Best Practice and Innovation in AT

Evidence-Based Practice

 

The Case of the HandShoe Mouse 

hand shoe mouse

Effects of the use of a special computer mouse : The HandShoe Mouse

Summary:

Biomechanical research has shown that a palm supporting surface provides a better solution to prevent neck, shoulder, arm and hand complaints. For example in view of the reduced or possible absence of grip forces a computer mouse design according to this concept is to be preferred. An additional point of attention is the angle of the supporting surface. This angle can have a significant (negative) effect on muscle tension for example in the “neutral (900 supination) or handshake position”.

 

Clinical Biomechanics

Summary:

Background information on how to work in a comfortable position is provided, for example the positive effects of a slanted mouse (palm supporting area at an angle of 25° or 30°).
Forearm and shoulder muscle activity will reduce in this position.
Increasing the slanted angle will result in a larger wrist extension and thus higher muscle activity.
Working with hand and forearm at a suitable slanted angle provides a more neutral hand position, so forearm and shoulder muscle activity will be reduced.
This paper also addresses possible sources of carpal tunnel pressure (CTP).

 

Effects of forearm and palm supports on the upper extremity during computer mouse use.
 

Summary:

The use of forearm and hand support is associated with less shoulder muscle activity and shoulder torsion while palm support is associated with less wrist extension. This type of support also results in lower applied forces to the mouse body. Participants reported less musculoskeletal discomfort when using a support.
It should be noted that some aspects addressed in this paper must also be looked at from the perspective of findings by other researchers presented in this overview of publications.

 

For additional research evidence visit: http://handshoemouse.com/publications/ and http://handshoemouse.com/research/ 


Impact of Word Prediction on Writing Skills of Students with Special Needs 

Silió, M. C., & Barbetta, P. M. (2010). The effects of word prediction and text-to-speech technologies on the narrative writing skills of Hispanic students with specific learning disabilities. Journal of Special Education Technology, 25(4), 17–32.

This quasi-experimental research study, published in a peer-reviewed academic journal, investigated whether, with writing time held constant, Hispanic students with specific learning disabilities (SLD) under:

  • word processing,
  • word processing with word prediction,
  • word processing with text-to-speech, or
  • word processing with word prediction and text-to-speech combined

would:

  1. perform more effectively in narrative composition writing as defined by writing fluency, syntax, and spelling accuracy,
  2. improve their overall organization of narrative composition writing, and
  3. maintain skills in narrative composition writing and organization on maintenance tests given two, four, and six weeks after writing ended.

RESULTS: Although outcomes varied for individual participants, the overall results demonstrated that word prediction alone and in combination with text-to-speech had a positive impact on the participants’ writing. With word prediction alone and with text-to-speech, participants in both cohorts wrote longer, more syntactically mature compositions that were better organized and had fewer spelling errors. The use of text-to-speech alone, however, resulted in little or no improvement. With few exceptions, participants maintained a high percentage of the composition skills they developed.

 

Cullen, J., Richards, S. B., & Frank, C. L. (2008). Using software to enhance the writing skills of students with special needs. Journal of Special Education Technology, 23(2), 33–43.

This research article, published in a peer-reviewed academic journal, investigated the effects of computer software on the writing performance of students with mild disabilities. In particular, it focuses on the effects of a talking word processor with spell checker alone (Write: Outloud) and in conjunction with word prediction software (Co:Writer) on journal entries. 

RESULTS: In general, both supports positively impacted the students’ writing, Co:Writer more so than Write: Outloud. As a whole group, the participants improved on each dependent variable during both intervention phases. However, these effects did not yield uniform outcomes across students. Collins, Richards and Lawless Frank conclude that while computer software that provides writing supports such as text-to-speech, spell checker and word prediction benefits students with disabilities, it is necessary to consider each student’s individual strengths and weaknesses when choosing software.

For addtional research evidence visit: Learning Technologies