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Record W3185201558 · doi:10.2196/30709

Online-Delivered Group and Personal Exercise Programs to Support Low Active Older Adults’ Mental Health During the COVID-19 Pandemic: Randomized Controlled Trial

2021· article· en· W3185201558 on OpenAlexafffund
Mark R. Beauchamp, Ryan M. Hulteen, Geralyn R. Ruissen, Yan Liu, Ryan E. Rhodes, Colin M. Wierts, Katrina J. Waldhauser, Samantha M. Harden, Eli Puterman

Bibliographic record

VenueJournal of Medical Internet Research · 2021
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsUniversity of VictoriaUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsRandomized controlled trialMental healthMedicinePandemicFlourishingDepression (economics)GerontologyIntervention (counseling)PsychosocialPsychological interventionPhysical therapyPsychologyPsychiatryCoronavirus disease 2019 (COVID-19)

Abstract

fetched live from OpenAlex

Background In response to the COVID-19 pandemic, experts in mental health science emphasized the importance of developing and evaluating approaches to support and maintain the mental health of older adults. Objective The aim of this study was to assess whether a group-based exercise program relative to a personal exercise program (both delivered online) and waitlist control (WLC) can improve the psychological health of previously low active older adults during the early stages of the COVID-19 pandemic. Methods The Seniors COVID-19 Pandemic and Exercise (SCOPE) trial was a 3-arm, parallel randomized controlled trial conducted between May and September 2020 in which low active older adults (aged ≥65 years) were recruited via media outlets and social media. After baseline assessments, consented participants were randomized to one of two 12-week exercise programs (delivered online by older adult instructors) or a WLC condition. A total of 241 older adults (n=187 women) provided baseline measures (via online questionnaires), were randomized (ngroup=80, npersonal=82, ncontrol=79), and completed measures every 2 weeks for the duration of the trial. The trial’s primary outcome was psychological flourishing. Secondary outcomes included global measures of mental and physical health, life satisfaction, and depression symptoms. Results The results of latent growth modeling revealed no intervention effects for flourishing, life satisfaction, or depression symptoms (P>.05 for all). Participants in the group condition displayed improved mental health relative to WLC participants over the first 10 weeks (effect size [ES]=0.288-0.601), and although the week 12 effect (ES=0.375) was in the same direction the difference was not statistically significant (P=.089). Participants in the personal condition displayed improved mental health, when compared with WLC participants, in the same medium ES range (ES=0.293-0.565) over the first 8 weeks, and while the effects were of a similar magnitude at weeks 10 (ES=0.455, P=.069) and 12 (ES=0.258, P=.353), they were not statistically significant. In addition, participants in the group condition displayed improvements in physical health when compared with the WLC (ES=0.079-0.496) across all 12 weeks of the study following baseline. No differences were observed between the personal exercise condition and WLC for physical health (slope P=.271). Conclusions There were no intervention effects for the trial’s primary outcome (ie, psychological flourishing). It is possible that the high levels of psychological flourishing at baseline may have limited the extent to which those indicators could continue to improve further through intervention (ie, potential ceiling effects). However, the intervention effects for mental and physical health point to the potential capacity of low-cost and scalable at-home programs to support the mental and physical health of previously inactive adults in the COVID-19 pandemic. Trial Registration ClinicalTrials.gov NCT04412343; https://clinicaltrials.gov/ct2/show/NCT04412343

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)0.016
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.107
GPT teacher head0.502
Teacher spread0.395 · 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 designRandomized trial
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

Citations63
Published2021
Admission routes2
Has abstractyes

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