Tailored multicomponent intervention for remote physical activity promotion in inactive adults

Background: The health benefits of physical activity are well established and widely recognized. Nevertheless, one third of adults worldwide as well as in Switzerland do not achieve the minimum of 150 minutes of at least moderate physical activity per week. The main reasons for this are a lack of time and a lack of motivation. With regard to individual and societal health consequences, effective programs to promote physical activity are therefore needed. Interventions to promote physical activity without face-to-face contact seem particularly suitable to reach inactive adults. Telephone coaching as well as regular messages (prompts) or internet-based programs have been shown to result in short-term health-relevant behavior changes. Thereby, individually tailored interventions, as well as the implementation of certain behavior change techniques (e.g. self-monitoring, action planning, barrier management) were found most effective in increasing physical activity. Existing studies mainly assessed the effect on self-reported physical activity. Objectively measured physical activity, long-term effects but also mechanisms of action leading to a change in physical activity behavior have rarely been investigated. Additionally, it remains unknown, which delivery modes are most effective and can best be translated into practice. Aim: This PhD project aimed to develop a physical activity promotion program and to evaluate different versions to communicate it. The short- and long-term effects of telephone coaching and short message services (SMS) prompting on self-reported and objectively assessed physical activity were investigated. A further objective was to examine, whether psychosocial determinants (e.g. outcome expectations, action planning) of physical activity mediate the effect of the intervention. Methods: The "Movingcall" study is a three-armed randomized controlled trial with a six-month intervention and a six-month no-contact follow-up period. Two hundred and eighty-eight insufficiently active adults, aged 20 to 65 years, were assigned to three different versions of a physical activity promotion program. A “coaching group” received 12 biweekly telephone coaching sessions. In a “coaching and SMS group” the coaching was extended by four SMS prompts among each coaching session (48 SMS in total). The "control group" received a minimal credible interven-tion consisting of a single written recommendation. All participants were additionally asked to plan and self-monitor their physical activity behavior on a personal web application. The intervention consisted of evidence-based behavior change techniques and training recommendations in all three study-arms. The intervention content was individually tailored to the preferences and needs of the participants. Outcome measures were assessed at baseline, after the intervention (6 months) and after the follow-up period (12 months). Self-reported moderate-to-vigorous physical activity (MVPA) in one week was assessed using a standardized interview based on the Simple Physical Activity Question-naire. Additionally, a wrist-worn accelerometer was applied to measure physical activity behavior of the same week objectively. Psychosocial determinants of physical activity as well as participants’ acceptance of the program were assessed via online questionnaires. Between group differences and changes over time in physical activity behavior were computed using linear mixed models. The mediating influences of psychosocial determinants were calculated in structural equation models. Results: The study population comprised two-thirds women, had a mean age of 42 years (SD = 11) and at baseline the self-reported MVPA was 108 minutes/week (SD = 142). After the six-month intervention, self-reported physical activity increased by 173 minutes/week (95% CI 95 to 252) in the coaching group and by 165 minutes/week (95% CI 84 to 246) in the coaching and SMS group compared to the control group. The increased level of self-reported physical activity was main-tained after the follow-up period and the observed group differences persisted. Via accelerometer assessed physical activity, increases of 32 minutes/week (95% CI 0 to 63) in the coaching and 34 minutes/week (95% CI 2 to 66) in the coaching and SMS group compared to the control group were observed. The objectively assessed physical activity of the two intervention groups returned to the baseline-levels after the follow-up period. Group differences persisted in the long-term, as the control group decreased its objectively assessed physical activity level below baseline values. Additional SMS prompts did not lead to a further increase in physical activity at either of the measurement points. The analysis of the psychosocial determinants of physical activity behavior revealed that the coaching resulted in a sustainable improvement of planning and barrier management. Right after the coaching interventions, there were also positive effects on self-efficacy, outcome expectations as well as on intention. An improvement in these determinants was, however, only weakly associated with increased physical activity. A mediation was only observed for increased objectively assessed physical activity after six months through increases in barrier management. The telephone coaching was well accepted and rated positively. More than 80% of the coaching as well as the coaching and SMS group and 19% of the control group reported that they were satisfied with the program. Conclusion: Telephone coaching led to higher physical activity levels in the short and long-term compared to a single written recommendation. The two intervention groups showed a relevant and sustainable increase in self-reported physical activity. However, the maintenance of achieved behavior change needs to be interpreted cautiously, as increases in objectively assessed physical activity returned to baseline after the follow-up period. Additional SMS prompts did not increase the efficacy of the coaching intervention. In accordance with theory and previous literature, the promotion of evidence-based behavior change techniques resulted in positive changes in psychosocial determinants of physical activity. Nevertheless, the intervention’s mechanisms of action remain largely unknown, as there was almost no mediation of physical activity by these determinants. Overall, telephone coaching can be considered an effective and well-accepted tool to support adults in adopting a physically active lifestyle

evaluation of vaginal discharge following treatment with a progesterone insert

Yellowish discharge after application of intravaginal progesterone releasing inserts is frequently observed in cows. The objective of this study was to compare the bacteriological contamination of the vagina and uterus before and after a treatment with a progesterone insert in heifers. Forty-two Holstein heifers received a progesterone releasing insert [Eazi-Breed controlled internal drug release (CIDR) insert; Pfizer Animal Health, Berlin, Germany] for 7d. The protruding tail had been removed from half of the inserts (no tail group: n=21; tail group: n=21). Nine heifers from the tail group lost the insert within the 7-d treatment interval and were excluded. Heifers identified in estrus were artificially inseminated on d 9 or 10. Vaginal discharge was scored on a 4-point scale [vaginal discharge score (VDS) 0 to 3] and vaginal swabs were taken for bacteriological examination on d 0 and 7 and the day of artificial insemination (AI). Furthermore, cytological and bacteriological samples were obtained from the uterus on d 7 and the day of AI. On d 0, coliforms and Streptococcus spp. were found in vaginal swabs of 21 heifers (64%). On d 7, all heifers showed purulent vaginal discharge (VDS 2 to 3). The VDS was higher in the tail group compared with the no tail group. Arcanobacterium pyogenes, coliforms, and Streptococcus spp. were isolated from the vaginal swabs in 32 of 33 (96%) heifers on d 7. On the day of AI, VDS had improved to 0 or 1 in 96% of the heifers. However, A. pyogenes, coliforms, and Streptococcus spp. were still isolated in 17 of 33 (53%) heifers from the vagina and in 32 of 33 (96%) heifers from the endometrium. Endometrial cytology revealed polymorphonuclear neutrophils (PMN) in 11 heifers (6 to 32% PMN). Five samples exceeded the threshold of 5% PMN, and 2 samples exceeded the 10% PMN threshold, indicative of subclinical endometritis. In conclusion, pyogenic bacteria were found in the vagina and uterus on d 7 and the day of AI after intravaginal progesterone treatment. The severity of the discharge was affected by the protruding tail of the insert

The NORMAN Suspect List Exchange (NORMAN-SLE): facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry

Background: The NORMAN Association (https://www.norman-.network.com/) initiated the NORMAN Suspect List Exchange (NORMAN-SLE; https://www.norman-.network.com/nds/SLE/) in 2015, following the NORMAN collaborative trial on non-target screening of environmental water samples by mass spectrometry. Since then, this exchange of information on chemicals that are expected to occur in the environment, along with the accompanying expert knowledge and references, has become a valuable knowledge base for "suspect screening" lists. The NORMAN-SLE now serves as a FAIR (Findable, Accessible, Interoperable, Reusable) chemical information resource worldwide.Results: The NORMAN-SLE contains 99 separate suspect list collections (as of May 2022) from over 70 contributors around the world, totalling over 100,000 unique substances. The substance classes include per- and polyfluoroalkyl substances (PFAS), pharmaceuticals, pesticides, natural toxins, high production volume substances covered under the European REACH regulation (EC: 1272/2008), priority contaminants of emerging concern (CECs) and regulatory lists from NORMAN partners. Several lists focus on transformation products (TPs) and complex features detected in the environment with various levels of provenance and structural information. Each list is available for separate download. The merged, curated collection is also available as the NORMAN Substance Database (NORMAN SusDat). Both the NORMAN-SLE and NORMAN SusDat are integrated within the NORMAN Database System (NDS). The individual NORMAN-SLE lists receive digital object identifiers (DOIs) and traceable versioning via a Zenodo community (https:// zenodo.org/communities/norman-.sle), with a total of > 40,000 unique views, > 50,000 unique downloads and 40 citations (May 2022). NORMAN-SLE content is progressively integrated into large open chemical databases such as PubChem (https://pubchem.ncbi.nlm.nih.gov/) and the US EPA's CompTox Chemicals Dashboard (https://comptox. epa.gov/dashboard/), enabling further access to these lists, along with the additional functionality and calculated properties these resources offer. PubChem has also integrated significant annotation content from the NORMAN-SLE, including a classification browser (https://pubchem.ncbi.nlm.nih.gov/classification/#hid=101).Conclusions: The NORMAN-SLE offers a specialized service for hosting suspect screening lists of relevance for the environmental community in an open, FAIR manner that allows integration with other major chemical resources. These efforts foster the exchange of information between scientists and regulators, supporting the paradigm shift to the "one substance, one assessment" approach. New submissions are welcome via the contacts provided on the NORMAN-SLE website (https://www.norman-.network.com/nds/SLE/)

The NORMAN Suspect List Exchange (NORMAN-SLE): Facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry

Background: The NORMAN Association (https://www.norman-network.com/) initiated the NORMAN Suspect List Exchange (NORMAN-SLE; https://www.norman-network.com/nds/SLE/) in 2015, following the NORMAN collaborative trial on non-target screening of environmental water samples by mass spectrometry. Since then, this exchange of information on chemicals that are expected to occur in the environment, along with the accompanying expert knowledge and references, has become a valuable knowledge base for “suspect screening” lists. The NORMAN-SLE now serves as a FAIR (Findable, Accessible, Interoperable, Reusable) chemical information resource worldwide. Results: The NORMAN-SLE contains 99 separate suspect list collections (as of May 2022) from over 70 contributors around the world, totalling over 100,000 unique substances. The substance classes include per- and polyfluoroalkyl substances (PFAS), pharmaceuticals, pesticides, natural toxins, high production volume substances covered under the European REACH regulation (EC: 1272/2008), priority contaminants of emerging concern (CECs) and regulatory lists from NORMAN partners. Several lists focus on transformation products (TPs) and complex features detected in the environment with various levels of provenance and structural information. Each list is available for separate download. The merged, curated collection is also available as the NORMAN Substance Database (NORMAN SusDat). Both the NORMAN-SLE and NORMAN SusDat are integrated within the NORMAN Database System (NDS). The individual NORMAN-SLE lists receive digital object identifiers (DOIs) and traceable versioning via a Zenodo community (https://zenodo.org/communities/norman-sle), with a total of > 40,000 unique views, > 50,000 unique downloads and 40 citations (May 2022). NORMAN-SLE content is progressively integrated into large open chemical databases such as PubChem (https://pubchem.ncbi.nlm.nih.gov/) and the US EPA’s CompTox Chemicals Dashboard (https://comptox.epa.gov/dashboard/), enabling further access to these lists, along with the additional functionality and calculated properties these resources offer. PubChem has also integrated significant annotation content from the NORMAN-SLE, including a classification browser (https://pubchem.ncbi.nlm.nih.gov/classification/#hid=101). Conclusions: The NORMAN-SLE offers a specialized service for hosting suspect screening lists of relevance for the environmental community in an open, FAIR manner that allows integration with other major chemical resources. These efforts foster the exchange of information between scientists and regulators, supporting the paradigm shift to the “one substance, one assessment” approach. New submissions are welcome via the contacts provided on the NORMAN-SLE website (https://www.norman-network.com/nds/SLE/)

The NORMAN Suspect List Exchange (NORMAN-SLE): facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry

The NORMAN Association (https://www.norman-network.com/) initiated the NORMAN Suspect List Exchange (NORMAN-SLE; https://www.norman-network.com/nds/SLE/) in 2015, following the NORMAN collaborative trial on non-target screening of environmental water samples by mass spectrometry. Since then, this exchange of information on chemicals that are expected to occur in the environment, along with the accompanying expert knowledge and references, has become a valuable knowledge base for "suspect screening" lists. The NORMAN-SLE now serves as a FAIR (Findable, Accessible, Interoperable, Reusable) chemical information resource worldwide.The NORMAN-SLE project has received funding from the NORMAN Association via its joint proposal of activities. HMT and ELS are supported by the Luxembourg National Research Fund (FNR) for project A18/BM/12341006. ELS, PC, SEH, HPHA, ZW acknowledge funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101036756, project ZeroPM: Zero pollution of persistent, mobile substances. The work of EEB, TC, QL, BAS, PAT, and JZ was supported by the National Center for Biotechnology Information of the National Library of Medicine (NLM), National Institutes of Health (NIH). JOB is the recipient of an NHMRC Emerging Leadership Fellowship (EL1 2009209). KVT and JOB acknowledge the support of the Australian Research Council (DP190102476). The Queensland Alliance for Environmental Health Sciences, The University of Queensland, gratefully acknowledges the financial support of the Queensland Department of Health. NR is supported by a Miguel Servet contract (CP19/00060) from the Instituto de Salud Carlos III, co-financed by the European Union through Fondo Europeo de Desarrollo Regional (FEDER). MM and TR gratefully acknowledge financial support by the German Ministry for Education and Research (BMBF, Bonn) through the project “Persistente mobile organische Chemikalien in der aquatischen Umwelt (PROTECT)” (FKz: 02WRS1495 A/B/E). LiB acknowledges funding through a Research Foundation Flanders (FWO) fellowship (11G1821N). JAP and JMcL acknowledge financial support from the NIH for CCSCompendium (S50 CCSCOMPEND) via grants NIH NIGMS R01GM092218 and NIH NCI 1R03CA222452-01, as well as the Vanderbilt Chemical Biology Interface training program (5T32GM065086-16), plus use of resources of the Center for Innovative Technology (CIT) at Vanderbilt University. TJ was (partly) supported by the Dutch Research Council (NWO), project number 15747. UFZ (TS, MaK, WB) received funding from SOLUTIONS project (European Union’s Seventh Framework Programme for research, technological development and demonstration under Grant Agreement No. 603437). TS, MaK, WB, JPA, RCHV, JJV, JeM and MHL acknowledge HBM4EU (European Union’s Horizon 2020 research and innovation programme under the grant agreement no. 733032). TS acknowledges funding from NFDI4Chem—Chemistry Consortium in the NFDI (supported by the DFG under project number 441958208). TS, MaK, WB and EMLJ acknowledge NaToxAq (European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant Agreement No. 722493). S36 and S63 (HPHA, SEH, MN, IS) were funded by the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU) Project No. (FKZ) 3716 67 416 0, updates to S36 (HPHA, SEH, MN, IS) by the German Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection (BMUV) Project No. (FKZ) 3719 65 408 0. MiK acknowledges financial support from the EU Cohesion Funds within the project Monitoring and assessment of water body status (No. 310011A366 Phase III). The work related to S60 and S82 was funded by the Swiss Federal Office for the Environment (FOEN), KK and JH acknowledge the input of Kathrin Fenner’s group (Eawag) in compiling transformation products from European pesticides registration dossiers. DSW and YDF were supported by the Canadian Institutes of Health Research and Genome Canada. The work related to S49, S48 and S77 was funded by the MAVA foundation; for S77 also the Valery Foundation (KG, JaM, BG). DML acknowledges National Science Foundation Grant RUI-1306074. YL acknowledges the National Natural Science Foundation of China (Grant No. 22193051 and 21906177), and the Chinese Postdoctoral Science Foundation (Grant No. 2019M650863). WLC acknowledges research project 108C002871 supported by the Environmental Protection Administration, Executive Yuan, R.O.C. Taiwan (Taiwan EPA). JG acknowledges funding from the Swiss Federal Office for the Environment. AJW was funded by the U.S. Environmental Protection Agency. LuB, AC and FH acknowledge the financial support of the Generalitat Valenciana (Research Group of Excellence, Prometeo 2019/040). KN (S89) acknowledges the PhD fellowship through Marie Skłodowska-Curie grant agreement No. 859891 (MSCA-ETN). Exposome-Explorer (S34) was funded by the European Commission projects EXPOsOMICS FP7-KBBE-2012 [308610]; NutriTech FP7-KBBE-2011-5 [289511]; Joint Programming Initiative FOODBALL 2014–17. CP acknowledges grant RYC2020-028901-I funded by MCIN/AEI/1.0.13039/501100011033 and “ESF investing in your future”, and August T Larsson Guest Researcher Programme from the Swedish University of Agricultural Sciences. The work of ML, MaSe, SG, TL and WS creating and filling the STOFF-IDENT database (S2) mostly sponsored by the German Federal Ministry of Education and Research within the RiSKWa program (funding codes 02WRS1273 and 02WRS1354). XT acknowledges The National Food Institute, Technical University of Denmark. MaSch acknowledges funding by the RECETOX research infrastructure (the Czech Ministry of Education, Youth and Sports, LM2018121), the CETOCOEN PLUS project (CZ.02.1.01/0.0/0.0/15_003/0000469), and the CETOCOEN EXCELLENCE Teaming 2 project supported by the Czech ministry of Education, Youth and Sports (No CZ.02.1.01/0.0/0.0/17_043/0009632).Peer reviewe

Einfluss aerober Bewegung auf Schlafqualität und BDNF bei Depression

Ausgangslage: Depression steht in Verbindung mit einer verminderten Schlafqualität (Steiger & Kimura, 2010) und einer tiefen BDNF-Konzentration (brain-derived neurotrophic factor; Sen, Duman, & Sanacora, 2008). Beide Parameter werden im Zusammenhang mit der biologischen Vermittlung eines antidepressiven Effekts körperlicher Aktivität diskutiert (Silveira et al., 2013). Aerobe Aktivität kann die Schlafqualität positiv beeinflussen (Kubitz, Landers, Petruzzello, & Han, 1996) und zu einer Steigerung der BDNFKonzentration führen (Seifert et al., 2010). Die vorliegende Arbeit untersucht, ob regelmässige aerobe Aktivität als Zusatztherapie zu einer Standardbehandlung, einen positiven Einfluss auf die objektive Schlafqualität, die BDNF-Konzentration und die Symptombelastung bei Depression aufweist. Methode: 18 Patienten mit einer mittelgradigen bis schweren depressiven Episode wurden randomisiert einem Ausdauertraining (17.5 kcal/kg/Woche) oder einem Dehnungs- und Mobilisationsprogramm zugeteilt. Die Intervention fand während eines stationären Aufenthaltes drei Mal wöchentlich für einen Zeitraum von sechs Wochen statt. Vor (Pre-Test) und nach (Post-Test) der Intervention wurde ein Schlaf-EEG durchgeführt. Die Schlafqualität wurde anhand der EEG-Variablen SWS (slow wave sleep) und WASO (wake after sleep onset) bewertet. Die BDNF-Konzentration wurde im Blutserum bestimmt und die Schwere der depressiven Störung anhand der Hamilton-Depressionsskala (HAMD-17) erfasst. Mittels ANCOVAs (analysis of covariance) wurde berechnet, ob sich die Interventionen verschieden auf die Zielparameter auswirkten. Resultate: Es konnte kein signifikanter Unterschied der beiden Bewegungsformen in ihrer Wirkung auf SWS (p = 0.424), WASO (p = 0.815), BDNF (p = 0.562) und die HAMD-17- Punktzahl (p = 0.368) festgestellt werden. Die Minderung depressiver Symptome wies keine signifikanten Zusammenhänge zu Veränderungen der objektiven Schlafqualität auf. Auch die BDNF-Konzentration zeigte keine Korrelationen zu Verbesserungen im Schlaf- EEG und der Symptombelastung. Schlussfolgerung: Im Vergleich zu einem Dehnungs- und Mobilisationsprogramm führte aerobes Ausdauertraining zu keiner zusätzlichen Verbesserung der objektiven Schlafqualität, der BDNF-Konzentration und der Symptombelastung. Es lassen sich keine Schlüsse zur biologischen Vermittlung eines antidepressiven Effekts aerober Aktivität über die Schlafqualität oder BDNF ziehen. Auf Grund der kleinen Probandenzahl verfügt die Studie nicht über genügend Teststärke um kleine oder mittlere Effekte aufzudecken. Es ist zudem möglich, dass die Kontrollgruppe ebenfalls antidepressiv wirksam war und Gruppenunterschiede daher geringer ausfielen

Exploring psychosocial mediators of remote physical activity counselling: a secondary analysis of data from a 1-year randomized control trial (Movingcall)

The present study investigated whether psychosocial determinants mediate the effect of a telephone coaching intervention on physical activity levels. Two hundred eighty-eight adults were randomly assigned to a six-month telephone coaching intervention (n = 12 calls) or a control group receiving a single written recommendation. Seven psychosocial determinants as defined in the MoVo model as well as objective and self-reported physical activity levels were measured after 6 and 12 months. Participants also reported which taught intervention strategies (behavior change techniques) they perceived as most useful. Structural equation modeling was used to determine the mediating role of psychosocial determinants. Up to 227 participants with complete data on psychosocial determinants and physical activity were included in the mediation analyses. Compared to the control group, a greater increase in self-reported and objectively assessed physical activity levels was observed the coaching intervention group. The mediation analyses showed that the intervention had a positive effect on self-efficacy, outcome expectations and intention strength after 6 months and on action planning and barrier management after 6 and 12 months. Increases in objectively assessed physical activity after 6 months were mediated by increased barrier management. None of the other psychosocial determinants worked as mediating factors on self-reported or objectively assessed physical activity. The participants perceived 'action planning' and 'problem solving' as the most useful strategies to increase their physical activity levels. Further understanding of working mechanisms of remote physical activity promotion is needed

Coaching and Prompting for Remote Physical Activity Promotion: Study Protocol of a Three-Arm Randomized Controlled Trial (Movingcall)

Background; . Physical inactivity is currently seen as one of the biggest global public health issue. Remote physical activity (PA) promotion programs are expected to be effective if they are individually tailored and include behavior change techniques, personal coaching, and regular prompting. However, it is still not fully understood which intervention components are most effective. This paper describes the rationale and design of a study on an individually tailored remote PA promotion program comparing the efficacy of coaching and prompting with a single written advice.; Methods; . In total, 288 adults (age 20 to 65 years) were randomly assigned to three different intervention arms of a 6-month-long PA promotion program. A minimal intervention group received a single written PA recommendation. The two remaining groups either received telephone coaching sessions (; n; = 12 calls) with or without additional short message service (SMS) prompting (; n; = 48 SMSs for each participant). Data assessment took place at baseline, at the end of the intervention, and after a six-month follow-up-period. The primary outcome of the study was self-reported PA. Objectively assessed PA, psychosocial determinants of PA, well-being, body mass index (BMI), and adherence were assessed as secondary outcomes.; Conclusion; . Findings of this three-arm study will provide insight into the short and long-term effects of coaching and prompting for PA promotion

Telephone-Based Coaching and Prompting for Physical Activity: Short- and Long-Term Findings of a Randomized Controlled Trial (Movingcall)

This study analyzed the short- and long-term efficacy of telephone coaching and short message service (SMS) prompting for physical activity (PA) promotion. Two-hundred-and-eighty-eight adults (age: 42 ± 11 years) were assigned randomly to three intervention arms: The intervention groups received 12 bi-weekly telephone calls with (coaching and SMS group) or without (coaching group) additional SMS prompts (; n; = 48 SMS). The control group received a single written PA recommendation. Self-reported and objective moderate-to-vigorous physical activity (MVPA) levels were assessed by a structured interview and by accelerometer at baseline, after the intervention (6 months), as well as after a no-contact follow-up (12 months). At post-test, self-reported MVPA increased by 173 min/week (95% CI 95 to 252) in the coaching group and by 165 min/week (95% CI 84 to 246) in the coaching and SMS group compared to control. These group differences remained similar in the follow-up test. For the objectively assessed MVPA, the coaching group increased by 32 min/week (95% CI 0.1 to 63) and the coaching and SMS group by 34 min/week (95% CI 1.6 to 66) compared to the control group. In the follow-up test, the objective MVPA levels of the intervention groups no longer differed from baseline, but group differences persisted as the control group decreased below baseline. Additional SMS prompts did not result in a further increase in PA. Telephone coaching can be considered an effective tool for PA promotion