The food and nutrition concerns of a sample of nonimmigrant,low-income women living with HIV
Bibliographic record
Abstract
The number of women living with poverty, HIV, and substance use is increasing in British Columbia and in Canada. Women living in poverty lack sufficient money to buy food. HIV and substance use have been shown to increase the risk for weight loss but women are also exposed to cultural weight norms that valorize thinness. Local funding is available for complementary therapies but little is known about the meanings of these therapies for women living with HIV. The purpose of this qualitative study was to explore the effect of these potentially conflicting issues on the food and nutrition concerns of a sample of low-income nonimmigrant women living with HIV and to compare their concerns to the assumptions made in a sample of food and nutrition documents. Thirteen nonimmigrant participants receiving income assistance, most of whom had a history of substance use, were recruited through an HIV clinic and an HIV support organization. Fifteen semi-structured, in-depth interviews were conducted; two of the participants were interviewed twice. Interviews were transcribed verbatim and analyzed for relevant themes. Documents were analyzed for assumptions about the reader. The participants lacked money to buy appropriate foods because income assistance was inadequate and they spent food money on drugs. Substance use negatively affected their food intakes and weights. Societal pressures to be thin, HIV concerns, and poverty were associated with positive and negative perceptions of weight and body shape changes. Through analysis of the data, different eating patterns became apparent: eating, not eating, healthy/unhealthy eating, and eating for HIV. Most of the women were striving for healthy eating when trying to eat for their HIV. Although most of the participants were using complementary therapies, they did not have a keen interest in them. Assumptions made in food and nutrition documents did not reflect the concerns of the participants. Because of the profound effects of poverty, substance use, and dominant weight norms for women on food, nutrition, and weight concerns, dietitians need to assess their clients' circumstances to provide relevant advice. To be successful, nutritional goals will have to take the clients' own priorities into account.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".