Exploring Young People’s Perceptions of the Effectiveness of Text-Based Online Counseling: Mixed Methods Pilot Study
Bibliographic record
Abstract
BACKGROUND: Young people aged 10-24 years are at the highest risk for mental health problems and are the least likely to seek professional treatment. Owing to this population's high consumption of internet content, electronic mental (e-mental) health services have increased globally, with an aim to address barriers to treatment. Many of these services use text-based online counseling (TBOC), which shows promising results in supporting young people but also greater variance in outcomes compared with adult comparators. OBJECTIVE: This pilot study qualitatively explored the characteristics of users aged 15-25 years accessing TBOC services, their motivations for access, and their perceptions about factors believed to influence the effectiveness of these modalities. METHODS: E-surveys were administered naturalistically to 100 young service users aged 15-25 years who accessed webchat and email counseling services via an Australian e-mental health service. Thematic analysis of qualitative themes and quantitative descriptive and proportional data presented in electronic surveys were examined across the areas of user characteristics, motivations for selecting TBOC modalities, and their perceptions of TBOC effectiveness. RESULTS: Participants were predominately female high school students of Caucasian or European descent from middle socioeconomic status, living with their parents in major cities. Four domains and various themes and subthemes were related to participants' reasons for accessing TBOC and perceptions of its effectiveness: user characteristics (ie, physical and mental health syndrome and perceived social difficulties), selection factors (ie, safety, avoidance motivation, accessibility, and expectation), factors perceived to increase effectiveness (ie, general therapeutic benefits, positive modality and service factors, and persisting with counseling to increase benefit), and factors perceived to decrease effectiveness (ie, negative modality and service factors, and persisting with counseling despite benefit). CONCLUSIONS: Participants were motivated to use TBOC to increase their sense of safety in response to negative perceptions of their social skills and the response of the online counsellor to their presenting problem. By using TBOC services, they also sought to improve their access to mental health services that better met their expectations. Factors that increased effectiveness of TBOC were the counsellor's interpersonal skills, use of text-based communication, and persisting with beneficial counseling sessions. Factors that reduced TBOC effectiveness were poor timeliness in response to service requests, experiencing no change in their presenting problem, not knowing what postcounseling action to take, and persisting with ineffective counseling sessions.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".