| Literature DB >> 31242911 |
Mikkel Magnus Thørrisen1,2, Jens Christoffer Skogen3,4,5, Ingvild Kjeken6,7, Irene Jensen8, Randi Wågø Aas6,9,5.
Abstract
BACKGROUND: Alcohol is associated with detrimental health and work performance outcomes, and one to three out of ten employees may benefit from interventions. The role of occupational health services (OHS) in alcohol prevention has received little attention in research. The primary aims of this study were to explore current practices of alcohol prevention targeting employees in occupational health settings, and examine whether and which perceived implementation barriers were associated with alcohol prevention activity. The secondary aim was to explore whether barriers were differentially associated with primary, secondary and tertiary prevention activities.Entities:
Keywords: Alcohol consumption; Implementation; Occupational health services; Prevention; Workforce; Workplace interventions
Mesh:
Year: 2019 PMID: 31242911 PMCID: PMC6595559 DOI: 10.1186/s13011-019-0217-2
Source DB: PubMed Journal: Subst Abuse Treat Prev Policy ISSN: 1747-597X
Fig. 1Conceptual model of the relationships between alcohol consumption, drinking categories, risk levels, intervention recommendations and prevention levels. aBased on [32]; bBased on [31, 33]; cBased on [31]
Characteristics of the study sample (N = 295)
| Range | |||||
|---|---|---|---|---|---|
| Variable |
|
| Median | Min | Max |
| Age (years) | 49.1 | 9.9 | 49.0 | 25.0 | 75.0 |
| OHS experience (years) | 12.3 | 9.1 | 10.0 | < 1.0 | 39.0 |
| Variable |
| % | |||
| Gender | |||||
| Male | 59 | 20.0 | |||
| Female | 236 | 80.0 | |||
| Professional background | |||||
| Occupational therapist | 8 | 2.7 | |||
| Nutritionist | 1 | 0.3 | |||
| Physical therapist | 51 | 17.3 | |||
| Physician | 41 | 13.9 | |||
| Psychologist | 6 | 2.0 | |||
| Nurse | 114 | 38.6 | |||
| Occupational hygienist | 23 | 7.8 | |||
| Othera | 51 | 17.3 | |||
M mean, SD standard deviation; a e.g., medical secretaries, engineers, educationalists/teachers, economists and social scientists
Alcohol prevention activity according to prevention level, and matrix of differences between prevention levels (N = 295)
| Primary activities | Secondary activities | |
|---|---|---|
Primary activities ( | – | t (294) = − 1.4 |
Secondary activities ( | t (294) = − 1.4 | – |
Tertiary activities ( | t (294) = 8.9 | t (294) = 10.0 |
Results from paired samples t-tests; M mean, SD standard deviation, Mdiff mean difference; * Statistically significant difference (p < .05); ns Statistically non-significant difference (p > .05)
Fig. 2Perceived barriers to implementing alcohol-preventive efforts in occupational health services (N = 295). Means and standard deviations. Visual analogue scales ranging from 1 (barrier to a very small extent) to 11 (barrier to a very large extent)
Associations between perceived implementation barriers and alcohol prevention activity, overall and differentiated according to prevention level (N = 295)
| Alcohol prevention activity | ||||
|---|---|---|---|---|
| Implementation barriers | All groups | Primary | Secondary | Tertiary |
| OHS competence, time, resourcesa | −0.22** (.001) | −0.20** (.002) | − 0.14* (.034) | −0.17** (.008) |
| Employer, employeeb | −0.03ns (.624) | −0.04ns (.527) | − 0.03ns (.651) | −0.01ns (.945) |
Results from multivariate hierarchical linear regression analyses; All models are adjusted for gender, age, professional background, OHS experience and drinking social norms; β = standardised coefficient; aBarriers internal to the OHS’ organisation (items: “lack of knowledge on interventions”, “lack of knowledge on importance”, “lack of time/resources”); bBarriers external to the OHS’ organisation (items: “lack of employer interest”, “employer resistance”, “alcohol is a private/personal matter”, “disclaimer of liability”); *p < .05; **p < .01; nsNon-significant (p ≥ .05)