‘Everyone is exhausted and frustrated’: exploring psychosocial impacts of the lack of access to safe water and adequate sanitation in Usoma, Kenya
Bibliographic record
Abstract
The lack of access to safe water and adequate sanitation pose significant health challenges for many individuals and communities in low and middle-income countries. Aside from direct health issues, the lack of access to safe water and adequate sanitation is increasingly associated with psychosocial concerns that affect the wellbeing of individuals and communities. However, the nature of these concerns has received little attention in peer-reviewed literature. This paper draws on environmental stress and ecosocial theories to explore psychosocial concerns related to water and sanitation in Usoma, a lakeshore community in Western Kenya. The study used qualitative key informant interviews (n = 9) and focus group discussions (n = 10). Results reveal deep feelings of anxiety and frustration, embarrassment, negative identity, feelings of marginalization, and lack of self-efficacy. These stressors were a byproduct of daily lived experiences associated with lack of access to safe water and adequate sanitation, as well as the coping strategies people adopted. The paper suggests that benefits of water interventions transcend disease reduction to improved wellbeing through complex social pathways. The findings contribute to knowledge gaps within the water–health nexus and direct policy responses toward largely unexplored psychosocial concerns associated with water and sanitation.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".