The Definition and Function of Interview Structure in Psychiatric and Psychotherapeutic Interviews
Bibliographic record
Abstract
The concept of interview structure has been discussed in the psychodynamic, psychiatric, and psychodiagnostic testing literature as a factor which affects the form and depth of an informant's responses. However, the specific characteristics and clinical implications of structure have not been studied nor measured systematically. We define interview structure as a function of the degree to which the interviewer controls, directs, and shapes the verbal interchange between the two protagonists. This involves regulating the length, focus, and depth of the interviewee's discourse as well as imposing limits and direction through the interviewer's questions and interventions. Based on a review of the literature on interviewing in psychiatric, psychological, and other social sciences, we propose seven quantitative measures that operationalize aspects of the concept of interview structure. Measures 1 through 5 relate to quantity of speech and yield percentages and averages allowing one to compare speech production between subject and interviewer. Measure 6 reflects the way the interviewer shapes his interventions that are formulated as declarative demands or questions, as open, semi-open, or closed-ended. Measure 7 is the percentage of non-lexical or brief utterances from the interviewer that serve as mild reinforcing acknowledgements, such as "mm-hmm" or "I see." In a companion article, we examine how these measures converge with another construct of structure and discriminate five different types of psychiatric and psychotherapeutic interviews in common use.
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 | 0.134 | 0.252 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.004 | 0.027 |
| Scholarly communication | 0.006 | 0.011 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.003 | 0.003 |
| 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".