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Infiltraciones de alcohol etílico en el tratamiento del neuroma de Morton

2008· article· en· W17349494 on OpenAlexaboutno aff
Joaquín Mir Gil, Alejandro Pérez Sanmartín, Antonio Córdoba Fernández, Luis Luque de la Jara, Flor del Alba Delgado García

Bibliographic record

VenueRevista Española de Podología · 2008
Typearticle
Languageen
FieldMedicine
TopicPeripheral Nerve Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesMedicinePhilosophy

Abstract

fetched live from OpenAlex

The overall purpose of this study was to evaluate the effectiveness of a psychosocial supportive intervention called the "Living with Hope Program" (LWHP) in increasing hope and quality of life for older adult, community-living, terminally ill cancer patients. Using a mixed method concurrent nested experimental design, 60 terminally ill cancer patients over the age of 60 years were randomly assigned to a treatment group and a control group. Baseline hope (Herth Hope Index [HHI]) and quality-of-life scores (McGill Quality of Life Questionnaire [MQOL]) were collected at the first visit in the patients' homes by trained research assistants. Those in the treatment group received the LWHP, which consisted of viewing an international award-winning video on hope and a choice of one of three hope activities to work on over a one-week period. The control group received standard care. Hope and quality-of-life data were collected one week later from both groups. Qualitative data using open-ended hope questions were collected from the treatment group. Patients receiving the LWHP had statistically significant higher hope (U=255, P=0.005) and quality-of-life scores at Visit 2 (U=294.5, P=0.027) than those in the control group. Qualitative data confirmed this finding, with the majority (61.5%) of patients in the treatment group reporting the LWHP increased their hope. This preliminary evaluation of the effectiveness of the LWHP suggests that it may increase hope and quality of life for older terminally ill cancer patients at home.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.213
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.040
GPT teacher head0.335
Teacher spread0.296 · 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 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

Citations1
Published2008
Admission routes1
Has abstractyes

Explore more

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