Mothers’ use of blogs while engaged in family-based treatment for a child’s eating disorder.
Bibliographic record
Abstract
INTRODUCTION: We explore parents' use of blogs while engaged in family-based treatment (FBT), a form of treatment in which parents engage as the primary givers of care for a child's eating disorder. We sought to bring together emergent literature on the value of blogging for social support with a body of literature on caregiving for a child with an eating disorder and to understand how parents use blogs while engaged in FBT. METHOD: We conducted a thematic analysis of 138 blog entries written by 5 mothers. RESULTS: Two main themes emerged: the importance of support and shifts in parenting. Blogs detailed how parents actively seek to meet their needs during a difficult time using online interactions to bolster sources of support that exist offline. This intensive form of treatment also provoked shifts in parenting, which parents described on their blogs. Parents' blogs were rich with descriptions of their use of mutually reinforcing on- and offline support. DISCUSSION: The unique context of the blogs allowed for access to data that were not generated for the purpose of research. Results add to the growing body of literature about parents' caregiving experiences and use of blogs for social support, and they offer implications for using online spaces as adjunct support for families. (PsycINFO Database Record
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| 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".