Smartphone Apps for Mindfulness Interventions for Suicidality in Asian Youths: Literature Review
Bibliographic record
Abstract
BACKGROUND: The advent of mobile technology has ushered in an era in which smartphone apps can be used as interventions for suicidality. OBJECTIVE: We aimed to review recent research that is relevant to smartphone apps that can be used for mindfulness interventions for suicidality in Asian youths. METHODS: The inclusion criteria for this review were: papers published in peer-reviewed journals from 2007 to 2017 with usage of search terms (namely "smartphone application" and "mindfulness") and screened by an experienced Asian clinician to be of clinical utility for mindfulness interventions for suicidality with Asian youths. RESULTS: The initial search of databases yielded 375 results. Fourteen full text papers that fit the inclusion criteria were assessed for eligibility and 10 papers were included in the current review. CONCLUSIONS: This review highlighted the paucity of evidence-based and empirically validated research into effective smartphone apps that can be used for mindfulness interventions for suicidality with Asian youths.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".