Psychosocial Needs of Bereaved Spouses in Nigeria: Implications for Grief Counselling Intervention
Bibliographic record
Abstract
Spousal death is a traumatic life event which engenders different reactions. It becomes more challenging when psychosocial needs are inadequate. This study examined the psychosocial needs of bereaved spouses in Nigeria. The research method adopted for this study was descriptive survey. The population of the study consisted of 1,924,301 bereaved spouses in Nigeria. Purposive and proportional sampling techniques were adopted in selecting a total sample of 1,594 bereaved spouses across the six geo-political zones in Nigeria. The Psychosocial Needs of Bereaved Spouses Scale was used for data collection. Means, percentages, rank order, t-test, and Analysis of Variance (ANOVA) statistical measures were used to analyze the data collected for the study. The findings of the study revealed that respondents needed to acquire a job to sustain the family, raise finances for family upkeep, pay house bills and deal with widowhood isolation, among others. Also, age at bereavement, length of years of loss and nature of death had significant influences on respondents’ psychosocial needs, while gender and religious affiliations had no significant influence on the psychosocial needs of the respondents. The study concluded that respondents’ psychosocial needs were high. The implication is that bereaved spouses need better psychosocial supports to facilitate better adjustments. Based on the findings of the study, it was recommended, among others, that counsellors should provide relevant community-based intervention programs and support services to assist bereaved spouses of different age groups, length of years of loss and nature of death, religion, and gender to meet their varying needs.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".