Table 3.
Results of the principal component analysis (2 factor solution)
| Chao item no. | Variable descriptor | Component | |
|---|---|---|---|
| 1 | 2 | ||
| 1A | Different doctors | .486 | |
| 1B | Past medical problems | .600 | |
| 1C | Location | -.402 | |
| 1D | Medication | .456 | |
| 1E | Same doctor | .431 | |
| 1 F | Prior knowledge | .428 | |
| 1G | Unknown problems | .483 | |
| 1H | Care for all problems | .480 | .474 |
| 2A | On-going relationship | .454 | .579 |
| 2B | Unrelated medical problems | .558 | |
| 2C | Personal problems | ||
| 2D | Knowledge of family members | .418 | .430 |
| 2E | Ease of communication | .525 | |
| 2 F | Knowledge of family problems | .579 | |
| 2G | Poor explanations | .647 | |
| 2H | Emergency care preference | .461 | |
| 2I | Waiting for own doctor | ||
| 2 J | Referrals | .514 | |
| 2 K | Provides pre-admission care | .483 | |
| 2 L | Provides ER care | .577 | |
| 2 M | Trust recommendations | .410 | .428 |
| 2 N | Recognition | .424 | .519 |
| 2O | Trust personal | .558 | .504 |
Overlapping items are highlighted in bold type.
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.
Rotation converged in 3 iterations.