tool (HAT): [(sum of n responses)/n)  1] 3 25 n is the number of items completed on the HAT. A HAT score will not be calculated if there are more than two items missing.

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JHT Read for Credit Quiz: Article # 132

Record your answers on the Return Answer Form found on the tear-out coupon at the back of this issue. There is only one best answer for each question. #1. The HAT is best described as a. a short version of the DASH b. a self administered intake measure c. a self administered outcome measure d. a therapist administered intake and outcome measure #2. The HAT demonstrated a. high reliability and validity scores b. high reliability but low validity scores c. high validity but low reliability scores d. low reliability and validity scores #3. The HAT primarily measures

a. job performance b. recreational limitations c. traditional ADL d. activity limitations #4. In put for the HAT questionnaire came from a. surgeons b. therapists c. surgeons and therapists d. professional test makers #5. The authors suggest that the HAT is appropriate as a clinical tool, but not suitable for research a. true b. false When submitting to the HTCC for re-certification, please batch your JHT RFC certificates in groups of 3 or more to get full credit.

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