MétaCan
Menu
Back to cohort
Record W2969332595 · doi:10.2196/15386

Using Video Feedback Through Smartphone Instant Messaging in Fundamental Nursing Skills Teaching: Observational Study

2019· article· en· W2969332595 on OpenAlexafffundvenue
Xiaoxian Yang, Ri‐hua Xie, Si Chen, Wei Yu, Yan Liao, Daniel Krewski, Shi Wu Wen

Bibliographic record

VenueJMIR mhealth and uhealth · 2019
Typearticle
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsUniversity of OttawaOttawa Hospital
FundersNatural Sciences and Engineering Research Council of CanadaSouthern Medical UniversityCanadian Institutes of Health ResearchUniversity of Ottawa
KeywordsObservational studyClass (philosophy)Video feedbackTeaching methodComputer scienceMedical educationNursingMultimediaMedicinePsychologyMathematics education

Abstract

fetched live from OpenAlex

BACKGROUND: Video feedback has been shown to be an effective teaching tool that can improve student learning when having them view their own performance. However, the literature on the effect of integrating smartphones with video feedback in fundamental nursing skills teaching is sparse. OBJECTIVE: This study aimed to explore the potential effects of video feedback through smartphone-based instant messaging on teaching undergraduate nursing students fundamental nursing skills. METHODS: We conducted a study on teaching fundamental nursing skills to 6 classes of second-year undergraduate nursing students. In 2 classes (the intervention group), the instructor elected to use smartphone-based video feedback to facilitate teaching; instructors in the other 4 classes (the control group) elected to use routine methods of teaching without video feedback. Scores from the final examination, in-class assignments, and the General Self-Efficacy Scale questionnaire were collected and compared between the two groups. Multiple linear regression analysis was performed to estimate the independent effect of video feedback after adjusting for gender, age, and prior experience in the use of WeChat/QQ in learning applications. An ad hoc questionnaire was used for student evaluation of the novel smartphone-based video feedback teaching method. RESULTS: A total of 195 nursing students (65 in the video feedback group and 130 in the control group) completed the study and were included in the final analysis. Mean and standard deviation of scores on the final examination, bed making, aseptic procedure, vital signs measurement, and oxygen therapy were 91.29 (SD 2.36), 90.52 (SD 3.18), 93.23 (SD 3.16), 91.65 (SD 4.21), and 92.06 (SD 3.58), respectively, in the video feedback group and 89.99 (SD 3.12), 81.71 (SD 8.63), 87.12 (SD 5.50), 87.45 (SD 8.00), and 90.37 (SD 6.36), respectively, in the control group (differences were statistically significant). The mean and standard deviation of scores for assignments in catheterization and enema and General Self-Efficacy Scale were 89.69 (SD 3.22), 91.14 (SD 3.15), and 24.52 (SD 5.35), respectively, in the video feedback group and 88.82 (SD 7.48), 90.79 (SD 6.08), and 24.50 (SD 6.16), respectively, in the control group (differences were not statistically significant). The majority (over 98%) of nursing students were satisfied with this smartphone-based video feedback teaching method. CONCLUSIONS: Video feedback through smartphone-based instant messaging may be an effective way to improve nursing students' academic performance and professional skills.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.211
GPT teacher head0.497
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations30
Published2019
Admission routes3
Has abstractyes

Explore more

Same venueJMIR mhealth and uhealthSame topicSimulation-Based Education in HealthcareFrench-language works237,207