Counselling and psychotherapy services in more developed and developing regions in China: A comparative investigation of practitioners and current service delivery
Bibliographic record
Abstract
BACKGROUND: Counselling and psychotherapy services have taken off with uneven speed across China since the 1980s after several years of stagnation. Researchers have attributed socioeconomic development (or the lack thereof) and regional differences as main barriers to the development in this field. However, little is known today about the status of counselling and psychotherapy services across China. AIMS: To investigate and compare the current situation of practitioners and service delivery of counselling and psychotherapy in more developed and developing regions across China. METHOD: Convenience sampling methods from counselling and psychological services organizations in 29 Chinese provinces, municipalities or autonomous regions were used to recruit 1,543 participants to take part in the investigation by completing a 93-item self-designed questionnaire. RESULTS: Organizations in developing and more developed regions in China varied in their current practices and employment situation of their practitioners, and in the quality of service delivery. However, counselling and psychotherapy offered at universities in both types of regions are of similar quality. CONCLUSION: In China, the level of socioeconomic development significantly influences the development of professional counselling and psychotherapy services. Important progress is evident in the field; however, the lack of systematic training and the scarcity of professional practitioners remain a challenge.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".