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Osteoporosis knowledge, health beliefs, and healthy bone behaviours in patients on androgen‐deprivation therapy ( <scp>ADT</scp> ) for prostate cancer

2013· article· en· W1606253719 on OpenAlexaff
Michelle B. Nadler, Shabbir M.H. Alibhai, Pamela Catton, Charles Catton, Matthew J. To, Jennifer M. Jones

Bibliographic record

VenueBritish Journal of Urology · 2013
Typearticle
Languageen
FieldMedicine
TopicBone health and treatments
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsAndrogen deprivation therapyMedicineProstate cancerOsteoporosisPopulationVitamin D and neurologyPhysical therapyInternal medicineGerontologyCancerEnvironmental health

Abstract

fetched live from OpenAlex

What's known on the subject? and What does the study add? There is an increase in use and duration of androgen‐deprivation therapy ( ADT ) in patients with prostate cancer. ADT can cause decreased bone mineral density and lean muscle loss, putting these patients at increased risk of fracture. Guidelines exist for the prevention and management of bone loss in this population; however, data suggests that most patients are not receiving proper screening, evaluation, or treatment for bone loss. Research to date suggests that patients on ADT are unaware of the risks and side‐effects of ADT and that most are not engaging in important preventative behaviours, e.g. calcium and vitamin D intake. To our knowledge, there are no studies in patients on ADT specifically assessing patients' osteoporosis ( OP ) knowledge, self‐efficacy, and feelings of susceptibility towards OP and their relationships to engagement in recommended healthy bone behaviours. We think that these data will aid in the development of health promotion uptake strategies that are directly targeted to this patient population. Objectives To describe in patients with prostate cancer, receiving androgen‐deprivation therapy ( ADT ): (i) knowledge, self‐efficacy ( SE ), and health beliefs about osteoporosis ( OP ); (ii) current engagement in healthy bone behaviours ( HBBs ). To explore the relationships between knowledge, SE , and health beliefs, and engagement in HBBs . Patients and Methods 175 patients receiving ADT by injection completed questionnaires assessing current HBBs , OP knowledge, SE , and health beliefs (motivation, perceived susceptibility, and seriousness). Descriptive statistics and independent samples t ‐tests were used to assess relationships between knowledge, SE , health beliefs, and engagement in HBBs . Results Only 38% of patients had undergone a dual X ‐ray absorptiometry scan in the past 2 years. OP knowledge was low (mean [ sd , range] 9.6 [4.4, 0–19]) and perceived SE moderate (84.7 [24.5, 0–120]). Health motivation was fairly high (23.6 [3.1, 6–30]), but perceived susceptibility (16.8 [4.3]) and seriousness (16.8 [4.2]) of OP were low. Few patients met the recommendations for vitamin D intake (42%) and exercise (31%), and 15% were at risk of over‐supplementation of calcium. Patients taking calcium supplements ( P = 0.04), and meeting guidelines for vitamin D ( P = 0.008) and for exercise ( P = 0.002) had significantly greater knowledge than those who did not. Patients who were engaging in less than four of five HBBs had lower knowledge ( P < 0.001) and health motivation ( P = 0.01) than those who were engaging in four or all five HBBs . Conclusions Most patients who are receiving ADT are not receiving appropriate screening, lack basic information about bone health, and are not engaging in the appropriate HBBs

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)0.001
metaresearch head score (Gemma)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.300
Teacher spread0.283 · 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".

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Citations37
Published2013
Admission routes1
Has abstractyes

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