Psychometric properties of the Sindhi version of the Mood and Feelings Questionnaire (MFQ) in a sample of early adolescents living in rural Pakistan
Bibliographic record
Abstract
There is a need for reliable and valid screening tools that assess depressive symptoms in adolescents in Pakistan. To address this need, the present study examined the psychometric properties and factor structure of a Sindhi-translated and adapted version of the child-report Mood and Feelings Questionnaire (MFQ-C) and the Short Mood and Feelings Questionnaire (SMFQ-C) in a community sample of adolescents living in Matiari, Pakistan. Questionnaires were translated into Sindhi and administered by study psychologists to 1350 participants (52.3% female) 9.0 to 15.9 years old. Measurement structure was examined using confirmatory factor analysis. Internal consistency was estimated, and convergent and divergent validity were explored using subscales from the Strengths and Difficulties Questionnaire and the Screen for Child Anxiety Related Emotional Disorders. The unidimensional structure of the MFQ-C was found to be adequate, but a four-factor structure comprising core mood, vegetative, cognitive and agitated distress symptoms best fit the data (CFI = 0.97, TLI = 0.97, RMSEA = 0.05). The original unidimensional structure of the SMFQ-C was supported (CFI = 0.97, TLI = 0.96, RMSEA = 0.07). The MFQ-C and the SMFQ-C respectively showed excellent (α = 0.92) and good internal consistency (α = 0.87) as well as satisfactory construct validity with some differences observed across the MFQ-C subscales. The SMFQ-C and the adapted MFQ-C appear to be reliable and valid measures of depressive symptoms among early adolescents living in rural Pakistan. Both total and subscale scores can be derived from the MFQ-C to assess general and specific dimensions of depressive symptoms in this population.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".