Evidence map›Paper›PMID 41219971›Full record

ArticleBMC medical informatics and decision making2025

Enhancing therapeutic decisions during robot-assisted gait therapy: current challenges and development of a novel app-based therapy protocol to address them.

Florian van Dellen, Tabea Aurich, Rob Labruyère

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Florian van DellenSwiss Children's Rehab, Children's University Hospital Zurich, Mühlebergstrasse 104, Affoltern Am Albis, CH-8910, Switzerland. florian.vandellen@kispi.uzh.ch.
Tabea AurichSwiss Children's Rehab, Children's University Hospital Zurich, Mühlebergstrasse 104, Affoltern Am Albis, CH-8910, Switzerland.
Rob LabruyèreSwiss Children's Rehab, Children's University Hospital Zurich, Mühlebergstrasse 104, Affoltern Am Albis, CH-8910, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTherapists’ decisions on influencing patient behavior during robot-assisted gait therapy directly impact clinical practice and, thus, therapeutic efficacy. These manipulations include device parameter adjustments and direct interactions with patients. Little research has been done on how therapists accomplish this task, and knowledge about what constitutes good decisions is scarce. The scarce knowledge is partly due to missing tools to document these decisions. Understanding how therapists assess behavior, manipulate patient behavior, and re-assess behavior for potential improvement could lead to better therapy outcomes.

methodsWe developed a novel mobile application to document therapeutic decisions based on expert knowledge and literature findings. Each documented manipulation consisted of three parts: The evaluation of the patient behavior (goal-oriented and compensatory), the manipulation by the therapist (direct interaction or device interaction), and the re-evaluation of the behavior concerning the consequences of this manipulation. The resulting application was pilot-tested with 10 patients in 5 sessions and 7 therapists in a real-world clinical setting.

resultsTherapists selected more than two therapy goals per session for 50% of the training sessions. The results show that 92% of the manipulations were direct interactions and 8% device interactions. Sixteen percent of the direct interactions targeted the selected goal and 43% compensatory movements. The type of manipulation had a statistically significant impact on the rate of improvement at re-evaluation, with direct interactions targeting compensatory movements having the best rate of improvement (48%) and the parameter adjustments having the lowest rate of improvement (25%). DISCUSSION: The app developed is a novel approach to documenting therapists’ decisions. The data collected in the pilot study revealed several challenges in the decision-making process that therapists can currently only address based on their experience, including goal structure, the relative importance of goal-directed movements versus compensatory patterns, and the type of manipulation taken. Quantitative data provided by the app has the potential to objectify and improve these decisions and could support a transfer of successful treatment approaches between therapists and clinics. In conclusion, the developed mobile application tracks therapists’ clinical reasoning during robot-assisted gait therapy and provides data that can be used to promote evidence-based decision-making.

Indexed as

GaitMobile ApplicationsRoboticsFemaleHumansMaleDecision support systemsDigital healthNeurologic gait disordersRehabilitationTherapeutic strategies

Identifiers

PMID41219971
PMCPMC12606835

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.