An mHealth Intervention for Persons with Diabetes Type 2 Based on Acceptance and Commitment Therapy Principles: Examining Treatment Fidelity
Bibliographic record
Abstract
BACKGROUND: Web-based interventions are becoming an alternative of treatment aimed to support behavioral changes and several advantages over traditional treatments are reported. New ways of delivering an intervention may result in new challenges regarding monitoring of treatment fidelity (TF) which is essential to ensure internal and external validity. Despite the importance of the theme, only a few studies in this field are reported. OBJECTIVE: To examine TF of a mobile phone delivered intervention based on Acceptance and Commitment Therapy (ACT) with electronic diaries and written situational feedback for persons with diabetes mellitus type 2, the recommendations from the Behavior Change Consortium (BCC) established by The National Institutes of Health (NHI) were applied. To analyze fidelity, they recommend 5 areas to be investigated (1) design of the study, (2) provider training, (3) delivery of treatment, (4) receipt of treatment, and (5) enactment of treatment. In the current study, these areas were examined based on the analysis of therapists' adherence to the treatment protocol and participants' and therapists' experience with the intervention. METHODS: To investigate the therapists' adherence to the treatment protocol, a total of 251 written feedback text messages were divided into text segments. Qualitative thematic analyses were then performed to examine how ACT and other therapeutic processes were used in the feedback by the therapists. For the therapists' and participants' experience analysis, participants answered a self-reported questionnaire and participated in 2 interviews. The therapists continuously reported their experiences to the researcher responsible for the project. RESULTS: The results show high adherence to the TF strategies 20/21 (95%) applicable items of the fidelity checklist recommended by NHI BCC were identified in the present study. Measured provider skill acquisition post-training was the only item absent in the fidelity checklist. The results also show high therapists' adherence to the treatment protocol. All ACT processes (values, committed action, acceptance, contact with the present moment, self as context and cognitive defusion) were found in the coded text segments of the feedback in addition to communication and motivation strategies. For 336/730 (46%) of total possible text segments coded independently by 2 researchers, the interrater reliability measured by Cohen's kappa was .85. The evaluation of participants' and therapists' experience with the intervention was generally positive. CONCLUSIONS: Based on the analyses of therapists' adherence to the treatment protocol grounded by ACT-principles and participants' and therapists' experience with the intervention, the 5 areas of TF recommended by NHI BCC were analyzed indicating a high level of TF. These results ensure an appropriate level of internal and external validity of the study and reliable intervention results and facilitate a precise replication of this intervention concept. Web-based psychological interventions to support people with chronic conditions are becoming increasingly more common. This study supports the results from a previous study which indicated that ACT could be reliably delivered in a written web-based format. TRIAL REGISTRATION: ClinicalTrials.gov NCT01297049; https://clinicaltrials.gov/ct2/show/NCT01297049 (Archived by WebCite at http://www.webcitation.org/70WC4Cm4T).
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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 | 0.016 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".