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Record W4226027923 · doi:10.2196/36768

Modification in the Motor Skills of Seniors in Care Homes Using Serious Games and the Impact of COVID-19: Field Study

2022· article· en· W4226027923 on OpenAlexvenueno aff
Jana Marina Kleschnitzki, Inga Großmann, Reinhard Beyer, Luzi Beyer

Bibliographic record

VenueJMIR Serious Games · 2022
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
Fundersnot available
KeywordsPandemicTinetti testCoronavirus disease 2019 (COVID-19)Intervention (counseling)PsychologyIsolation (microbiology)Test (biology)GerontologyMotor skillMedicinePhysical therapyDevelopmental psychologyDiseasePsychiatry

Abstract

fetched live from OpenAlex

Background The pandemic has highlighted the importance of low-threshold opportunities for exercise and physical activity. At the beginning of 2020, the COVID-19 pandemic led to many restrictions, which affected seniors in care facilities in the form of severe isolation. The isolation led, among other things, to a lack of exercise, which has led to a multitude of negative effects for this target group. Serious games can potentially help by being used anywhere at any time to strengthen skills with few resources. Objective The aim of this study is to evaluate the effectiveness of a serious game to strengthen motor skills (study 1) and the influence of pandemic restrictions (study 2) on seniors in care facilities. Methods The data on motor skills (measured by the Tinetti test) originated from an intervention study with repeated measurements that was interrupted by the pandemic conditions. Data were collected 4 times every 3 months with an intervention group (IG, training 3 times for 1 hour per week) and a control group (CG, no intervention). There were 2 substudies. The first considered the first 6 months until the pandemic restrictions, while the second considered the influence of the restrictions on motor skills. Results The sample size was 70. The IG comprised 31 (44%) participants, with 22 (71%) female and 9 (29%) male seniors with an average age of 85 years. The CG comprised 39 (56%) participants, with 31 (79%) female and 8 (21%) male seniors with an average age of 87 years. In study 1, mixed-design ANOVA showed no significant interaction between measurement times and group membership for the first measurements (F2.136=1.414, P<.25, partial η2=.044), but there was a significant difference between the CG (mean 16.23, SD 1.1) and the IG (mean 19.81, SD 1.2) at the third time of measurement (P=.02). In study 2 the mixed-design ANOVA (used to investigate motor skills before and after the pandemic conditions between the 2 groups) couldn’t reveal any significant interaction between measurement times and group membership: F1.67=2.997, P<.09, partial η2=.043. However, there was a significant main effect of the time of measurement: F1.67=5.44, P<.02, partial η²=.075. Conclusions During the first 6 months, the IG showed increased motor skills, whereas the motor skills of the CG slightly deteriorated and showed a statistically significant difference after 6 months. The pandemic restrictions leveled the difference and showed a significant negative effect on motor skills over 3 months. As our results show, digital games have the potential to break down access barriers and promote necessary maintenance for important skills. The pandemic has highlighted the importance of low-threshold opportunities for exercise and physical activity. This potentially great benefit for the challenges of tomorrow shows the relevance of the topic and demonstrates the urgent need for action and research. Trial Registration Deutsches Register klinischer Studien DRKS00016633; https://tinyurl.com/yckmj4px

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score0.423

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.014
GPT teacher head0.349
Teacher spread0.335 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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".

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Citations4
Published2022
Admission routes1
Has abstractyes

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