A Mixed-Methods Study Using a Nonclinical Sample to Measure Feasibility of Ostrich Community: A Web-Based Cognitive Behavioral Therapy Program for Individuals With Debt and Associated Stress
Bibliographic record
Abstract
BACKGROUND: There are increasing concerns about the health and well-being of individuals facing financial troubles. For instance, in the United Kingdom, the relationship between debt and mental health difficulties is becoming more evident due to the economic downturn and welfare reform. Access to debt counseling services is limited and individuals may be reluctant to access services due to stigma. In addition, most of these services may not be appropriately resourced to address the psychological impact of debt. This study describes outcomes from an Internet-based cognitive behavioral therapy (ICBT) program, Ostrich Community (OC), which was developed to provide support to those struggling with debt and associated psychological distress. OBJECTIVE: The aim of this feasibility study was to assess the suitability and acceptability of the OC program in a nonclinical sample and examine mental health and well-being outcomes from using the program. METHODS: A total of 15 participants (who were not suffering from severe financial difficulty) were assisted in working through the 8-week ICBT program. Participants rated usability and satisfaction with the program, and after completion 7 participants took part in a semistructured interview to provide further feedback. Before the first session and after the final session all participants completed questionnaires to measure well-being and levels of depression, stress, and anxiety and pre- and postscores were compared. RESULTS: Satisfaction was high and themes emerging from the interviews indicate that the program has the potential to promote effective financial behaviors and improve financial and global psychosocial well-being. When postcompletion scores were compared with those taken before the program, significant improvements were identified on psychometric measures of well-being, stress, and anxiety. CONCLUSIONS: The OC program is the first ICBT program that targets poor mental health associated with financial difficulty. This feasibility study indicates that OC may be an effective intervention for increasing financial resilience, supporting individuals to become financially independent, and promoting positive financial and global well-being. Further work with individuals suffering from debt and associated emotional difficulties will help to examine clinical effectiveness more closely.
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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 | 0.010 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".