Miedo a caer. El taijiquan como forma de terapia de exposición gradual en vivo
Bibliographic record
Abstract
<p class="MsoNormal" style="text-align: justify; margin: 0cm 0cm 6pt;"><span style="mso-ansi-language: EN-US;" lang="EN-US"><span style="font-size: small;"><span style="font-family: Calibri;">Falls in the elderly can cause injuries that lead to loss of independence. Loss of postural sway, balance, and slower reaction times are strong predictors of falling (Lajoie &amp; Gallagher, 2004). Traditional exercise programs focus on studying and treating these factors (Tideiksaar, 1997); however, fear of falling – another strong predictor of falls – has received relatively little attention in the treatment literature (Maki et al., 1991). There are indications of a direct link between fear of falling, and actual falls (Myers et al., 1996), and a relationship between fear-related avoidance of activities and falling (Delbaere et al., 2004). Taijiquan, an ancient Chinese martial art turned exercise regimen (Wolf et al., 2001), has been shown to be effective ameliorating fear of falling and traditional antecedents of falling (Tsang et al., 2004). Like graded exposure therapies, Taijiquan practitioners slowly and progressively achieve increasingly difficult postures that simulate potentially fearful situations in a calming environment. Relative to other exercise treatments, such as computerized balance training, education, and graded exercise, Taijiquan has produced significant reductions in fear of falling and in actual falls (McGibbon et al., 2005). Herein the available research on Taijiquan and falls is reviewed to advocate for Taijiquan as a form of graded exposure therapy to reduce fear of falling and falls in seniors. Implications and future research directions will be discussed.</span></span></span></p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".