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Record W4405360001 · doi:10.2196/64437

Mitochondrial Fitness Science Communication for Aging Adults: Prospective Formative Pilot Study

2024· article· en· W4405360001 on OpenAlexvenueno aff
Cathy A. Maxwell, Brandon Grubbs, Mary S. Dietrich, Jeffrey T. Boon, John Dunavan, Kelly Knickerbocker, Maulik Patel

Bibliographic record

VenueJMIR Formative Research · 2024
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsnot available
FundersVanderbilt University
KeywordsSummative assessmentFormative assessmentGerontologyIntervention (counseling)HelpfulnessLikert scaleMedicinePsychologyPhysical therapyDevelopmental psychologyNursing

Abstract

fetched live from OpenAlex

BACKGROUND: A key driver that leads to age-associated decline and chronic disease is mitochondrial dysfunction. Our previous work revealed strong community interest in the concept of mitochondrial fitness, which led to the development of a video-based science communication intervention to prompt behavior change in adults aged 50 years and older. OBJECTIVE: This study aimed to conduct formative and summative evaluations of MitoFit, an instructional, biologically based communication intervention aimed at improving physical activity in older adults aged 50 years and older. METHODS: In the phase-1 formative evaluation, community-dwelling older adults (N=101) rated the acceptability, appropriateness, and helpfulness of our MitoFit video series, titled "How to Slow Down Aging Through Mitochondrial Fitness." In the phase-2 summative evaluation, a subgroup of phase-1 participants (n=19) participated in a 1-month MitoFit intervention prototype to evaluate the intervention and data collection feasibility. RESULTS: In phase 1, participants (mean age 67.8, SD 8.9 y; 75/100, 75% female) rated the MitoFit videos as acceptable (≥4 out of 5 on a Likert-scale survey; from 97/101, 96% to 100/101, 99%), appropriate (101/101, 100%), and helpful (from 95/101, 94% to 100/101, 99%) to support adaptation and continued work on our novel approach. Previous knowledge of mitochondria ranged from 52% (50/97; What are mitochondria?) to 80% (78/97; What are the primary functions of mitochondria?). In phase 2, participants (mean age 71.4, SD 7.9 y; 13/19, 72% female) scored better than the national average (50) on the Patient-Reported Outcomes Measurement Information System-19 for physical function (57), social activities (55.5), depression (41), fatigue (48.6), and sleep disturbance (49.6) but worse for anxiety (55.3) and pain interference (52.4). Additionally, 95% (18/19) of participants demonstrated MitoFit competencies within 2 attempts (obtaining pulse: 19/19, 100%; calculating maximum and zone 2 heart rate: 18/19, 95%; and demonstration of exercises: 19/19, 100%). At 1 month after instruction, 68% (13/19) had completed a self-initiated daily walking/exercise plan and submitted a daily activity log. A walking pulse was documented by 85% (11/13) of participants. The time needed to walk 1 mile ranged from 17.4 to 27.1 minutes. The number of miles walked in 1 month was documented by 62% (8/13) of participants and ranged from 10 miles to 31 miles. The number of days of strength training ranged from 2 to 31 days/month. Intervention feasibility scores ranged from 89% (17/19; seems easy to follow) to 95% (18/19; seems implementable, possible, and doable). Overall, 79% (15/19) stated an intention to continue the MitoFit intervention. Furthermore, 4 weeks after delivery of the prototype intervention, the percentage of participants doing aerobic activity for regular moderate activity increased from 35% (6/17) to 59% (10/17; P=.03). CONCLUSIONS: MitoFit was enthusiastically embraced and is a cost-effective, scalable, and potentially efficacious intervention to advance with community-dwelling older adults.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.031
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.166

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0310.027
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0020.003
Open science0.0020.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.070
GPT teacher head0.450
Teacher spread0.380 · 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 source (direct Gemma or distilled Codex), 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".

Quick stats

Citations3
Published2024
Admission routes1
Has abstractyes

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