Electronic Health Interventions for Preventing and Treating Negative Psychological Sequelae Resulting From Pediatric Medical Conditions: Systematic Review
Bibliographic record
Abstract
BACKGROUND: Pediatric medical conditions have the potential to result in challenging psychological symptoms (eg, anxiety, depression, and posttraumatic stress symptoms [PTSS]) and impaired health-related quality of life in youth. Thus, effective and accessible interventions are needed to prevent and treat psychological sequelae associated with pediatric medical conditions. Electronic health (eHealth) interventions may help to meet this need, with the capacity to reach more children and families than in-person interventions. Many of these interventions are in their infancy, and we do not yet know what key components contribute to successful eHealth interventions. OBJECTIVE: The primary objective of this study was to conduct a systematic review to summarize current evidence on the efficacy of eHealth interventions designed to prevent or treat psychological sequelae in youth with medical conditions. METHODS: MEDLINE (PubMed) and PsycINFO databases were searched for studies published between January 1, 1998, and March 1, 2019, using predefined search terms. A total of 2 authors independently reviewed titles and abstracts of search results to determine which studies were eligible for full-text review. Reference lists of studies meeting eligibility criteria were reviewed. If the title of a reference suggested that it might be relevant for this review, the full manuscript was reviewed for inclusion. Inclusion criteria required that eligible studies (1) had conducted empirical research on the efficacy of a Web-based intervention for youth with a medical condition, (2) had included a randomized trial as part of the study method, (3) had assessed the outcomes of psychological sequelae (ie, PTSS, anxiety, depression, internalizing symptoms, or quality of life) in youth (aged 0-18 years), their caregivers, or both, (4) had included assessments at 2 or more time points, and (5) were available in English language. RESULTS: A total of 1512 studies were reviewed for inclusion based on their title and abstracts; 39 articles qualified for full-text review. Moreover, 22 studies met inclusion criteria for the systematic review. Of the 22 included studies, 13 reported results indicating that eHealth interventions significantly improved at least one component of psychological sequelae in participants. Common characteristics among interventions that showed an effect included content on problem solving, education, communication, and behavior management. Studies most commonly reported on child and caregiver depression, followed by child PTSS and caregiver anxiety. CONCLUSIONS: Previous research is mixed but suggests that eHealth interventions may be helpful in alleviating or preventing problematic psychological sequelae in youth with medical conditions and their caregivers. Additional research is needed to advance understanding of the most powerful intervention components and to determine when and how to best disseminate eHealth interventions, with the goal of extending the current reach of psychological interventions.
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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 | 0.008 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".