Multiple neurodegenerative diseases are characterized by aggregation of tau molecules. Adult humans express six isoforms of tau that contain either 3 or 4 microtubule binding repeats (3R or 4R tau). Different diseases involve preferential aggregation of 3R (e.g Pick disease), 4R , or both 3R and 4R tau molecules [e.g. Alzheimer disease and chronic traumatic encephalopathy]. Three ultrasensitive cell-free seed amplification assays [called tau real-time quaking induced conversion (tau RT-QuIC) assays] have been developed that preferentially detect 3R, 4R, or 3R/4R tau aggregates in biospecimens. In these reactions, low-fg amounts of a given self-propagating protein aggregate (the seed) are incubated with a vast excess of recombinant tau monomers (the substrate) in multi-well plates. Over time, the seeds incorporate the substrate to grow into amyloids that can then be detected using thioflavin T fluorescence. Here we describe a tau RT-QuIC assay (K12 RT-QuIC) that, using a C-terminally extended recombinant 3R tau substrate (K12CFh), enables sensitive detection of Pick disease, Alzheimer disease, and chronic traumatic encephalopathy seeds in brain homogenates. The discrimination of Pick disease from Alzheimer disease and chronic traumatic encephalopathy cases is then achieved through the quantitative differences in K12 RT-QuIC assay thioflavin T responses, which correlate with structural properties of the reaction products. In particular, Fourier transform infrared spectroscopy analysis of the respective K12CFh amyloids showed distinct β-sheet conformations, suggesting at least partial propagation of the original seed conformations in vitro. Thus, K12 RT-QuIC provides a single assay for ultrasensitive detection and discrimination of tau aggregates comprised mainly of 3R, or both 3R and 4R, tau isoforms. Recent calls for better biomarkers of neurodegenerative diseases  have eliMAPT mutations (FTDP 17 MAPT) and others 1/2 where n = number of replicates. This method of error estimation is further described in [As a measure of seed concentrations in samples, we employed logSD to 60 h . LogSD50ilutions . Error bribed in .− 4 dilution in conditions identical to those described above for K12 RT-QuIC. Fibrils were scraped from the microwell plate and analyzed by SDS-PAGE for percent conversion of substrate to approximate the concentration of fibrils generated. We estimated that nearly ~ 100% of the K12CFh was converted in all reaction conditions. Serial dilutions of fibrils was conducted identically to those for brain homogenate, in a background of 10 mM HEPES pH 7.4, 1x N-2, and 0.53% KO BH.To estimate the analytical sensitivity of K12 tau RT-QuIC, synthetic K12CFh fibrils were assayed over serial dilutions of a known concentration of starting fibrils. Fibrils were generated by seeding 6.5 μM K12CFh substrate with either AD, PiD, or KO BH at 10− 9 and 10− 8 for AD and PiD, respectively, within 50 h , very similar to that obtained previously using the 3R RT-QuIC assay [n = 8) and 7.5–7.6 (n = 2), respectively. The brains with 4R tau pathology reactions all had much lower seeding activities , albeit higher than those of brains that were immunohistochemically negative for tau pathology . Cut-off times for log SD50/mg tissue determinations were set to 60 h based on observations that no further PiD-, AD-, or CTE-seeded reactions exceeded 100 standard deviations of the baseline ThT fluorescence at time points beyond 60 h. Spontaneous conversion of K12CFh was not observed in tau KO-seeded wells prior to 120 h. Spearman-Kärber based estimations of log SD50/mg tissue values for various tau aggregation disease cases and controls are summarized in Table To further explore the seeding selectivity of the K12CFh substrate, we performed serial dilution analyses on several brain homogenates with confirmed 3R pathology (PiD), mixed 3R/4R pathology , and controls that had either 4R pathology  or lacked tau pathology according to immunohistochemical analysis. Figure IC assay . The AD − 3–10− 6) range of BH dilutions indicating that it was primarily the character, rather than the concentration, of the seeds in the AD versus PiD brain specimens that determined the divergent fluorescence amplitudes. These fluorescence maxima differences were also seen in comparisons of reactions seeded with 8 PiD brain homogenates  compared to 2 fAD, 6 sAD, 2 CTE, and 3 PART brain homogenates   Fig. a. Modify− 1). The spectra of the PiD-seeded reaction products had prominent 1633, 1625 cm− 1 β-sheet vibrational modes, which were distinct from 3R/4R-seeded reaction products with prominent 1630 and 1618 cm− 1 vibrations; these results provide evidence that two distinct conformers of K12CFh aggregates resulted from the differential seeding (3R versus 3R/4R) of K12 RT-QuIC reactions. Further spectral differences were observed in the 1655–1700 cm− 1 region containing turn and other parallel/antiparallel β-sheet bands as well as at 1516–7 cm− 1 where tyrosine absorbs -seeded, K12CFh products Fig. c.50/mg tissue values, thus representing similar  seeding doses of the tau aggregates therein, and mixed them together in ratios ranging from 10:0–0:10 AD:PiD before analyzing ThT fluorescence amplitudes in the K12 RT-QuIC. Additional file − 4. Reactions seeded only with AD BH (10:0 AD:PiD) showed characteristically high ThT fluorescence values that decrease with a decreasing ratio of AD:PiD. However, surprisingly, even with the addition of 1/10 equivalent of PiD BH, the ThT fluorescence maxima of the reactions dropped to levels approaching those obtained with PiD BH alone. These results suggested that either (1) PiD tau seeds are more efficient at seeding K12CFh fibrillization, or (2) that this PiD BH had a several fold higher seed concentration than the AD BH, which is possible because of ~ 0.5 log margin of error that we have observed is typical of end-point dilution RT-QuIC titrations.To investigate what might be observed when assaying samples with mixed AD/PiD pathology, we took AD and PiD brain homogenates with nominally comparable logSD5A) versus in K12 RT-QuIC (5B). Grey circles in both panels represent KO BH-seeded reactions, which serve as negative controls. The AD RT-QuIC showed occasional (5/48) positive reactions occurring in KO-seeded wells, prior to the published assay endpoint of 30 h (grey shaded area). Nonetheless, similar mean seed concentrations for AD brain samples were obtained with Spearman-Kärber analyses of end-point dilution data the two assays, i.e., 8.7 +/− 0.2 and 8.4 +/− 0.2 log SD50/mg with AD tau RT-QuIC and K12 RT-QuIC, respectively.By performing K12 RT-QuIC analysis on serial dilutions of synthetic K12CFh fibrils, we were able to crudely estimate the concentration of fibrils that the K12 RT-QuIC assay can detect. Additional file postmortem brain samples to aid in the characterization of decedents’ molecular pathologies for diagnostic and research purposes. Presumably, it can be similarly applied in animal models in pathogenesis or preclinical therapeutic studies to follow the accumulation of 3R and 3R/4R tau aggregates. Applications to antemortem diagnosis or therapeutic trials in humans will depend largely upon the ability to detect tau seeds in accessible tissue or fluid specimens such as CSF, but such capability remains to be shown.Given that tau deposition appears to underlie the pathogenesis of multiple neurodegenerative diseases, it is important to have robust and practical assays for different types of tau aggregates for use in diagnostics and research. Tau RT-QuIC assays exploit the fundamental self-propagating activity of pathological forms of tau, offering detection methods that are more sensitive than, and complementary to, conventional methods such as immunohistochemistry, immunoblotting, and ELISA. Thus, tau RT-QuIC assays allow measurements of multiple types of tau aggregates whether they represent the predominant cause of neurodegeneration or much less abundant co-pathology that is secondary to another disease process. Our K12 RT-QuIC assay allows the ultrasensitive detection and discrimination of both 3R and 3R/4R types of pathological tau using a single tau substrate (K12CFh). From a practical perspective, this assay halves the number of assays and recombinant tau substrates required to measure these types of tau seeds. More fundamentally, our findings also demonstrate the different templating activities of 3R versus 3R/4R tau-associated aggregates. However, our observation that the discriminatory ability of the assay based on maximum ThT fluorescence can break down with extreme near-end-point dilutions of BH . Thus, overall, we have simplified the amplification of AD tau aggregates by two methods: (1) by modifying the ionic species present in the reaction mixture of the original AD tau RT-QuIC [A key to success in developing RT-QuIC or other seed amplification assays is maximizing the kinetic difference between seeded and unseeded (spontaneous) polymerization of the substrate molecules. In our experience the K12CFh substrate is readily seeded but is less prone to spontaneous polymerization than the tau fragments that we have used in our previous tau RT-QuIC assays , 28, 29. RT-QuIC  and (2) − 1 range of the major spectral differences indicated that they likely reflect variations in β-sheets formed by the polypeptide backbone because, although side-chain vibrations can absorb in this range, they typically make up only about 10% of the spectral intensity [− 1 are also consistent with conformational differences. The divergent ThT maxima exhibited by the 3R- versus 3R/4R-seeded K12CFh fibrils might be due to distinct alignments of the ThT fluorophores on fibrils with different amyloid cores and/or to the differential bundling of the fibrils.The ability of K12 RT-QuIC to distinguish PiD- from 3R/4R-seeded reactions based on the ThT fluorescence maxima and FTIR spectra of the reaction products suggests that at least some of the distinct conformational features of PiD and 3R/4R tau filaments can be imposed on, and propagated by, the K12CFh tau fragment. The 1618–1633 cmntensity . Nonethe50/mg tissue = 4–6) reflects lesser deposition of AD-like tau. Interestingly, 2 of 3 PART samples had seeding levels comparable to that of 4R tau and IHC tau-negative brain homogenates. This intermediate seeding activity was also observed with the original AD tau RT-QuIC assay  could be because the filament core conformations of AD and CTE, at least, are closely similar to one another , 16. Mor50/mg AD brain compared to 7.45 log SD50/mg PiD brain  and 3R/4R (AD) tau RT-QuIC assays, and requires the preparation of one tau substrate, herein called K12CFh, instead of the 2 required for our previous assays. Further, this single K12CFh tau fragment showed less frequent spontaneous fibrillization compared to the substrates used in the AD RT-QuIC assay, improving the confidence with which a true positive can be declared. Importantly, the analytical sensitivity of the assay is consistent with those of the previously-published AD and PiD tau RT-QuIC assays.Surprisingly, given the strong selectivity of our previous 3R tau RT-QuIC assay, our results also show that 3R/4R tau aggregates can seed the fibrilization of a pure 3R tau fragment that is C-terminally extended. So, from a more fundamental perspective, our biophysical characterization of the products of K12 RT-QuIC provided evidence that at least some features of the original conformations of the aggregates are propagated faithfully in these fibrillization reactions, making the assay a promising tool for further studying the misfolding process or inhibitors thereof.Additional file 1. Purification of K12CFh tau. Following overnight autoinduction of K12CFh-expressing E. coli, tau is bound to a his column and eluted over a stepwise gradient of 23–100% buffer B (46–200 mM imidazole). Designated fractions are pooled and precipitated in acetone overnight, washed, dissolved in 8 M GdnHCl in PBS, and desalted by PD-10 size exclusion column. K12CFh fractions void of GdnHCl are pooled and stored at − 80 °C for future use.Additional file 2. Salt optimization of the K12 tau RT-QuIC assay. Panels represent lag time (time to threshold of ThT > 100*SD baseline fluorescence) for reactions seeded with serial dilutions of PiD and AD brain tissue in four salts at 400 mM. Top: addition of 40 μM heparin; bottom: absence of heparin.Additional file 3. Robustness of ThT amplitude differences with modified reaction conditions. Panels represent mean ThT amplitude data for three PiD and three AD brain homogenate reactions seeded at 1 × 10− 4 dilution in K12 tau RT-QuIC. Each panel shows a variation of a reaction condition  beyond that of the optimized conditions listed in the figure. For gain and temperature plots, the same reaction at endpoint was scanned over increasing gain and temperature of the plate holder.Additional file 4. Second derivative FTIR spectra of PiD (3R)-, AD (3R/4R)- and CTE (3R/4R)-seeded K12CFh products in fingerprint region from 800 to 1200 cm− 1. Each trace represents spectra from eight pooled K12 RT-QuIC reaction products seeded with an individual 1 × 10− 4 dilution of brain homogenate. Multiple traces represent reaction products seeded with brain homogenate from separate individuals: eight PiD (red), three sAD (orange), three fAD (green), and three CTE (blue).Additional file 5. K12 RT-QuIC performance in the presence of AD and PiD tau seeds. Sixteen replicate K12 RT-QuIC reactions were performed at the given ratio of AD:PiD seeds.Additional file 6. Analytical sensitivity of K12 RT-QuIC seeded with synthetic K12CFh fibrils. Panels represent lag time analysis (time where ThT fluorescence exceeded 100*SD baseline fluorescence) for eight replicate reactions seeded with the designated synthetic K12CFh fibril concentrations. Assay conditions and dilution buffer were identical to those described in methods.


Compared to the employed, the unemployed are characterized by a substantially worse health status, particularly with regards to mental health. At the same time, conventional offers of prevention and health promotion rarely reach the unemployed. The JOBS Program is a health promotion program that combines job application training with elements of social learning theory and self-efficacy. Randomized field studies in the USA and Finland found significant positive effects on reintegration into the labor market and health amongst the unemployed. In this confirmatory study, we analyze whether the JOBS Program produces similar positive effects for the unemployed in Germany.This study is designed as a country-wide, multi-center, non-blinded, two-armed, parallel-group, randomized controlled trial over 6 months. A total of approximately 1500 unemployed, who are willing to participate, are randomly assigned either to an intervention group or a waiting control group with an allocation ratio of 1:1. Guided by a team of two trainers, the intervention group completes JOBS Program Germany in small groups of 8 to 15 unemployed for a period of 1 week in units of 5 h a day. Primary outcome measures are the reintegration into the labor market, self-efficacy, life satisfaction, subjective state of health, depressive symptoms, and psychological distress. Of secondary interest are moderating variables such as socio-demographic characteristics, the duration of unemployment, and the job-search intensity. Outcomes will be repeatedly assessed via computer-assisted telephone interviews at three points in time: immediately before the intervention (pre-test), immediately after the intervention (post-test), and 6 months after the intervention has ended (6-months follow-up).This confirmatory study will provide empirical evidence on the effectiveness of the JOBS Program on the reintegration and  health of the unemployed in Germany. If our results from the randomized controlled trail in a country-wide field experiment confirm its effectiveness, the JOBS Program Germany could, perspectively, be implemented into the German employment promotion and social security system on a long-term basis.DRKS00022388. Registered on 20 July, 2020.German Clinical Trials Register (DRKS),  Unemployment poses a problem for society as a whole and, in particular, a challenge for prevention and health promotion programs. Meta-analyses have shown that compared to the employed, the unemployed have a worse health status , 2, partA promising strategy to meet the challenges of improving the health among the unemployed is interdepartmental cooperation between health promotion and employment promotion. In Germany, the Federal Centre for Health Education (BZgA) and the National Association of Statutory Health Insurance Funds (GKV-Spitzenverband) are currently cooperating with the Federal Employment Agency on a large-scale program called “Linking of Employment Promotion and Health Promotion in the Community Setting”. Within this activity, they have adopted the so-called JOBS Program, which is a preventive intervention program that was originally developed in the 1990s by the Michigan Prevention Research Center –7. The JRandomized field studies that have evaluated the JOBS Program in the United States , 10 and While the positive results from the US, Finland, and Ireland seem promising, it remains an open empirical question whether the JOBS Program will unfold similar effects for the unemployed in Germany. From an international comparative perspective, it should be noted that the success of employment promotion and health promotion among the unemployed probably depends on the country-specific labor market structure and the health and social security systems, respectively. Also, the original JOBS Program was conceived as a preventive measure, primarily for the short-term unemployed, who have recently lost their jobs. In the US study, participants were unemployed for less than 13 weeks; the mean duration of employment in the Finnish study was about 10.7 months and only 28% of the participants had been unemployed for longer than 12 months. In Germany, the proportion of long-term unemployed is particularly high in international comparison. In 2019 about 32% have been unemployed for at least 1 year or longer . Also, tA randomized control trial in the Netherlands  suggestsAgainst this background, our confirmatory study analyzes whether the JOBS Program increases reemployment and improves health among the unemployed in Germany.The objective of this study is to investigate the effects of the JOBS Program intervention on the reintegration into the labor market, life satisfaction, state of health, depressive symptoms, and psychological distress among the unemployed in Germany. Of secondary interest are moderating factors such as socio-demographic characteristics, the duration of unemployment, and the job-search intensity.We will compare the reintegration into the labor market and mental health amongst unemployed, who will be randomly assigned to an intervention group that completes JOBS Program Germany, to a waiting control group. The waiting control group will complete JOBS Program Germany only after the trial has terminated.Given the confirmatory nature of this study, our hypotheses closely resemble those formulated in the respective studies that have investigated the JOBS Program in the US and Finland –13. CompHypothesis1: The JOBS Program Germany will increase the level and quality of reemployment in the intervention group compared to the waiting control group.Hypothesis 2: The JOBS Program Germany will increase self-esteem and self-efficacy and decrease depressive symptoms and distress in the intervention group compared to the waiting control group.Hypothesis 3: The risk of depression, assessed by a high level of depressive symptoms before the JOBS Program Germany, will moderate the effects of the JOBS Program Germany on reemployment and mental health outcomes. The JOBS Program Germany will have stronger employment promoting and mental health effects on those with a higher risk of depression.Hypothesis 4: The job-search intensity, assessed before the JOBS Program Germany starts, will moderate the effects of the JOBS Program Germany on reemployment. The JOBS Program Germany will have stronger employment promoting effects on those with lower initial levels of job-search intensity.Hypothesis 5: The length of unemployment will moderate the effects of the JOBS Program Germany on reemployment. The JOBS Program Germany will have a stronger employment promoting effect for those who have been unemployed for a moderate period compared to (1) the recently unemployed and (2) the long-term unemployed.Hypothesis 6: The length of unemployment will moderate the effects of the JOBS Program Germany on mental health. The JOBS Program Germany will have stronger mental health effects for those who have been unemployed for a moderate period compared to (1) the recently unemployed and (2) the long-term unemployed.t0), (2) immediately after the intervention (t1), and (3) 6 months after the intervention has ended  on behalf of BZgA and in close coordination with the research team at the University of Kassel. Computer-assisted telephone interviews (CATI) will be conducted based on questionnaires developed by the research team at the University of Kassel. The data will be analyzed exclusively by the research team at the University of Kassel. The sample will comprise adult men and women who are unemployed according to the German Social Code, Book III, and who are willing to participate in the JOBS Program Germany voluntary.Job-search skillsActive teaching/learning methodsInoculation against setbacksTrainer referent powerSocial supportThe intervention is based on the JOBS Program that was developed by the Michigan Prevention Research Center , 7. The Accompanied by a team of two trainers, the intervention group completes JOBS Program Germany in small groups of 8 to 15 unemployed people for 5 days in units of 5 h a day over a period of 1 week. Trainings will be completed in the community-settings at each of the participating locations.Resembling the Finnish implementation of the JOBS Program , trainerWhile the JOBS Program Germany is free of charge for the participants, similar prevention and health promotion programs for the unemployed, according to paragraph 20 of the German Social Code, Book V, are usually associated with participant fees. Because there is no equivalent free-of-charge health promotion program for the unemployed, we have opted for a passive waiting control group that will not participate in JOBS Program Germany and, thus, not receive effective treatment during the six months of the trial. The unemployed in the waiting control group will complete JOBS Program Germany after the trial has ended.Due to the country-wide implementation of the JOBS Program Germany in the community-settings, the exact dates of enrollment and trainings will vary across the participating locations. Also, at some locations, more than one JOBS Program Germany will be conducted. However, for any given JOBS Program Germany at a given location, the time schedule is fixed.t1). During these information events, two trainers, who will later lead the respective JOBS Program Germany, will explain the intervention and provide participants with a written information sheet that summarizes the objectives, procedure, and contents of the program. Trainers will also address any questions from potential participants. Participation is voluntary and free of charge, and a withdrawal is possible at any time without consequences. At the end of the information events, trainers will obtain written informed consent from the unemployed who are willing to participate.Figure Following the information event, participants who have given informed consent will be contacted and asked to complete an initial CATI during which participants’ eligibility for the trial is assessed. Participants meet the inclusion criteria if they are between 18 and 65 years old and currently unemployed according to the German Social Code, Book III by the time of the interview. Participants who, by the time of the interview, are full-time students or otherwise inactive on the labour market, and those with insufficient command of the German language to complete the CATI are excluded from the trial.t0). The allocation (stratified by location) will take place automatically with a 1:1 ratio in an alternating fashion. The first participant who successfully completes the CATI will be allocated to the intervention group; the second participant will be allocated to the waiting control group, and so on. Because allocation is carried out in “real-time”, there is no predetermined list. Hence, whether a participant is allocated to the intervention or control group is not known in advance. Moreover, because at any point in time more than one CATI will be conducted simultaneously, interviewers cannot predict the allocation of a given participant prior to the end of the current interview. The information about the group to which participants will be assigned is only revealed to the interviewers by the time the interview is completed.After assessing the baseline measures, all eligible participants will be randomly assigned to an intervention or waiting control group upon completion of the initial CATI  group and their place in the intervention group is filled with another participant who has not yet been allocated to either group. Any such deviation from the randomly allocated intervention will be recorded in the methods reports and in the dataset. Participants in the waiting control group will be told that JOBS Program Germany will start in 6 months Participants who are randomly allocated to the waiting control group cannot participate in JOBS Program Germany, meaning that it is not possible for participants to self-select into the intervention group.Participants in the waiting control group are not allowed to join JOBS Program Germany during the 6 months of the trial. However, participants in both the intervention and waiting control group will not actively be discouraged or otherwise prevented from participating in any employment promotion measures of the Federal Employment Agency or any prevention or health promotion measures of their choice other than the JOBS Program Germany. Participation in the intervention is voluntary and may be terminated by the participants at any time.t1). Participants of the intervention group and waiting control group will be asked whether they currently participate or have participated in any measure of the Federal Employment Agency or in any health promotion measure. The intervention group is additionally asked to confirm that they have completed JOBS Program Germany. Primary and secondary outcomes are also assessed.The post-test interview will take place within 4 weeks after the intervention group has completed JOBS Program Germany (t2). Again, participants in both the intervention and the waiting control group will be asked to report participation in any job-search or health promotion related measure. Also, all outcome measures are assessed. Upon completion of the final CATI, the unemployed in the waiting control group will be invited to complete JOBS Program Germany.The final CATI will be conducted 6 months after the intervention group has completed JOBS Program Germany t0), immediately after the JOBS Program Germany have completed (t1) and 6 months after the JOBS Program Germany have completed   will be interviewed before the JOBS Program Germany (mpleted t and 6 moReintegration into the labor market will be assessed using a binary indicator of participants’ current employment status (employed vs. unemployed). For those participants who are employed, we will also assess whether they have a fixed-term or a permanent employment contract as well as their weekly working hours. Any subsided labor market activities  will be assessed, additionally.Participants’ self-esteem is measured with a revised German version of the widely used Rosenberg Self-Esteem Scale , 19, forWe assess life satisfaction with a German version of the Satisfaction with Life Scale (SWLS) . A recenWe assess participants’ health status by asking for a self-evaluation of their overall state of health (answers on a 5-point Likert-type Item labeled from “very good” to “very bad”). Additionally, we examine whether participants feel restricted in their everyday activities by chronic health problems. Moreover, we use the Patient-Health-Questionnaire 15 (PHQ-15) to assess the severity of somatic symptoms.Psychological distress is measured with a short, 21-Item version of the depression-anxiety-stress-scale (DASS-21). Psychometric properties of the DASS-21  have been assessed in Germany  and the Depressive symptoms are measured using the WHO Well-Being Index (WHO-5) and the Patient-Health-Questionnaire 9 (PHQ-9). The WHO-5 consists of five questions, which assess the subjective well-being. A systematic review, including 213 studies, suggests that the WHO-5 is an adequate instrument for screening depressive symptoms in clinical trials . The WHOt0, t1, t2, see Fig. t0), we also assess basic socio-demographic characteristics, such as participants’ age, gender, citizenship, and level of education.The duration of unemployment, job-search intensity, and, if applicable, job satisfaction are collected via telephone interviews at all three occasions (d) ranging from about .14 to .32. for self-esteem, self-efficacy, psychological distress, and depressive symptoms [t0) and the 6-months follow-up (t2). We further expect about 60% of the unemployed who attend the information event to participate in our study, resulting in an estimated 2500 unemployed who attend an information event. We summarize our assumptions about response rates and panel attrition in Table This trial is conceptualized as a confirmatory study. The respective studies in the US and Finland reported small effect sizes , and the 6-months follow-up interview (t2), respectively  study and will not be part of the analyses. Instead, participants in these first four locations are treated as a pilot sample. This pilot sample will comprise approximately 50 participants who will be allocated to intervention and waiting control groups as described above. The main study is expected to start in April 2021. Participants in the pilot-study will complete JOBS Program Germany (if assigned to the intervention group), the post-test interview . Participants’ contact information will be stored separately from the survey data . After data collection, each respondent will be assigned a unique identification code, and the survey data (but not the contact information) will be transferred to the research team at the University of Kassel. Data transfer will be conducted via a secure data exchange server. The entire process of data collection, processing, storage, and backup will be documented in a detailed report.Statistical methods will include t-tests  as well as linear and (binary) logistic regression models. We will compare primary and secondary outcomes between the intervention and waiting control groups.Reintegration into the labor market (employed vs. unemployed) and the type of contract (temporary vs. permanent) will be assessed using t-tests  and logistic regression models. In all analyses, we will treat Likert-Type items as continuous variables. For life-satisfaction, depressive symptoms, and psychological distress, we will first construct (additive) indices. We will then test mean differences in the respective indices between intervention and waiting control groups using t-tests. In multivariate analyses, we will use linear regression models to adjust for baseline-measures of the respective outcomes. Additional models will also adjust for socio-demographic characteristics and indicators of labor market biography, such as the duration of unemployment. We proceed in a similar fashion to analyze self-esteem, self-efficacy and our secondary outcomes job satisfaction and job-search intensity.To test for potential effect modifications, we include interaction terms between our treatment-indicator and the respective moderators  in the respective regression models.All multivariate analyses will include controls for socio-demographic variables and (un-)employment history. We will repeat our main analyses stratified by gender. All analyses will be carried out according to the  “intention-to-treat” principle. Participants will be treated as belonging to the group to which they were originally (randomly) allocated. We tolerate low proportions of missing values of up to 5%, and perform listwise-deletion . If the proportion of missing values exceeds the predefined threshold of 5%, we will treat missing values by means of multiple imputation –33.t1). The research team of Kassel University is obliged to provide research reports to the funder on a yearly basis. Thus, interim results will be reported to the funder. We will also report interim results to the BZgA. The trial will not be modified or terminated before the scheduled 6 months regardless of the results of any interim analyses.Interim analyses will be carried out using the statistical methods described above immediately after JOBS Program Germany have been completed Fig. , t1. TheThe research team at the University of Kassel will hold meetings with BZgA, National Association of Statutory Health Insurance Funds, and SOKO on a monthly basis or more frequently if required . In these meetings, any organisational aspects, including but not limited to recruitment of locations and participants, participation rates in JOBS Program Germany, and overall time schedule are monitored and discussed. Corrective actions to preserve the integrity of the study will be taken if deemed appropriate.Results will be published via multiple channels. The funding agency, the Federal Ministry of Education and Research, will be informed on a regular basis, at least once a year, about the progress of the project and also about the interim and final results.Furthermore, the cooperating partners, above all the BZgA, will be informed about the study results by the research team at the University of Kassel. The BZgA covers a wide range of media, including regular newsletters, which can provide information about the JOBS Program Germany and the respective study results.The research team at the University of Kassel will report all results of the confirmatory evaluation study independently from the founding party or any cooperating partners, and regardless of strength and direction  of the effects. This reporting will take place in the context of university teaching, at national and international labor- and public health-related conferences, and in the form of publications in international peer-reviewed journals. Authorship eligibility will be based on the recommendations of the international committee for medical journals editors (ICMJE).The various publication channels ensure that no result remains unknown and that the dissemination will be tailored to the different target groups. In addition to the publication of the results in the international scientific community, it is ensured that university students, the unemployed in Germany, health organizations and health insurance companies, institutions of employment promotion and their practitioners, as well as political decision-makers will be fully informed about the study results. This ensures low-threshold and transparent accessibility of the results and prevents publication bias.Access to the full study protocol is regularly granted to the funder and, upon request and after a formal agreement on confidentiality, to interested scientists. Because informed consent, sought from the participants, does not include general release of the data, we will not publish the participant level datasets. Statistical code will be made available via appropriate data repositories.Substantive modifications to the study protocol, including but not limited to changes of the study objectives, the eligibility criteria, the sample sizes, the allocation, the outcomes, or the statistical analyses will be discussed with all cooperation partners. Any such changes will be documented and published as amendments to this study protocol. Amendments shall also be made to the trial registry entry in the DRKS. Specific attention must be drawn to the course of the SARS-CoV-2/COVID-19 pandemic that might impair participant recruitment or may hamper the education of potential trainers.Compared to the employed, the risk of morbidity is significantly higher for unemployed persons in Germany. Furthermore, the prevention and health promotion hardly reach the unemployed. The JOBS Program is a health promotion program that specifically targets the unemployed. It combines job application training with elements of social learning theory and self-efficacy to improve the reintegration into the labor market and  health.In this confirmatory study, we assess whether the positive effects of the JOBS Program in the United States , FinlandDespite the discussed limitations, our study potentially provides the basis for a valuable addition to the German employment promotion and social security system. If the positive effects on reemployment and  health can be replicated in the German context, the JOBS Program Germany could be implemented on a regular, long-term basis to benefit the unemployed. Since the administrative infrastructure is already in place and the relevant agencies are already involved, implementation of the JOBS Program Germany could perspectively be extended.This is version 1 of the study protocol, submitted in December, 2020. Recruitment is expected to start in March, 2021. Recruitment will approximately be completed by the end of September 2021.


Super-resolution multi-contrast X-ray imaging performed using a Shack–Hartmann sensor for hard X-rays is presented. Different approaches of 2D lens arrays as Shack–Hartmann sensors for hard X-rays are compared. For the first time, a combination of Shack–Hartmann sensors for hard X-rays (SHSX) with a super-resolution imaging approach to perform multi-contrast imaging is demonstrated. A diamond lens is employed as a well known test object. The interleaving approach has great potential to overcome the 2D lens array limitation given by the two-photon polymerization lithography. Finally, the radiation damage induced by continuous exposure of an SHSX prototype with a white beam was studied showing a good performance of several hours. The shape modification and influence in the final image quality are presented. In this way, several multi-contrast imaging techniques using hard X-rays have emerged in recent decades employing synchrotron and laboratory sources  wavefront sensors  have been known since the early twentieth century in the visible light range. In 1900, Johannes Hartmann created the first tool to check for approximate focus, and to measure aberrations in the mirrors and lenses of large telescopes c)c)The SHSX design based on continuous hollow parabolic lenses consists of continuous 1D parabolic cavities with a radius at the parabola apex of 20 µm and a pitch of 170 µm, as shown Fig. 1. Characterization and focal distance measurements of the X-ray lens array were performed using a monochromatic beam with 8.5 keV X-ray energy. The acquisition of radiographic images was performed using the CMOS camera Phantom v2640, lens-coupled to a 50 µm LYSO scintillator. The effective pixel size was 5.3 µm (magnification ∼2.5). One hundred images were taken for each measurement with a frame rate of 100 frames s3.1.et al., 2001et al., 1996R is the parabola apex radius, N is the number of stacked biconcave lenses and δ is the refractive index decrement. The calculated focal lengths for SHSX v1.0, SHSX v2.0 and SHSX v2.1 are 24.6, 41.6 and 41.6 cm, respectively (δ = 3.7 × 10−6 and R = 20 µm). In this experiment, the focal length was defined as the distance at which the average gain has a maximum value. The experimental focal lengths for SHSX v1.0, SHSX v2.0 and SHSX v2.1 are 29.7 cm, 37.7 cm and 40.7 cm, respectively, as shown in Fig. 2The gain of a CRL is defined as the ratio of the on-axis image intensity in the image plane with the lens in place to the corresponding intensity without the lens  and 3(b)x- and y-directions are located at different distances. Using the relative parameter Δ [equation (2)et al., 2019et al., 2018aet al., 2019et al., 2019According to experimental data [Figs. 3(Fx and Fy), as well as the parameter Δ, are presented in Table 1Minimizing the size of the focal spots will allow a more sensitive wavefront sampling during interleaving measurements  and 5(b)c)As discussed previously, different generations of SHSX show different performances, which could be caused by structural variations due to different designs or printing defects. Gain and visibility maps are drawn at the focal points to study the homogeneity of the internal structure, qualitative and quantitative evaluation of SHSX performances. Gain maps for the SHSX v1.0 and v2.0 [Figs. 5b)The visibility has been calculated using equation (3)a)et al., 2018As a result, we can conclude that the shown SHSX v1.0 acts more like a Hartmann sensor than a Shack–Hartmann. It performs periodic modulations of the wavefront without amplifying the beam intensity at the modulation points [Fig. 6 was chosen due to a smooth phase gradient and earlier metrology on it  using a white beam  sensors for hard X-rays. Our experiments showed that SHSX based on 2D refractive lens arrays could be used for fast wavefront monitoring and single-shot multi-contrast imaging. We were able to reach an angular resolution of approximately 0.29 µrad. Even in the case of using a sample-shift technique by interleaving measurements at shifted sample positions to increase the spatial resolution, the measurement time spend on measurements is still in a range of seconds, which is much less than in case of using other wavefront-sensitive instruments. The spatial resolution in these experiments was demonstrated to be 21 µm. Chromatic aberrations in white-beam illumination, despite possible concerns are not detrimental to the measurement, but only reduce sensitivity gradually. Nevertheless, we noticed strong effects of radiation damage. The SHSX shrinks in size within 15 h under hard X-ray white beam illumination. In the case of using a two-dimensional Gaussian function fit procedure instead of Fourier extraction to analyze the spot pattern, the small shrinkage observed was not critical.10.1107/S1600577520002830/ve5120sup1.pdfFigure S1: Images of a diamond lens in differential phase contrast; Fig. S2: Images of diamond lens in dark-field contrast; Fig. S3: Super-resolution images of diamond lens in dark-field contrast. DOI:


Despite the exceptionally high prevalence of tobacco use in Lebanon, few cessation programs exist. The American University of Beirut (AUB) developed one of the first smoking-cessation programs in the country in 2015, and the program became free-of-charge to patients in 2018. The program offers initial visit(s) with a primary care provider, in-person and/or telephone counseling, acupuncture, and medications.We assessed patient characteristics, treatments used, and patient outcomes in the first year of implementing the free smoking-cessation program, compared to the original program. We compared 87 smokers who initiated treatment in the free program with 47 patients in the original program.At baseline, smokers in the free program were younger, smoked fewer cigarettes per day, and had lower CO levels than smokers in the original program. At 1 month follow-up, 72.9% were abstinent in the free program, compared with 42.2% in the original program (p<0.001). Smokers who had ≥2 primary care visits and those who had ≥1 acupuncture visits had higher rates of abstinence at 1 month and those who were prescribed bupropion had higher rates of abstinence at 12 months.Implementation of the free smoking cessation program demonstrates preliminary efficacy, with telephone support offering potential for scalability. The incidence of lung cancer in Lebanon is highest among females and second highest among males in the Eastern Mediterranean Region2. Despite the high burden of smoking in the Lebanese population, few resources exist to support smokers with tobacco cessation treatment3.Lebanon has high smoking prevalence rates of combustible tobacco use compared to other middle-income countries, reaching 34% in males and 21% in females for daily cigarette smoking, and 26% and 24%, respectively, for waterpipe smoking5. The program offers counseling to promote learning behavior modification and provides nicotine replacement therapy (NRT), including nicotine gum and patch. Effective from 1 January 2018, AUB implemented a tobacco-free university policy. As part of the policy, the smoking cessation program became free-of-charge with the goal of increasing access to tobacco treatment services.The American University of Beirut (AUB), a leading institution of higher education in Lebanon and the region, with an affiliated tertiary medical center, developed one of the first smoking-cessation programs in the country in 2015 in response to an identified need within the university community6.The free program accepts smokers of all combustible tobacco products, including cigarettes and waterpipe. The program is staffed with two physicians who are tobacco treatment specialists, two nurses specialized in behavioral smoking cessation counseling, and one administrator. Patients who enroll in the program receive up to eight sessions of counseling, as well as nicotine replacement therapy (NRT) free-of-charge . PatientAt the initial visit, the patient is introduced to the program, offered psychological support, provided information on managing withdrawal symptoms and coping strategies, and scheduled for a behavioral counseling session within one week of the planned quit date. The six remaining sessions lasting 45 minutes each are held on a weekly basis for two months with the nurse/smoking cessation specialist. Patients are requested to participate in these six sessions in person. If the patient is unable to visit the clinic, the session is held either via telephone or via a video call through the mobile application WhatsApp. Additionally, participants are encouraged to contact the nurse in case they experience any adverse drug reaction or need behavioral support and guidance through their cessation treatment process. In parallel with the weekly sessions, patients have two follow-up visits with the physician to evaluate withdrawal symptoms and potential medication side effects (at one and two months post quit-date). After completing eight weeks of treatment, patients are contacted by telephone on a monthly basis to ensure compliance and abstinence, and CO measures are collected at 1, 6, and 12 months. All program metrics are recorded in the patient’s electronic health record.7. Treatments received included behavioral counseling, acupuncture, and prescribed medications . Outcomes included CO-verified abstinence at 1, 6, and 12 months after the set quit date. Descriptive statistics are reported, including mean and standard deviation for continuous variables, and frequency and percentage for categorical variables. Quit outcomes were compared between the original and free programs across all three follow-up periods using average treatment effects estimation with inverse-probability weights that adjusted for age and nicotine dependence. Comparison of patient baseline characteristics between the free and original programs were conducted using t-tests for continuous variables and chi-squared tests for categorical variables. Associations between treatment types and quit outcomes at 1, 6, and 12 months among participants in the free program were examined using chi-squared tests. Associations with p<0.05 were considered statistically significant. Data analysis was conducted in 2020 using Stata version 15.1 (StataCorp LLC). Ethical approval was acquired from the AUB Institutional Review Board.We conducted a retrospective study of patients treated in the first year of the free program, spanning from November 2018 to December 2019, compared with the original program (2015–2017). Patient characteristics at baseline included age, gender, tobacco product used at the initial visit , number of cigarettes per day, CO level, and the Fagerström Test for Nicotine Dependence (FTND) scoreThe analysis included 87 patients who completed the initial visit in the free program compared with 47 patients in the original program . Among tOverall, 62 (72.9%) were abstinent at 1 month in the free program, compared with 19 (42.2%) in the original program (p=0.006). No significant differences were observed at 6 and 12 months . Among s8.In its initial year, the free program demonstrated a high level of effectiveness and has expanded the reach of the original program, including among younger and light smokers. Smokers in the free cessation program had significantly higher abstinence rates at 1 month follow-up compared with their counterparts who had participated in the original program. This finding is consistent with prior evidence of the beneficial effects of removing financial barriers for smoking cessation treatment9, and therefore it is not surprising that smokers who had more than one physician encounter were more likely to quit successfully. In addition, smokers who participated in acupuncture had higher abstinence rates. This result is consistent with a recent systematic review that evaluated the evidence in support of the beneficial effect of acupuncture on smoking cessation6. Also, our findings suggest that bupropion may be more effective than NRT in supporting patients to maintain long-term abstinence. Although our study did not document mental health diagnoses, patients were more likely to be prescribed bupropion over NRT if they had co-occurring mental health conditions. Given emerging evidence that bupropion may be more beneficial than NRT for smokers with a history of depression10, and the increasing public health concern about mental health in Lebanon12, this finding has important practice implications on prescribing cessation medications as a part of tobacco use treatment in Lebanon and beyond.Among smokers who participated in the free smoking-cessation program, we found higher abstinence rates in those who had more than one physician visit, those who participated in acupuncture, and those treated with bupropion. Delivery of physician advice to smokers is a critical component of clinical practice guidelines for smoking cessation13.Although the program has enjoyed exceptional success in the Lebanese context, where few resources exist to support smokers with cessation services, it has thus far operated at a small scale. Efforts are needed to scale up the program to meet the unmet needs of smokers, who represent a large portion of the Lebanese population. Telephone-based counseling services (i.e. quit lines) should be considered in this regard, as they are a recommended solution for delivering population-based smoking cessation support, especially in low-resource settings1. There are many patient-level barriers to waterpipe smokers seeking cessation support, including misperceptions about harm, as well as the social and cultural norms associated with the practice. From a clinical point of view, a recent survey of Lebanese primary care practitioners found they were more likely to counsel patients against cigarette smoking than waterpipe smoking, underscoring a lack of knowledge about waterpipe smoking cessation techniques14.In addition, while the vast majority of patients in the program were cigarette smokers, the prevalence of waterpipe smoking in Lebanon is comparable to the prevalence of cigarette smokingImplementation of the free smoking-cessation program demonstrates preliminary efficacy, with telephone support offering potential for scalability. Future enhancements to the program should also consider strategies to facilitate the delivery of smoking cessation services to waterpipe smokers.


Earthquakes are a consequence of the motions of the planet’s tectonic plates, yet predicting when and where they may occur, and how to prepare remain some of the shortcomings of using scientific knowledge to protect human life. A devastating Mw 7.0 earthquake on October 30, 2020, offshore Samos Island, Greece was a consequence of the Aegean and Anatolian upper crust being pulled apart by north–south extensional stresses resulting from slab rollback, where the African plate is subducting northwards beneath Eurasia, while the slab is sinking by gravitational forces, causing it to retreat southwards. Since the retreating African slab is coupled with the overriding plate, it tears the upper plate apart as it retreats, breaking it into numerous small plates with frequent earthquakes along their boundaries. Historical earthquake swarms and deformation of the upper plate in the Aegean have been associated with massive volcanism and cataclysmic devastation, such as the Mw 7.7 Amorgos earthquake in July 1956 between the islands of Naxos and Santorini (Thera). Even more notable was the eruption of Santorini 3650 years ago, which contributed to the fall of the Minoan civilization. The Samos earthquake highlights the long historical lack of appreciation of links between deep tectonic processes and upper crustal deformation and geological hazards, and is a harbinger of future earthquakes and volcanic eruptions, establishing a basis for studies to institute better protection of infrastructure and upper plate cultures in the region. This high-magnitude normal-slip earthquake, MW 7.0 (USGS) (Table The Mw 7.0 Samos (Néon Karlovasion) earthquake occurred as the result of normal faulting, where the upper crust of the Aegean was pulled apart, with the initial rupture at an estimated focal depth of 11–21 km near the border between Turkey and Greece, in the Aegean Sea. The earthquake caused massive damage in Greece and Turkey, and was globally the deadliest of 2020, with 118 deaths attributed to the earthquake and associated phenomena. Effects of the earthquake included high-intensity ground shaking with associated collapse of buildings, liquefaction, rock falls, landslides, and tsunami10, but in the Aegean and Anatolia of western Turkey, the tectonic forces are highly complex12. As Arabia is already colliding with Eurasia in the east  Mw 7.0 earthquake occurred on a moderately N-dipping, nearly E-W striking fault plane offshore the island of Samosen, Fig. , which bWe report fault slip data from the Büyük Menderes and Gediz Grabens that show similar slip systems as those activated during the Mw 7.0 Samos earthquake. Along the Kuşadası fault system where the graben extends into the Aegean Sea towards Samos Island Figs. b, 3b,c, 47 presents shallow seismic images. Their Fig. 10 shows there is a N dipping E-W normal fault between Samos and Kuşadası faults which is suitable to be the connection between these two. Another offshore study around the area suggests that Samos fault extends towards the Küçük Menderes Graben in the east48. Neither of these models present data for the exact linkage. However, based on the consistency between kinematic features of the Kuşadası fault and the focal mechanism solutions of the Samos earthquake, and our perspective on the area, we suggest that the fault responsible for October 31 Mw 7.0 earthquake is very likely to be the western continuation of the Kuşadası Fault, showing that the spectacular continental rift system of the Büyük Menderes graben extends offshore, in the more highly-extended Aegean system.. This connection needs further examination by offshore studies.The western extent of Kuşadası Fault strand and its connection with Samos Fault, on the other hand is not well established. There are seismic studies around the area, but they all include the narrow belt confined to the Turkish side of the bay, therefore they are inconclusive in terms of connecting the Kuşadası and Samos Systems. The study of Aksu et al.43 conducted a paleoseismology study on this fault, showing slip events on this system at 15, 8.4 and 3.6 ka, with slip magnitudes of 0.7, 0.9, and 3.1 m on the north dipping Kalafat segment, and events at 7.9, 3.4, 2.0 ka on the south dipping Yavansu strand with vertical displacements of 0.6, 3.5 and 2.6 m (M 6.5–7.1). This yields an approximate overall recurrence interval of 2400 years for slip events of ~ 1.9 m along the western on-land end of the Kuşadası fault system, but that interval is becoming shorter with time.It is important to assess the past activity on active faults. By understanding the characteristics of the fault, mitigation of related geological hazards can be done to prevent damage. Mozafari et al.26, where readers are referred for further information.A large number of ancient cites were built close to the active fault zones, and destroyed by strong historical earthquakes55. The most recent, significant event before the Samos Earthquake was a M 6.6 earthquake on July 20, 2017 near Bodrum, on the southwest coast of Turkey (https://earthquake.usgs.gov/earthquakes/eventpage/us20009ynd/executive). These events show that faults of this area can generate earthquakes of larger magnitude than most other extensional systems around the world.Aegean earthquakes are characterized by both normal and transtensional events, with 29 earthquakes of M > 6.0 within 250 km of the Samos event in the past 100 years. These include the M 6.8 1955 Söke earthquake, M 7.7 July 1956 earthquake between Nazos and Santorini, and an associated M 7.2 aftershock. The1967 Skyros (M 6.6), 1969 Alaşehir (M 6.7), and 1970 Gediz (M 6.9) earthquakes are other significant earthquakes of the Aegean and western Anatolia extensional system17, with some historically volcanoes, such as Methana volcano at the western edge of the volcanic arc, Milos and Santorini volcanos in the central part, and Nisyros at the eastern edge near the Turkish coast, which have caused tremendous catastrophes, perhaps rising to some of the most significant in human history, together with the earthquakes60.The South Aegean active volcanic arc formed along the convergent plate boundary of the northward subducting African plate underneath the active margin of the Eurasian plate16 causes the upper plate to extend  Mw 7.0 earthquake occurred at a critical location for testing the links between deep tectonic subduction, the rollback of the trench system, and how it is coupled with and linked to the fragmentation of the upper plate into numerous small microtectonic blocks. While catastrophic, the earthquake presents an opportunity and demonstrates the societal need to better understand the active surface deformation and driving mechanisms of deformation in the Aegean and western Anatolia.The African lithosphere is subducting to the north in the Hellenic and Cyprus trenches, but the trench and upper plate are retreating as the slabs roll back to the south. Coupling between the upper and lower platesend Fig. , formingend Fig. . We relaend Fig. . We showThe Aegean and Western Anatolia represent a unique place on Earth to elucidate geologic processes changing from subduction, to the ongoing plate collision, and the transition in between, which in this case has fragmented the upper plate into numerous smaller microplates. It shows that immediately before continental collision, the overriding plate may be broken into small platelets that move laterally with respect to each other, displacing parts of formerly continuous geological features, and that this complication may be difficult to recognize in parts of the Tethyan and other orogenic belts where collision is more advanced. The rollback process of the African plate forms the geometrically complex normal fault systems, and earlier transtensional systems, responsible for the spectacular upper crustal extension and active seismicity in this area. These relationships also explain why in collision orogens, there are often small preserved “pockets” of extensional basins, fault systems, and sedimentary and volcanic deposits. Tectonic escape is moving most of Anatolia westward along the North and East Anatolian and associated fault systems, with predominantly strike-slip tectonics in eastern Anatolia, and extensional tectonics in the west. However, the boundaries between these regimes are not yet well-defined. It is imperative that further studies are conducted in various aspects including the fault systems geometries, paleoseismic records, earthquakes, and tectonic activity evaluation, to better understand the links between tectonic processes, upper crustal deformation, and better protection of society from devastating geological hazards.The October 30, 2020 Samos Earthquake (M 7.0) was a major event mainly related to upper plate extension caused by the rollback of the subducting African Plate.Earthquake solutions and analysis of active fault planes in western Anatolia demonstrate this spectacular extension, and show that the modern extension was preceded on many faults by oblique extension and strike-slip motions, perhaps reflecting a change in tectonic setting from sideways escape from the Africa-Arabia collision with Eurasia, to the pure extension related to slab rollback of the African plate, and the retreat of the Hellenic trench.The Kuşadası and Samos faults have similar trends, kinematic features and they are formed in the same extensional system, therefore, they are probably linked in offshore areas. Further seismic studies should be conducted to improve this connection.Extension of the upper plate driven by slab rollback produces relatively large magnitude earthquakes, compared to other areas of continental extension, globally.The region is prone to continuing earthquake and volcanic hazards from historical times to modern days.Further detailed studies are needed in this area to better understand and predict earthquake frequency, possible locations, and to establish better building codes to protect people's lives and property.


School-based social and emotional learning (SEL) programs have been shown to be effective in producing positive outcomes for adolescents. However, variability in implementation quality can have a negative impact on these program effects. The aim of this current study is to examine the variability in implementation quality for schools implementing the MindOut program and to identify factors that were likely to contribute to this variability. Employing a mixed methods approach, quantitative and qualitative implementation data were collected from teachers (n = 16) and students (n = 280) who participated in the MindOut program. Quantitative indicators were used to score schools’ implementation quality across four dimensions , and these were averaged to determine overall level of implementation (high/low). Qualitative data identified factors that contributed to implementation quality, and factors were then analyzed in accordance with the schools’ implementation level grouping. Findings indicated that variability in implementation quality existed both between and within schools. A total of eight schools were assigned as high implementers and another eight as low implementers. Influencing factors were categorized into five themes: (i) program factors, (ii) participant factors, (iii) teacher factors, (iv) school contextual factors, and (v) organizational capacity factors. Several differences between high and low implementers were found in relation to these influencing factors. The findings contribute to the evidence on implementation quality in schools by advancing knowledge on measuring implementation quality across multiple dimensions and informants successfully. These findings can also inform practitioners of the main influencing factors in schools so that strategies can be developed to optimize implementation quality in the future. Well-designed evidence-based social and emotional learning (SEL) programs in schools have been shown to be effective in promoting positive outcomes for students ,2,3,4. HAs awareness of the importance of evaluating implementation quality increases, we also observe a rise in studies reporting on these type of data ,4,12. HoWhile quantitative data on implementation quality can help determine variability in implementation levels and how this relates to outcome attainment, these type of data are not able to answer why this variability might exist. Qualitative evaluations of implementation answer the “why” by allowing researchers to identify the factors that may contribute to implementation variability. Durlak and Dupre  developeIt is clear that both quantitative and qualitative methods of evaluating implementation are important in implementation research. While a number of studies have assessed implementation using one of these methods, fewer studies have included data on both and even fewer examples of these data being integrated have been reported . Mixed mTo assess variability in implementation quality across four dimensions and determine schools’ overall level of implementation (high/low) using an implementation quality index (quantitative);To identify factors that may have influenced the variability in implementation quality as identified by teachers and students ;To examine the relationship between schools’ level of implementation quality and these reported implementation factors (integration).This study is part of a larger c-RCT study of the MindOut program in post-primary schools in Ireland, which involves three distinct phases. Underpinned by CASEL’s competency framework , MindOutThe original c-RCT study  involvedThis study employed a mixed-methods design analyzing the quantitative and qualitative data independently first, then merging and comparing these data through concurrent triangulation method to enhance the validity and credibility of the findings . In thisThe qualitative data were used to identify key factors that may have impacted implementation as identified by both teachers and students. Finally, the integration phase of the study allowed for a deeper exploration of the qualitative data in accordance with the schools’ implementation group allocation to determine if the two groups differed in their reporting of influencing factors. All of the process measures were developed specifically for this study to best capture the details of the MindOut program. The teacher and student quantitative measures were piloted prior to the study. Brief descriptions of the quantitative and qualitative measures employed in this study are provided below, and full details are available from the authors on request.Teacher Weekly Reports: Teachers in the intervention group were asked to complete weekly questionnaires online following delivery of each of the 12 sessions that included questions on the implementation of the program  The questions from this measure that were used to form the implementation index indicators are outlined in Student Review Questionnaire: At the end of program delivery, students from the intervention schools completed a written questionnaire reporting on their experiences of the program  Once again, the selected questions from the Student Review Questionnaire that were used to form the implementation index indicators are described in Classroom Observations: Classroom observations were conducted by the research team with a random sub-sample of schools during the first and second half of the program . Schools were ranked in random order using Microsoft Excel and the first six schools were visited. Observations were guided by questions on adherence to core components, adaptation, quality of delivery and participant responsiveness. Two researchers visited schools on the same day and completed questionnaires independently followed by a consultation whereby a final score for each item was agreed. Inter-rater reliability for items achieved 83% agreement. As it was not feasible, due to timing and resources, to conduct classroom observations in all intervention schools, this measure was used as a validation tool of the implementation indicators. Implementation Quality Indicators: Indicators were carefully selected from the Teacher Weekly Reports and Student Review Questionnaire based on their representativeness of one of the four dimensions of implementation [entation ,6,16. Inentation ,21,22,23Dosage: Dosage was measured through 2 indicators. Dosage 1 was measured by asking teachers if they completed the session , and this was summed across the 12 sessions. Dosage 2 was measured by asking students to tick  if they recalled being present for each of the 12 sessions. Scores were summed across the 12 sessions and students’ scores were averaged within each school. On average, students reported attending 80% of lessons across the 16 schools (range = 41%–95%). Correlations between the two dosage indicators showed that there was a significant relationship between both r = 0.56, p = < 0.05).Adherence: Adherence was measured through 2 indicators from teachers. Adherence 1 was adherence to the key lesson dimensions for each of the 12 sessions based on the Weekly Report data. Different sessions included a different number of items depending on the number of activities . The items across all 12 sessions were summed to give a total score. Adherence 2 was measured through a single item, which asked teachers to rate what percentage of each session was delivered . Scores were summed across the twelve sessions and a total mean score was calculated. Correlations were run between the two adherence indictors and demonstrated a significant positive relationship between both .Quality of Delivery: Quality of delivery was measured through 2 indicators. Quality of Delivery 1 assessed students’ rating of their teachers’ delivery of the program  . A reliability analysis was conducted which demonstrated a high internal consistency between the six items (α = 0.93). A mean score of the combined items was calculated for each student first, and then these scores were combined for an average school score. Quality of Delivery 2 was a single item asking students to give an overall rating of their teachers’ delivery of the program . Students’ individual scores were averaged for each school to give a mean overall rating. Both of the Quality of Delivery indicators were shown to be highly correlated with each other .Participant Responsiveness: Participant Responsiveness was measured using 4 indicators. Participant Responsiveness 1 was measured based on teachers’ ratings of students’ responses to the activities within each session. An average score was calculated for each individual session, and following this, a total mean score was calculated across all 12 sessions for each school. Participant Responsiveness 2 measured teachers’ perceptions of students’ interaction with each of the 12 sessions based on their interest, skills learned and engagement  . A reliability test was run between the 3 items, which demonstrated that the three items showed high internal consistency (α = 0.98). An average score for each of the three items was calculated first, and a total mean score was then calculated across the 12 sessions. Participant Responsiveness 3 measured students’ response to the program across a number of areas  . A reliability test was run between the 4 items, which demonstrated that the three items showed high internal consistency (α = 0.88). A mean score for each of the four items was calculated for each student, and then, a mean score was calculated by averaging the student scores within each school. Participant Responsiveness 4 used one item to assess students’ overall rating of the program (1 = “very poor” 10 = “excellent”). Students’ individual scores were averaged for each school to give an overall mean. A reliability test was run between the four participant responsiveness indicators and showed an acceptable internal consistency (α = 0.73).Telephone Interview: Within 2 weeks of completing the program, teachers (n = 17) were contacted by the researcher via telephone and were asked a series of semi-structured interview questions in relation to their overall experience of implementing the program .Student Participatory-based Workshops: Participatory-based workshops were conducted with a random sub-sample of schools (n = 5). These schools were selected from the randomized list used for the classroom observations, and the next 5 schools on the list (#7-11) were contacted for these workshops. The workshops were based on the methodology used in other studies [ studies ,32 and iStudent Review Questionnaire: The Student Review Questionnaire also contained open-ended questions that gathered qualitative information on the students’ program experience .All of the indicator scores were aggregated at the school level and then converted into a percent score, which allowed for the indicator scores within each dimension to be averaged for a total dimension score. A similar process has been carried out in other implementation studies ,34. InteThere was no weighting of items, therefore, all dimensions contributed equally to the total implementation quality score. Similar methods of combining indicators across dimensions to produce a total index score are found in other studies ,21,22,23All teacher telephone interviews were audio-recorded and transcribed verbatim via a transcription service. Thematic analysis  was usedIntegration of quantitative and qualitative data occurred at an interpretation level using the concurrent triangulation method . Each thA total of 16 schools (n = 280 students) were included in this study.  A majority of schools (63%) chose to deliver the program with a 5th year group instead of a Transition Year (TY) class. (Transition Year (TY) is a one-year optional program that exists between the Junior Certificate program  and the Leaving Certificate program . Transition Year is a less structured year which gives students more space to learn, mature and develop without the presence of exam pressures .) The avTwelve of the sixteen schools implemented the MindOut program in its entirety. Of the four schools that did not complete the program, two delivered less than 60% of the program. Students reported attending 80% of lessons on average across the 16 schools (range = 41%–95%). Based on the visual binning procedure, six schools were classified as low implementers for dosage. On average, teachers reported delivering 71% of the key activities and adhered to 82% of the sessions. Seven schools were identified as low implementers for adherence using the visual binning procedure. Classroom observation scores from the specific sessions the researchers observed were used to validate the teachers’ self-report measures from the same session. Based on the total number of delivered activities on the day, all six schools received a classroom delivery score that was within 10% of the teachers’ adherence score based on their reporting of delivered activities.The average rating given by students for teachers’ quality of delivery was 76% (range = 57%–93%). Eight schools were identified as high implementers for quality of delivery based on visual binning. Once again, classroom observations scores were used to check validity of the self-report data. All six schools that participated in classroom observations had classroom observation scores that were within 10% of the total quality of delivery score. Given that classroom observation scores for quality of delivery were based on one session only and indicator score reflected quality of delivery over the course of the program, slight differences in these scores could be expected.Based on teacher reports, an average rating of students’ interaction with the sessions was calculated across the 12 sessions for each school, and the mean score across all schools was 77% (range = 59%–95%). A total of 75% of students rated the program at 7 or above on a 10-point scale. In accordance with the visual binning procedure, eight schools were identified as high implementers. Classroom observations scores were used to check for reliability. All six schools that participated in classroom observations had total participant response scores that were within 10% of the classroom observation scores. Again, as classroom observation scores for participant responsiveness were based on a single session only whereas the indicator scores were based on the entire program, it is likely that there would be slight differences between the scores.The means and ranges for schools across all dimensions can be found below . The visBased on the visual binning procedure for Total Implementation Quality, two schools were in the low group (1), six in moderately-low (2), six in moderately-high (3) and two in the high group (4). After combining the low/moderately low schools into one group (low implementation) and the high/moderately high schools into the other group (high implementation), eight schools were assigned to both of these groups. The schools that were identified as high implementers for Total Implementation Quality all ranked in the “high” group for at least three of the four dimensions. In comparison, all of the schools identified as low implementing scored in the “high” group in two or less dimensions. The visual binning scores for each of the individual dimensions as well as for Total Implementation Quality can be found in Five themes were identified from the teacher Telephone Interview data: (i) Program factors, (ii) Participant factors, (iii) Teacher factors, (iv) School contextual factors and (v) Organizational capacity factors. The first four themes were also identified through the Student Review Questionnaire and Participatory Workshop data. The fifth theme was only identified as an influencing factor by teachers. The themes and sub-themes for both the teacher and student data can be found in Program factors included the program’s relevance, accessible resources, user-friendliness and teaching strategies. Most teachers felt that the program was age-appropriate for senior students, “I think the fact that all of the content was aimed at that age group, and it was relevant to them. I feel that it went down a treat” with a few teachers suggesting some sessions might suit a younger group. Teachers also felt that the content within the program was culturally relevant for Irish students and thought the lessons were current and timely, “There are so many good practices in here and it’s also culturally ... you know it’s pitched in the right way for the Irish culture.” There was a general consensus from teachers that the resources included useful material that was well laid out and easy to access. Program factors discussed by students included relevance, variety of teaching strategies and the program structure. A majority of students felt that the program was relevant for their age and generation, but a few students could not relate to the content. Students commented on the teaching strategies and said they preferred the interactive teaching strategies, group work and videos, “it was a good way of learning about mental health and made it interesting by using videos and activities so it wasn’t as boring and fully theory”.Participant factors identified by teachers included group dynamic as well as students’ engagement and response to the program. In relation to group dynamic, some teachers felt that the program was easy to implement because of their group, “I suppose I was very lucky with the particular group I had. They were very willing to be involved.” Other teachers felt the group dynamic negatively affected implementation “Their resilience would be very low…they would be weaker students so they wouldn’t necessarily have the vocabulary to ... or the confidence to discuss emotional issues.” There were mixed reports on students’ responsiveness and engagement in the program with some teachers saying their students responded well and others saying the students were disengaged and uninterested. Participant factors discussed by students included their reported experiences of the program, experienced benefits of the program, as well as their enjoyment and interest with the sessions. The majority of students had positive things to say, “it is excellent for all people”, but a few students had negative feelings towards the program, “I didn’t enjoy it or think it was worthwhile”. A majority of students commented on how the program benefitted them, stating that it was helpful and providing examples of specific skills they had developed. In terms of enjoyment and interest with the program, again, the results were mixed with many students finding the program enjoyable and interesting and others commenting that parts were boring. Teacher factors included teachers’ attitudes to the program, their comfort and interest in the content, their preparedness for the lesson as well as their own teaching experience and previous training. In general, teachers were positive towards the program commenting that it was enjoyable to deliver and that the content was valuable. Many teachers stated the importance of being trained in SPHE before delivering MindOut and being comfortable and interested in the content of the program, “It’s important that the teacher ... is interested or passionate about this whole area of mental health because then they’ll be more confident in delivering it and hopefully then the students can take more from it then.” Teacher factors for students were related to teachers’ facilitation skills and preparedness. Some students felt their teacher delivered the program poorly and should have been better prepared, “my teacher wasn’t engaging with us properly and didn’t have some things ready for the class”. School contextual factors described by teachers included the timing of the sessions, the time of year the program is delivered, year of delivery, physical space and technology. Many teachers commented on issues with the timing of the program in regard to completing the sessions during the 35 min class period. These teachers commented on how this impacted the delivery such as cutting activities from the session, inability to complete activities well and failing to complete sessions altogether, “…and while I did get them done they weren’t done you know as well as they should have been”. Teachers also highlighted the importance of starting the program early in the academic year as they get busier and less likely to find time to deliver as the year progresses. There were mixed opinions on which year group was best suited to receive the program. Some schools favored TY due to the lack of exam pressures and more provision to implement, while and other teachers felt that TY was too busy and students were more likely to be absent compared to 5th year, “…a lot of the time there were people missing because it’s TY and they are busy doing all sorts of different things in the school.” School contextual factors mentioned by students included the lack of time for the sessions and classroom disruptions. Some students stated that they felt program sessions were rushed, “we were very rushed for time making it slightly stressful”. A few students discussed how their peers’ disengagement  interfered with completing the sessions on time. Organizational capacity factors included external support, staff support, and support from management. Teachers felt that support from other staff in terms of awareness and helping to deliver the program would be important for sustainability of the program. Some teachers were concerned that other staff members and management did not value the program, “I do think it would have been easier if management had given me that little bit more support… I just didn’t have it.” In terms of external support, teachers expressed that they would like to receive updates from Health Promotion Officers in terms of relevant material and would benefit from meeting with other teachers delivering the program to learn from their experiences and feel more supported. Students did not refer to any factors for this theme. In comparing the demographic data between the two groups, there was a noticeable difference in average class sizes with the high implementers reporting larger group sizes (M = 19.7 SD = 5.34) compared to the low implementers (M = 14.5 SD = 3.67). In terms of year of delivery, a majority of the high-implementing group (75%) delivered the program to 5th years and a majority of the low-implementation group (63%) delivered the program to TY groups. The themes from the qualitative data were further analyzed in accordance with school implementation level grouping to highlight the differences and similarities between the two groups. Further details of this analysis can be found in A number of factors were identified in the data from the high-implementation schools which were unique to this group. In terms of the participant characteristics, the high-implementation group tended to speak more positively about the dynamic of their group  and were more likely to indicate higher student engagement and positive responses to the program. For student data, high implementers were more likely to discuss benefits of the program by providing examples of specific SEL skills they had developed. Whilst there were mixed views for both groups in terms of levels of interest in the program, in general, the high-implementation students made more positive comments. For teacher characteristics, high-implementing teachers demonstrated more positive attitudes when discussing their experience of the program. For organizational factors, high-implementing schools reported a need for more external support from Health Promotion Officers and agencies to continue to build their skills around SEL and mental health. Likewise, a number of specific factors concerning the low-implementation schools also emerged from the data. For participant characteristics, the teachers in the low-implementation group spoke more negatively about the dynamic of their group  and were more likely to comment on student disengagement, lack of interest and negative responses. Similarly, the students in the low-implementation group reported more negative experiences of the program and tended to speak in more general terms when discussing the perceived benefits of the program . In terms of teacher characteristics, students in the low-implementation group reported negative comments about their teachers’ facilitation skills, whereas the high-implementation students did not make any reference to this. In relation to school contextual factors, the low-implementation group commented on issues with delivering the program to a TY group , whereas the high implementers, a majority (75%) of which delivered the program to 5th years, did not discuss any similar issues. Students in the low-implementation group reported experiencing more issues with classroom disruptions and peer disengagement. Finally, in terms of the organizational capacity factors, the low-implementation teachers group expressed their desire for more support from school management for delivering the program.There were no differences between the two groups for “Program factors” based on teacher feedback. Both groups reported that the program dealt with current issues, was relevant and user-friendly. For teacher characteristics, both groups suggested that the teachers’ own teaching experience, as well as their comfort and interest in the program, were essential for implementation. In relation to “School contextual factors”, both groups expressed the importance of introducing the program early in the year and having it completed before the spring term. Both groups agreed that the timing of the sessions  was one of the most difficult challenges faced during implementation. Students of both groups reported finding the program long and suggested shortening some of the sessions. For “Organizational capacity factors”, teachers in both groups reported that they would have liked more support from other staff within the school. This study set out to assess the variability in implementation quality of schools delivering the MindOut program and to investigate the factors that most likely contributed to this variability, particularly in relation to schools’ implementation level. These aims were achieved through a mixed methods approach assessing quantitative and qualitative data from teachers and students and integrating these to form a clearer picture of implementation quality in schools. A major finding from this analysis was that variability in implementation quality existed both between and within schools, which is in line with other research ,22,23. IThis study also examined factors that affected implementation as identified by both teachers and students. While the sample included a range of mixed gender schools, the majority of the teachers involved were female. It is therefore unclear to what extent these findings on teachers’ perspectives would also apply to male teachers. Consistent with the findings of previous studies ,10,11, oA unique aspect of the present study is that it also examined whether or not high- and low-implementation groups differed in their reporting of implementation factors. The analysis found that schools in the high-implementation group were more likely to have larger class sizes in comparison to the low-implementation group, which contradicts previous studies indicating that increased class sizes lead to decreases in quality implementation ,43. It iIn terms of “Teacher factors”, teachers of higher-implementing schools demonstrated more positive attitudes towards the program compared to low implementers. Perceived value of the program, acceptance of the intervention and its perceived effectiveness are all factors that lead to stronger implementation . TherefoThis study employed a mixed-methods design using the strengths of both quantitative and qualitative research. Unlike a majority of implementation studies that focus primarily on data from program implementers only, this study assessed implementation based on feedback from both teachers and students. While feedback from the implementer is important, students provide a different perspective and additional data, particularly in relation to the quality of delivery and participant responsiveness. A major limitation of this study is that implementation was assessed primarily using self-report data, which is often criticized for being biased and over-estimating implementation practices . Though This study demonstrated that variability in implementation existed both between schools as well as within schools, across different dimensions. This highlights the need for researchers to systematically assess implementation quality in evaluation studies to ensure benefits of a program are not lost due to poor implementation. This finding also provides a rationale for evaluating implementation across several dimensions given that so much variability can be seen within schools. Future research assessing how implementation variability influences outcome achievement will be important within the context of this program evaluation. The next phase of this study (phase 3) will explore this, by assessing how variability in implementation quality impacts on students’ outcomes. This study also provided a rich narrative on what factors may be contributing to the variability in implementation quality between schools. More specifically, these data highlight the factors that are more likely to be associated with high- and low-implementing schools. These findings are especially important for program developers and practitioners as it allows them to embed strategies into the planning and delivery stages of implementation  in an effort to optimize quality of implementation, which will lead to better outcomes for participants. This study demonstrated an effective way of assessing implementation quality of a school-based program by scoring schools on a range of indicators and combining these scores to produce a total implementation score for each school. Based on the total implementation quality score, eight schools were identified as high implementers, and another eight were low implementers. Not all schools scored consistently high or low across all four dimensions. This finding highlights that variability in implementation quality not only existed between schools but within schools as well. This study also identified the factors that are likely to contribute to the variability in implementation quality as defined by teachers and students. Finally, this study was able to determine if certain factors were more likely to modify implementation quality when comparing high- and low-implementation groups. These findings contribute to the evidence on implementation quality in schools by advancing knowledge on measuring and assessing implementation quality across multiple dimensions successfully. The findings also help to inform practitioners of the factors that impact implementation variability so that strategies can be developed to mitigate this variance in the future. The findings from this study will help to inform the next stage of the study, which will examine how variable levels of implementation quality relate to program outcomes.