| Literature DB >> 33628067 |
Eman Mortada1,2, Amro Abdel-Azeem1,3, Abdulmajeed Al Showair3, Marwa M Zalat1,4.
Abstract
PURPOSE: The main objectives of the study are firstly to measure the COVID-19 preventive health behaviors related among health care providers (HCPs), then to identify the determinants of such behavior using the protection motivation theory (PMT). PATIENTS AND METHODS: An online cross-sectional survey, containing closed-ended questions, was distributed among healthcare professionals including physicians, pharmacists, technicians, and nurses. It consisted of questions assessing socio-demographic and occupational characteristics, in addition to questions from the modified PMT that has been tailored for the COVID-19 pandemic through five sub-constructs: perceived severity and perceived vulnerability, response efficacy, self-efficacy, response costs, and behavioral intention.Entities:
Keywords: COVID-19; behavioral intention; coping appraisal; preventive health practice; protection motivation theory; threat appraisal
Year: 2021 PMID: 33628067 PMCID: PMC7898786 DOI: 10.2147/RMHP.S289837
Source DB: PubMed Journal: Risk Manag Healthc Policy ISSN: 1179-1594
Figure 1Conceptual framework of PMT and its five constructs.
Socio-Demographic, Work-Related Characteristics of the Sampled HCPs and Their Intention to Comply with COVID-19 Preventive Behavior (n=385)
| Characteristics | Responses | Total | Intension of HCPs to Comply with COVID-19 Preventive Behavior | P value | ||
|---|---|---|---|---|---|---|
| Do not Intend | Intend | |||||
| Age groups(y) | ≤ 35 | 112(29.1) | 45(31.5) | 67(27.7) | 0.63 | 0.73 |
| 35–44 | 146(37.9) | 52(36.4) | 94(38.8) | |||
| ≥45 | 127(33.0) | 46(32.2) | 81(33.5) | |||
| X ±SD | 40.08±8.2 | |||||
| Gender | Male | 151(39.2) | 68(47.6) | 83(34.3) | 6.63 | 0.01* |
| Female | 234(60.8) | 75(52.4) | 159(65.7) | |||
| Marital state | Not Married | 71(18.4) | 30(21.0) | 41(16.9) | 0.97 | 0.32 |
| Married | 314(81.6) | 113(79.0) | 201(83.1) | |||
| Having children | No | 88(22.9) | 37(25.9) | 51(21.1) | 1.17 | 0.28 |
| Yes | 297(77.1) | 106(74.1) | 191(78.9) | |||
| Nationality | Non-Saudi | 88(22.9) | 34(23.8) | 54(22.3) | 0.11 | 0.77 |
| Saudi | 297(77.1) | 109(76.2) | 188(77.7) | |||
| Profession | Physician | 113(29.4) | 48(33.6) | 65(26.9) | 19.23 | <0.0001* |
| Pharmacist | 43(11.2) | 23(16.1) | 20(8.3) | |||
| Nurse | 166(43.1) | 42(29.4) | 124(51.2) | |||
| Technician | 63(16.4) | 30(21.0) | 33(13.6) | |||
| Being on workforce during the pandemic COVID-19 in KSA | No | 81(21.0) | 24(16.8) | 57(23.6) | 2.48 | 0.12 |
| Yes | 304(79.0) | 119(83.2) | 185(76.4) | |||
| Work sector | Primary healthcare center | 238(61.8) | 89(62.2) | 149(61.6) | 6.99 | 0.14 |
| General public hospitals | 39(10.1) | 15(10.5) | 24(9.9) | |||
| Private hospital/center | 33(8.6) | 6(4.2) | 27(11.2) | |||
| Health Quarantine | 29(7.5) | 14(9.8) | 15(6.2) | |||
| Surveillance team | 46(11.9) | 19(13.3) | 27(11.2) | |||
| Working hours/day | ≤ 8 | 286(74.3) | 99(69.2) | 187(77.3) | 3.04 | 0.08 |
| > 8 | 99(25.7) | 44(30.8) | 55(22.7) | |||
| Working experience(y) | ≤10 | 95(24.7) | 35(24.5) | 60(24.8) | 0.35 | 0.84 |
| 11–20 | 179(46.5) | 69(48.3) | 110(45.5) | |||
| > 20 | 111(28.8) | 39(27.3) | 72(29.8) | |||
| Level of training in IPC measures | Basic | 187(48.6) | 82(57.3) | 105(43.4) | 7.59 | 0.02* |
| Intermediate | 109(28.3) | 31(21.7) | 78(32.2) | |||
| Advanced | 89(23.1) | 30(21.0) | 59(24.4) | |||
| PPEs are available during work time | Sometimes | 96(24.9) | 38(26.6) | 58(24.0) | 13.6 | 0.001* |
| Often | 135(35.1) | 64(44.8) | 71(29.3) | |||
| Always | 154(40.0) | 41(28.7) | 113(46.7) | |||
| COVID-19 Infected | No | 329(85.5) | 120(83.9) | 209(86.4) | 0.43 | 0.51 |
| Yes | 56(14.5) | 23(16.1) | 33(13.6) | |||
| Total | 385(100.0) | 143(37.1) | 242(62.9) | |||
Note: *P ≤ 0.05 is significance.
Abbreviations: IPC, infection prevention and control; PPE, personal protective equipment; HCPs, health care providers.
Descriptive Statistics and Cronbach Alpha for Protection Motivation Theory Subscales
| Items | Min - Max | X±SD | Cronbach Alpha | |
|---|---|---|---|---|
| Perceived severity | 5 | 5–25 | 18.62±3.6 | 0.78 |
| Perceived vulnerability | 3 | 3–15 | 12.12±2.35 | 0.76 |
| Self-efficacy | 5 | 5–25 | 19.5±3.2 | 0.72 |
| Response-efficacy | 7 | 7–35 | 30.1±4.6 | 0.73 |
| Behavioral intension | 4 | 4–16 | 14.4±2.2 | 0.75 |
Figure 2Behavioral intention of respondent HCPs to comply with COVID-19 preventive behavior.
Subscales of PMT Among HCPs and Their COVID-19 Behavioral Intentions (n=385)
| Characteristics | Intention of HCPs to Comply with COVID-19 Preventive Behavior | P value | ||
|---|---|---|---|---|
| Do not Intend | Intend | |||
| Threat appraisal | 30.04±6.3 | 31.15±4.99 | −1.92 | 0.06 |
Perceived severity | 18.2±4.4 | 18.9±3.49 | −1.77 | 0.078 |
Perceived vulnerability | 11.9±2.54 | 12.3±2.22 | −1.61 | 0.108 |
| Coping appraisal | 44.6±7.41 | 47.57±6.43 | −4.09 | <0.001* |
Self-efficacy | 18.6±3.3 | 20.2±3.07 | −4.59 | <0.001* |
Response-efficacy | 29.13±5.03 | 30.71±4.26 | −3.28 | 0.001* |
Response-cost | 3.2±1.07 | 3.3±1.07 | −.75 | 0.46 |
Note: *P ≤ 0.05 is significance.
Abbreviation: HCPs, health care providers.
Correlation Between COVID-19 Behavioral Intention, and Constructs of Protection Motivation Theory Among HCPs
| Correlation Variables | 1 | 2 | 3 | 4 | 5 | 6 |
|---|---|---|---|---|---|---|
| 1. Behavioral intension | 1 | |||||
| 2. Perceived severity | 0.272** | 1 | ||||
| 3. Perceived vulnerability | 0.248** | 0.556** | 1 | |||
| 4. Self-efficacy | 0.218** | 0.096 | 0.128* | 1 | ||
| 5. Response-efficacy | 0.167** | 0.153** | 0.234** | 0.593** | 1 | |
| 6. Response-cost | 0.13* | 0.388** | 0.270** | 0.091 | 0.111* | 1 |
Notes: **Correlation is significant at the 0.01 level (2-tailed); *Correlation is significant at the 0.05 level (2-tailed).
Logistic Regression Analysis for Factors Predicting COVID-19 Behavioral Intensions
| Predictors | B | Wald | P value | Exp(B) | 95% C.I. for EXP(B) | |
|---|---|---|---|---|---|---|
| Lower | Upper | |||||
| Constant | −6.206 | 23.582 | 0.000 | 0.002 | ||
| Gender | 0.568 | 6.217 | 0.013* | 1.765 | 1.129 | 2.759 |
| Profession | 0.145 | 1.855 | 0.173 | 1.156 | 0.938 | 1.424 |
| Availability of PPE | 0.373 | 5.621 | 0.018* | 1.452 | 1.067 | 1.977 |
| IPC training | 0.214 | 2.264 | 0.132 | 1.239 | 0.937 | 1.638 |
| Perceived severity | 0.039 | 1.141 | 0.286 | 1.040 | 0.968 | 1.118 |
| Perceived vulnerability | 0.061 | 0.967 | 0.325 | 1.062 | 0.942 | 1.199 |
| Response efficacy | 0.019 | 0.309 | 0.578 | 1.019 | 0.954 | 1.088 |
| Self-efficacy | 0.122 | 7.020 | 0.008* | 1.130 | 1.032 | 1.237 |
| Response cost | −.025 | 0.046 | 0.831 | 0.975 | 0.777 | 1.225 |
Note: *P ≤ 0.05 is significance.
Abbreviations: IPC, infection prevention and control; PPE, personal protective equipments; HCPs, health care providers.