Satisfied versus dissatisfied: Experiences of retirement village living
Bibliographic record
Abstract
OBJECTIVE: This study aims to understand and distinguish between satisfied and dissatisfied older people, through a comparison of their lived experience within a retirement village. METHODS: An exploratory qualitative research design was utilized to identify and describe consumer experiences of lifestyle living and how that experience translates to positive or negative satisfaction. The net promoter score (NPS) was employed to identify highly satisfied (Promoters) and highly dissatisfied (Detractors) people. RESULTS: Sixty-two interviews in retirement lifestyle villages were analysed, including satisfied (n = 33) and dissatisfied (n = 29) consumers of the service. Results reveal that satisfied people: (1) feel grateful for a service that exceeds their purchase expectations; (2) feel connected to others inside or (3) outside the lifestyle village; (4) feel 'heard' by the service provider; and (5) feel that they have retained their independence. Dissatisfied people describe: (1) broken promises, specifically those made at the time of purchase; (2) not feeling 'connected' to others inside the village; (3) feeling unheard or ignored by the service provider; and (4) the service not meeting their needs. CONCLUSIONS: Revealing these detailed insights clarified the nuanced, hazy and often ambiguous differences between dissatisfied and satisfied people. It also provided insights into the high priority needs, expectations and choices of people as they transition into and through older age. The research should help industry, government and society in general to provide products and services that fit into this lived experience and better meet the changing needs of older people.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 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".