Internet-Administered Cognitive Behavioral Therapy for Common Mental Health Difficulties in Parents of Children Treated for Cancer: Intervention Development and Description Study
Bibliographic record
Abstract
BACKGROUND: Following the end of a child's treatment for cancer, parents may report psychological distress. However, there is a lack of evidence-based interventions that are tailored to the population, and psychological support needs are commonly unmet. An internet-administered low-intensity cognitive behavioral therapy (LICBT)-based intervention (EJDeR [internetbaserad självhjälp för föräldrar till barn som avslutat en behandling mot cancer]) may provide a solution. OBJECTIVE: The first objective is to provide an overview of a multimethod approach that was used to inform the development of the EJDeR intervention. The second objective is to provide a detailed description of the EJDeR intervention in accordance with the Template for Intervention Description and Replication (TIDieR) checklist. METHODS: EJDeR was developed through a multimethod approach, which included the use of existing evidence, the conceptualization of distress, participatory action research, a cross-sectional survey, and professional and public involvement. Depending on the main presenting difficulty identified during assessment, LICBT behavioral activation or worry management treatment protocols are adopted for the treatment of depression or generalized anxiety disorder when experienced individually or when comorbid. EJDeR is delivered via the Uppsala University Psychosocial Care Programme (U-CARE) portal, a web-based platform that is designed to deliver internet-administered LICBT interventions and includes secure videoconferencing. To guide parents in the use of EJDeR, weekly written messages via the portal are provided by e-therapists comprising final year psychology program students with training in cognitive behavioral therapy. RESULTS: An overview of the development process and a description of EJDeR, which was informed by the TIDieR checklist, are presented. Adaptations that were made in response to public involvement are highlighted. CONCLUSIONS: EJDeR represents a novel, guided, internet-administered LICBT intervention for supporting parents of children treated for cancer. Adopting the TIDieR checklist offers the potential to enhance fidelity to the intervention protocol and facilitate later implementation. The intervention is currently being tested in a feasibility study (the ENGAGE study). INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2018-023708.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".