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Record W3120594701 · doi:10.2196/24807

A Self-Help App for Syrian Refugees With Posttraumatic Stress (Sanadak): Randomized Controlled Trial

2021· article· en· W3120594701 on OpenAlexvenueno aff
Susanne Röhr, Franziska Jung, Alexander Pabst, Thomas Grochtdreis, Judith Dams, Michaela Nagl, Anna Renner, Rahel Hoffmann, Hans‐Helmut König, Anette Kersting, Steffi G. Riedel‐Heller

Bibliographic record

VenueJMIR mhealth and uhealth · 2021
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsRandomized controlled trialMedicinePosttraumatic stressClinical psychologyPsychologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Syrian refugees residing in Germany often develop posttraumatic stress as a result of the Syrian civil war, their escape, and postmigration stressors. At the same time, there is a lack of adequate treatment options. The smartphone-based app Sanadak was developed to provide cognitive behavioral therapy-based self-help in the Arabic language for Syrian refugees with posttraumatic stress. OBJECTIVE: The aim of this study was to evaluate the effectiveness and cost-effectiveness of the app. METHODS: In a randomized controlled trial, eligible individuals were randomly allocated to the intervention group (IG; app use) or control group (CG; psychoeducational reading material). Data were collected during structured face-to-face interviews at 3 assessments (preintervention/baseline, postintervention/after 4 weeks, follow-up/after 4 months). Using adjusted mixed-effects linear regression models, changes in posttraumatic stress and secondary outcomes were investigated as intention-to-treat (ITT) and per-protocol (PP) analysis. Cost-effectiveness was evaluated based on adjusted mean total costs, quality-adjusted life years (QALYs), and cost-effectiveness acceptability curves using the net benefit approach. RESULTS: Of 170 screened individuals (aged 18 to 65 years), 133 were eligible and randomized to the IG (n=65) and CG (n=68). Although there was a pre-post reduction in posttraumatic stress, ITT showed no significant differences between the IG and CG after 4 weeks (Posttraumatic Diagnostic Scale for DSM-5, Diff -0.90, 95% CI -0.24 to 0.47; P=.52) and after 4 months (Diff -0.39, 95% CI -3.24 to 2.46; P=.79). The same was true for PP. Regarding secondary outcomes, ITT indicated a treatment effect for self-stigma: after 4 weeks (Self-Stigma of Mental Illness Scale/SSMIS-stereotype agreement: d=0.86, 95% CI 0.46 to 1.25; stereotype application: d=0.60, 95% CI 0.22 to 0.99) and after 4 months (d=0.52, 95% CI 0.12 to 0.92; d=0.50, 95% CI 0.10 to 0.90), the IG showed significantly lower values in self-stigma than the CG. ITT showed no significant group differences in total costs and QALYs. The probability of cost-effectiveness was 81% for a willingness-to-pay of €0 per additional QALY but decreased with increasing willingness-to-pay. CONCLUSIONS: Sanadak was not more effective in reducing mild to moderate posttraumatic stress in Syrian refugees than the control condition nor was it likely to be cost-effective. Therefore, Sanadak is not suitable as a standalone treatment. However, as the app usability was very good, no harms detected, and stigma significantly reduced, Sanadak has potential as a bridging aid within a stepped and collaborative care approach. TRIAL REGISTRATION: German Clinical Trials Register DRKS00013782; https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00013782. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1186/s12888-019-2110-y.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.039
GPT teacher head0.413
Teacher spread0.375 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designRandomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations89
Published2021
Admission routes1
Has abstractyes

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