Insufficient physical activity is associated with various health risks; however, most current physical activity interventions have critical barriers to scalability. Delivering interventions via technology and identifying active and inert components in early-phase development are ways to build more efficient and scalable interventions. We developed a novel intervention to promote physical activity that targets 3 brief guided thinking tasks, separately and in combination, using brief audio recordings: (1) episodic future thinking (EFT), (2) positive affective imagery (PAI), and (3) planning.The aim of this GeT (Guided Thinking) Active study is to optimize a scalable guided thinking intervention to promote physical activity using principles of the Multiphase Optimization Strategy (MOST). Mechanism-focused analyses will inform which components are optimal candidates for inclusion in an intervention package and which need refinement.We will enroll 192 participants randomized to receive intervention components delivered via an audio recording that they will listen to prior to weekly in-lab physical activity sessions. Participants in the high dose conditions will also be instructed to listen to the audio recording 4 additional days each week. We will evaluate effects of the components on physical activity over 6 weeks in a 2 (EFT vs recent thinking) × 2  × 2 (planning vs no planning) × 2 (dose: 5×/week vs 1×/week) full factorial randomized trial.The National Cancer Institute funded this study (R21CA260360) on May 13, 2021. Participant recruitment began in February 2022. Data analysis will begin after the completion of data collection.The GeT Active study will result in a scalable, audio-recorded intervention that will accelerate progress toward the full development of guided thinking interventions to promote physical activity.ClinicalTrials.gov NCT05235360; https://clinicaltrials.gov/ct2/show/NCT05235360DERR1-10.2196/40908 M=8.4 components among 26 interventions [Insufficient levels of regular physical activity, defined as less than 150 minutes a week of moderate-to-vigorous physical activity (MVPA), are associated with numerous health risks, including cardiovascular disease, obesity, and various cancers . Nearly ventions ) withoutDelivering physical activity interventions via technology-based platforms can address scalability and dissemination barriers by minimizing cost and resource demands. Physical activity interventions delivered via smartphone apps, websites, and audio recordings ,13,17 haWe developed a novel intervention to promote physical activity that targets 3 brief intervention techniques, separately and in combination. Episodic future thinking (EFT) is a guided time-perspective task that directs individuals to actively imagine themselves in the future at a meaningful event -27. PosiIn developing and optimizing a scalable physical activity intervention, EFT, PAI, and planning have several advantages as potential intervention components. First, each component can be delivered as a brief intervention . Lack of time is a common barrier to physical activity ,33; therThird, each component targets a different putative mechanism and thus different barriers to activity . A key mTo optimize the intervention with EFT, PAI, and planning, the unique and combined effects of the components need to be compared as they have previously only been examined separately, and their combined effects on physical activity are unknown. Three possible effects have implications when deciding which combination of components is optimal : (1) indComparing different frequencies of intervention use  and how different doses influence the effects of EFT, PAI, and planning provides additional information for determining optimal combinations . Optimal dosage of physical activity interventions is typically unexamined and a part of the “black box.” Determining mechanisms of the intervention components also accelerates the optimization process. We will use an experimental medicine approach ,58 to teThe overall objective of the GeT Active study is to optimize a scalable guided thinking intervention to promote physical activity, using principles of the MOST framework . We willWe plan to enroll 192 participants who will be randomized to receive the intervention components delivered via an audio recording that they will listen to prior to the weekly in-lab physical activity sessions. Participants in the high dose conditions will also be instructed to listen to the audio recording 4 additional days during each week. We will use a full factorial design whereby participants will be randomized to 1 of 16 combinations of the 4 intervention components . The 4 iThe first intervention component is episodic future thinking (EFT). In the baseline session, participants will complete an interview with a research assistant (RA) to identify and imagine a positive event that is important to them and that they will experience 4-6 months into the future. In the audio recording (2 minutes and 35 seconds in length), participants will be prompted to imagine themselves at that future event in specific and vivid detail , including imagining they have accomplished their goal of becoming more physically active over the preceding months. The content is similar to EFT tasks that have positively influenced food choice ,28. PartThe second intervention component is positive affective imagery (PAI). Participants will be guided by the audio recording (3 minutes and 50 seconds in length) to think about positive feelings and associations with physical activity in specific, personal, and positive detail. They will imagine themselves engaging in physical activity, reframing physical sensations with positive attributions, and feeling satisfied about the challenge and accomplishment of physical activity. The content is similar to PAI tasks in previous studies ,28,34. PThe third intervention component is planning. Participants will be guided by the audio recording (2 minutes and 35 seconds in length) to think about the remainder of their week and when , where , and how  they plan to attain their remaining MVPA to reach the weekly 150-minute goal. The content is similar to planning tasks that have been shown to influence physical activity ,40,41. PThe fourth component is the intervention dose. Participants will receive their assigned combination of intervention components either once a week during the in-person visit (low dose) or 5 times a week . Participants in the high dose conditions will receive instructions on how to access their audio recording file and will be assigned 4 additional days, including 1 weekend day, to listen to their audio recording. They will receive text message reminders to listen to the recording on those 4 days.In each audio recording, the guided thinking components always appear in the following order: EFT/ERT, PAI/neutral imagery, and planning. We selected this order to minimize the cognitive load that temporal switching between tasks will require. This order allows listeners to imagine a future (or past) event first and then switch to the guided thinking tasks that are more present-focused. Planning is the final guided thinking component because it is designed to leverage the increased motivation for physical activity targeted by the other components and focus on enacting physical activity . We will use a 2 (EFT vs recent thinking) × 2  × 2 (planning vs no planning) × 2 (dose: high vs low) full factorial design with a 1:1 allocation ratio to evaluate the components and their combinations in this randomized trial. This is not a 16-arm trial requiring comparison on individual experimental conditions; instead, the design allows for comparisons of means computed across aggregates of experimental conditions . For example, the main effect of the EFT component will be tested by comparing the mean MVPA for the half of the sample who receive the EFT component  on January 14, 2021.The inclusion criteria are that participants must (1) be 18-64 years of age, (2) be capable of providing informed consent, (3) have access to a smartphone, (4) be willing to attend all study visits and comply with the protocol, (5) be conversant in English, and (6) not currently meet recommended physical activity guidelines (defined as <150 minutes/week of self-reported MVPA). For safety considerations that could make moderate-intensity activity unsafe , we willWe will recruit 192 community-dwelling adults who are not currently meeting recommended physical activity guidelines. Recruitment strategies will focus on online postings and social media advertisements on various platforms  in the Dallas-Fort Worth area. We will also actively recruit adults from traditionally underrepresented groups through advertising and postings in online outlets and community facilities that serve racial and ethnic minority groups.Initial eligibility will be determined with an online prescreen questionnaire, in which potential participants will report their physical activity for a typical week over the past 6 months using items from the International Physical Activity Questionnaire (IPAQ) . They wiOn the day prior to the baseline study visit, we will assess participants’ physical activity during the past week using the telephone-based 7-day Physical Activity Recall (PAR), a valid and reliable measure of physical activity . ParticiWe will stratify randomization based on 2 levels of baseline MVPA to explore the extent to which baseline MVPA moderates intervention effects: 1) individuals who report <60 minutes of weekly MVPA  and (2) those who report between 60 and 149 minutes of weekly MVPA . These MVPA cutoffs reflect meaningful distinctions in current physical activity recommendations [ individuThere will be a total of 7 in-person visits over the 6-week study period. During these visits, participants will listen to their assigned audio recording, engage in a supervised 30-minute moderate-intensity walk on a treadmill, and complete study measures.After completing the informed consent process, all participants will receive the same physical activity prescription  that is consistent with current recommendations . All parPrior to listening to their assigned audio recording, participants will complete a baseline measure of study variables and demographics. Participants will then listen to their assigned audio recording before completing the in-lab brisk walking session. The audio file will be stored on a secured website and accessed via a tablet. Participants will be instructed to sit comfortably, close their eyes, and pay close attention to the guided thinking tasks. After listening to the audio recording and before walking, participants will complete assessments of the putative mechanisms.Participants will receive instructions on how to wear a hip-worn accelerometer (ActiGraph wGT3X-BT) and then complete a supervised 30-minute brisk walk on a treadmill. Participants will also wear a heart rate monitor to ensure their walking intensity remains in the moderate range . We will instruct participants to use the walking intensity to guide their unsupervised walking sessions during the remainder of the week. Participants will complete assessments of affective response, perceived exertion, and arousal during and immediately postexercise. Following the brisk walking session, participants will be reminded to aim for an additional 120 minutes (2 hours) of activity during the upcoming week, wear the accelerometer every day, listen to the audio recording on the designated days (high dose conditions).During the weekly visit, the previous week’s data from the accelerometer will be downloaded and recorded. The RA will then conduct a 7-day PAR with participants to assess self-reported physical activity over the previous week. Participants in the high dose conditions will be asked to report their adherence to listening to the audio recording. The remainder of the weekly visits will follow the same procedure as the baseline visit. In the visits at weeks 3 and 6, participants will also complete a questionnaire that includes several exploratory variables assessed in the baseline questionnaire.The primary outcome will be weekly MVPA minutes assessed via hip-worn accelerometers (ActiGraph wGT3X-BT). Participants will wear the accelerometers for 1-week periods throughout the 6-week intervention. Participants will be asked to wear the device every day during waking hours, removing it only for sleep or when engaging in activities involving water . Data from accelerometers are well-validated ,65. We wWe will use measures of affective response to exercise and intrinsic motivation for exercise to assess affective evaluations. The Feeling Scale (FS)  measuresWe will use a computerized delayed discounting task  to assesA 4-item measure of action planning  will be All participants will listen to their assigned intervention recording during the in-person visits. For participants in the high dose condition, we will assess adherence via 2 sources: self-reports and tracking data that indicates access and time spent on the audio recording. For self-reported adherence, high dose participants will be asked at the beginning of each in-person visit to indicate how many days during the past week they listened to the audio recording.Following recommendations for optimization , we willUnivariate and multivariate outliers will be identified and corrected following the data screening guidelines of Tabachnick and Fidell . PatternThe first aim is to identify the optimal combination of components for meeting weekly physical activity minute guidelines. MLMs will be used to account for the nested structure of the data . Weekly physical activity minutes will be the dependent variable; time (weeks 0-5) will be a within-person predictor, and the main effects for each intervention component, along with all 2-way and higher order interactions, will be included as between-person predictors.The second aim is to determine the mechanisms of each intervention component. A series of MLMs, similar to models of the first aim, will test the extent to which (A) each intervention component is associated with within-person change in its putative mechanism, and (B) the within-person change in each mechanism is prospectively associated with physical activity minutes.d=0.40) [r=.40 between pre- and postintervention physical activity levels, a sample size of 176 will be sufficient to detect significant effects with 80% power and a Type I error rate of .05. This sample size estimate was generated using the Factorial Power Plan macro in SAS software, which is specifically designed to calculate power for factorial designs [Based on a small-to-moderate effect size (Cohen d=0.40)  and assu designs . The sam designs ,74. We w designs ,73.This project was funded by the National Cancer Institute (R21CA260360) on May 13, 2021, with a start date of May 15, 2021, and an end date of April 30, 2023. Recruitment and data collection began in February 2022, and 41 participants have enrolled in the study as of July 2022. Data collection is expected to be completed in summer 2023. Data analysis will begin after the completion of data collection.Delivering interventions to promote physical activity via technology-based platforms  is a promising avenue to address scalability and dissemination barriers among existing interventions. The GeT Active optimization study is innovative because it identifies optimal combinations of intervention components and unpacks the “black box” in early-phase development (vs later on in the process), consistent with current frameworks of intervention development ,20,21.The results expected from the GeT Active optimization study will inform future refinements, testing, and use of these guided thinking tasks to promote physical activity. For example, if multiple combinations are equally effective for physical activity, this could result in a package of components that is flexible and customizable for future use . Evidence on the effect of frequency of use  will be important in refining the intervention and subsequent dissemination, particularly if 1 component benefits from multiple uses but the others do not. We also anticipate a diverse sample with different baseline physical activity levels that will allow us to explore individual differences in the effect of the intervention components .The results from the GeT Active optimization study will also accelerate the development of the intervention more efficiently than standard approaches, which tend to either test multiple intervention components as an entire package or disparately in stand-alone studies . By testThe study has a few limitations. First, the intervention lasts for 6 weeks, which is a short period of time to observe effects on physical activity. We sought to balance the need to enroll a sufficient number of participants to provide a rigorous test of the guided thinking components and their combinations with a follow-up period long enough to observe sufficient variability in physical activity adherence. We are confident that 6 weeks will be long enough to provide meaningful tests of the components on physical activity, as prior studies have observed that participants begin to show meaningful variability in physical activity adherence within 4 to 6 weeks -77. A loThe GeT Active study will result in a scalable, audio-recorded intervention to promote physical activity that will be ready for the next stage of optimization focused on refinement and evaluation . The res


This review focuses on how membranes interact allosterically with enzymes to regulate cell signaling and metabolic pathways leading to inflammation and other diseases. Our group has developed “substrate lipidomics” to quantify the substrate phospholipid specificity of each PLA2 and coupled this with molecular dynamics simulations to reveal that enzyme specificity is linked to specific hydrophobic binding subsites for membrane phospholipid substrates. We have also defined unexpected headgroup and acyl chain specificity for each of the major human PLA2 enzymes, which explains the observed specificity at a structural level. Finally, we discovered that a unique hydrophobic binding site—and not each enzyme’s catalytic residues or polar headgroup binding site—predominantly determines enzyme specificity. We also discuss how PLA2s release specific fatty acids after allosteric enzyme association with membranes and extraction of the phospholipid substrate, which can be blocked by stereospecific inhibitors. After decades of work, we can now correlate PLA2 specificity and inhibition potency with molecular structure and physiological function.Lipids play critical roles in several major chronic diseases of our times, including those that involve inflammatory sequelae such as metabolic syndrome including obesity, insulin sensitivity, and cardiovascular diseases. However, defining the substrate specificity of enzymes of lipid metabolism is a challenging task. For example, phospholipase A Lipids play critical roles in the metabolic syndrome including obesity, insulin sensitivity and type 2 diabetes, numerous cardiovascular diseases, and fatty liver disease including nonalcoholic steatohepatitis; these constitute the major chronic diseases of our times, and all of these involve sequelae of inflammation. Over 47,000 distinct molecular species of lipids have been identified by the LIPID MAPS Consortium (www.lipidmaps.org), so defining substrate specificity of enzymes of lipid metabolism is a challenging task.The ASBMB 2021 Bert and Natalie Vallee Award in Biomedical Sciences honors our work on how phospholipase Asn-2 fatty acyl chains in membrane phospholipid substrates  or anti-inflammatory fish oil omega-3 eicosapentenoic acid and docosahexenoic acid; others favor membrane remodeling linoleic acid, antibacterial saturated fatty acids, or oxidized fatty acids in low-density lipoproteins. Each PLA2 releases a specific fatty acid after the enzyme associates with membranes causing an allosteric effect and extracts a single phospholipid substrate into its catalytic site. Stereospecific inhibitors . All. All2s cGroup Numbering System was originally developed to differentiate the PLA2s that had been described at the time : secreted phospholipase A2 (sPLA2); cytosolic phospholipase A2 (cPLA2); calcium-independent phospholipase A2 (iPLA2); platelet-activating factor (PAF) acetyl hydrolase, also known as lipoprotein-associated PLA2 (Lp-PLA2), lysosomal PLA2, and adipose PLA2, but if one wants to be specific about the particular PLA2, the designation by Type would then be preceeded by the Group Number  and iPLA2β instead of Group VIA). Another naming system was developed independently for iPLA2 which describes enzymes based on sequence similarities rather than on catalytic substrate similarities based on a classic well-studied potato (patatin) triacylglycerol lipase resulting in “patatin-like PLA2” (PNPLA) for which Group VIA iPLA2 is known as PNPLA9. Other PNPLA enzymes actually exhibit different activities than PLA2, for example, PNPLA3 is actually a triacylglycerol lipase rather than a PLA2, and there is enormous interest in this enzyme currently because of its association with nonalcoholic fatty liver disease and its advanced form nonalcoholic steatohepatitis  of each of the four Types of PLA2 discussed here, but the secreted PLA2Type includes the largest number of well-studied distinct Groups and Subgroups. The first PLA2s to be characterized were secreted enzymes from various snake venoms and porcine pancreas, and the human Group IIA, which was originally cloned from human synovial fluid, is perhaps the most well studied , and macrophages additionally secrete the Lp-PLA2. The Group VIIA Lp-PLA2 is the fourth enzyme Type we have studied extensively. It is known as the secreted Lp-PLA2, and it associates with low-density lipoproteins and high-density lipoproteins in the blood stream and specifically releases only oxidized or short-chain fatty acids. This enzyme was independently discovered and named as PAF acetyl hydrolase because of its potent ability to hydrolyze PAF releasing acetate from the sn-2 position , that since it was water soluble, it is going to interact with a phospholipid substrate which resides only in membranes or micelles and not freely in solution. Thus, the enzyme must first associate with the lipid aggregate and the first step for a phospholipase to act requires that the water-soluble enzyme associate with the membrane or the micelle. In We recognized very early on in our initial studies in the early 1970s , 16 that2 enzymes we will discuss herein are all water soluble. The first step depends on the concentration of enzyme and membranes or micelles. Note that the phospholipids in red laterally diffuse around the surface of the micelle or membrane very rapidly until a single phospholipid is “sucked” into the catalytic site. Catalysis occurs, and the products diffuse back around the surface of the micelle or membrane. The second step occurs when the enzyme is associated with the surface, and this step depends kinetically on the surface concentration of the specific phospholipid substrate in the surface of the micelle. This realization led our group to propose “surface dilution kinetics”  to look specifically for the first time at the interaction of proteins with individual phospholipid substrates and their interactions with the membrane .2 in aqueous solution, then mixes it with phospholipid vesicles, allows them to associate, dilutes in D2O, and then measures the rate of deuterium exchange with the amide protons in the amino acids in separate peptides in the polypeptide backbone of the enzyme. In essence, where the enzyme interacts with the membrane or where a phospholipid is pulled up into the enzyme active site, the rate of deuterium exchange is changed, both by proximity and by conformational changes that can be quite complicated. Peptides show increases and others show decreases in deuterium exchange depending on whether that portion of the enzyme is more exposed or less exposed to solvent. However, decreases are especially noteworthy when they result from decreased accessibility due to hydrophobic interactions  molecule in black was docked in its active site and the cPLA2 was docked to a membrane patch as suggested by the DXMS results. The membrane patch consisted of a full sn-1 palmitoyl, sn-2 oleoyl phosphatidylcholine (POPC) bilayer membrane in purple . MD simulations were carried out for 300 ns. See In cis double bonds interacting primarily with aromatic amino acid side chains with π-π stacking.The first thing one notices is how rapidly the purple phospholipids in the membrane move with lateral diffusion, but basically staying oriented. In contrast, the phospholipid in the catalytic site is much more restricted in motion as is the whole protein as it struggles to find the minimal energy conformation of both the phospholipid ligand and the enzyme. The AA is seen in its characteristic curved form in its final conformation with its four sn-2 carbonyl position oriented to initiate the catalytic event.In a separate experiment, the PAPC substrate in its final energy minimized docked conformation was pulled out of the active site along a straight trajectory back into the membrane, and then a slight force was applied in the opposite direction to allow this phospholipid to re-enter the active site. This allows one to visualize how the enzyme, docked to a membrane, might pull a single phospholipid out of the membrane and into the catalytic site. See 2 is a very different enzyme, though it has the same Ser–Asp dyad as its catalytic machinery. In 2 with the same PAPC substrate as employed with cPLA2 in its catalytic site as well as the same POPC membrane patch and then carried out MD simulations for 300 ns. See 2 is a little bit more of an open site than cPLA2, and in the middle of the simulation, one observes a conformational change whereby the enzyme opens up to accommodate the sn-2 fatty acid chain, in this case AA, in a distinct subsite that binds very specifically to the sn-2 fatty acid. The sn-1 fatty acid, palmitate in this case, is less restricted, and it appears to extend some into the membrane patch. Note that the red helix on the enzyme is buried in the membrane, so one might visualize the membrane as allowing the tail of the sn-1 chain to protrude into the membrane, whereas the sn-2 fatty acid, which is the leaving or cleaved fatty acid, is bound entirely in its sn-2 subsite.The human Group VIA iPLA2 which allows us to look at any natural or synthetic phospholipid alone or in mixtures, rather than relying on the traditional specifically radioactively labeled phospholipids  where the polar group is surrounded by charged and polar amino acids  containing a sn-2 linoleic acid is compared. Figure 9D shows the same subsite for iPLA2 with linoleic acid in the phospholipid chain, and the two cis double bonds in linoleic acid are aligned very nicely with aromatic tyrosine side chains and perfect π-π stacking, explaining why it binds even better than AA.This can be understood and explained more clearly if the association of these two enzymes with the phospholipid substrate 2 in the same manner that PAPE was docked and the 1-μs simulation is initiated, the phospholipid immediately diffused from the active site and moved into the membrane. See Figure 9C. In other words, the difference in having two less carbons and two less double bonds in linoleic acid (18:2) than AA (20:4) was enough to reduce the affinity of this fatty acid chain dramatically so that it no longer could bind over any reasonable time period within the active site.However, when the same PLPC phospholipid is docked in the active site of cPLA2, which is a much smaller 13-kDa protein containing seven disulfide bonds and which utilizes a His–Asp for hydrolysis along with a required Ca2+. Its specificity favors linoleic acid in its sn-2 position like iPLA2  and oxidized fatty acids such as oxovaleryl phosphatidylcholine. However, this 45-kDa extracellular enzyme utilizes a catalytic triad consisting of Ser His Asp in carry out hydrolysis. Current work in our laboratory is aimed at more fully characterizing the unique specificity of this enzyme for the sn-2 fatty acyl groups.DXMS has shown that the human Group VIIA lipoprotein-associated PLAproteins , 22. Thi2s, often in collaboration with Professor George Kokotos from Athens. Refer to the study by Dennis et al.  in PLPC was described in close contacts with the enzyme’s aromatic side chains, we had also observed that an sn-2 myristic acid (M) in sn-1 palmitoyl, sn-2 myristoyl phosphatidylcholine bound with close contacts in a distinct region of the same sn-2 subsite surrounded entirely by aliphatic sidechains in the enzyme active site. In hindsight, the two fluroketone inhibitors  discriminated these two parts of the sn-2 subsite of iPLA2  and stearic acid (18:0) for which the length of the fatty acid chain is the only difference, though sometimes the sn-1 position is occupied by monounsaturated and polyunsaturated fatty acids. For some of the enzymes, particularly for sPLA2, this is a rather shallow site and most of the fatty acid chain resides in the membrane. This concept is consistent with the overall finding that potent PLA2 inhibitors exhibit Type and Group specificity based on the uniqueness of the hydrophobic site at the sn-2 position, and this is where catalysis occurs for PLA2s. For all of these enzymes, it appears that as soon as catalysis occurs, the products diffuse into the membrane and the cycle repeats itself as indicated in sn-2 hydrophobic subsite in each enzyme determines its unique specificity.Furthermore, the This article contains The authors declare that they have no conflicts of interest with the contents of this article.


Covid-19 pandemic became an unexpected stressor for the entire population and, particularly, for pregnant women and lactating mothers. The alarming infectious risk together with the lockdown period could affect the emotional state of mothers-to-be, as well as breastfeeding rates, mother-baby bonding, or neonatal weight gain. The aim of this study is to describe the impact of this world health emergency in mother-baby pairs right after the first wave of Sars-Cov-2 pandemic (from March to May 2020).A prospective observational study was carried out in mother–child dyads from those women who gave birth between June and August 2020 in a tertiary hospital. 91 mother-baby pairs were initially enrolled and 56 of them completed the follow-up. The study design had two separate steps: i) Step one: A clinical interview plus three psychometric tests ; ii) Step two: mother–child dyads were followed using a round of three brief telephone interviews  to accurately depict the newborn’s outcome in the neonatal period.In terms of maternal mental health, 25% of the sample screens positively in the EPDS, requiring further evaluation to rule out depressive symptoms. STAI-state and PBQ detect no abnormalities in either anxiety levels or mother–child bonding in our sample, as 100% of the mothers score below the cut-off points in each test (34 and 26 respectively). When comparing feeding practices (breast/bottle feeding) in 2020 to those practices during pre-pandemic years (2017–2019), a significant increase in breastfeeding was found in pandemic times. All newborns in the sample showed an adequate weight gain during their first month of life.Women and newborns in our sample did not experience an increase in adverse outcomes in the neonatal period in terms of maternal mental health, breastfeeding rates, bonding and further neonatal development.The online version contains supplementary material available at 10.1186/s12884-022-05036-9. The coronavirus disease 2019 (Covid-19) caused by the novel Sars-Cov-2 virus originated in Wuhan, China, towards the end of 2019, and was soon to be spread worldwide forcing the WHO to declare it as a pandemic on the 11th of March 2020. Several studies have demonstrated the impact of pandemics and natural disasters on the general population's physical and mental health , and theThe threat posed by the current pandemic has enforced many changes in medical care in a rapid and sudden way , 8. SpecA wide range of maternal psychosocial factors  and their interrelationships has been identified as etiological factors likely to trigger antenatal stress and perinatal or postpartum depression among pregnant women . HoweverOn the other hand, when an infectious disease outbreak, epidemic, or pandemic occurs-particularly when it is associated with a novel pathogen-the question will naturally arise as to whether the pathogen can be transmitted through breastfeeding . BeneficTraces of SARS-CoV-2 genetic material have been found in breastmilk, however, to date there is no evidence of transmission via breastfeeding , 21. TheHere, we aim to evaluate the effects of the first wave of COVID-19 pandemic on the women who gave birth during the immediate post-lockdown period in a Maternity Hospital belonging to the Public Health System in Catalonia, in order to characterize the impact on mothers’ perinatal mental health, on the establishment of a successful mother–child relationship and on the newborn’s wellbeing during the first 28 days of their life .A prospective observational study was carried out from June to August 2020 at Hospital Universitari Germans Trias i Pujol, located in Badalona (Barcelona). This is a Tertiary Hospital belonging to the Public Health System, which sees an average of nearly 2000 births per year.Our hospital provides medical assistance to a multicultural and multiethnic population. More than a 30% of our patients are migrants from Asia and Africa, with the subsequent idiomatic barrier.Participants were recruited during the first 12–24 h after labour, usually after the pediatrician’s first newborn assessment. Eligibility criteria included all healthy term (37—41.6 weeks) or late preterm  newborns admitted to the Maternity Unit, regardless of the hours/days of hospitalization. All patients admitted to the Neonatal Unit immediately or shortly after birth, those with an important language barrier or those declining to participate were excluded.Participants enrolled in a series of interviews conducted in two separate steps:In phase one, a survey (in Spanish) was handed to every mother agreeing to participate. Through a total of 36 questions we explored the following domains: i) the newborn’s future household depiction, in economic  and emotional terms (expected or unexpected pregnancy and feelings around it), ii) breastfeeding intention, iii) psychiatric history: personal and family history of psychiatric disorders, previous/current psychiatric treatment, sleep disorders and substance abuse, iv)impact of COVID-19 in the patients’ lives   , a subsePhase two consisted of a round of three brief telephone interviews conducted when the newborn was 7, 14 and 28 days of age. Breastfeeding status, mother’s satisfaction with the aid received in establishing breastfeeding, the weight of the newborn and other questions relating to the health status of the child were asked, in an effort to accurately depict the outcome of the newborn in the neonatal period.As reference group to compare, data from our own hospital records were sourced for the same period of time in the three previous years (2017 to 2020), including exclusive breastfeeding percentages and other major neonatal outcomes in neonates admitted in the maternal area.A questionnaire originally designed by Cox et al.  to screetrait anxiety, a predisposition to anxiety in different scenarios, and state anxiety, the degree of anxiety felt at a particular moment. It can be split consequently in two subsets of questions, STAI-T and STAI-S. Questions are scored using a 4-point Likert-type scale. As pregnancy entails a series of major changes in a woman’s life, STAI scores have been found to be higher in pregnant women when compared to the general population. Variations in the STAI-S have been documented through all trimesters of pregnancy, and have already been proposed as a useful tool to monitor the response to interventions aimed at lowering prenatal anxiety  for continuous variables or as numbers/percentages for categorical variables. The contrast hypothesis for two samples was evaluated with the Student´s t-test for quantitative variables and Chi-squared test in cases of categorical ones. If variables did not adjust to normality, a Kruskall-Wallis test was done. Associations between breastfeeding, demographic variables and results of psychological test were estimated by univariable and multivariable logistic regression, and presented as odds ratios and 95% CI. Associations between STAI scores, EPDS, PBQ scores were estimated by univariable and multivariable linear regression, and presented as unstandardized regression coefficients and 95% CI. In all cases the rejection level for a null hypothesis was α < 0,05.The Statistical Package for Social Sciences (SPSS) version 23.0 was used to perform the analyses.st June 2020 – 3rd August 2020), a total of 377 newborns were delivered in our hospital. Of these, 286 mother-infant dyads were excluded for language barriers or refusal to participate. 91 mother-infant dyads were recruited, with 56 (61%) included in the final analysis. A subset of 5 mothers in this group failed to complete either all or some psychological tests. However, given that they answered all phone interviews during follow-up we decided to include them where appropriate in the analysis. Amongst the remaining 35 (39%), 25 were ruled out during phase 1 due to their forms either coming back blank or being lost, with the other 10 failing to answer the phone at any of the interviews scheduled within the follow-up  mother gave a positive answer to question 10 assessing for suicidal ideation, being promptly referred to the Psychiatric Department of our hospital for further evaluation.state and PBQ detected no abnormalities in either anxiety levels or mother–child bonding in our sample, as 100% of the mothers scored below the cut-off points in each test (34 and 26 respectively).STAI-state  and STAI-state and PBQ scores . Linear regression for STAI-state was predicted by EPDS (p = 0.002) and PBQ score (p = 0.036) . Mutiple regression and 95% CI of the unstandardized regression coefficients for psychometric tests were calculated  rates as shown in Fig. - At birth all 5/5 cases of mixed feeding started formula on medical recommendation, while 7/7 mothers opting not to breastfeed did so out of their own accord.- At 7 days follow-up, 5 mothers in the EBF group added formula to their newborn’s diet , while 2 mothers in the mixed-feeding group went back onto EBF.- Day 14 results in 5 more women switching from EBF to mixed-feeding, with only 1/5 doing so as instructed by her pediatrician. Also at this time, 1 mother in the mixed-feeding group stopped formula in favor of EBF.- Finally, when interviewed on day 28, 3 mothers report having changed from EBF to mixed feeding (MBF) , with 3 more in the MBF group stating changes: 1 going back to EBF and 2 leaving breastfeeding for good.Analysis of the motivation behind the type of feeding chosen showed the following results:p = 0.09) as shown in Fig. Weight at 30 days of life was extracted from each newborn’s clinical history, therefore monitoring weight increase during their first month of life ([weight at 30 days of life – weight recorded at birth]/30 days). Results show an average of 31.4 g increase daily [21.9 – 37.5]. Subgroup analysis comparing weight increase between the different types of feeding recorded showed no significant differences  considered themselves poorly informed when asked at birth. Particularly, out of the 7 women choosing formula feeding from birth, 3 considered the aid received insufficient. When asked again at the end of the study on day 30, 16/56 (28.5%) women were still not satisfied with the support received.Previous breastfeeding rates from the past three years concerning the same period of time  were sourced from our hospital registry and are presented in Fig. p = 0.045 and p 0.003 respectively). A statistically significant rise is also found in breastfeeding rates in 2020 when compared to the aggregated proportions observed in the pre-pandemic years (2017 to 2019).From June to August 2020 a total of 377 babies were delivered in our centre, with women intending to practice some form of breastfeeding (EBF + mixed) adding up to a total of 331 (88.5%). A small variation was found from the proportion observed in our study (EBF + mixed = 87.5%), supporting the representativity of the sample. When comparing the rates of types of feeding between 2020 and each one of the previous years, significant variations are found in 2020 versus years 2017 and 2019 .In order to explore if the manner of delivery had been affected, Fig. Our study found that 25% of pregnant women were positively screened by the EPDS, even though they showed low levels of anxiety, with the entire sample scoring below the threshold in the STAI. Additionally, PBQ does not detect anomalies in the quality of bonding established amongst mother and child.Feeding rates registered during the first months of the Covid-19 pandemic show not only steadiness but a significant increase in the number of mothers practicing any form of breastfeeding (EBF or MBF) when compared to pre-pandemic years. For babies, no major health issues were reported during follow-up and the average weight gain in their first month of life was adequate.In our sample, the incidence of depressive symptoms in the immediate postpartum was slightly higher than previously observed in the Spanish population, with 25% screening positively in the EPDS (against 21% at 6 weeks postpartum reported in previous studies) , 38. PreThe mental health of pregnant women affects the health outcomes of both the pregnant women and their infants . InfantsOther studies have reported high levels of anxiety and depression in pregnant and postpartum women during the COVID pandemic –44. SomeRates and severity of postpartum depression (PPD) and anxiety symptoms among women seeking treatment for PPD have worsened during the COVID-19 pandemic . PostparA very recent multinational study found high levels of depressive symptoms and generalized anxiety among pregnant and breastfeeding women during the COVID-19 outbreak. The study findings underline the importance of monitoring perinatal mental health during pandemics and other societal crises to safeguard maternal and infant mental health .Prior to the pandemic 90% of Catalan children were breastfed according to available epidemiological data , but theElevated posttraumatic stress, anxiety/depression, and loneliness are highly prevalent in pregnant and postpartum women across 64 countries during the COVID-19 pandemic. Excessive information seeking and worries related to children and medical care are associated with elevated symptoms, whereas engaging in hygiene-related preventive measures were not. In addition to screening and monitoring mental health symptoms, addressing excessive information seeking and women's worries about access to medical care and their children's well-being, and developing strategies to target loneliness  should be part of intervention efforts for perinatal women .In any case, our findings do not support our initial hypothesis postulating that the stress caused by the pandemic in pregnant women was going to have a negative effect on their newborn’s health, worsening women’s mood, altering the establishment of breastfeeding, and impairing the development of a solid mother–child bond. These unforeseen results may suggest that pregnant women took benefit from the standstill caused by the pandemic; perhaps the anticipated work-leave, the obligatory at-home rest and the increase in the time spent with their families and newborn babies, allowed them to bond and get to know each other .Additionally, several care-related factors may have contributed to this positive effect. Maintaining women’s wellbeing was a priority from the beginning, and efforts were made to ease the experience of women in labor, allowing them to be accompanied by a person of their choice  throughout their stay . Second,We acknowledge some limitations to the study. First, a significant proportion of our population could not be included in the study. It seems clear that a bias of selection was introduced since the competence in Spanish was lacking in more than a 50% of potential participants. Sadly, we could not count on a cultural agent to translate the scales.Additionaly, some patients refused to participate for logistical reasons . Second, comparisons are made using a larger historical cohort extracted from the hospital registry, including all births occurred in months of interest and presenting only static data . Therefore, direct comparisons cannot be made, with differences serving only as starting points to formulate new hypotheses.But our study also pointed out some negative aspects of our clinical practice. First, from our sample a total of 19 out of 56 (33.9%) of mothers claim to be misinformed with regards to breastfeeding when asked at birth, a proportion that remains almost unchanged 28 days after  . ConsideSecond, postpartum represents a delicate time of transition, where psychological difficulties and disturbances are often encountered ; so, we Finally, attention should be given to practicalities to better deal with the difficulties imposed by the pandemic, while restrictions last: it would be advisable to reduce surveillance appointments to the minimum needed to ensure adequate healthcare. In order to safely do this, mother–child dyads should be provided with means of accessing information, asking doubts if needed or communicating the need for an appointment (other than being forced to consult to the emergency services). For this system to function properly, communication between primary care and specialized centers and amongst all the caregivers involved in the process  would be of the utmost importance, working as a single force to efficiently reduce out-of-home visits.To our knowledge this is the first study in our area of influence which has evaluated the impact of SARs-Cov-2 pandemic on maternal mental health  and their consequences in breastfeeding rates. Public health campaigns and medical care systems need to explicitly address the impact of COVID-19 related stressors on mental health in perinatal women, as prevention of viral exposure itself does not mitigate the pandemic's mental health impact .Women and newborns in our sample showed no signs of adverse outcomes in the neonatal period in terms of breastfeeding, bonding and weight gain, despite the adversities forced upon healthcare by the pandemic. Although maternal anxiety levels were seemingly unaffected, depression scores were higher than in pre-pandemic times. Conversely, breastfeeding rates were higher than those observed prior to the arrival of Sars-Cov-2 virus infection.Additional file 1. Annex 1.Additional file 2: Supplementary Table 1. Factors associated with mental health test.


Given the importance of the continuous follow-up of chronic patients, we evaluated the performance of French private practice general practitioners (GPs) practicing in multi-professional group practices (MGP) regarding chronic care management during the first Covid-19 lockdown in Spring 2020 compared to GPs not in MGP. We consider two outcomes: continuity of care provision for chronic patients and proactivity in contacting these patients.The cross-sectional web questionnaire of 1191 GPs took place in April 2020. We exploit self-reported data on: 1) the frequency of consultations for chronic patients during lockdown compared to their “typical” week before the pandemic, along with 2) GPs’ proactive behaviour when contacting their chronic patients. We use probit and bivariate probit models (adjusted for endogeneity of choice of engagement in MGP) to test whether GPs in MGP had significantly different responses to the Covid-19 crisis compared to those practicing outside MGP.Out of 1191 participants (response rate: 43.1%), around 40% of GPs were female and 34% were younger than 50 years old. Regression results indicate that GPs in MGP were less likely to experience a drop in consultations related to complications of chronic diseases (− 45.3%). They were also more proactive (+ 13.4%) in contacting their chronic patients compared to their peers practicing outside MGP.We demonstrate that the MGP organisational formula was beneficial to the follow-up of patients with chronic conditions during the lockdown; therefore, it appears beneficial to expand integrated practices, since they perform better when facing a major shock. Further research is needed to confirm the efficiency of these integrated practices outside the particular pandemic setup.The online version contains supplementary material available at 10.1186/s12913-022-07937-z. The Covid-19 pandemic and its subsequent health system responses has already had considerable consequences on the most vulnerable populations. Chronic patients in particular have been severely affected by the pandemic . Besides“maison de santé pluridisciplinaire”]. MGP are created on a voluntary basis. They provide primary care for the local population and may take part in public health, prevention, health education and the social activities of their choice. All these activities form a “health project” that is signed by all the MGP team members and reported to regional health authorities as proof of coordinated care. This health project usually grants access to some funding in order to facilitate the foundation of the MGP; the conditions of access and the amount varying according to the region. The MGP is required to have at least two full-time equivalent GPs and one paramedic. This institutional cooperation with paramedics is the main novelty for the French ambulatory care system, since this type of cooperation is not mandatory in the primary care system . While the minimal requirement on the number of MGP members is two full-time equivalent GPs and one paramedic, on average there were 3.4 different paramedics and 0.5 specialists as well as 3.8 full-time equivalent GPs (data in our sample). The policy was launched in 2007 and has proven to be extremely popular among physicians: in 2020, more than 1300 MGP were actively operating compared to less than 20 in 2008 [In France, self-employed general practitioners (GP) ensure more than 90% of primary care. As in other developed countries, a clear trend towards the integration of primary care providers is observed: in a 2010 survey, 54% of GPs indicated practicing in a group; a figure which rose to 61% in 2019 . However in 2008 , 12. In This article aims at evaluating how GPs in MGP perform regarding chronic care management in response to a major shock. Continuous follow-up of chronic patients being essential for better quality of care, the current pandemic, beyond the calamity it represents, provides an opportunity to examine how GPs in MGP can adapt their practices under these unusual conditions. Using an appropriate statistical model, we compare GPs’ performance in MGP, with their counterparts practicing outside MGP, regarding the frequency of consultations for chronic patients as well as their proactivity in contacting these patients during the first lockdown.We used data from the national panel of French self-employed GPs, set up in 2018 .Conseil National de l’Information Statistique).GPs were randomly selected from a French exhaustive database of health professionals as of January 1, 2018 and who have signed an informed consent at inclusion (in 2019) to answer six future cross-sectional surveys (one every 9 months). Sampling was stratified for gender, age, workload  and practice location in low GP density municipalities. The panel is representative of GPs practicing in France (excluding Mayotte). GPs planning to retire or to move before the end of data collection, those exclusively practicing alternative medicine as well as those with few gatekeeping duties (fewer than 200 patients) were excluded. The sample benefits from the French “public statistics” label of the National Authority for Statistical Information  software.A special Covid-19 cross-sectional survey was decided in March 2020 in order to study GP practices in the face of the pandemic. In line with the prior systematic collection of longitudinal data planned in 2019, an ad-hoc committee was formed at the beginning of the first lockdown in France in order to elaborate short-form surveys focusing on the GPs’ response to the COVID-19 crisis. The committee was comprised of various public health scientists , already trained in surveys among GPs. Since there was no past experience of lockdowns, the questionnaire was not based on standardised questions, although it was inspired by literature dealing with the H1N1 crisis . We piloThe web-survey took place between April 9 and April 21 2020; 1191 GPs out of 2761 contacted (43.1%) responded. Since the eligibility criteria were verified at inclusion (in 2019), all the remaining GPs were eligible to participate in the survey in 2020.We exploit the part of the questionnaire focused on the impact of the lockdown on GPs’ activity . A “don’t know” answer was also included in each item of the questionnaire.département level . This indicator was constructed by the Directorate for Research, Studies, Assessment and Statistics  from National Institute of Statistics and Economic Studies (Insee) Covid-19 mortality data collected between March 1 and April 20 2020 [départements, where an average change in excess mortality rate was 110.5%.We used an indicator variable of the intensity of the Covid-19 pandemic at the  20 2020 . We usedIn addition, we used a set of five dummy variables regarding motivations for the choice of the current practice location from Round 1 of the survey that took place from October 2018 to April 2019. The GPs had to choose between the items related to 1) healthcare services available in the area, 2) the possibility of creating or joining a group practice, 3) the search for an area with low GP density, 4) available amenities for the GPs’ families, or 5) a previous experience as an intern, locum or associate in the area; it was possible to choose several items simultaneously.département in 2013.Finally, we exploited a previous edition of the survey  to construct a dummy variable indicating the presence of a MGP in a To correct for possible systematic non-response bias in our subsample, we used weights to match the nationwide GP population for the four main stratification variables: age, gender, workload and GP density. When missing data occurred for some variables, they were included in the analysis and treated as a separate ‘missing’ category.We defined a set of dependent variables regarding chronic care management  and their estimation of the percentage of the French population that would be contaminated by Covid-19 by the end of 2020 ,and the control variables include GP i’ personal and professional characteristics: gender, age (in tertiles), workload (in tertiles), as well as a dummy variable indicating whether the practice is located in the area with the lowest (first decile) GP density in 2018 or not.We use probit regressions to estimate the following model:To address the possible endogeneity of choice of practicing in MGP, we estimate the bivariate probit model, since it is suited to simultaneously estimating both equations with binary outcome variables:Pioneer départementi is a dummy variable indicating practices located in a département that had adopted MGP early (before 2013),Motivationi is a set of dummy variables regarding the selection criteria prior to the choice of the current practice location ).where the equation related to practicing in MGP contains several variables that might influence the GPs’ choice, but are unlikely to have an impact on chronic care management strategies during the sanitary crisis:département before 2013 . This strengthens the fulfilment of the exclusion condition. As bivariate probit models do not allow testing for overidentification restrictions, we follow the procedure described in Wooldridge [i. Next, we estimate the model described above by a Two-Stage Least Squares using the fitted value for MGPi. Having this adapted framework at our disposal, we were able to test the statistical properties of the instrumental variables using the Sargan overidentification test . For both models, we calculate the marginal effects (on predicted probabilities) for GPs practicing outside MGP, outside the most affected départements, male, youngest, with lowest workload, those not practicing in lowest GP density areas.These two sets of instruments relate to the past behaviour of GPs or the behaviour of peers in the same oldridge . Using aAll analyses were conducted with Stata 14 .départements most affected by Covid-19 (9% in MGP). The average perceived severity of Covid-19 was around 7.8 (out of 10). Forty-four percent of GPs estimated that by the end of 2020 less than half of the French population would be contaminated by Covid-19 and 13% believed that 75% or more would be contaminated.Out of the 1191 GPs that responded to the survey, almost 40% were female and 34% were younger than 50 years old .Regarding the frequency of visits related to complications of chronic diseases Table , the estAs far as the second behaviour in Table p = 0.11 and 0.09 respectively), however the instruments were weak: the F statistic was below the commonly-used threshold of 10.As for the instruments used, Sargan test results indicated the validity of the instruments  was also beneficial to patients, at least to those with chronic conditions, and not only to healthcare professionals - there are more results in the literature demonstrating that latter point, while only a few were really able to deal with patients’ outcomes . In our We have obtained encouraging results on the added value of MGP during COVID-19. These results can provide recommendations both for the short term and for the long term management of chronic patients. In the short term, a solution could be to appoint secretaries or medical assistants  in charge of the follow-up of chronic patients. In the long run, it advocates for further development of integration in primary care all across the national territory. However, we should recognize that, beyond these casual observations, further research is needed to demonstrate the added value of integrated practices  once the COVID-19 pandemic setup is over.Additional file 1. “Covid-19” online questionnaire, fourth national panel of French self-employed general practitioners .


There has been a rapid increase in the use of commercially available activity trackers, such as Fitbit, in physical activity intervention research. However, little is known about the long-term sustained use of trackers and behavior change after short-term interventions.This study aims to use minute-level data collected from a Fitbit tracker for up to 2 years after the end of a randomized controlled trial to examine patterns of Fitbit use and activity over time.Participants in this secondary data analysis were 75 female breast cancer survivors who had been enrolled in a 12-week physical activity randomized controlled trial. Participants randomized to the exercise intervention (full intervention arm) received a Fitbit One, which was worn daily throughout the 12-week intervention, and then were followed for 2 years after the intervention. Participants randomized to the waitlist arm, after completing the randomized controlled trial, received a Fitbit One and a minimal version of the exercise intervention (light intervention arm), and then were followed for 2 years after the intervention. Average and daily adherence and MVPA were compared between the 2 groups in the interventional and postinterventional periods using both linear and generalized additive mixed effects models.P<.001). Average adherence was significantly lower for both study arms during the follow-up period than in the intervention period; however, there were statistically different patterns of adherence during the follow-up period, with the light intervention arm having steeper declines than the full intervention arm over time (P<.001). Similar to the adherence results, mean minutes of Fitbit-measured MVPA was higher for the full intervention arm than for the light intervention arm during the 12-week intervention period . During the follow-up period, average MVPA was significantly lower than the 12-week intervention period for both the full intervention arm  and the light intervention arm . Although the mean MVPA in each arm was similar across the follow-up period (P=.33), the pattern of daily MVPA was significantly different between the 2 groups (P<.001).Adherence to wearing the Fitbit during the 12-week intervention period was significantly higher in the full intervention arm than in the light intervention arm (85% vs 60%; While adherence to wearing activity trackers and maintaining physical activities declined after completion of a 12-week exercise intervention, a more active interventional strategy resulted in greater wear time and activity levels during the intervention and more stable patterns of adherence and activity in the long term. An improved understanding of long-term maintenance patterns may inform improved exercise interventions that result in sustained increases in physical activity.ClinicalTrials.gov NCT02332876; https://clinicaltrials.gov/ct2/show/NCT02332876 There are currently 3.9 million breast cancer survivors in the United States; most of whom do not engage in sufficient physical activity to meet current recommendations . GreaterSelf-monitoring is one of the key skills to promote behavior changes , and mayInitial studies on Fitbit adoption have demonstrated that they are effective in increasing physical activity levels when coupled with other interventions -21, but This analysis explored adherence to wearing the Fitbit and physical activity 2 years after the end of a 3-month randomized controlled trial comparing a physical activity intervention (full intervention arm) with a waitlist control that received a “light” intervention (light intervention arm) after completing the 12-week assessments . The aimParticipants in this secondary data analysis were originally randomized to a 12-week physical activity intervention group or a waitlist control group. After completing final measures for the randomized trial at week 12, participants were invited to enroll in a maintenance study where their Fitbit data would be collected for the next 2 years and they would complete online questionnaires every 6 months over the next 2 years . Participants were asked to provide written informed consent for participating in the maintenance study. Data from the original randomized trial and the 2-year follow-up were collected from February 2015 to July 2018. The intervention trial was registered with Clinicaltrials.gov (NCT02332876).Eligible participants were female breast cancer survivors, aged 21-85 years, who were diagnosed less than 5 years prior to study enrollment, had completed chemotherapy or radiation treatment, were sedentary , and had access to the internet and a Fitbit-compatible computer, tablet, or phone. Exclusion criteria included any medical condition that could make it potentially unsafe to be in an unsupervised physical activity intervention , other A detailed description of the original trial’s protocol was previously published . BrieflyParticipants randomized to the full intervention arm had a 30- to 45-minute in-person meeting where they went on a 10-minute walk at moderate intensity and set personalized physical activity goals with a researcher trained in motivational interviewing aimed at gradually working up to 150 minutes/week of MVPA. Participants were given a Fitbit One  to self-monitor their physical activity, set up the Fitbit with their coach, taught how to use it, and taken on a 10-minute walk. Participants were also informed that their health coach would be reviewing their Fitbit activity data weekly and that they would receive feedback on the Fitbit data during the scheduled phone calls and between calls as needed. Participants received 2 scheduled phone calls (2- and 6-week time points) and emails every 3 days throughout the 12-week intervention. The intervention was delivered by a clinical psychologist with extensive training and experience in promoting behavior change (SJH) and by a staff member who was trained by SJH. For further details on the intervention, see Hartman et al . No addiAfter completion of measures at the final visit, participants in the light intervention arm were provided with a “light” version of the exercise intervention. In a 15-20-minute in-person meeting, participants in the light intervention arm worked with a measurement research assistant to set personalized physical activity goals. The research assistant had received training on goal setting from SJH, with a brief introduction to using motivational interviewing. Participants received the Fitbit One with instructions on how to use it to support self-monitoring. Different from the full intervention arm, participants did not set up the Fitbit with their health coach, they were not told that their health coach could see their data nor that they would receive any feedback on their Fitbit data. Participants were also not taken on the 10-minute walk to demonstrate moderate intensity. Participants were offered the same 2 phone calls (2 and 6 weeks later), but these calls were framed as optional. Participants received the same automated emails every 3 days for the next 12 weeks that the full intervention arm received.At the completion of their respective intervention, participants in both arms were asked to sync and charge their Fitbit at least once per week. When participants had not synced their Fitbit for 2 weeks, study staff would contact them to ask them to sync and provide any tech support if there were challenges syncing. Participants also received 4 online questionnaires to complete every 6 months across the 2-year follow-up.accel.weartime within the “accelerometry” package [The Fitbit One, a commercially available accelerometer-based activity tracker, was used to examine patterns of physical activity throughout the 12-week intervention. Fitbit uses a proprietary algorithm to classify each minute as being in sedentary, light, moderate, or vigorous activity, and provides metabolic equivalents (METs) for each minute. Data were wirelessly uploaded to the user’s Fitbit account online and then downloaded by the research team through a database called Fitabase , which allows for collecting data at the minute level. Daily adherence to wearing the Fitbit tracker was defined as wearing the tracker for over 10 hours in a day or logging at least some activity (over 1 minute of MVPA). This definition for a valid Fitbit wear day was used because participants were not instructed to wear the Fitbit all day; rather they were instructed to use the Fitbit to track activity. Thus, wearing the tracker specifically to log MVPA was deemed to be valid wear based on these instructions. Fitbit wear time was determined by processing of minute-level Fitbit data using the R function  package . Nonwear package , greaterBoth groups wore the ActiGraph for 7 days prior to receiving the Fitbit and starting the full or light intervention. The ActiGraph GT3X+, a well-validated research-grade accelerometer , provideOn the questionnaire administered at 6, 12, 18, and 24 months, participants were asked if they were still wearing their Fitbit. If they reported they were not wearing it, they were asked the reason they stopped wearing the Fitbit.t test (unpaired) and chi-square test. Baseline characteristics were summarized between the full intervention arm and the light intervention arm.Participants who did not consent for 2-year maintenance study were excluded from the analysis. Group differences in baseline characteristics between those who consented to the 2-year study and those who did not were assessed using 2-sample independent The mean weekly rolling average adherence to wearing the Fitbit and mean MVPA were calculated by averaging the outcomes over the first 12-week period and over the 2-year follow-up period separately for each individual. Descriptive statistics and boxplots were used to summarize the adherence to wearing the Fitbit and MVPA at 12-week and 2-year follow-up as well as the change from 12 weeks to 2 years.For comparing mean outcomes and mean change in outcomes between the 2 intervention groups, we used the following linear mixed effects model:b0 and random slope b1 are included to account for correlation among repeated measures within each individual. The coefficient β1 indicates the mean outcome difference between the full intervention arm and the light intervention arm at the first 12 weeks; β1 + β3 indicates the mean outcome difference between the 2 arms at 2-year follow-up; β2 indicates the mean outcome change from the first 12-week and 2-year follow-up for the light intervention arm; β2 + β3 indicates the mean outcome change between the first 12-week and 2-year follow-up for the full intervention arm; β3 indicates the difference in mean outcome change from the first 12-week and 2-year follow-up between the full intervention arm and the light intervention arm. The P value for testing the significance was calculated based on the estimated coefficient and estimated covariance from the linear mixed effects model.where Arm and Period are binary variables for the study arm (full or light intervention) and study period (12-week or 2-year follow-up), respectively; random intercept To compare the trend of adherence and MVPA between the full intervention arm and the light intervention arm, we used the generalized additive mixed effects model (GAMM):where Time is a continuous variable for the study day ; s(Time) is the smooth term for “Time”; and s(Time) × Arm is the interaction term between “Time” and “Arm.” Models with and without prespecified knots were assessed.2. Graph of the best fit was used to display the trends of adherence and MVPA over the study period.We used the minimized generalized cross-validation score for smoothness selection. To select the best fitted model, in terms of the interaction term between time and group and knots specification in the GAMM, we conducted model comparisons using analysis of variance and model’s Akaike information criteria. For the goodness of fit of the chosen models, we examined the model’s deviance and the adjusted Rt test to compare the MVPA during the preintervention period (measured by ActiGraph) with MVPA during the 12-week intervention, and MVPA during the 2-year follow-up period for both the full intervention arm and the light intervention arm. We also compared the preintervention MVPA between the 2 study groups using the 2-sample independent t test (unpaired).We also used paired All procedures were approved by the University of California San Diego Human Subjects Protection Program (IRB#140694).P>.05) differences in demographic or clinical variables between participants who did and did not enroll in the maintenance study.Of the 911 women who were screened for eligibility, 97 were eligible and scheduled for a visit, and 87 participants were randomized. Most common reasons for being ineligible were being too active (n=225), unable/unwilling to attend clinic visits (n=106), breast cancer surgery more than 5 years ago (n=81), and medical exclusion (n=36). Of the 87 randomized, 75 agreed to enroll in the 2-year maintenance study: 37/43 in the full intervention arm (86%) and 38/44 in the light intervention arm (86%). The current analyses comprise data from the 75 participants who enrolled in the maintenance study. There were no significant (P>.05) differences between the 2 arms.Participants in the 2-year follow-up study were 75 female breast cancer survivors who were predominantly diagnosed at stage 1. A little more than half had received chemotherapy and at the start of the original trial they were on average 2.6 years from the diagnosis. The average age of participants was 57 years (SD 10.4 years), with the majority being non-Hispanic, White, and having a college education or greater . There wP<.001). In addition, average adherence from the postintervention to 2-year follow-up period significantly dropped from the 12-week intervention period for both the full intervention arm  and the light intervention arm . However, during the postintervention to 2-year period there were no significant differences in average adherence between the 2 groups (P=.71).Average adherence to wearing the Fitbit was significantly higher for the full intervention arm during the 12-week intervention period compared with the light intervention arm during the 12-week intervention period—mean adherence 85% (SD 23%) for the full intervention arm versus 60% (SD 34%) for the light intervention arm (2 groups —mean adhP<.001) average adherence during the 12-week interventional period (P=.24), with both groups having stable adherence over time.We then compared the temporal patterns of adherence between the 2 groups during the 12-week intervention period and the postintervention to 2-year period using the GAMM. While participants in the full intervention arm had significantly higher . While there were steep initial declines in both arms, adherence in the full intervention arm declined more gradually over the remainder of the study period in comparison with the light intervention arm.By contrast, in the postintervention to 2-year period , althougA total of 67 participants answered the self-report question of whether or not they were still wearing their Fitbit. Of these, 32 participants reported that they had stopped wearing their Fitbit: 13 (41%) stated that their Fitbit broke, 12 (38%) reported that they lost their Fitbit or their charger, 6 (19%) stated that they were no longer interested in wearing the Fitbit, and 3 (9%) indicated a health issue that stopped them from being active. Several participants replaced lost or broken Fitbits during the follow-up years and then subsequently had a lost or broken Fitbit a second time or lost interest in wearing it.P<.001) and participants in the light intervention arm showed a trend for increased average minutes of MVPA from preintervention to across the 12 weeks  and the light intervention arm , but there was no significant difference in average MVPA between the 2 groups (P=.33). Although average MVPA decreased during the 2-year follow-up in comparison to preintervention MVPA, there was a trend for greater average MVPA for participants in the full intervention arm , but no difference from preintervention for the light intervention arm .Participants in the full intervention arm significantly increased average minutes of MVPA from preintervention to across the 12-week intervention period  daily MVPA than the light intervention arm during the intervention, there was no difference in the temporal pattern of daily MVPA across the 12-week period (P=.99), with both groups having relatively stable daily MVPA.We then compared the temporal patterns of activity between the 2 groups during the 12-week intervention period and from the postintervention to 2-year period . SimilarP<.001). Among participants who continued to adhere to wearing the Fitbit, the full intervention arm had a relatively stable trend with a gradual decline in daily MVPA, while the light intervention arm had an irregular temporal pattern with fluctuations in MVPA over time. Of note, with the relatively low level of adherence that continued to decline over the follow-up period, the curvature trend of the daily MVPA in the light intervention arm was measured in a small number of individuals.While the average MVPA for the entire postintervention period was similar between groups, the daily MVPA over time was significantly different between the 2 groups ; P<.001.This study examined patterns of wearing an activity tracker and engaging in MVPA during and after completion of a 12-week randomized trial of a full exercise intervention in comparison with a light intervention, through 2 years of follow-up. Our study yielded several key findings. First, the exercise intervention, which entailed more comprehensive feedback and external accountability, resulted in greater adherence to wearing the Fitbit and minutes of MVPA than the light intervention. Second, both full and light interventional groups had significant reductions in adherence and physical activity during the long-term follow-up. Finally, while both groups had similar average adherence and MVPA during the postintervention to 2-year period, the full intervention group had a more stable temporal pattern of adherence and daily MVPA during this time than the light intervention group, in addition to a trend toward maintaining some gains in MVPA over preintervention levels. These results provide new insight into wearable technology and activity patterns during and after completion of an exercise intervention and suggest the potential importance of sustained self-monitoring and feedback interventions to maintain increased activity levels over time.We found that the full exercise intervention resulted in greater daily MVPA in comparison with the light intervention during the 12-week interventional period. The primary added feature of the full exercise intervention was external accountability, where participants were aware that their activity would be checked by their health coach, discussed with them at planned phone calls, and would receive additional contacts in between calls based on their Fitbit data. Our results suggest that this accountability led to greater adherence to wearing the Fitbit and MVPA during the intervention period. Wearing the Fitbit did not decrease over time during the 12-week intervention period for either study arm. This may have been due to the external cues and reminders to wear and sync their Fitbit that participants received from the emails that came 2-3 times a week during that period, but stopped at 12 weeks, or may have been due to the novelty of using a Fitbit. However, wearing the Fitbit decreased after the intervention period with the most commonly reported reasons for discontinued use of the Fitbit were that it broke or was lost. Now that most Fitbits are wrist-worn, it may help to decrease loss of devices, but devices breaking is likely to be a continued issue that impacts continued wearing of devices. With the well-established benefits of self-monitoring for behavior change, identifying ways to increase long-term engagement with activity trackers is needed.We also found that both the full and the light intervention group increased minutes of MVPA from the preintervention to the intervention period and maintained it during the 12-week intervention period. The initial increase in MVPA at the start rather than gradually increasing overtime may have been due to the intervention’s goal-setting approach that utilized motivational interviewing, where participants were allowed to set any starting goal that they chose. With more studies having day-level physical activity data, future studies could examine different methods of setting goals and different patterns of exercise to see if they relate to long-term maintenance of activity. This study adds to the literature by demonstrating the importance of additional intervention components, particularly increasing external accountability, when using activity trackers to promote exercise, and the challenges with lost and broken trackers.Our study is one of the first to use wearable activity trackers to assess long-term maintenance of behavior after completion of a short-term intervention in breast cancer survivors. Although some prior studies have assessed long-term physical activity, they have either examined sustained long-term physical activity interventions or relied upon self-reported MVPA . In our Although there were significant declines in activity levels during the postintervention follow-up for both groups, it is interesting that the temporal patterns of both adherence and physical activity were more stable in those who received the full exercise intervention. Comparison of these results with previous trials is difficult as this study took advantage of having minute-level physical activity data for months, rather than having brief snapshots of MVPA from 7 days of accelerometer wear or self-report. By examining patterns of activity over time we see that even a short-term intensive exercise intervention may result in some lasting change in behavior patterns beyond the intervention period. Together, the results suggest that an intensive short-term physical activity intervention, coupled with a continued long-term maintenance intervention, may be necessary to sustain higher activity levels in the long term. Further study is needed to develop the optimal short- and long-term strategies to enhance activity tracker use to achieve sustained physical activity.This study provides unique insight into long-term activity levels after completion of an exercise intervention, but there are several limitations that should be noted. The sample size limited our ability to detect potentially smaller differences between groups, including average adherence and MVPA in the postintervention period. In addition, the progressive decline in adherence to wearing the Fitbit in long-term follow-up meant that there was a large amount of missing MVPA data. Without other measures of MVPA we are unable to know how much activity individuals were engaging in after their Fitbit broke, was lost, or if they were no longer interested in wearing, and our results are limited to those who continued to wear their Fitbit. In addition, the predominantly well-educated, White non-Hispanic sample may limit external generalizability. The sample also had a majority of early stage breast cancer survivors and thus may not generalize to women with more advanced breast cancer. Although the initial trial was randomized, there is the potential for selection bias among those participants who decided to continue in the long-term study. Finally, knowledge of participation in the study may have conferred some effect of external accountability among participants that would not be present outside of the research setting.This study examined patterns of wearable technology use and activity levels among breast cancer survivors during and after completion of a physical activity intervention. We found higher activity levels among participants receiving an intervention with greater engagement and accountability, but that activity levels reduced in follow-up after completion of the intervention. These results provide important insights regarding behavior during and after a physical activity intervention, and may help inform the design of future interventions to more effectively promote, both short- and long-term, sustained increases in physical activity.


The concept of polypharmacy in the type 2 diabetic patient is both historic and redundant. A combination of three or more medications usually at doses which are less than those utilized for monotherapy is efficacious not only in the therapy of hyperglycemia but also in the therapy of the comorbidities of hypertension and hyperlipidemia. In addition, multiple medications are now accepted as being necessary to reduce albuminuria and decelerate the decline in renal function in the patient with diabetic nephropathy. Historically, the use of polypharmacy (more than five different medications per patient) was not encouraged in either the diabetic or the nondiabetic patient . The reaIn 2006, I laid out the case for combination oral therapy as first-line therapy for the type 2 diabetic patient . I suggeSince then, there have been multiple studies of triple oral therapy in type 2 diabetic subjects with almost all of these studies utilizing metformin in combination with sulfonylureas, DPP-4 inhibitors, thiazolidinediones, and SGLT-2-inhibitors and more recently injections of various GLP-1 receptor agonists . FurtherOver 75% of type 2 diabetic patients also have hypertension due to the high insulin levels associated with insulin resistance increasing salt and water retention and the association of insulin resistance with increased sympathetic nervous system activity .Multiple antihypertensives used in combination to achieve target blood pressure levels have been widely utilized for many years in the type 2 diabetic patient. Ideally, the drugs utilized should be from different classes and include a diuretic . The usuWith resistant hypertension, aldosterone excess has been shown to be common, and the use of a steroidal mineralocorticoid receptor antagonist, such as spironolactone or eplerenone, has been shown to be efficacious in the majority of cases . Since iThe choice of the calcium channel blocker is also important. The dihydropyridine calcium channel blockers (CCBs) tend to stimulate the sympathetic nervous system more than the nondihydropyridine CCBs so that lower blood pressure levels can usually be obtained with less side effects utilizing the nondihydropyridine CCBs . In addi3-receptor should be utilized since through vasoconstriction nonvasodilating beta blockers increase insulin resistance, decrease insulin release, worsen glycemic control, and accelerate progression to microalbuminuria [If a beta blocker is utilized in the diabetic subject, a vasodilating beta block such as carvedilol or nebivolol which vasodilate through stimulation of the Buminuria , 28.Also, in the diabetic subject, thiazide diuretics even at lower doses also increase insulin resistance and decrease insulin release . This isThe most important component of the therapy for the dyslipidemia associated with type 2 diabetes is lowering the low-density lipoprotein (LDL) cholesterol level. American Association of Clinical Endocrinology (AACE) guidelines recommend lowering of LDL to 55 mg/dl or below in diabetic patients with established coronary artery disease . The EurA starting dose of a statin usually lowers the LDL cholesterol level by as much as 50% . HoweverThe addition of ezetimibe will lower the LDL by at least another 10% , 37. If Therefore, with the availability of ezetimibe and bempedoic acid, LDL targets can in most situations be achieved with triple oral therapy (statin/ezetimibe/bempedoic acid). Should the LDL not be at goal, then the addition of a PCSK9-inhibitor should be considered .If further LDL lowering or replacement of drugs that cannot be tolerated is needed, the addition of colesevelam which lowers LDL by 16% and C-reactive protein by 22% and lowers the HbA1c by 0.26% can be used. While colesevelam is a bile acid sequestrant, it has been modified to limit gastrointestinal side effects which results in greater patient compliance .The addition of a fish oil derivative icosapent ethyl which not only lowers triglycerides but independent of triglyceride levels lowers both cardiac events and cardiac mortality, especially in the diabetic patient, may be needed and should be added if triglyceride levels are over 150 mg/dl .Thus, to satisfactorily control hyperlipidemia and especially LDL cholesterol in the diabetic patient as many as four or more, oral agents may be required .Blockers of the renin-angiotensin-aldosterone system (RAAS) are efficacious in both decreasing proteinuria and decelerating the decline in renal function in both the type 1 and type 2 diabetic patients who have diabetic nephropathy. Glomerular pressure is decreased with ACE inhibitors through dilatation of the efferent arteriole which by decreasing the glomerular pressure results in decreases in proteinuria as well as deceleration of the progression to renal failure through a decrease in podocyte injury and deceleration of the glomerulosclerosis .At present, only the ACE inhibitor captopril is approved for the therapy of nephropathy associated with type 1 diabetes and the angiotensin II receptor blocker (ARB) losartan for the therapy of nephropathy associated with type 2 diabetes , 45. HowWith or without RAAS blockers, proteinuria decreases and the decline in renal dysfunction decelerates with SGLT-2 inhibitors. Through blockade of the SGLT-2 receptor in the proximal tubule, SGLT-2 inhibitors block not only the reabsorption of glucose but also the reabsorption of sodium which increases the quantity of sodium presenting to the macula densa which is situated in the juxtaglomerular apparatus at the top of the thick ascending limb of the loop of Henle at the point where the loop of Henle meets the distal convoluted tubule. This increase in urinary sodium content is misinterpreted by the macular densa to be due to an increase in plasma volume. This misinterpretation results in not only a decrease in RAAS activity from the renin secreting cells in the juxtaglomerular apparatus but also a negative “tubuloglomerular” feedback. Anatomically, the juxtaglomerular apparatus is in close proximity to the afferent glomerular arteriole which results in constriction of this arteriole which decreases both intraglomerular pressure and hyperfiltration . The vasAnother mechanism for the renoprotective effect is that SGLT-2 inhibitors increase the production of ketone bodies which are preferentially utilized by the kidney as a source of energy. The shift away from the use of free fatty acids and glucose as a source of energy toward the greater use of ketone bodies results in a decrease in the workload of the kidney which in turn results in a deceleration of the decline in renal function .p = 0.001). In addition, stroke, cardiovascular, death, and myocardial infarction which are increased with renal dysfunction were reduced by 20%  and hospitalization for heart failure by 39%  [The SGLT-2 receptor blockers that have been studied in combination with RAS blockade to asses renoprotection are canagliflozin, empagliflozin, and dapagliflozin. In a double-blind, placebo-controlled study, type 2 diabetic subjects with albuminuria and chronic kidney disease and who were already utilizing RAAS blockers were randomized to either placebo or canagliflozin 100 mg daily. This study was prematurely terminated due to a positive interim analysis where the composite of dialysis, transplantation, developing a GFR of under 15 ml/min, doubling of the serum creatinine, or death  was significantly reduced by 30%  .Empagliflozin was utilized in the EMPA-REG outcome trial where 525 subjects in the empagliflozin group who were randomized to 10 mg or 25 mg of empagliflozin were compared to 388 subjects randomized to placebo. In this study, doubling of the serum creatinine was reduced by 44% and initiation of dialysis or transplantation by 55% .The DAPA-CKP trial enrolled subjects who had an albumin-to-creatinine ratio of 200 mg-500 mg/g and an estimated GFR of 25-75 ml/min and of whom 68% had diabetes. These subjects were randomized either to dapagliflozin 10 mg once daily or placebo. The end-point was a composite of a 58% decline in GFR, development of end-stage renal disease , or renal or cardiac death. This end-point over an average of 2.4 years was reduced by 36% (95% CI 0.52-0.79) in those with diabetes and 50% in those without diabetes group (95% CI 0.53-0.92) .Mineralocorticoid receptor antagonists (MRAs) reduce albuminuria and preserve renal function. The mineralocorticoid receptor is a nuclear receptor expressed in many tissues including the kidney, immune cells, and fibroblasts . In the p = 0.04) [Thus, in the patient with diabetic nephropathy when RAAS blockade fails to return the urine albumin level to normal, the addition of a SGLT-2 antagonist or a mineralocorticoid receptor blocker can be added. If the urine albumin level is still elevated, then advancement to triple oral therapy with RAAS blocker MRA agonists and SGLT-2 receptor blockers should be considered. While to date there is no hard evidence that triple therapy would be efficacious in the therapy of diabetic nephropathy, there is a retrospective report of a prospective study of patients with diabetic nephropathy already on a RAS inhibitor treated with finerenone where there was a 19% decrease (95% CI 0.72-0.92) in the frequency of a decline in the glomerular filtration rate of over 40%. In this study, a small number of subjects were also taking SGLT-2 inhibitors, and these subjects were more likely to have a greater decrease in albuminuria  .Therefore, the combination of RAAS inhibitors, SGLT-2 inhibitors, and MR-receptor blockers is likely to be utilized in diabetic patients who do not reduce urine albumin levels to below 30 mg/g creatinine since below this level advancement to renal failure is very unlikely and cardiovascular events are decreased , 59 Fig.p = 0.003) with GLP-1 receptor agonists [p = 0.005) in new or worsening nephropathy in spite of 76% (95% CI 1.11-2.78) increase in the microvascular complication of retinopathy [GLP-1 receptor agonists have also been shown to have a renoprotective effect. While GLP-1 receptors have been demonstrated in the kidney, the receptors in humans are confined to the proximal tubule and preglomerular vascular smooth muscle cells . The diragonists . Semagluinopathy .α suppression has been shown to decrease macroalbuminuria, but not microalbuminuria, and decelerate the progression to renal failure in patients with diabetic nephropathy.Another therapy that is a candidate to reduce albuminuria and frequency of renal decompensation is pentoxifylline . This olp = 0.003) [Another candidate for renoprotection is the vasodilating beta blocker carvedilol which has been shown to reduce albuminuria. In the GEMINI study of hypertensive type 2 diabetic subjects, carvedilol compared with placebo reduced albuminuria by 16.2%  . This deTherefore, as many as six currently available drugs could be utilized to decrease proteinuria and decelerate the decline in renal function in the patient with diabetic nephropathy. At the present time, the most effective combination for diabetic nephropathy appears to be that of a RAAS-inhibitor, a nonsteroidal mineralocorticoid receptor antagonist, and an SGLT-2 inhibitor. However, second-line drugs such as GLP-1 receptor agonists, pentoxifylline, and carvedilol could be used either as a replacement for or as an addition to these medications .The concept of polypharmacy is redundant as far as therapy for type 2 diabetes, its comorbidities, and its complications are concerned. The use of multiple drug combinations in randomized placebo-controlled trials has been shown to be efficacious in treating not only hyperglycemia but also the comorbidities of hypertension and hyperlipidemia in the type 2 diabetic patient as well as the complication of diabetic nephropathy. In spite of this well-documented evidence of decreased morbidity and mortality with these medications, patients with advanced diabetes despite having the worst renal and cardiovascular prognosis are at high risk of being undertreated, and this is universal and not associated with type of clinical setting in which they are treated .