| Literature DB >> 35591159 |
Carmen Moret-Tatay1, Maddalena Boccia2,3, Alice Teghil2,3, Cecilia Guariglia2,3.
Abstract
Global navigation satellite systems (GNSS) can provide better data quality for different purposes; however, some age groups might lie outside its use. Understanding the barriers to its adoption is of interest in different fields. This work aims at developing a measurement instrument of the adoption attitudes towards this technology and examining the relationship of variables such as age and gender. A UTAUT model was tested on 350 participants. The main results can be summarised as follows: (i) the proposed GNSS scale on human spatial navigation attitudes towards geopositioning technology showed optimal psychometric properties; (ii) although statistically significant differences were found in the Wayfinding Questionnaire (WQ) between men and women, these did not reach the level of statistical significance for the scores on attitudes towards GNSS; (iii) by testing a model on human spatial navigation attitudes towards geopositioning technology, it was possible to show a higher relationship with age in women.Entities:
Keywords: aging; attitudes; gender differences; global navigation satellite system
Mesh:
Year: 2022 PMID: 35591159 PMCID: PMC9099947 DOI: 10.3390/s22093470
Source DB: PubMed Journal: Sensors (Basel) ISSN: 1424-8220 Impact factor: 3.847
Figure 1Proposed model on human spatial navigation attitudes towards global navigation satellite systems based on the UTAUT theory.
Mann-Whitney U test employed to examine differences across gender, upper and lower CI, as well as the Rank-Biserial Correlation. Global navigation satellite systems = GNSS.
| W |
| Rank-Biserial | 95% CI for Rank-Biserial Correlation | ||
|---|---|---|---|---|---|
| Lower | Upper | ||||
| GNSS | 14,819 | 0.771 | 0.006 | −0.139 | 0.104 |
| Navigation | 484.00 | <0.001 | 0.392 | 0.231 | 0.532 |
| Estimation | 4999.50 | <0.001 | 0.438 | 0.283 | 0.570 |
| Anxiety | 2001.50 | <0.001 | −0.424 | −0.559 | −0.268 |
Spearman’s Partial Correlations between AGE, WQ subfactors, and GNSS, conditioned by gender. ** = p < 0.001; * = p < 0.05.
| Variable | Age | GPS | Navigation | Estimation |
|---|---|---|---|---|
| Age | - | |||
| GNSS | −0.466 ** | - | ||
| Navigation | −0.099 | 0.201 ** | - | - |
| Estimation | −0.012 | 0.082 | 0.682 ** | - |
| Anxiety | 0.078 | 0.069 | −0.226 ** | −0.128 * |
Figure 2Spearman’s Partial Correlations for Age, Navigation, and GNSS, conditioned by gender.
Figure 3Estimation and loadings of the model proposed. ** = p < 0.001; * = p < 0.05.
Figure 4Path coefficients amongst variables for each gender group and the whole data set. P1 = Anxiety-GNSS; P2 = Anxiety-Navigation; P3 = Age-GNSS; P4 = GNSS-Navigation; P5 = Estimation-GNSS; P6 = Estimation-Navigation.
Error measures on the models under study, Q2 and R2.
| RMSE | MAE | MAPE | Q² | R2 | ||
|---|---|---|---|---|---|---|
| Men | GNSS | 466.014 | 358.632 | 23.466 | 0.280 | 0.10 |
| Navigation | 85.848 | 68.900 | 17.382 | 0.471 | 0.52 | |
| Women | GNSS | 466.444 | 357.992 | 23.522 | 0.281 | 0.30 |
| Navigation | 85.986 | 69.162 | 17.464 | 0.469 | 0.49 | |
| Whole | GNSS | 443.756 | 335.550 | 21.409 | 0.208 | 0.22 |
| Navigation | 78.783 | 62.721 | 14.698 | 0.534 | 0.55 |