Goals in motion: exploring goal setting among adults living with HIV who participated in an online community-based exercise intervention
Bibliographic record
Abstract
Introduction Adults living with HIV may experience various health-related challenges in life. Exercise has been shown to provide numerous benefits. However, the specific goals that individuals aim to achieve through exercise are not well-documented. Our aim was to explore goal setting among adults living with HIV who participated in an online community-based exercise (CBE) intervention. Methods We conducted a multi-method, longitudinal study using data from a 12-month online CBE intervention study involving 6-month intervention and follow-up phases. Goal Attainment Scaling was used to quantify the number and types of goals set and achieved at each phase. We analyzed interview data with a subsample to identify experiences with and factors influencing goal setting. Results Thirty-two participants initiated the intervention and were included in analyses. The majority were men (69%); median age of 53 years. Participants articulated a median of four goals before and after the intervention, most commonly related to increasing muscle, reducing weight, and improving strength. Approximately 50% of goals were achieved at the end of intervention and follow-up phases. Interview data (n = 10) indicated goal setting was influenced by personal health concerns, family, and perceived obligations to research. Most found goal setting personal and helpful, while some experienced challenges. Conclusions Adults living with HIV prioritized physical-health-related goals during an online CBE intervention, with diverse experiences influencing their goal-setting process. Findings may inform the design and evaluation of online exercise programs for adults living with HIV. Clinical Trial Registration identifier (NCT05006391).
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".