| Literature DB >> 35409668 |
José Antonio Muñiz-Velázquez1, Alejandro José Tapia Frade1, Javier Lozano Delmar1, Puri Alcaide-Pulido1, Andrés Del Toro1.
Abstract
Happiness at work is a consolidated topic. Perhaps the PR and communication sector, often at the forefront of organizational change, is one of the industries where most progress has been made in this regard. The objective of the present study was to carry out an exploratory analysis on the extent to which PR is a profession that enables the development of happiness in the workplace. To this end, a questionnaire was administered to a sample of PR professionals in Spain (N = 256). The questionnaire consisted of the PERMA-profiler, a model where work relationships, engagement, positive affections/emotions, vital sense/purpose and achievements are measured. The results show a remarkable level of happiness among surveyed professionals, especially among women, who obtained higher scores on all five factors, although with a statistically significant difference only in two of the five factors in PERMA (Engagement and Relationships). Neither age nor the hierarchical level of the respondent had any incidence. Therefore, PR can be a profession that notably enables human flourishing at work, even more so among women.Entities:
Keywords: communication consultants; corporate communication; engagement at work; happiness; job satisfaction; organizational development; public relations; purpose; well-being at work
Mesh:
Year: 2022 PMID: 35409668 PMCID: PMC8997484 DOI: 10.3390/ijerph19073987
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Mean and SD obtained in the Workplace PERMA-profiler (range from 0 to 10), by gender, age and position.
| P | E | R | M | A | Total | N | H | Total with H and N | |||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Gender | Male | Mean | 6.4727 | 6.7212 | 7.3273 | 6.6970 | 7.1394 | 6.8715 | 4.9879 | 6.5636 | 5.1333 |
| SD | 2.05950 | 1.87551 | 1.59667 | 1.89679 | 1.56832 | 1.59752 | 2.02247 | 1.95302 | 1.43708 | ||
| Female | Mean | 7.1475 | 7.4754 | 8.2186 | 6.8169 | 7.5246 | 7.4366 | 4.7322 | 7.2295 | 5.6686 | |
| SD | 1.31534 | 1.28416 | 1.25366 | 1.65206 | 1.11169 | 1.03312 | 1.95667 | 1.59607 | 0.95133 | ||
| Age | Under 32 | Mean | 6.9624 | 7.2151 | 8.4140 | 6.7097 | 7.5699 | 7.3742 | 4.4785 | 7.1828 | 5.6536 |
| SD | 1.84766 | 1.51507 | 1.50007 | 1.62683 | 1.18489 | 1.23485 | 2.19174 | 1.90166 | 1.15322 | ||
| 32–38 | Mean | 6.8182 | 7.1333 | 7.6909 | 6.6909 | 7.3152 | 7.1297 | 5.0061 | 7.0545 | 5.3853 | |
| SD | 1.43561 | 1.60195 | 1.30818 | 1.58030 | 1.18707 | 1.21617 | 1.83865 | 1.56184 | 1.08998 | ||
| Over 38 | Mean | 7.0222 | 7.3667 | 7.6833 | 6.9333 | 7.3167 | 7.2644 | 4.9778 | 6.8278 | 5.4532 | |
| SD | 1.51187 | 1.48907 | 1.34658 | 1.95986 | 1.44767 | 1.33045 | 1.84306 | 1.72113 | 1.19528 | ||
| Position | High management | Mean | 7.4348 | 7.7101 | 7.7826 | 7.3986 | 7.7246 | 7.6101 | 4.6667 | 7.0145 | 5.7712 |
| SD | 1.33309 | 1.34552 | 1.32817 | 1.52933 | 1.21372 | 1.15990 | 1.56031 | 1.67768 | 1.04659 | ||
| Intermediate management | Mean | 6.8611 | 7.3403 | 7.9306 | 6.6319 | 7.3542 | 7.2236 | 5.1042 | 6.9583 | 5.4246 | |
| SD | 1.40218 | 1.39653 | 1.19881 | 1.82087 | 1.20559 | 1.16493 | 1.93164 | 1.61058 | 1.09486 | ||
| Senior Technician | Mean | 6.7821 | 7.0000 | 7.6026 | 6.6538 | 7.2308 | 7.0538 | 4.2564 | 7.5000 | 5.5018 | |
| SD | 1.61091 | 1.64924 | 1.58330 | 1.66662 | 1.26410 | 1.27164 | 2.00955 | 1.51217 | 1.14517 | ||
| Technician | Mean | 6.7758 | 6.9636 | 8.3576 | 6.5636 | 7.3758 | 7.2073 | 4.9879 | 7.0061 | 5.4364 | |
| SD | 1.77088 | 1.44398 | 1.26174 | 1.60615 | 1.11121 | 1.12258 | 2.23603 | 1.81952 | 1.11095 | ||
| Total | Mean | 6.9379 | 7.2411 | 7.9416 | 6.7797 | 7.4049 | 7.2610 | 4.8117 | 7.0226 | 5.5023 | |
| SD | 1.60901 | 1.52823 | 1.42612 | 1.72724 | 1.27917 | 1.25921 | 1.97515 | 1.73700 | 1.14785 | ||
Significance coefficients of differences by gender, age and position.
| i | j | P | E | R | M | A | Total | N | H | Total with H and N | Happiness (Q16-i23) | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Gender | Male | Female | 0.079 | 0.029 * | 0.000 * | 0.895 | 0.236 | 0.069 | 0.507 | 0.040 * | 0.027 * | 0.610 |
| Age | Under 32 | 32–38 | 0.880 | 0.955 | 0.015 | 0.998 | 0.547 | 0.553 | 0.320 | 0.918 | 0.422 | 0.805 |
| Over 38 | 0.991 | 0.848 | 0.011 | 0.903 | 0.371 | 0.803 | 0.380 | 0.388 | 0.510 | 0.939 | ||
| 32–38 | Over 38 | 0.817 | 0.692 | 0.999 | 0.884 | 0.963 | 0.906 | 0.988 | 0.650 | 0.983 | 0.952 | |
| Position | High management | Intermediate management | 0.236 | 0.592 | 0.952 | 0.064 | 0.275 | 0.286 | 0.750 | 0.980 | 0.328 | 0.666 |
| Technician | 0.144 | 0.049 | 0.129 | 0.069 | 0.483 | 0.318 | 0.844 | 1.000 | 0.426 | 0.331 | ||
| Senior technician | 0.313 | 0.185 | 0.944 | 0.281 | 0.355 | 0.219 | 0.828 | 0.652 | 0.751 | 0.278 | ||
| Intermediate management | Technician | 0.997 | 0.541 | 0.338 | 1.000 | 0.973 | 0.999 | 0.997 | 0.981 | 0.996 | 0.952 | |
| Senior Technician | 0.999 | 0.762 | 0.741 | 0.991 | 0.999 | 0.970 | 0.322 | 0.437 | 0.974 | 0.829 | ||
| Senior technician | Technician | 1.000 | 0.541 | 0.077 | 0.996 | 0.959 | 0.947 | 0.398 | 0.617 | 0.994 | 0.973 |
* p < 0.05.
Key data of other similar studies.
| Study | Sector | Country | N | M | SD |
|---|---|---|---|---|---|
| Ascenso, Perkins and Williamon [ | Musicians | Several | 601 | 7.34 | 1.68 |
| Butler and Kern [ | General Population | Several | 32,000 | 7.02 | 1.66 |
| Ryan et al. [ | General Population | Australian | 439 | 6.6 | 1.5 |
| Pastrana and Salazar-Piñeros [ | General Population | Colombia | 230 | 7.73 | 1.37 |
| Lima-Castro et al. [ | General Population | Ecuador | 1247 | 8.17 | 3.12 |
| Cobo-Rendón et al. [ | Students | Chile | 1462 | 4.95 | 1.4 |
| Watanabe et al. [ | Several | Japan | 310 | 5.88 | 1.8 |