In summary, we found no significant impact on the overall risk of SA the first 4 years after implementing the Norwegian Agreement for a More Inclusive Working Life. When stratifying by sex, there was an overall positive effect of the IA Agreement among female workers, whilst no effect was found among male workers. Companies signing the Agreement were more likely to be large (≥ 50 employees) and were more often within the manufacturing and health and social work sectors. In large manufacturing companies, there was a statistically significant reduction in SA among both male and female workers after the implementation of the IA Agreement, in both intervention and control companies; thus no impact was found for the intervention. In large health and social companies there was, in contrast, an increase in SA after the introduction of the IA Agreement. The increase was lower in the intervention group compared to the control group, resulting in a positive impact of the actual IA intervention on SA. This pattern was mainly evident among female workers in large health and social companies. In sum, the results indicate that the impact of the IA Agreement on SA varied considerably depending on sex, industry, and company size.
Methodological considerations
One of the strengths of this study is the use of statistical analyses that take into account the difference in SA pre and post intervention. Difference-in-difference analysis is a causal inference method that can be applied to counter selection bias and confounding. The large study population also made it possible to stratify by sex, industry and company size. This stratification, in combination with the DID analyses, could therefore reduce the bias and confounding that may result from the significant differences in the distribution of company size, industry and sex between the intervention and control groups. However, self-selection bias may be an issue, as we observed that the employees in companies signing the IA Agreement had a higher SA prior to the intervention, compared with employees in control companies. This might challenge the key assumption of exogeneity in DID, which posits that the selection into the intervention (the Agreement) should not be predicted by the outcome (SA) prior to the intervention. However, there is no evidence that individuals choose where they work based on the company’s IA status, and the companies do not only base their choice of signing the IA Agreement on prior SA level (18).
One of the many challenges in evaluating the IA Agreement’s impact on SA was that we did not have data on exactly when the IA Agreement was signed by a specific company (only yearly data). We did not have data on when they started introducing the different preventive measures, either. Other studies have shown, however, that most companies signing the Agreement increased their effort to lower SA following the start of the IA Agreement in 2001, regardless of the date they formally signed the Agreement (5). Even so, the specific preventive actions or activities they may offer is not available in our data, preventing us from evaluating the possible differential impact of activities on SA. To address this, we have used company size as a proxy measure as this can indicate differences in the means or resources they have available to use in implementing the IA activities, applying for grants and so on. Larger companies may have more resources available to make use of and benefit from the possibilities in the IA Agreement more than small companies.
Another limitation of this study is the focus on SA alone as the outcome, as the IA Agreement incorporates three goals that might influence each other. Reducing SA is only one of the goals. The two other goals are to secure recruitment of people with disabilities and vulnerable groups into the labour market and to prolong working life. These three goals may affect each other, as a company that increases the recruitment of people with disabilities and prolongs working life for older workers, might also experience increased SA due to this. It is therefore possible that we may present an underestimation of the impact of the intervention on SA in our study for companies with a high goal attainment on inclusion of disabled workers, but this is unknown. It is therefore important to have in mind that our results are only evaluating one of the goals of the IA Agreement.
Our results in light of other findings
Our finding that the impact of the IA Agreement on SA varied considerably depending on sex and industry contributes to limited literature on the impacts of this population based intervention. Evaluations of the IA Agreement have been published in some reports without peer review (5, 6, 19, 20), and have indicated a positive impact of the IA Agreement in manufacturing, as this sector shows a decrease in SA after implementation of the intervention. Earlier reports have also indicated a negative impact of the intervention in the health and social work sector, as SA increases in this sector in the same period (5). Our results were therefore a bit surprising as we found the opposite; there was no impact of the IA Agreement in manufacturing, and a positive impact in health and social work. These contradicting results can be explained by the fact that we use an analytical method that takes into account the intervention and control group differences, both before the IA Agreement was implemented and 4 years after. This explanation is strengthened by the fact that we get similar findings (decrease in SA for employees in manufacturing companies and increase in SA for employees in health and social work companies) when we use the same statistical methods as in the reports, without the use of DID method.
Similar to a 2011 study on the impact of the IA Agreement on SA (7), our results also show no impact in the overall sample. However, in contrast, we find that the impact varies by industry. This may partly be explained by the considerably smaller sample in the 2011 study, which impedes stratification by industry. In their analysis, they also used office workers as a reference, and did not include information on company size or take into account the baseline difference in SA. Another study by Midtsundstad et al from 2014 showed, on the other hand, a positive impact of the intervention on overall SA and a varying effect by industry (8). They used the same DID method as in our study and found a positive impact on SA among IA companies in the public administration sector. This is partially in line with our findings; however, in our study, the positive impact in the public administration sector was only found in women and varied according to company size. They also did not find positive impacts of the intervention for manufacturing, construction and transport; although the overall SA decreased in manufacturing, it was not due to the intervention, which is also similar to our findings. This can indicate that the decrease in SA may be related to other factors than the IA Agreement, for example company characteristics or the focus on SA and work environment in the manufacturing sector as a whole, resulting in an impact for all companies and not only those signing the IA Agreement. We also found a positive impact among female health and social workers in medium and large companies, which was not found in the other study (8). A potential reason for this discrepancy in results may be that they focused on older workers (aged 50+) whilst our study included younger and middle-aged workers (aged 25–34). Beyond these two studies, there is little scientific knowledge on the impact of the IA Agreement on SA that also takes into account the possible differential impacts by industry. Other scientifically based evaluations of the IA Agreement have been carried out, largely reporting a positive impact, however, they have evaluated other outcomes, such as disability benefits (10) and return to work after rehabilitation (9), and are therefore not comparable to our study.
Implications
The present study strengthens the evidence that the impact of the IA Agreement on SA varies greatly between industries and the size of the companies. Very few clear implications can be given based on this study, as we do not have data on the preventive measures used in different sectors. It is, however, evident that there is a need for a greater focus on work- and industry-related exposures and the possibilities for preventive measures addressing the specific challenges in each industry. Previous studies have found that 23–28% of long-term SA is attributable to work-related exposures (21, 22). This indicates that interventions targeting the work environment can be considered an important method for decreasing SA. According to the surveillance of work environment for the working population in Norway (13), health and social workers have challenges in terms of high emotional demands, role conflicts, job strain, unwanted sexual attention, violence and threats, working nights, neck bending, and awkward lifting. In contrast, manufacturing workers have more exposure to noise, vibrations, awkward lifting, squatting/kneeling, downsizing, and job insecurity. This may indicate that reducing SA in these two sectors would warrant different preventive strategies and actions.
The IA Agreement has up until now, been focused on close follow up of those on sick leave, adjustments of work tasks and the possibility to get other tasks that the employee can do even when sick. It can also be argued that the differences in impact of the intervention can be due to the fact that the reason for SA will in most cases depend on the workplace, work tasks and opportunities for adjustments. In some industries, the possibilities to adapt the work tasks are more limited than in others, such as manual workers in manufacturing compared with office workers in public administration.