The effects of an autonomy-supportive computerized training intervention on exercise motivation, enjoyment, strength gains and adherence in older adults
Bibliographic record
Abstract
Objective: To investigate whether modified exercise protocols, using programmable cards to increase or decrease participant autonomy, will result in differences in motivation levels. It was predicted that participants who were able to make choices in their training program were more intrinsically motivated and report greater autonomy than participants who were not able to make choices. Design: Six week randomized controlled trial Method: Participants (N=30) were recruited from a cardiac rehabilitation or a senior wellness exercise program. Participants were randomly allocated to one of three conditions, where participants either have a choice or no choice in increasing their load: choice (n=10), no choice (n=10) and control (n=10). The Behavioral Regulation in Exercise Questionnaire, the Psychological Need Satisfaction in Exercise Questionnaire and the Physical Activity Enjoyment Scale were collected pre- and post-intervention. An ANCOVA analysis was used to determine the effects of autonomy on motivation. Results: Participants in the no choice group felt less autonomy (M=4.78±0.22) than the participants in the choice group (M=5.67±0.22, p<0.05). Significant differences were also noted in competence levels, where individuals in the choice group felt more competent (M=5.37±0.18) compared to the no choice group (M=4.81±0.18, p<0.05). The no choice group (M=33.54±1.12, M=40.86±1.16, M=15.61±1.06) had significant increases in absolute strength gains compared to the choice (M=28.91±1.04, M=37.31±1.16, M=10.34±1.07) and control groups (M=26.55±1.22, M=35.42±1.30, M=9.69±1.19) at p<0.05 for core, lower and upper body exercises respectively. The control group had the lowest exercise adherence levels (M=0.791±0.05) compared to the choice group (M=0.935±0.04, p<0.05). There were no significant differences between the groups for intrinsic motivation levels. Conclusions: Giving participants a choice leads to greater autonomy and competence than no choice. The results provide a foundation to increase physical activity adherence in the aging population by using computerized mechanisms that provide exercisers with the choice to increase their exercise load.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".