Spouse Caregivers’ Experiences of Suffering in Relation to Care for a Partner With Brain Tumor
Bibliographic record
Abstract
BACKGROUND: Spouses often undertake the main caring role for a partner with primary malignant brain tumor (PMBT). Yet, demanding and challenging caring responsibilities especially because of the partner's cognitive declines can affect the spouse caregiver's well-being. OBJECTIVE: The aim of this study was to investigate spouses' experiences of suffering in their role as main caregiver of a partner with PMBT. METHODS: A hermeneutical qualitative design was used to collect and analyze data. Ten spouses (aged 36-76 years) were interviewed in depth twice 1 year apart, using semistructured interview guides. RESULTS: The spouse caregivers' experiences of suffering in their role as their partner's main caregiver were interpreted according to 3 central themes: "Enduring everyday life," "Being overlooked and hurt," and "Being acknowledged and feeling good." CONCLUSION: Spouse caregivers of a partner with PMBT are suffering from exhaustion and suppression of their own emotions to endure the caring responsibilities. They need support to manage their everyday hardship; however, their experiences seem to be easily overlooked. This causes disappointment and hurts their dignity. Acknowledgment through simple acts of practical help or time to talk are consoling and alleviate their experiences of suffering. IMPLICATIONS FOR PRACTICE: An intervention that supports healthcare professionals to facilitate the spouse caregivers' suffering is welcoming. The focus of the intervention may involve a sensitive awareness toward the spouse caregiver's individual resources and limitations and the relational and communicative competences of the healthcare professionals in their encounters with spouse caregivers that avoid hurting the spouse caregiver's dignity.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".