Using a randomized-controlled study design, we found that a smoking cessation intervention for blue-collar apprentices delivered in a unionized apprenticeship setting, and that incorporated messages about the dual risks of smoking and occupational hazards, produced significantly higher quit rates in the intervention versus control conditions 30 days after the intervention. The difference in quit rates was not maintained 6 months later, however, suggesting that many who had quit subsequently relapsed. Additionally, we found that baseline smokers in the intervention group who had not quit smoking 6 months after the intervention were three times more likely to report that they decreased the amount of cigarettes they smoke by at least half a pack. We also observed a high prevalence of smoking among the apprentices in the study compared to the general population (41% vs. 20.2%). This high prevalence of smoking among workers in the building trades has recently been reported by a national study [34
The rates of smoking cessation reported by the apprentices in the control group is unusually high given that the median unaided prolonged abstinence rates in the general U.S. population is about 5% [35
]. However, the prevalence of smoking in this population is almost twice the prevalence in the general population. Also, expressed interest in smoking cessation and attempts is higher in our population than in the general population. Compared to 42.5% in the general population [36
], 56.6% of the apprentices reported at baseline that they had stopped smoking for at least 1 day or longer in the last year because they were trying to quit smoking. Likewise, 45% of smokers in our study reported that they were seriously thinking of quitting in the next 30 days at baseline. As expected, the 6-month prolonged abstinence quit rates were closer to the national average.
Before discussing the meaning and implication of our findings, it is useful to consider study limitations. Biochemical validation of smoking status was not feasible. In addition, we could not employ other means of testing smoking cessation, such as testing expired breath for carbon monoxide, because the apprentices are regularly exposed to occupational hazards that elevate carbon monoxide levels. Therefore, the study relied on self-report of smoking status. The need for validation of smoking cessation in population-based studies has been questioned [37
]. We anticipated that apprentices in the intervention group might be less likely to report that they are still smoking if survey data were being collected by the same program staff who implemented the intervention. Therefore, we had one group of staff members implement the intervention components, while a different group collected survey data.
Even though we separated the union training sites into intervention and control groups, it is still possible that there was contamination in this study because it was possible for apprentices in the control and intervention apprentice sites to work together at the same worksites. Such contamination is expected to make the intervention and control groups more alike and bias our results toward the null. Also, we were unable to collect the 6-month survey at the same timeframe for all the sites. We used the same study survey for all sites. This means that the question about smoking at time 3 means different length of time from the intervention for different sites. For the last two intervention sites surveyed, it actually meant that we were assessing whether they maintained their smoking cessation 8 and 9 months after the intervention and not for 6 months as was the case for the other two intervention groups and all the control sites. Our analyses show that smoking cessation rates in these two sites were not significantly different from smoking cessation in the other intervention sites. This limitation speaks to the reality of working with a group that has a fixed academic calendar in which they needed to cover certain material. Thus, they were unwilling at times to accommodate our study schedule and we had to reschedule our data collection to fit their schedule.
Although we had a high response rate for each time period (range 80.7–93.6%), we analyzed data from 1,213 apprentices (67% of baseline) who had information for all time periods of our survey thus making selection bias possible. We conducted sensitivity analyses comparing our embedded cohort of apprentices who had information for all time periods to all apprentices at each time of data collection. There were no significant differences in the demographic characteristics of our embedded cohort and the entire population. In addition, we evaluated cross-sectional smoking cessation rates at each of the study time points (baseline, immediate post-intervention, and 6-month post-intervention) for all the apprentices in the study who met the criteria to be classified as a smoker at baseline and who had contributed to either or both follow-up assessments. Our results show that the shape of the cessation in the cross-sectional group mirror smoking cessation in the embedded cohort of those with data for all time points (Fig. ).
Fig. 2 Unadjusted cross-sectional differences in quit rate among all smokers in the MassBuilt cohort (baseline: n = 763, 30 days after intervention: n = 621, 6 months after intervention: n = 525) (more ...)
The strengths of the study are worth noting. We were able to randomly assign apprentice sites to intervention and control conditions in the study thereby increasing the internal validity and limiting selection bias, which could occur if sites with workers who are more motivated to quit self selected themselves into the intervention group. Also, the randomized-controlled design allowed us to compare pre- and post-intervention changes in the intervention group with changes in a control group. The longitudinal design of the study allowed us to assess the prolonged effect of the intervention to see if the smoking cessation we observed after the intervention was maintained for at least 6 months. The longitudinal design, ultimately, revealed that the effect of the intervention diminished at time 3 such that there were no statistically significant differences between the intervention and the control groups. The initial success of the intervention suggests that the need to develop strategies to help apprentices who quit smoking stay quit. Potentially, the length of the intervention could be extended and a system set in place to provide support to smokers who quit.
We based our study on empirical evidence from worksite-based smoking cessation programs. However, further studies are needed to ascertain what works in apprentice-based smoking cessation versus worksite-based smoking cessation programs. Perhaps, redressing disparities in smoking cessation entails complementary efforts in both apprenticeship programs and worksites. This is especially important for construction workers. According to National Health Interview Survey data from 1997 to 2004, occupations with smoking rates above 30% were all blue-collar, with construction workers having the highest prevalence of smoking at 38.8% [34
]. Workplace smoking bans can decrease cigarette smoking [19
]. However, blue-collar workplaces have been slow to implement bans [22
] and many blue-collar workers work outside where they can easily smoke (e.g., construction sites).
This study’s findings have implications for future research and practice on smoking cessation among blue-collar workers. To our knowledge, our study is the first randomized-controlled study to intervene on smoking cessation among blue-collar workers at their training sites in collaboration with their unions. Unions represent many workers in blue-collar occupations and can be another channel through which interventionists can reach blue-collar workers, who, otherwise would be scattered across several worksites [38
]. We have not found other reported smoking cessation interventions that targeted this untapped area of worksite health promotion. However, the study also underscores a need to find ways to provide continued assistance with maintenance of smoking cessation to apprentices who quit smoking.
In conclusion, this study demonstrated the feasibility of integrating smoking cessation programs into training programs for apprentices in the building trades. The dissemination of such programs could occur through labor-management health and welfare funds, which provide insurance to some 10 million union members and their dependents, largely employed in the building trades [39
]. An insurance-funded program that is delivered annually in apprenticeship programs, and that includes evidence-based behavioral counseling coupled with NRT, would be sustainable and may help with relapse prevention. Additionally, the toxics and tobacco curriculum is readily available through the BUILT project in California, which developed materials using state funds. Public health advocates ought to urge these labor-management health and welfare funds to provide training and worksite-based programs such as MassBUILT, as part of comprehensive wellness programming. Such programs could lead to long-term savings for jointly sponsored labor-management insurance funds.