ArticlePloS one2018
Survey of potential receptivity to robotic-assisted exercise coaching in a diverse sample of smokers and nonsmokers.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- Exercise interventions for smoking cessation.The Cochrane database of systematic reviews · 2019Pooled it
- Acceptability of Robotic-Assisted Exercise Coaching Among Diverse Youth: Pilot Study.JMIR pediatrics and parenting · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 4 institutions in 1 country.
Funding
Abstract
A prior project found that an intensive (12 weeks, thrice weekly sessions) in-person, supervised, exercise coaching intervention was effective for smoking cessation among depressed women smokers. However, the sample was 90% White and of high socioeconomic status, and the intensity of the intervention limits its reach. One approach to intervention scalability is to deliver the supervised exercise coaching using a robotic human exercise trainer. This is done in real time via an iPad tablet placed on a mobile robotic wheel base and controlled remotely by an iOS device or computer. As an initial step, this preliminary study surveyed potential receptivity to a robotic-assisted exercise coaching intervention among 100 adults recruited in two community settings, and explored the association of technology acceptance scores with smoking status and other demographics. Participants watched a brief demonstration of the robot-delivered exercise coaching and completed a 19-item survey assessing socio-demographics and technology receptivity measured by the 8-item Technology Acceptance Scale (TAS). Open-ended written feedback was obtained, and content analysis was used to derive themes from these data. Respondents were: 40% female, 56% unemployed, 41% racial minority, 38% current smoker, and 58% depression history. Mean total TAS score was 34.0 (SD = 5.5) of possible 40, indicating overall very good receptivity to the robotic-assisted exercise intervention concept. Racial minorities and unemployed participants reported greater technology acceptance than White (p = 0.015) and employed (p<0.001) respondents. No association was detected between the TAS score and smoking status, depression, gender or age groups. Qualitative feedback indicated the robot was perceived as a novel, motivating, way to increase intervention reach and accessibility, and the wave of the future. Robotic technology has potential applicability for exercise coaching in a broad range of populations, including depressed smokers. Our next step will be to conduct a pilot trial to assess acceptability and potential efficacy of the robotic-assisted exercise coaching intervention for smoking cessation.
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What OpenQuestion holds
Registered trials
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.