The Demographic Psychosocial Inventory:A New Instrument to Measure Risk Factors forAdjustment Problems Among Immigrants
Bibliographic record
Abstract
Objective-The purpose of this study was to develop and test the Demographic Psychosocial Inventory (DPSI), a self-report questionnaire that assesses demographic and background characteristics of immigrants, and psychosocial risk factors of demoralization. Method-Based on a review of instruments used to study immigrants, and researchers' experience in this area, an 85-item questionnaire was developed that includes 10 scales and three general indices. Subjects are asked to indicate their level of satisfaction with various aspects of their lives, their reasons for immigration, and problems they had encountered since they immigrated. Results-DPSI (Demographic Psychological Inventory) was tested on 1,200 adult immigrants who came to Israel from the former USSR since 1989. The reliability of the scales and general indices was generally high as measured by Cronbaeh's Alpha. For one general index and two scales it was above .78, for one general index and two scales it was between .60 and .73, for one general index and two scales between.41 and .55, and for one scale .23. The general indices were highly correlated with the Psychiatric Epidemiology Research Interview Demoralization Scale (PERI-D) and the Brief Symptom Inventory (BSI). The results suggest that the greatest risk factors of demoralization are a greater number of distress sources, difficulty in dealing with conflict, greater discrepancy between actual difficulties encountered and those expected, and more reasons for immigration. The single most important variable in predicting a demoralization case was the number of distress sources. We developed DPSI cutting points for caseness based on comparisons to BSI and PERI-D. For the BSI, DPSI cutting points are .44 for males, and .48 for females. These cutting points recognize about 61% of those who are cases according to BSI, and about 72% of those who are not cases according to BSI. For the PERI-D, DPSI cutting points for caseness are .42 for males and .44 for females. These cutting points recognize about 63% of those who are demoralized according to PERI-D and about 68% of those who are not demoralized according to PERI-D. DPSI tends to recognize slightly more cases as being at risk of demoralization than those who are demoralized according to PERI-D, and slightly less than those identified as cases according to BSI. Conclusions-DPSI is a promising instrument for gathering demographic and background characteristics of immigrants, and for studying psychosocial risk factors for development of demoralization. DPSI is available in English, Hebrew, and Russian.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".