Negative effects associated with internet-delivered cognitive behaviour therapy: An analysis of client emails
Bibliographic record
Abstract
Internet-delivered cognitive behaviour therapy (ICBT) is an efficacious form of treatment for anxiety and depression, yet it is still possible for clients to experience negative effects associated with treatment. In the ICBT literature, the term negative effects is broadly used to refer to all potentially adverse or unwanted events or experiences that are perceived as undesirable by the client and may or may not be associated with long-term symptoms or distress. Previous ICBT studies have asked clients to retrospectively describe negative effects at post-treatment; however, no research has examined the content of clients' emails to their therapist to see whether clients are reporting negative effects as they arise. In the current study, 96 clients (80 completers; 16 non-completers) were randomly selected from a published ICBT trial and directed content analysis was used to examine client emails for mention of negative effects. In addition, correlational analyses were used to examine the relationship between negative effects and: 1) demographic characteristics; 2) treatment engagement; 3) treatment satisfaction; 4) working alliance; and 5) symptom outcomes among completers. The results indicated that 61.5% of clients experienced at least one negative effect during treatment, although total number of negative effects was not significantly correlated with client demographic characteristics, lessons completed, working alliance, treatment satisfaction, or symptom outcomes. Among completers, technical difficulties, implementation problems, and negative emotional states were the most commonly reported negative effects, whereas dropout was the most commonly reported negative effect by non-completers. Negative effects that have been identified in previous research, such as symptom deterioration, novel symptoms, and severe adverse events, were not identified in client emails. The high incidence of negative effects in the current study suggests there may be value in systematically monitoring client emails for negative effects throughout treatment as a supplement to retrospective post-treatment reports. This will give therapists the opportunity to intervene as negative effects occur and potentially mitigate any impact they have on treatment outcomes. Future research, both qualitative and quantitative, is needed to gain a more nuanced understanding of negative effects associated with ICBT.
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 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 | 0.002 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".