Job satisfaction of the accredited social health activists in Amdang community development block of North 24 Parganas district, West Bengal
Bibliographic record
Abstract
Background: Job satisfaction is a positive emotional state towards one’s job which influences efficiency in performance. Job satisfaction of accredited social health activist (ASHA) under national health mission, is not documented in many areas of the country. The present study was done to assess job satisfaction of ASHA in Amdanga community development block of North 24 Parganas district, West Bengal.Methods: A cross sectional study was done during August–November 2019 among all the 114 ASHAs in Amdanga block. Interviews were conducted using a questionnaire developed based on measures of job satisfaction (MJS) tool. Questionnaire contained 7 facets and 42 items in individual facets of satisfaction such as personal component, workload, professional support, training, incentive and care providing. Responses were recorded in 3-point Likert’s scale for each item, total score ranging from 42–126. Item median scores are calculated for each subscale. Scores falling at median and above were categorized as satisfied and scores falling below median score were categorized as dissatisfied. Mann-Whitney U test and Kruskal-Wallis test were applied to determine associated factors.Results: Overall 62.3% ASHAs were satisfied with their work. However, 33.3% ASHAs were dissatisfied about their incentive and 37.7% were dissatisfied with their workload. Overall satisfaction was significantly associated with age, socio-economic status, service duration of ASHA (p<0.05).Conclusions: Overall satisfaction level among ASHAs in the area though high, individual aspects like incentives, workload needs to be looked into to take necessary strategies.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".