The effect of word prediction settings (frequency of use) on text input speed in persons with cervical spinal cord injury: a prospective study
Résumé
Purpose: To determine whether activation of the frequency of use and automatic learning parameters of
word prediction software has an impact on text input speed.
Methods: Forty-five participants with cervical spinal cord injury between C4 and C8 Asia A or B accepted
to participate to this study. Participants were separated in two groups: a high lesion group for participants
with lesion level is at or above C5 Asia AIS A or B and a low lesion group for participants with lesion is
between C6 and C8 Asia AIS A or B. A single evaluation session was carried out for each participant. Text
input speed was evaluated during three copying tasks:
- without word prediction software (WITHOUT condition)
- with automatic learning of words and frequency of use deactivated (NOT_ACTIV condition)
- with automatic learning of words and frequency of use activated (ACTIV condition)
Results: Text input speed was significantly higher in the WITHOUT than the NOT_ACTIV (p<0.001) or
ACTIV conditions (p¼0.02) for participants with low lesions. Text input speed was significantly higher in
the ACTIV than in the NOT_ACTIV (p¼0.002) or WITHOUT (p<0.001) conditions for participants with high
lesions.
Conclusions: Use of word prediction software with the activation of frequency of use and automatic learning
increased text input speed in participants with high-level tetraplegia. For participants with low-level
tetraplegia, the use of word prediction software with frequency of use and automatic learning activated
only decreased the number of errors.
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