OUTCOME MEASURES USED TO ASSESS HAND ACTIVITY IN AMPUTEE AND INTACT POPULATIONS: A LITERATURE REVIEW
Bibliographic record
Abstract
BACKGROUND: The human hand is critical in assisting with activities of daily living (ADL). Amputation of the hand can affect a person physically, socially and psychologically. Knowledge of outcome measures used to assess upper limb activity of intact and amputee populations may aid in guiding research to develop applicable measurement tools specific to the amputee population. Tools could aid developments in prosthetic design and prescription, which benefit both users and healthcare researchers. OBJECTIVE(S): This literature review examined outcome measurement tools used with non-amputee and amputee populations to assess hand activity. The objectives were to identify which characteristics of hand activity are captured by currently available measurement tools. METHODOLOGY: Searches were conducted using PubMed, Cochrane and ProQuest for studies investigating hand activity for amputee and non-amputee populations. A total of 15 studies were included. PRISMA guidelines were used to assist with study selection. Data extraction and narrative synthesis were carried out. FINDINGS: A total of 32 outcome measures were found. Frequently used tools were: Box and Block Test, Swedish Disabilities of the Arm Shoulder and Hand Questionnaire, and range of motion. Studies employed a combination of 2 to 12 tools. Themes extracted were: importance of function and quality of life, the need for realistic tasks, and the need for outcome measures specific of the population. CONCLUSION: There is a gap in research surrounding outcome measurement tools used to assess hand activity in the amputee population. A combination of outcome measures are required to obtain insight into the hand activities of intact and amputee populations. Function and quality of life are important aspects to consider when describing hand activity. Layman's Abstract The human hand provides important functionality to help us live our daily lives. Hands enable us to perform tasks such as turn a key, cook food, use a phone and get dressed. Amputation of the hand not only affects activities of daily living (ADL), but also mental health. Hands are often assessed by healthcare professionals but there are few measurement tools available to assess artificial hands, commonly known as prosthetic hands. Developing new measurement tools would help us learn more about how people perform tasks if they are missing a hand, or using a prosthetic hand, will benefit society. The goal of this review was to examine measurement tools that assess hand activity. The first objective was to identify which types of hand activities are captured by currently available measurement tools. This review included 15 studies and compared to find common themes. Frequently used measurement tools were: Box and Block Test, Swedish Disabilities of the Arm Shoulder and Hand Questionnaire, and range of motion. All studies used a combination of measurement tools. The key themes commonly found were: importance of function and quality of life to be assessed, the need for realistic tasks and the need for tools designed specifically for the population of amputees or prosthesis users. Article PDF Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/39023/30502 How To Cite: Carlyle K, Day S. Outcome measures used to assess hand activity in amputee and intact populations: A literature review. Canadian Prosthetics & Orthotics Journal. 2022; Volume 5, Issue 2, No.4. https://doi.org/10.33137/cpoj.v5i2.39023 Corresponding Author: Kirsty Carlyle, MEngDepartment of Biomedical Engineering, Faculty of Engineering, University of Strathclyde, Glasgow, United Kingdom.E-Mail:kirsty.carlyle@strath.ac.uk ORCID ID: https://orcid.org/0000-0002-0291-4717
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.019 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".