Knowledge, attitudes, and barriers of dietitians toward screening patients for food insecurity
Bibliographic record
Abstract
Abstract Background Global food insecurity (FI) prevalence in 2020 was 30.4%. In Israel, in 2021, it was 16.2%. FI is associated with a high prevalence of chronic diseases, more hospital admissions and visits, and a shorter lifespan. Screening for FI in the health setting is less common, despite recommendations. Methods Between July 2022 - February 2023, a mixed-methods study distributed an online survey and a request for qualitative interviews among a convenience sample of registered dietitians (RDs). The survey obtained sociodemographic characteristics and information on work experience, knowledge, attitudes, and barriers toward screening for FI. Sixty-one questions were modified from existing questionnaires. An expert committee reviewed the questions. Later, the questionnaire was pilot-tested by ten RDs and amended according to their comments on the clarity. Results Overall, 140 RDs were surveyed, and 7 RDs were interviewed. 96.7% of the participants were female, with a mean of 13.36±9.9 years of experience. 97% of RDs didn't screen for FI. 65.5% didn't know the percentage of households living with FI in Israel, and 72.1% of RDs didn't know where to refer food-insecure patients for additional assistance. Positive attitudes toward screening and treating FI were documented. About 80% of RDs indicated that FI is relevant to their patients and are willing to screen for FI. Religious and traditional RDs had 10.08 times and 4.46 times, respectively, greater odds of having positive attitudes toward screening and treating food-insecure patients. The main barriers identified were a lack of time, knowledge of screening tools, and missing information on appropriate treatment and referral. Conclusions Further education and training in screening FI should be implemented among RDs. System barriers should be addressed to allow RDs routine screening for FI. Additional research is needed to explore healthcare providers’ attitudes and barriers toward screening and treating FI. Key messages • Most registered dietitians had a low level of knowledge and did not screen routinely for food insecurity. • The majority were positive towards screening, highlighting system and training barriers.
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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 | 0.011 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".