Web-based Self-help Program for Adjustment Problems After an Accident (SelFIT): Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Accidents and the resulting injuries are among the world's biggest health care issues, often causing long-term effects on psychological and physical health. With regard to psychological consequences, accidents can cause a wide range of burdens including adjustment problems. Although adjustment problems are among the most frequent mental health problems, there are few specific interventions available. The newly developed program SelFIT (German acronym: Selber wieder fit nach einem Unfall; "fit again after an accident") aims to remedy this situation by offering a low-threshold, web-based self-help intervention for psychological distress after an accident. OBJECTIVE: The overall aim is to evaluate the efficacy and cost-effectiveness of the SelFIT program plus care as usual (CAU) compared to only CAU. Furthermore, the program's user-friendliness, acceptance, and adherence are assessed. We expect that the use of SelFIT will be associated with a greater reduction in psychological distress, greater improvement in mental and physical well-being, and greater cost-effectiveness compared to CAU. METHODS: Adults (n=240) experiencing adjustment problems due to an accident they had between 2 weeks and 2 years before entering the study will be randomized into either the intervention or control group. Participants in the intervention group receive direct access to SelFIT. The control group receives access to the program after 12 weeks. There are 6 measurement points for both groups (baseline as well as after 4, 8, 12, 24, and 36 weeks). The main outcome is a reduction in anxiety, depression, and stress symptoms that indicate adjustment problems. Secondary outcomes include well-being, optimism, embitterment, self-esteem, self-efficacy, emotion regulation, pain, costs of health care consumption, and productivity loss, as well as the program's adherence, acceptance, and user-friendliness. RESULTS: Recruitment began in December 2019 and will continue at least until January 2021, with the option to extend this for another 6 months until July 2021. As of July 2020, 324 people have shown interest in participating, and 48 people have given their informed consent. CONCLUSIONS: To the best of our knowledge, this is the first study examining a web-based self-help program designed to treat adjustment problems resulting from an accident. If effective, the program could complement the still limited offerings for secondary and tertiary prevention of psychological distress after an accident. TRIAL REGISTRATION: ClinicalTrials.gov NCT03785912; https://clinicaltrials.gov/ct2/show/NCT03785912. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/21200.
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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 | 0.028 | 0.022 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.014 | 0.005 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.095 | 0.014 |
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".