Evaluation of the Effectiveness of a Musical Cognitive Restructuring App for Black Inner-City Girls: Survey, Usage, and Focus Group Evaluation
Bibliographic record
Abstract
BACKGROUND: Research on mobile health (mHealth) app use during adolescence is growing; however, little attention has been paid to black adolescents, particularly black girls, who are generally underresearched and underserved in psychological intervention research. Cognitive restructuring is an important tool in anxiety and fear management and involves two parts: (1) recognizing and deconstructing erroneous thoughts and (2) replacing negative anxiety and stress-provoking thoughts with positive thoughts. In our work with black adolescent females, we found that cognitive restructuring is a difficult skill to practice on one's own. Thus, drawing upon the importance of music in the black community, we developed the Build Your Own Theme Song (BYOTS) app to deliver a musical form of the technique to middle-school black girls. OBJECTIVE: Our aim in this mixed methods study is to evaluate the effectiveness of the BYOTS app. We hypothesize that participants will expect the app to be effective in reducing negative thoughts and that the app will meet their expectations and data generated from the app will demonstrate a reduction in negative thinking and anxiety. METHODS: A total of 72 black or biracial seventh- and eighth-grade adolescent females were enrolled in Sisters United Now (SUN), an eight-session culturally infused and app-augmented stress and anxiety sister circle intervention. Before using the BYOTS app, girls completed the Multidimensional Anxiety Scale for Children 2 and the App Expectations Survey. Usage data collected from the app included an assessment of negative thinking before and after listening to their song. After completion of the intervention, focus groups were held to gather qualitative data on participants' app experience. RESULTS: =2.82, P=.004). Four effectiveness themes emerged from the focus groups: difference in behavior and temperament, promoted calmness, helpfulness in stressful home situations, and focused thinking via the SUN theme song. CONCLUSIONS: The BYOTS app is a useful tool for delivering musical cognitive restructuring to reduce negative thinking and anxiety in an underserved urban population. Changes were supported both quantitatively and qualitatively. Participants, their peers, and their family noted the difference. Findings support expanding the research to black girls of various socioeconomic statuses and geographic diversity. Currently, the app augments SUN, a culturally relevant intervention. Future research will explore BYOTS as a stand-alone app.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 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) | 0.003 | 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".