Do brief alcohol interventions among unemployed at-risk drinkers increase re-employment after 15 month?

Do brief alcohol interventions among unemployed at-risk drinkers increase re-employment after 15... Abstract Background At-risk alcohol use is associated bi-directionally to unemployment, and decreases chances of re-employment. Brief alcohol interventions (BAI) can reduce at-risk alcohol use. This study aimed to investigate 15-month effects of BAI on unemployment among persons with at-risk alcohol use. Methods As part of the randomized controlled ‘Trial on proactive alcohol interventions among job-seekers, TOPAS’, 1243 18- to 64-year-old job-seekers with at-risk alcohol use were systematically recruited at three job agencies in Germany (2008/09), and randomized to (i) a stage tailored intervention based on the trans-theoretical model of intentional behavior change (ST), (ii) a non-stage tailored intervention based on the theory of planned behavior (NST) and (iii) assessment only (AO). To test the effects of ST and NST on employment status 15 months after baseline, latent growth models were calculated among those initially unemployed (n = 586). Results In all three groups, unemployment significantly decreased over 15 months (ST: odds ratio, OR = 0.06; 95% confidence interval, CI: 0.01–0.27; NST: OR = 0.04; 95% CI: 0.01–0.18; AO: OR = 0.05; 95% CI: 0.01–0.21). No intervention effects were found on unemployment. Age (P = 0.002), school education (P = 0.001), self-rated health (P = 0.04), the Alcohol Use Disorder Identification Test-Consumption score (P = 0.02) and motivation to change (P = 0.04) significantly affected the development of unemployment over time. Conclusion After 15 months, no BAI effect on unemployment was found. The mediated effect of BAIs on unemployment could be a longsome process needing longer follow-ups to be detected. Introduction Unemployment has been shown to be associated bi-directionally to health and health behaviors.1 While unemployment affects indicators of physical2 and mental health adversely,3 studies also showed that health risk behaviors and suboptimal health increase the risk of becoming unemployed and lower the chances to be re-employed.4 Consequently, employability might be enhanced by improving health behavior and health status of unemployed individuals.5 Thus, unemployed individuals are in special need for interventions on health behavior.6 One possible approach might be reducing at-risk alcohol use7 as alcohol-related morbidity was shown to be associated to unemployment.8 An intervention among individuals with alcohol dependence was shown to successfully increase rates of abstinence and chances to be re-employed.9 Similarly, chances of re-employment might be enhanced among at-risk drinkers. At-risk drinking may be defined as more than seven drinks per week or more than three drinks per occasion for women and more than 14 drinks per week or more than 4 drinks per occasion for men.10 Brief alcohol interventions seem to be promising in reducing at-risk alcohol use;11 also among job-seekers with initially low motivation to change drinking.12 However, only few studies have investigated BAI effects on other, although closely related life-domains. In a preceding study we showed that the theoretical background used for designing interventions for populations with primarily low motivation to change alcohol use, makes a difference concerning their efficacy.12 We tested two theory based interventions. Intervention A was based on the trans-theoretical model of intentional behavior change (TTM13) representing ‘stage models’. These models assume that behavior change happens in distinct motivational stages, and that interventions are most effective when tailored to the individual stage of motivation. According to the TTM, individuals move from not thinking about change (precontemplation), through being ambivalent about change (contemplation), planning to change (preparation) and manifesting change (action) to maintaining change (maintenance). Cognitive-affective and behavioral processes of change help people move through the early and later stages, respectively.14 Moving through the stages is associated with changes in the perception of the pros and cons of change (decisional balance) and one’s own situation-specific belief in the ability to change (self efficacy). Intervention B was based on the theory of planned behavior (TPB; Ref. 15) representing ‘continuous’ behavior theories that assume that a single prediction equation is valid for all individuals.16 The stage concept has been often criticized due to scarce evidence for the existence of mutually distinctive stages and sequential movement through these stages17 and due lack of convincing intervention effects.18 However, lack of intervention effects has been explained by the neglect of the multiple dimensions of the stage models.18 Interventions that incorporate the multiple dimensions of behavior change theories, and of the TTM in particular, show more convincing intervention effects.19 In line with these findings our multiple-dimension stage-tailored intervention significantly reduced alcohol use after 15 months among job-seekers with initially low motivation to change compared to the non-stage tailored and no intervention. However, it remains unclear whether these BAIs may have had an effect on unemployment status after 15 months. In this secondary outcome paper we aimed to investigate whether the stage and/or non-stage tailored BAI reduced unemployment among unemployed individuals over a period of 15 months. We hypothesized that the above described stage tailored BAI might as well lead to a decrease of unemployment in comparison to the non-stage tailored or no BAI. Methods The study presents secondary outcome data of the three arm randomized controlled trial ‘Trial Of Proactive Alcohol interventions among job-Seekers, TOPAS’ (ClinicalTrials.gov Identifier: NCT01311245) described in more detail elsewhere.12 TOPAS was conducted by the Research Collaboration on Early Intervention in health risk behaviors (EARLINT) in Western Pomerania, northeastern Germany. Informed consent was provided by all trial participants. The local ethics committee of the University Medicine Greifswald approved the study. Interventions Both interventions, the stage tailored (ST) and the non-stage tailored (NST), consisted of two individualized computer-generated 3–4 page feedback letters and self-help manuals, each delivered by mail in response to preceding assessments. The baseline assessment was conducted on the ward and a 3-month assessment was conducted by phone. In both intervention groups, baseline letters included normative feedback, e.g. on ones own drinking and responses to theoretical constructs in comparison to others. Both 3-months letters included normative and ipsative feedback, i.e. on intra-individual changes between time points. ST: Normative and ipsative feedback on the main TTM constructs (decisional balance, self-efficacy, processes of change) was dependent on stage of change. Feedback letters were accompanied by a stage-matched manual for further information, advice and practice. NST: To provide non-stage tailored feedback, assessment data on TPB constructs (attitude, subjective norm, perceived behavioral control, according beliefs and their evaluations) were used, accompanied by information and/or advice and a standard manual. Each text module was independent of any other TPB construct. Assessment only (AO): The AO control group received minimal assessments and no further intervention. Recruitment As described elsewhere,20 the sample was recruited at three job agencies over 12 months in 2008/09. In Germany, unemployed individuals, those threatened by unemployment, and those below minimal income register at government or municipal owned job agencies to receive unemployment benefit and/or health insurance coverage. There are two types of job agencies with different responsibilities. While type A job-agencies care for the not yet and short-term unemployed (up to 12 months) job-seekers, type B job-agencies care for the long-term unemployed job-seekers (more than 12 months). This study was conducted at two type A and at one type B job agency. Study assistants asked all adults, who appeared in the waiting area to fill in a questionnaire on health behaviors provided by electronic handheld computers (figure 1). Exclusion criteria were: being younger than 18 or older than 64 years, being cognitively or physically incapable, having insufficient German language or reading skills, being already recruited during an earlier visit and being an escorting person. A total of 7396 job-seekers (74.6% of those eligible) participated and provided evaluable alcohol screening measures. Those who screened positive for at-risk alcohol use and negative for particular severe alcohol problems (n = 1717; 23.2%) were eligible and asked to participate in TOPAS. At-risk alcohol use was determined using the Alcohol Use Disorder Identification Test-Consumption (AUDIT-C; Ref. 21) with gender-specific cut-off values of 4 for women and 5 for men.22 Individuals with particularly severe alcohol problems at baseline were identified and excluded from further participation using the total AUDIT score23 and values ≥ 20.24 In total, 1243 job-seekers (72.4%) received their allocated intervention (ST, NST or AO). Trial participants received a voucher of €10 by mail. As the aim of this secondary outcome study was to investigate the effect of BAI on unemployment, it includes n = 642 participants unemployed at baseline. Figure 1 View largeDownload slide Participant flow of unemployed participants as part of the Trial of Proactive Alcohol Interventions among job-Seekers, 2008/09, Germany Figure 1 View largeDownload slide Participant flow of unemployed participants as part of the Trial of Proactive Alcohol Interventions among job-Seekers, 2008/09, Germany Further assessments and follow-ups The 3-month assessment and the 6- and 15-month follow-ups were predominantly conducted as computer-assisted telephone interviews. If 10 contact attempts failed, participants received an according questionnaire by mail or were contacted at their homes. The 6-month follow-up participants received a voucher of €30; the 15-month follow-up participants took part in a lottery drawing of 20 vouchers of €50. Measures Dependent variable Unemployment status at baseline and at month 3 was assessed using a single item with three response categories: ‘Are you currently (1) unemployed, (2) not unemployed but job-seeking or (3) neither 1/nor 2?’ Those answering with category ‘(1) were categorized as ‘unemployed’, all others as ‘not unemployed’. Unemployment status at months 6 and 15 was assessed using two items. Item 1 asked ‘Are you currently employed?’ with four response categories: ‘(0) no, (1) full-time employed with at least 35 working hours a week, (2) part-time employed with 15-34 working hours a week, (3) part-time employed or employed with less than 15 working hours a week.’ People who responded (0) or (3) received item 2 ‘Are you then: (1) still in school or studying, (2) less than 6 months unemployed (3) up to 2 years unemployed (4) more than 2 years unemployed, (5) a housewife, (6) military service, (7) maternity leave, (8) retired?’. Those responding with categories (2), (3) or (4) were categorized as ‘unemployed’, all others as ‘not unemployed’. Covariates ‘Socio-demographic variables’ included sex, age in years, living in a steady partnership (yes/no), school education and duration of lifetime unemployment in months. For international comparability common German types of school education were categorized as: less than 10 years, 10–11 years, and more than 11 years of school (including those still in school). All variables were assessed at baseline. ‘At-risk alcohol use’ was determined at baseline using the AUDIT-C.21 Three items assess frequency of drinking, number of drinks per occasion, and frequency of drinking six or more drinks per occasion. The AUDIT-C sum score ranges from 0 to 12. ‘Motivation to change’ was assessed using the German version25 of the RCQ.26 The 12-item RCQ consists of three subscales [precontemplation (pc), contemplation (c), action (ac)], with four items each and a five-point Likert scale [strongly disagree (−2)/strongly agree (+2)]. As described elsewhere12 two methods of stage allocation were applied consecutively. The RCQ has been reported to be valid in predicting behavior change over time.27 ‘Self-rated health’ was assessed at baseline with the question ‘Would you say your health in general is: excellent (1), very good (2), good (3), fair (4), poor (5)?’ This item is known to be an independent predictor of mortality.28 To achieve reasonable group sizes for analyses, the categories (1) and (2) as well as (4) and (5) were collapsed. Data analysis Descriptive statistics and drop-out analyses were conducted with Stata version 12.29 Intervention effects on unemployment status were investigated calculating a latent growth model (LGM) conducted with Mplus version 6.12.30 The LGM examined the development of the probability of unemployment over time. Individual differences in development were captured by random effects or latent growth factors representing the probability of unemployment at month 15 (intercept, time scores: 1, 1, 1) and the linear rate of change from month 3 to month 15 (slope, time scores: −4, −3, 0). Unemployment was modeled as a binary variable, i.e. unemployed (1) vs. no longer unemployed (0) was regressed on the growth factors using a logit model. Maximum likelihood estimation with robust standard errors was applied using all available data (i.e. all participants who completed at least the 3 months-assessment or one of the two follow-ups contributed information, n = 588) under a missing at random assumption (MAR31). To allow for chance imbalances and to make the MAR assumption more plausible, baseline variables (sex, age, living in a partnership, school education, duration of lifetime unemployment, self-rated health, AUDIT-C and motivation to change) were included as covariates. Two cases were excluded from the analysis due to missing values on the covariate ‘duration of lifetime unemployment’, resulting in 586 cases, included in the final analyses. For reasons of interpretability age, duration of lifetime unemployment and AUDIT-C were mean centered. To test the effect of BAI on unemployment, the two latent growth factors were regressed on study group. Odds ratios (OR) and 95%-confidence intervals (CI) are presented. A P values < 0.05 was considered significant. Results Sample characteristics Of the sample (n = 586; ST: n = 196; NST: n = 196; AO: n = 194), 403 (68.8%) were male (table 1). The mean age was 32.0 (SD=11.8) years. The mean duration of life-time unemployment was 31.6 months (SD = 44.0). The mean AUDIT-C score was 5.7 (SD = 1.4). Table 1 Sample characteristics (N = 586); trial of proactive alcohol interventions among job-Seekers, 2008/09, Germany Variables Stage tailored Non-stage tailored Assessment only N % N % N % Socio-demographic variables Sex Female 56 28.6 66 33.7 61 31.4 Male 140 71.4 130 66.3 133 68.6 Age in years (M, SD) 31.3 11.2 33.5 12.5 31.2 11.6 Partnership Yes 115 58.7 108 55.1 107 55.2 No 81 41.3 88 44.9 87 44.9 School education <10 years 53 27.0 51 26.0 41 21.1 10–11 years 96 49.0 107 54.6 118 60.8 >11 yeara 47 24.0 38 19.4 35 18.0 Lifetime unemployment in months (M, SD) 26.2 33.5 34.8 42.5 34.0 53.6 Alcohol use AUDIT-C (M, SD) 5.7 1.4 5.8 1.4 5.7 1.4 Motivation to change Precontemplation 152 77.6 147 75.0 139 71.7 Contemplation 20 10.2 23 11.7 19 9.8 Preparation 4 2.0 7 3.6 5 2.6 Action 20 10.2 19 9.7 31 16.0 Self-rated health Excellent/very good 92 34.2 54 27.6 65 33.5 Good 91 46.4 109 55.6 102 52.6 Fair/poor 38 19.4 33 29.1 27 13.9 Variables Stage tailored Non-stage tailored Assessment only N % N % N % Socio-demographic variables Sex Female 56 28.6 66 33.7 61 31.4 Male 140 71.4 130 66.3 133 68.6 Age in years (M, SD) 31.3 11.2 33.5 12.5 31.2 11.6 Partnership Yes 115 58.7 108 55.1 107 55.2 No 81 41.3 88 44.9 87 44.9 School education <10 years 53 27.0 51 26.0 41 21.1 10–11 years 96 49.0 107 54.6 118 60.8 >11 yeara 47 24.0 38 19.4 35 18.0 Lifetime unemployment in months (M, SD) 26.2 33.5 34.8 42.5 34.0 53.6 Alcohol use AUDIT-C (M, SD) 5.7 1.4 5.8 1.4 5.7 1.4 Motivation to change Precontemplation 152 77.6 147 75.0 139 71.7 Contemplation 20 10.2 23 11.7 19 9.8 Preparation 4 2.0 7 3.6 5 2.6 Action 20 10.2 19 9.7 31 16.0 Self-rated health Excellent/very good 92 34.2 54 27.6 65 33.5 Good 91 46.4 109 55.6 102 52.6 Fair/poor 38 19.4 33 29.1 27 13.9 Note: n, number of cases; M, mean; SD, standard deviation. a Including those still in school. Table 1 Sample characteristics (N = 586); trial of proactive alcohol interventions among job-Seekers, 2008/09, Germany Variables Stage tailored Non-stage tailored Assessment only N % N % N % Socio-demographic variables Sex Female 56 28.6 66 33.7 61 31.4 Male 140 71.4 130 66.3 133 68.6 Age in years (M, SD) 31.3 11.2 33.5 12.5 31.2 11.6 Partnership Yes 115 58.7 108 55.1 107 55.2 No 81 41.3 88 44.9 87 44.9 School education <10 years 53 27.0 51 26.0 41 21.1 10–11 years 96 49.0 107 54.6 118 60.8 >11 yeara 47 24.0 38 19.4 35 18.0 Lifetime unemployment in months (M, SD) 26.2 33.5 34.8 42.5 34.0 53.6 Alcohol use AUDIT-C (M, SD) 5.7 1.4 5.8 1.4 5.7 1.4 Motivation to change Precontemplation 152 77.6 147 75.0 139 71.7 Contemplation 20 10.2 23 11.7 19 9.8 Preparation 4 2.0 7 3.6 5 2.6 Action 20 10.2 19 9.7 31 16.0 Self-rated health Excellent/very good 92 34.2 54 27.6 65 33.5 Good 91 46.4 109 55.6 102 52.6 Fair/poor 38 19.4 33 29.1 27 13.9 Variables Stage tailored Non-stage tailored Assessment only N % N % N % Socio-demographic variables Sex Female 56 28.6 66 33.7 61 31.4 Male 140 71.4 130 66.3 133 68.6 Age in years (M, SD) 31.3 11.2 33.5 12.5 31.2 11.6 Partnership Yes 115 58.7 108 55.1 107 55.2 No 81 41.3 88 44.9 87 44.9 School education <10 years 53 27.0 51 26.0 41 21.1 10–11 years 96 49.0 107 54.6 118 60.8 >11 yeara 47 24.0 38 19.4 35 18.0 Lifetime unemployment in months (M, SD) 26.2 33.5 34.8 42.5 34.0 53.6 Alcohol use AUDIT-C (M, SD) 5.7 1.4 5.8 1.4 5.7 1.4 Motivation to change Precontemplation 152 77.6 147 75.0 139 71.7 Contemplation 20 10.2 23 11.7 19 9.8 Preparation 4 2.0 7 3.6 5 2.6 Action 20 10.2 19 9.7 31 16.0 Self-rated health Excellent/very good 92 34.2 54 27.6 65 33.5 Good 91 46.4 109 55.6 102 52.6 Fair/poor 38 19.4 33 29.1 27 13.9 Note: n, number of cases; M, mean; SD, standard deviation. a Including those still in school. The 586 participants who provided data for analyses differed from those unemployed participants who did not provide data for the analyses in terms of motivation to change: they were significantly less often in contemplation (P < 0.05). All other baseline characteristics were not significantly different. A total of n = 537 participated at month 3, and 533 and 450 at the 6- and 15-months follow-ups, respectively. BAI effect on unemployment status As depicted in figure 2, in all study groups, the odds of being unemployed at month 15 significantly decreased (ST: OR = 0.06; 95% CI: 0.01–0.27; NST: OR = 0.04; 95% CI: 0.01–0.18; AO: OR = 0.05; 95% CI: 0.01–0.21). No significant intervention effect on unemployment status was found (table 2). Age (P = 0.002), school education (P = 0.001), self-rated health (P = 0.04), AUDIT-C (P = 0.02) and motivation to change (P = 0.04) significantly affected the development of unemployment over time. Table 2 Latent growth curve model results: intervention effects and covariates for the odds of being unemployed at month 15; Trial of Proactive Alcohol Interventions among job-Seekers, 2008/09, Germany OR 95% CI P value Study group (assessment only)     Stage tailored intervention 1.39 0.59; 3.23 0.53     Non-stage tailored intervention 0.90 0.39; 2.04 0.83     Sex (male) 1.57 0.66; 3.75 0.40     Age 1.08 1.04; 1.13 0.002     Living in a partnership (no) 0.73 0.36; 1.44 0.44 School education (<10 years)     10–11 years 0.12 0.04; 0.36 0.001     >11 years 0.06 0.01; 0.24 0.001     Duration of lifetime unemployment 1.00 0.99; 1.00 0.52     AUDIT-C 1.53 1.13; 2.05 0.02 Motivation to change (precontemplation)     Contemplation 3.05 0.92; 10.04 0.12     Preparation 1.69 0.25; 11.19 0.65     Action 4.45 1.38; 14.31 0.04 Self-rated health (excellent/very good)     Good 1.43 0.65; 3.15 0.46     Fair/poor 4.18 1.31; 13.36 0.04 OR 95% CI P value Study group (assessment only)     Stage tailored intervention 1.39 0.59; 3.23 0.53     Non-stage tailored intervention 0.90 0.39; 2.04 0.83     Sex (male) 1.57 0.66; 3.75 0.40     Age 1.08 1.04; 1.13 0.002     Living in a partnership (no) 0.73 0.36; 1.44 0.44 School education (<10 years)     10–11 years 0.12 0.04; 0.36 0.001     >11 years 0.06 0.01; 0.24 0.001     Duration of lifetime unemployment 1.00 0.99; 1.00 0.52     AUDIT-C 1.53 1.13; 2.05 0.02 Motivation to change (precontemplation)     Contemplation 3.05 0.92; 10.04 0.12     Preparation 1.69 0.25; 11.19 0.65     Action 4.45 1.38; 14.31 0.04 Self-rated health (excellent/very good)     Good 1.43 0.65; 3.15 0.46     Fair/poor 4.18 1.31; 13.36 0.04 Notes: CI, confidence interval, reference categories in parentheses. OR, odds ratios. Significant associations (P < 0.05) are shown in bold. Table 2 Latent growth curve model results: intervention effects and covariates for the odds of being unemployed at month 15; Trial of Proactive Alcohol Interventions among job-Seekers, 2008/09, Germany OR 95% CI P value Study group (assessment only)     Stage tailored intervention 1.39 0.59; 3.23 0.53     Non-stage tailored intervention 0.90 0.39; 2.04 0.83     Sex (male) 1.57 0.66; 3.75 0.40     Age 1.08 1.04; 1.13 0.002     Living in a partnership (no) 0.73 0.36; 1.44 0.44 School education (<10 years)     10–11 years 0.12 0.04; 0.36 0.001     >11 years 0.06 0.01; 0.24 0.001     Duration of lifetime unemployment 1.00 0.99; 1.00 0.52     AUDIT-C 1.53 1.13; 2.05 0.02 Motivation to change (precontemplation)     Contemplation 3.05 0.92; 10.04 0.12     Preparation 1.69 0.25; 11.19 0.65     Action 4.45 1.38; 14.31 0.04 Self-rated health (excellent/very good)     Good 1.43 0.65; 3.15 0.46     Fair/poor 4.18 1.31; 13.36 0.04 OR 95% CI P value Study group (assessment only)     Stage tailored intervention 1.39 0.59; 3.23 0.53     Non-stage tailored intervention 0.90 0.39; 2.04 0.83     Sex (male) 1.57 0.66; 3.75 0.40     Age 1.08 1.04; 1.13 0.002     Living in a partnership (no) 0.73 0.36; 1.44 0.44 School education (<10 years)     10–11 years 0.12 0.04; 0.36 0.001     >11 years 0.06 0.01; 0.24 0.001     Duration of lifetime unemployment 1.00 0.99; 1.00 0.52     AUDIT-C 1.53 1.13; 2.05 0.02 Motivation to change (precontemplation)     Contemplation 3.05 0.92; 10.04 0.12     Preparation 1.69 0.25; 11.19 0.65     Action 4.45 1.38; 14.31 0.04 Self-rated health (excellent/very good)     Good 1.43 0.65; 3.15 0.46     Fair/poor 4.18 1.31; 13.36 0.04 Notes: CI, confidence interval, reference categories in parentheses. OR, odds ratios. Significant associations (P < 0.05) are shown in bold. Figure 2 View largeDownload slide Current unemployment by study group over 15 months; Trial of Proactive Alcohol Interventions among job-Seekers, 2008/09, Germany Figure 2 View largeDownload slide Current unemployment by study group over 15 months; Trial of Proactive Alcohol Interventions among job-Seekers, 2008/09, Germany Discussion We applied latent growth models to investigate the changes in unemployment status in response to two different BAIs and assessment only. Although our stage-tailored BAI reduced alcohol use among job-seekers with initially low motivation to change their drinking,12 we did not find significant study group differences with regard to changes of unemployment status over time. All study groups significantly reduced the odds of being unemployed. Thus, increased re-employment rates in the assessment only group mainly contributed to the lack of intervention effects. A few further explanations are possible. First, we used relatively low cut-off values to identify at-risk drinking. The impact of reducing alcohol use on re-employment might not be as high among at-risk drinkers as the impact of abstaining from alcohol among alcohol dependent job-seekers9 as at-risk drinkers experience lower alcohol problem severity and less negative consequences from drinking.32 Subgroup analyses among those who indicated to binge drink at least once a week neither revealed any intervention effects (results not shown). As the cut-off values used in his study have been criticized for generating false-positives,33 our study may also include false-positives, obscuring potential intervention effects. Secondly, the dosage of BAI might have been too low to have an impact on re-employment. There are findings showing that the effect of BAIs increases with higher numbers of intervention contacts.34 However, in Finland a comprehensive health care intervention over three years could not improve the chances of being re-employed.35 Third, the negative effects of unemployment very much depend on the national compensation systems. For example, a previous US study found that without monetary compensation at-risk drinking increased among individuals who experienced periods of unemployment, while with compensation at-risk drinking did not differ from stably employed individuals.36 In Germany, financial benefits are commonly paid and might compensate negative effects of unemployment that lead to health risk behaviors and further unemployment. Therefore, our findings need to be studied in other areas beyond Germany. Growing chances of being re-employed are mediated by improvement of health status.4,5 Our study confirmed that higher initial self-rated health and reduced alcohol use were both associated with lower odds of being unemployed after 15 months. Thus, it might be expected that BAIs that result in reduced at-risk drinking and in improved health can be helpful in improving chances to be re-employed. However, this is a longsome process with results that might not be observed within 15 months. Individuals who initially indicated high motivation to change (being in ‘action’) had higher odds of being unemployed after 15 months. It might be suspected that these as well suffer from higher problem severity compared to those with lower motivation to change37 and thereby getting re-employed is impeded. However, this was a rather small group within our sample and results should be regarded with caution. Given the effectiveness of our stage-tailored intervention concerning reduced alcohol use among job-seekers with initially low motivation to change, we calculated subgroup analyses for each motivational stage of change and for collapsed subgroups. However, no intervention effect could be found in neither of the subgroup analyses (results not shown). Several study limitations should be taken into account. Firstly, measurement of current unemployment status differed at different time points. At baseline and month 3, participants were asked about being currently unemployed; at both follow-ups they were asked about being employed. Although answers were categorized equally for all time points as ‘unemployed’ or ‘not unemployed’, information might have been lost and the operationalization might be prone to distortion. Secondly, recruitment was done at three job agencies and the analyses should at best be controlled for recruitment site. However, as the job agencies’ different areas of responsibility and duration of life-time unemployment involved one another, we could not control for recruitment site in addition to duration of lifetime unemployment. Thirdly, the sample was recruited from one single area characterized by an elevated unemployment rate in comparison to Germany in general (2008: Mecklenburg–Western Pomerania: 14.1% vs. Germany: 7.8%38) and to Europe (2008: 7.0%39). Thus, despite personal factors, structural aspects as well might have a great impact on re-employment. Fourthly, further factors such as mental health which was not assessed in our study but is associated to unemployment3 might influence re-employment itself as well as intervention effects on re-employment; and should be considered in future research. Despite these limitations, three main strengths should be mentioned: Firstly, this study provides findings on long-term effects of BAIs in non-medical settings beyond year 1. Secondly, our sample was recruited proactively at job agencies which may have contributed to a high proportion of participants with low socioeconomic status, a subpopulation otherwise hard to reach for health research.40 Thirdly, LGMs were conducted, giving the opportunity to model the trajectories of unemployment status over a period of 15 months and how these trajectories vary among individuals who were assigned to different study groups and with differences concerning socio-demographic and socio-economic background as well as health behavior. Further LGMs are suitable to handle missing data properly. Acknowledgements The authors appreciate Stefanie Tobschall and the study staff for collecting the data, the study participants for providing information, and the staff of the three job agencies for supporting our study (Agentur für Arbeit Greifswald, Agentur für Arbeit Stralsund, Job-Center Stralsund). Funding The study was funded by the German Research Foundation (FR2661/1-1, FR2661/1-2). Work on this paper was funded by the German Cancer Aid (108376, 109737, 110676, 110543, 111346), the State Graduate Funding (K.H.) and the Alfried Krupp von Bohlen and Halbach Foundation (S.B.). The founders were not involved in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript. Conflicts of interest: None declared. Key points Among alcohol at-risk drinkers who were initially unemployed our brief alcohol interventions (BAIs) had no significant effect on unemployment status over a period of 15 months. The lack of intervention effect is most likely due to the high re-employment rate in both intervention groups as well as the assessment only group. However, as better initial self-rated health and lower amounts of alcohol use were both associated with being re-employed after 15 months, it might be expected that BAIs resulting in reduced at-risk drinking and in improved health can be helpful in improving chances of re-employment. Those mediated effects of BAIs on unemployment could be a longsome process needing longer follow-ups to be detected. BAI effects on further aspects of quality of life such as physical and mental health should be investigated. References 1 Janlert U . Unemployment as a desease and diseases of the unemployed . Scand J Work Environ Health 1997 ; 23 : 79 – 83 . Google Scholar PubMed 2 Norström F , Virtanen P , Hammarström A , et al. How does unemployment affect self-assessed health? A systematic review focusing on subgroup effects . BMC Public Health 2014 ; 14 : 1310 . Google Scholar CrossRef Search ADS PubMed 3 Van Der Noordt M , Uzelenberg H , Droomers M , et al. 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Curr Drug Abuse Rev 2011 ; 4 : 4 – 27 . Google Scholar CrossRef Search ADS PubMed 8 Eliason M . Alcohol-related morbidity and mortality following involuntary job loss: Evidence from Swedish register data . J Stud Alcohol Drugs 2014 ; 75 : 35 – 46 . Google Scholar CrossRef Search ADS PubMed 9 Burtscheidt W , Schwarz R , Wölwer W , et al. Outpatient behavioural treatment in alcoholism: alcohol consumption and sociodemographic factors . Fortschr Neurol Psychiatr 2001 ; 69 : 526 – 31 . Google Scholar CrossRef Search ADS PubMed 10 NIAAA . Available at: www.niaaa.nih.gov/alcohol-health/overview-alcohol-consumption/moderate-binge-drinking (9 March 2017, date last accessed). 11 Alvarez-Bueno C , Rodriguez-Martin B , Garcia-Ortiz L , et al. Effectiveness of brief interventions in primary health care settings to decrease alcohol consumption by adult non-dependent drinkers: a systematic review of systematic reviews . Prev Med 2015 ; 76(Suppl.) : 33 – 8 . Google Scholar CrossRef Search ADS 12 Freyer-Adam J , Baumann S , Schnuerer I , et al. Does stage tailoring matter in brief alcohol interventions for job-seekers? A randomized controlled trial . Addiction 2014 ; 109 : 1845 – 56 . Google Scholar CrossRef Search ADS PubMed 13 Prochaska JO , Velicer WF . The transtheoretical model of health behavior change . Am J Health Promot 1997 ; 12 : 38 – 48 . Google Scholar CrossRef Search ADS PubMed 14 Prochaska JO , DiClemente CC , Norcross JC . In search of how people change: Applications to addictive behaviors . Am Psychol 1992 ; 47 : 1102 – 14 . Google Scholar CrossRef Search ADS PubMed 15 Ajzen I . The theory of planned behavior . Organ Behav Hum Decis Process 1991 ; 50 : 179 – 211 . Google Scholar CrossRef Search ADS 16 Weinstein ND , Rothman AJ , Suton SR . Stage theories of health behavior: conceptual and methodological issues . Health Psychol 1998 ; 17 : 290 – 9 . Google Scholar CrossRef Search ADS PubMed 17 West R . Time for a change: putting the Transtheoretical (Stages of Change) Model to rest . Addiction 2005 ; 100 : 1036 – 9 . Google Scholar CrossRef Search ADS PubMed 18 Bridle C , Riemsma RP , Pattenden J , et al. Systematic review of the effectiveness of health behavior interventions based on the transtheoretical model . Psychol Health 2005 ; 20 : 283 – 301 . Google Scholar CrossRef Search ADS 19 Webb TL , Joseph J , Yardley L , Michie S . Using the Internet to promote health behavior change: a systematic review and meta-analysis of the impact of theoretical basis, use of behavior change techniques, and mode of delivery on efficacy . J Med Internet Res 2010 ; 12 : e4 . Google Scholar CrossRef Search ADS PubMed 20 Freyer-Adam J , Gaertner B , Tobschall S , John U . Health risk factors and self-rated health among job-seekers . BMC Public Health (Online Journal) 2011 ; 11 : 659 . Google Scholar CrossRef Search ADS 21 Bush K , Kivlahan DR , McDonell MB , et al. The AUDIT alcohol consumption questions (AUDIT-C): an effective brief screening test for problem drinking. Ambulatory care quality improvement project (ACQUIP). Alcohol use disorders identification test . Arch Intern Med 1998 ; 158 : 1789 – 95 . Google Scholar CrossRef Search ADS PubMed 22 Reinert D , Allen J . The alcohol use disorders identification test: an update of research findings . Alcohol Clin Exp Res 2007 ; 31 : 185 – 99 . Google Scholar CrossRef Search ADS PubMed 23 Saunders JB , Aasland OG , Babor TF , et al. Development of the Alcohol Use Disorders Identification Test (AUDIT): WHO collaborative project on early detection of persons with harmful alcohol consumption Part II . Addiction 1993 ; 88 : 617 – 29 . 24 Donovan DM , Kivlahan DR , Doyle SR , et al. Concurrent validity of the Alcohol Use Disorders Identification Test (AUDIT) and AUDIT zones in defining levels of severity among out-patients with alcohol dependence in the COMBINE study . Addiction 2006 ; 101 : 1696 – 704 . Google Scholar CrossRef Search ADS PubMed 25 Hannöver W , Thyrian JR , Hapke U , et al. The readiness to change questionnaire in subjects with hazardous alcohol consumption, alcohol misuse and dependence in a general population survey . Alcohol Alcohol 2002 ; 37 : 362 – 9 . Google Scholar CrossRef Search ADS PubMed 26 Rollnick S , Heather N , Gold R , Hall W . Development of a short ′readiness to change′ questionnaire for use in brief, opportunistic interventions among excessive drinkers . Br J Addict 1992 ; 87 : 743 – 54 . Google Scholar CrossRef Search ADS PubMed 27 Heather N , Rollnick S , Bell A . Predictive validity of the readiness to change questionnaire . Addiction 1993 ; 88 : 1667 – 77 . Google Scholar CrossRef Search ADS PubMed 28 Idler . Self-rated health and mortality: a review of twenty-seven community studies . J Health Soc Behav 1997 ; 38 : 21 – 37 . CrossRef Search ADS PubMed 29 StataCorp . Stata Statistical Software: Release 12. College Station , TX : Stata Corp LP , 2011 . 30 Muthén LK , Muthén BO . Mplus User's Guide . 6th edn Los Angeles : Muthén & Muthén , 1998 -2010. 31 Little RJ , Rubin DB . Statistical Analysis with Missing Data . 2nd edn New York : John Wiley & Sons , 2002 . Google Scholar CrossRef Search ADS 32 Reinhardt S , Bischof G , Grothues J , et al. Performance of the pictorial representation of illness and self measure in individuals with alcohol dependence, alcohol abuse or at-risk drinking . Psychother Pschosom 2006 ; 75 : 249 – 56 . Google Scholar CrossRef Search ADS 33 Delaney KE , Lee AK , Lapham GT , et al. Inconsistencies between alcohol screening results based on AUDIT-C scores and reported drinking on the AUDIT-C questions: prevalence in two US national samples . Addict Sci Clin Pract 2014 ; 9 : 2 . Google Scholar CrossRef Search ADS PubMed 34 Mdege ND , Fayter D , Watson JM , et al. Interventions for reducing alcohol consumption among general hospital inpatient heavy alcohol users: a systematic review . Drug Alcohol Depend 2013 ; 131 : 1 – 22 . Google Scholar CrossRef Search ADS PubMed 35 Romppainen K , Saloniemi A , Kinnunen U , et al. Does provision of targeted health care for the unemployed enhance re-employment? BMC Public Health 2014 ; 14 : 1200 . Google Scholar CrossRef Search ADS PubMed 36 Bolton KL , Rodriguez E . Smoking, drinking and body weight afer re-employment: does unemployment experience and compensation make a difference? BMC Public Health 2009 ; 9 : 77 . Google Scholar CrossRef Search ADS PubMed 37 Williams EC , Kivlahan DR , Saitz R , et al. Readiness to change in primary care patients who screened positive for alcohol misuse . Ann Fam Med 2006 ; 4 : 213 – 20 . Google Scholar CrossRef Search ADS PubMed 38 Federal Statistical Office . Germany—The Country and its People . Wiesbaden : Federal Statistical Office ; 2009 . 39 European Commission. Unemployment rate by sex and age groups - annual average. 2014 http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=une_rt_a&lang=en (9 March 2017, date last accessed). 40 Bender AM , Jorgensen T , Helbech B , et al. Socioeconomic position and participation in baseline and follow-up visits: the Inter99 study . Eur J Prev Cardiol 2014 ; 21 : 899 – 905 . Google Scholar CrossRef Search ADS PubMed © The Author 2017. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The European Journal of Public Health Oxford University Press

Do brief alcohol interventions among unemployed at-risk drinkers increase re-employment after 15 month?

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Oxford University Press
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© The Author 2017. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.
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1101-1262
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1464-360X
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10.1093/eurpub/ckx142
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Abstract

Abstract Background At-risk alcohol use is associated bi-directionally to unemployment, and decreases chances of re-employment. Brief alcohol interventions (BAI) can reduce at-risk alcohol use. This study aimed to investigate 15-month effects of BAI on unemployment among persons with at-risk alcohol use. Methods As part of the randomized controlled ‘Trial on proactive alcohol interventions among job-seekers, TOPAS’, 1243 18- to 64-year-old job-seekers with at-risk alcohol use were systematically recruited at three job agencies in Germany (2008/09), and randomized to (i) a stage tailored intervention based on the trans-theoretical model of intentional behavior change (ST), (ii) a non-stage tailored intervention based on the theory of planned behavior (NST) and (iii) assessment only (AO). To test the effects of ST and NST on employment status 15 months after baseline, latent growth models were calculated among those initially unemployed (n = 586). Results In all three groups, unemployment significantly decreased over 15 months (ST: odds ratio, OR = 0.06; 95% confidence interval, CI: 0.01–0.27; NST: OR = 0.04; 95% CI: 0.01–0.18; AO: OR = 0.05; 95% CI: 0.01–0.21). No intervention effects were found on unemployment. Age (P = 0.002), school education (P = 0.001), self-rated health (P = 0.04), the Alcohol Use Disorder Identification Test-Consumption score (P = 0.02) and motivation to change (P = 0.04) significantly affected the development of unemployment over time. Conclusion After 15 months, no BAI effect on unemployment was found. The mediated effect of BAIs on unemployment could be a longsome process needing longer follow-ups to be detected. Introduction Unemployment has been shown to be associated bi-directionally to health and health behaviors.1 While unemployment affects indicators of physical2 and mental health adversely,3 studies also showed that health risk behaviors and suboptimal health increase the risk of becoming unemployed and lower the chances to be re-employed.4 Consequently, employability might be enhanced by improving health behavior and health status of unemployed individuals.5 Thus, unemployed individuals are in special need for interventions on health behavior.6 One possible approach might be reducing at-risk alcohol use7 as alcohol-related morbidity was shown to be associated to unemployment.8 An intervention among individuals with alcohol dependence was shown to successfully increase rates of abstinence and chances to be re-employed.9 Similarly, chances of re-employment might be enhanced among at-risk drinkers. At-risk drinking may be defined as more than seven drinks per week or more than three drinks per occasion for women and more than 14 drinks per week or more than 4 drinks per occasion for men.10 Brief alcohol interventions seem to be promising in reducing at-risk alcohol use;11 also among job-seekers with initially low motivation to change drinking.12 However, only few studies have investigated BAI effects on other, although closely related life-domains. In a preceding study we showed that the theoretical background used for designing interventions for populations with primarily low motivation to change alcohol use, makes a difference concerning their efficacy.12 We tested two theory based interventions. Intervention A was based on the trans-theoretical model of intentional behavior change (TTM13) representing ‘stage models’. These models assume that behavior change happens in distinct motivational stages, and that interventions are most effective when tailored to the individual stage of motivation. According to the TTM, individuals move from not thinking about change (precontemplation), through being ambivalent about change (contemplation), planning to change (preparation) and manifesting change (action) to maintaining change (maintenance). Cognitive-affective and behavioral processes of change help people move through the early and later stages, respectively.14 Moving through the stages is associated with changes in the perception of the pros and cons of change (decisional balance) and one’s own situation-specific belief in the ability to change (self efficacy). Intervention B was based on the theory of planned behavior (TPB; Ref. 15) representing ‘continuous’ behavior theories that assume that a single prediction equation is valid for all individuals.16 The stage concept has been often criticized due to scarce evidence for the existence of mutually distinctive stages and sequential movement through these stages17 and due lack of convincing intervention effects.18 However, lack of intervention effects has been explained by the neglect of the multiple dimensions of the stage models.18 Interventions that incorporate the multiple dimensions of behavior change theories, and of the TTM in particular, show more convincing intervention effects.19 In line with these findings our multiple-dimension stage-tailored intervention significantly reduced alcohol use after 15 months among job-seekers with initially low motivation to change compared to the non-stage tailored and no intervention. However, it remains unclear whether these BAIs may have had an effect on unemployment status after 15 months. In this secondary outcome paper we aimed to investigate whether the stage and/or non-stage tailored BAI reduced unemployment among unemployed individuals over a period of 15 months. We hypothesized that the above described stage tailored BAI might as well lead to a decrease of unemployment in comparison to the non-stage tailored or no BAI. Methods The study presents secondary outcome data of the three arm randomized controlled trial ‘Trial Of Proactive Alcohol interventions among job-Seekers, TOPAS’ (ClinicalTrials.gov Identifier: NCT01311245) described in more detail elsewhere.12 TOPAS was conducted by the Research Collaboration on Early Intervention in health risk behaviors (EARLINT) in Western Pomerania, northeastern Germany. Informed consent was provided by all trial participants. The local ethics committee of the University Medicine Greifswald approved the study. Interventions Both interventions, the stage tailored (ST) and the non-stage tailored (NST), consisted of two individualized computer-generated 3–4 page feedback letters and self-help manuals, each delivered by mail in response to preceding assessments. The baseline assessment was conducted on the ward and a 3-month assessment was conducted by phone. In both intervention groups, baseline letters included normative feedback, e.g. on ones own drinking and responses to theoretical constructs in comparison to others. Both 3-months letters included normative and ipsative feedback, i.e. on intra-individual changes between time points. ST: Normative and ipsative feedback on the main TTM constructs (decisional balance, self-efficacy, processes of change) was dependent on stage of change. Feedback letters were accompanied by a stage-matched manual for further information, advice and practice. NST: To provide non-stage tailored feedback, assessment data on TPB constructs (attitude, subjective norm, perceived behavioral control, according beliefs and their evaluations) were used, accompanied by information and/or advice and a standard manual. Each text module was independent of any other TPB construct. Assessment only (AO): The AO control group received minimal assessments and no further intervention. Recruitment As described elsewhere,20 the sample was recruited at three job agencies over 12 months in 2008/09. In Germany, unemployed individuals, those threatened by unemployment, and those below minimal income register at government or municipal owned job agencies to receive unemployment benefit and/or health insurance coverage. There are two types of job agencies with different responsibilities. While type A job-agencies care for the not yet and short-term unemployed (up to 12 months) job-seekers, type B job-agencies care for the long-term unemployed job-seekers (more than 12 months). This study was conducted at two type A and at one type B job agency. Study assistants asked all adults, who appeared in the waiting area to fill in a questionnaire on health behaviors provided by electronic handheld computers (figure 1). Exclusion criteria were: being younger than 18 or older than 64 years, being cognitively or physically incapable, having insufficient German language or reading skills, being already recruited during an earlier visit and being an escorting person. A total of 7396 job-seekers (74.6% of those eligible) participated and provided evaluable alcohol screening measures. Those who screened positive for at-risk alcohol use and negative for particular severe alcohol problems (n = 1717; 23.2%) were eligible and asked to participate in TOPAS. At-risk alcohol use was determined using the Alcohol Use Disorder Identification Test-Consumption (AUDIT-C; Ref. 21) with gender-specific cut-off values of 4 for women and 5 for men.22 Individuals with particularly severe alcohol problems at baseline were identified and excluded from further participation using the total AUDIT score23 and values ≥ 20.24 In total, 1243 job-seekers (72.4%) received their allocated intervention (ST, NST or AO). Trial participants received a voucher of €10 by mail. As the aim of this secondary outcome study was to investigate the effect of BAI on unemployment, it includes n = 642 participants unemployed at baseline. Figure 1 View largeDownload slide Participant flow of unemployed participants as part of the Trial of Proactive Alcohol Interventions among job-Seekers, 2008/09, Germany Figure 1 View largeDownload slide Participant flow of unemployed participants as part of the Trial of Proactive Alcohol Interventions among job-Seekers, 2008/09, Germany Further assessments and follow-ups The 3-month assessment and the 6- and 15-month follow-ups were predominantly conducted as computer-assisted telephone interviews. If 10 contact attempts failed, participants received an according questionnaire by mail or were contacted at their homes. The 6-month follow-up participants received a voucher of €30; the 15-month follow-up participants took part in a lottery drawing of 20 vouchers of €50. Measures Dependent variable Unemployment status at baseline and at month 3 was assessed using a single item with three response categories: ‘Are you currently (1) unemployed, (2) not unemployed but job-seeking or (3) neither 1/nor 2?’ Those answering with category ‘(1) were categorized as ‘unemployed’, all others as ‘not unemployed’. Unemployment status at months 6 and 15 was assessed using two items. Item 1 asked ‘Are you currently employed?’ with four response categories: ‘(0) no, (1) full-time employed with at least 35 working hours a week, (2) part-time employed with 15-34 working hours a week, (3) part-time employed or employed with less than 15 working hours a week.’ People who responded (0) or (3) received item 2 ‘Are you then: (1) still in school or studying, (2) less than 6 months unemployed (3) up to 2 years unemployed (4) more than 2 years unemployed, (5) a housewife, (6) military service, (7) maternity leave, (8) retired?’. Those responding with categories (2), (3) or (4) were categorized as ‘unemployed’, all others as ‘not unemployed’. Covariates ‘Socio-demographic variables’ included sex, age in years, living in a steady partnership (yes/no), school education and duration of lifetime unemployment in months. For international comparability common German types of school education were categorized as: less than 10 years, 10–11 years, and more than 11 years of school (including those still in school). All variables were assessed at baseline. ‘At-risk alcohol use’ was determined at baseline using the AUDIT-C.21 Three items assess frequency of drinking, number of drinks per occasion, and frequency of drinking six or more drinks per occasion. The AUDIT-C sum score ranges from 0 to 12. ‘Motivation to change’ was assessed using the German version25 of the RCQ.26 The 12-item RCQ consists of three subscales [precontemplation (pc), contemplation (c), action (ac)], with four items each and a five-point Likert scale [strongly disagree (−2)/strongly agree (+2)]. As described elsewhere12 two methods of stage allocation were applied consecutively. The RCQ has been reported to be valid in predicting behavior change over time.27 ‘Self-rated health’ was assessed at baseline with the question ‘Would you say your health in general is: excellent (1), very good (2), good (3), fair (4), poor (5)?’ This item is known to be an independent predictor of mortality.28 To achieve reasonable group sizes for analyses, the categories (1) and (2) as well as (4) and (5) were collapsed. Data analysis Descriptive statistics and drop-out analyses were conducted with Stata version 12.29 Intervention effects on unemployment status were investigated calculating a latent growth model (LGM) conducted with Mplus version 6.12.30 The LGM examined the development of the probability of unemployment over time. Individual differences in development were captured by random effects or latent growth factors representing the probability of unemployment at month 15 (intercept, time scores: 1, 1, 1) and the linear rate of change from month 3 to month 15 (slope, time scores: −4, −3, 0). Unemployment was modeled as a binary variable, i.e. unemployed (1) vs. no longer unemployed (0) was regressed on the growth factors using a logit model. Maximum likelihood estimation with robust standard errors was applied using all available data (i.e. all participants who completed at least the 3 months-assessment or one of the two follow-ups contributed information, n = 588) under a missing at random assumption (MAR31). To allow for chance imbalances and to make the MAR assumption more plausible, baseline variables (sex, age, living in a partnership, school education, duration of lifetime unemployment, self-rated health, AUDIT-C and motivation to change) were included as covariates. Two cases were excluded from the analysis due to missing values on the covariate ‘duration of lifetime unemployment’, resulting in 586 cases, included in the final analyses. For reasons of interpretability age, duration of lifetime unemployment and AUDIT-C were mean centered. To test the effect of BAI on unemployment, the two latent growth factors were regressed on study group. Odds ratios (OR) and 95%-confidence intervals (CI) are presented. A P values < 0.05 was considered significant. Results Sample characteristics Of the sample (n = 586; ST: n = 196; NST: n = 196; AO: n = 194), 403 (68.8%) were male (table 1). The mean age was 32.0 (SD=11.8) years. The mean duration of life-time unemployment was 31.6 months (SD = 44.0). The mean AUDIT-C score was 5.7 (SD = 1.4). Table 1 Sample characteristics (N = 586); trial of proactive alcohol interventions among job-Seekers, 2008/09, Germany Variables Stage tailored Non-stage tailored Assessment only N % N % N % Socio-demographic variables Sex Female 56 28.6 66 33.7 61 31.4 Male 140 71.4 130 66.3 133 68.6 Age in years (M, SD) 31.3 11.2 33.5 12.5 31.2 11.6 Partnership Yes 115 58.7 108 55.1 107 55.2 No 81 41.3 88 44.9 87 44.9 School education <10 years 53 27.0 51 26.0 41 21.1 10–11 years 96 49.0 107 54.6 118 60.8 >11 yeara 47 24.0 38 19.4 35 18.0 Lifetime unemployment in months (M, SD) 26.2 33.5 34.8 42.5 34.0 53.6 Alcohol use AUDIT-C (M, SD) 5.7 1.4 5.8 1.4 5.7 1.4 Motivation to change Precontemplation 152 77.6 147 75.0 139 71.7 Contemplation 20 10.2 23 11.7 19 9.8 Preparation 4 2.0 7 3.6 5 2.6 Action 20 10.2 19 9.7 31 16.0 Self-rated health Excellent/very good 92 34.2 54 27.6 65 33.5 Good 91 46.4 109 55.6 102 52.6 Fair/poor 38 19.4 33 29.1 27 13.9 Variables Stage tailored Non-stage tailored Assessment only N % N % N % Socio-demographic variables Sex Female 56 28.6 66 33.7 61 31.4 Male 140 71.4 130 66.3 133 68.6 Age in years (M, SD) 31.3 11.2 33.5 12.5 31.2 11.6 Partnership Yes 115 58.7 108 55.1 107 55.2 No 81 41.3 88 44.9 87 44.9 School education <10 years 53 27.0 51 26.0 41 21.1 10–11 years 96 49.0 107 54.6 118 60.8 >11 yeara 47 24.0 38 19.4 35 18.0 Lifetime unemployment in months (M, SD) 26.2 33.5 34.8 42.5 34.0 53.6 Alcohol use AUDIT-C (M, SD) 5.7 1.4 5.8 1.4 5.7 1.4 Motivation to change Precontemplation 152 77.6 147 75.0 139 71.7 Contemplation 20 10.2 23 11.7 19 9.8 Preparation 4 2.0 7 3.6 5 2.6 Action 20 10.2 19 9.7 31 16.0 Self-rated health Excellent/very good 92 34.2 54 27.6 65 33.5 Good 91 46.4 109 55.6 102 52.6 Fair/poor 38 19.4 33 29.1 27 13.9 Note: n, number of cases; M, mean; SD, standard deviation. a Including those still in school. Table 1 Sample characteristics (N = 586); trial of proactive alcohol interventions among job-Seekers, 2008/09, Germany Variables Stage tailored Non-stage tailored Assessment only N % N % N % Socio-demographic variables Sex Female 56 28.6 66 33.7 61 31.4 Male 140 71.4 130 66.3 133 68.6 Age in years (M, SD) 31.3 11.2 33.5 12.5 31.2 11.6 Partnership Yes 115 58.7 108 55.1 107 55.2 No 81 41.3 88 44.9 87 44.9 School education <10 years 53 27.0 51 26.0 41 21.1 10–11 years 96 49.0 107 54.6 118 60.8 >11 yeara 47 24.0 38 19.4 35 18.0 Lifetime unemployment in months (M, SD) 26.2 33.5 34.8 42.5 34.0 53.6 Alcohol use AUDIT-C (M, SD) 5.7 1.4 5.8 1.4 5.7 1.4 Motivation to change Precontemplation 152 77.6 147 75.0 139 71.7 Contemplation 20 10.2 23 11.7 19 9.8 Preparation 4 2.0 7 3.6 5 2.6 Action 20 10.2 19 9.7 31 16.0 Self-rated health Excellent/very good 92 34.2 54 27.6 65 33.5 Good 91 46.4 109 55.6 102 52.6 Fair/poor 38 19.4 33 29.1 27 13.9 Variables Stage tailored Non-stage tailored Assessment only N % N % N % Socio-demographic variables Sex Female 56 28.6 66 33.7 61 31.4 Male 140 71.4 130 66.3 133 68.6 Age in years (M, SD) 31.3 11.2 33.5 12.5 31.2 11.6 Partnership Yes 115 58.7 108 55.1 107 55.2 No 81 41.3 88 44.9 87 44.9 School education <10 years 53 27.0 51 26.0 41 21.1 10–11 years 96 49.0 107 54.6 118 60.8 >11 yeara 47 24.0 38 19.4 35 18.0 Lifetime unemployment in months (M, SD) 26.2 33.5 34.8 42.5 34.0 53.6 Alcohol use AUDIT-C (M, SD) 5.7 1.4 5.8 1.4 5.7 1.4 Motivation to change Precontemplation 152 77.6 147 75.0 139 71.7 Contemplation 20 10.2 23 11.7 19 9.8 Preparation 4 2.0 7 3.6 5 2.6 Action 20 10.2 19 9.7 31 16.0 Self-rated health Excellent/very good 92 34.2 54 27.6 65 33.5 Good 91 46.4 109 55.6 102 52.6 Fair/poor 38 19.4 33 29.1 27 13.9 Note: n, number of cases; M, mean; SD, standard deviation. a Including those still in school. The 586 participants who provided data for analyses differed from those unemployed participants who did not provide data for the analyses in terms of motivation to change: they were significantly less often in contemplation (P < 0.05). All other baseline characteristics were not significantly different. A total of n = 537 participated at month 3, and 533 and 450 at the 6- and 15-months follow-ups, respectively. BAI effect on unemployment status As depicted in figure 2, in all study groups, the odds of being unemployed at month 15 significantly decreased (ST: OR = 0.06; 95% CI: 0.01–0.27; NST: OR = 0.04; 95% CI: 0.01–0.18; AO: OR = 0.05; 95% CI: 0.01–0.21). No significant intervention effect on unemployment status was found (table 2). Age (P = 0.002), school education (P = 0.001), self-rated health (P = 0.04), AUDIT-C (P = 0.02) and motivation to change (P = 0.04) significantly affected the development of unemployment over time. Table 2 Latent growth curve model results: intervention effects and covariates for the odds of being unemployed at month 15; Trial of Proactive Alcohol Interventions among job-Seekers, 2008/09, Germany OR 95% CI P value Study group (assessment only)     Stage tailored intervention 1.39 0.59; 3.23 0.53     Non-stage tailored intervention 0.90 0.39; 2.04 0.83     Sex (male) 1.57 0.66; 3.75 0.40     Age 1.08 1.04; 1.13 0.002     Living in a partnership (no) 0.73 0.36; 1.44 0.44 School education (<10 years)     10–11 years 0.12 0.04; 0.36 0.001     >11 years 0.06 0.01; 0.24 0.001     Duration of lifetime unemployment 1.00 0.99; 1.00 0.52     AUDIT-C 1.53 1.13; 2.05 0.02 Motivation to change (precontemplation)     Contemplation 3.05 0.92; 10.04 0.12     Preparation 1.69 0.25; 11.19 0.65     Action 4.45 1.38; 14.31 0.04 Self-rated health (excellent/very good)     Good 1.43 0.65; 3.15 0.46     Fair/poor 4.18 1.31; 13.36 0.04 OR 95% CI P value Study group (assessment only)     Stage tailored intervention 1.39 0.59; 3.23 0.53     Non-stage tailored intervention 0.90 0.39; 2.04 0.83     Sex (male) 1.57 0.66; 3.75 0.40     Age 1.08 1.04; 1.13 0.002     Living in a partnership (no) 0.73 0.36; 1.44 0.44 School education (<10 years)     10–11 years 0.12 0.04; 0.36 0.001     >11 years 0.06 0.01; 0.24 0.001     Duration of lifetime unemployment 1.00 0.99; 1.00 0.52     AUDIT-C 1.53 1.13; 2.05 0.02 Motivation to change (precontemplation)     Contemplation 3.05 0.92; 10.04 0.12     Preparation 1.69 0.25; 11.19 0.65     Action 4.45 1.38; 14.31 0.04 Self-rated health (excellent/very good)     Good 1.43 0.65; 3.15 0.46     Fair/poor 4.18 1.31; 13.36 0.04 Notes: CI, confidence interval, reference categories in parentheses. OR, odds ratios. Significant associations (P < 0.05) are shown in bold. Table 2 Latent growth curve model results: intervention effects and covariates for the odds of being unemployed at month 15; Trial of Proactive Alcohol Interventions among job-Seekers, 2008/09, Germany OR 95% CI P value Study group (assessment only)     Stage tailored intervention 1.39 0.59; 3.23 0.53     Non-stage tailored intervention 0.90 0.39; 2.04 0.83     Sex (male) 1.57 0.66; 3.75 0.40     Age 1.08 1.04; 1.13 0.002     Living in a partnership (no) 0.73 0.36; 1.44 0.44 School education (<10 years)     10–11 years 0.12 0.04; 0.36 0.001     >11 years 0.06 0.01; 0.24 0.001     Duration of lifetime unemployment 1.00 0.99; 1.00 0.52     AUDIT-C 1.53 1.13; 2.05 0.02 Motivation to change (precontemplation)     Contemplation 3.05 0.92; 10.04 0.12     Preparation 1.69 0.25; 11.19 0.65     Action 4.45 1.38; 14.31 0.04 Self-rated health (excellent/very good)     Good 1.43 0.65; 3.15 0.46     Fair/poor 4.18 1.31; 13.36 0.04 OR 95% CI P value Study group (assessment only)     Stage tailored intervention 1.39 0.59; 3.23 0.53     Non-stage tailored intervention 0.90 0.39; 2.04 0.83     Sex (male) 1.57 0.66; 3.75 0.40     Age 1.08 1.04; 1.13 0.002     Living in a partnership (no) 0.73 0.36; 1.44 0.44 School education (<10 years)     10–11 years 0.12 0.04; 0.36 0.001     >11 years 0.06 0.01; 0.24 0.001     Duration of lifetime unemployment 1.00 0.99; 1.00 0.52     AUDIT-C 1.53 1.13; 2.05 0.02 Motivation to change (precontemplation)     Contemplation 3.05 0.92; 10.04 0.12     Preparation 1.69 0.25; 11.19 0.65     Action 4.45 1.38; 14.31 0.04 Self-rated health (excellent/very good)     Good 1.43 0.65; 3.15 0.46     Fair/poor 4.18 1.31; 13.36 0.04 Notes: CI, confidence interval, reference categories in parentheses. OR, odds ratios. Significant associations (P < 0.05) are shown in bold. Figure 2 View largeDownload slide Current unemployment by study group over 15 months; Trial of Proactive Alcohol Interventions among job-Seekers, 2008/09, Germany Figure 2 View largeDownload slide Current unemployment by study group over 15 months; Trial of Proactive Alcohol Interventions among job-Seekers, 2008/09, Germany Discussion We applied latent growth models to investigate the changes in unemployment status in response to two different BAIs and assessment only. Although our stage-tailored BAI reduced alcohol use among job-seekers with initially low motivation to change their drinking,12 we did not find significant study group differences with regard to changes of unemployment status over time. All study groups significantly reduced the odds of being unemployed. Thus, increased re-employment rates in the assessment only group mainly contributed to the lack of intervention effects. A few further explanations are possible. First, we used relatively low cut-off values to identify at-risk drinking. The impact of reducing alcohol use on re-employment might not be as high among at-risk drinkers as the impact of abstaining from alcohol among alcohol dependent job-seekers9 as at-risk drinkers experience lower alcohol problem severity and less negative consequences from drinking.32 Subgroup analyses among those who indicated to binge drink at least once a week neither revealed any intervention effects (results not shown). As the cut-off values used in his study have been criticized for generating false-positives,33 our study may also include false-positives, obscuring potential intervention effects. Secondly, the dosage of BAI might have been too low to have an impact on re-employment. There are findings showing that the effect of BAIs increases with higher numbers of intervention contacts.34 However, in Finland a comprehensive health care intervention over three years could not improve the chances of being re-employed.35 Third, the negative effects of unemployment very much depend on the national compensation systems. For example, a previous US study found that without monetary compensation at-risk drinking increased among individuals who experienced periods of unemployment, while with compensation at-risk drinking did not differ from stably employed individuals.36 In Germany, financial benefits are commonly paid and might compensate negative effects of unemployment that lead to health risk behaviors and further unemployment. Therefore, our findings need to be studied in other areas beyond Germany. Growing chances of being re-employed are mediated by improvement of health status.4,5 Our study confirmed that higher initial self-rated health and reduced alcohol use were both associated with lower odds of being unemployed after 15 months. Thus, it might be expected that BAIs that result in reduced at-risk drinking and in improved health can be helpful in improving chances to be re-employed. However, this is a longsome process with results that might not be observed within 15 months. Individuals who initially indicated high motivation to change (being in ‘action’) had higher odds of being unemployed after 15 months. It might be suspected that these as well suffer from higher problem severity compared to those with lower motivation to change37 and thereby getting re-employed is impeded. However, this was a rather small group within our sample and results should be regarded with caution. Given the effectiveness of our stage-tailored intervention concerning reduced alcohol use among job-seekers with initially low motivation to change, we calculated subgroup analyses for each motivational stage of change and for collapsed subgroups. However, no intervention effect could be found in neither of the subgroup analyses (results not shown). Several study limitations should be taken into account. Firstly, measurement of current unemployment status differed at different time points. At baseline and month 3, participants were asked about being currently unemployed; at both follow-ups they were asked about being employed. Although answers were categorized equally for all time points as ‘unemployed’ or ‘not unemployed’, information might have been lost and the operationalization might be prone to distortion. Secondly, recruitment was done at three job agencies and the analyses should at best be controlled for recruitment site. However, as the job agencies’ different areas of responsibility and duration of life-time unemployment involved one another, we could not control for recruitment site in addition to duration of lifetime unemployment. Thirdly, the sample was recruited from one single area characterized by an elevated unemployment rate in comparison to Germany in general (2008: Mecklenburg–Western Pomerania: 14.1% vs. Germany: 7.8%38) and to Europe (2008: 7.0%39). Thus, despite personal factors, structural aspects as well might have a great impact on re-employment. Fourthly, further factors such as mental health which was not assessed in our study but is associated to unemployment3 might influence re-employment itself as well as intervention effects on re-employment; and should be considered in future research. Despite these limitations, three main strengths should be mentioned: Firstly, this study provides findings on long-term effects of BAIs in non-medical settings beyond year 1. Secondly, our sample was recruited proactively at job agencies which may have contributed to a high proportion of participants with low socioeconomic status, a subpopulation otherwise hard to reach for health research.40 Thirdly, LGMs were conducted, giving the opportunity to model the trajectories of unemployment status over a period of 15 months and how these trajectories vary among individuals who were assigned to different study groups and with differences concerning socio-demographic and socio-economic background as well as health behavior. Further LGMs are suitable to handle missing data properly. Acknowledgements The authors appreciate Stefanie Tobschall and the study staff for collecting the data, the study participants for providing information, and the staff of the three job agencies for supporting our study (Agentur für Arbeit Greifswald, Agentur für Arbeit Stralsund, Job-Center Stralsund). Funding The study was funded by the German Research Foundation (FR2661/1-1, FR2661/1-2). Work on this paper was funded by the German Cancer Aid (108376, 109737, 110676, 110543, 111346), the State Graduate Funding (K.H.) and the Alfried Krupp von Bohlen and Halbach Foundation (S.B.). The founders were not involved in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript. Conflicts of interest: None declared. Key points Among alcohol at-risk drinkers who were initially unemployed our brief alcohol interventions (BAIs) had no significant effect on unemployment status over a period of 15 months. The lack of intervention effect is most likely due to the high re-employment rate in both intervention groups as well as the assessment only group. 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The European Journal of Public HealthOxford University Press

Published: Oct 5, 2017

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