Guide Intergenerational Communication Across the Life Span (Leas Communication Series)

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In fact, there is a considerable variety of preferences and values within any of these groups. For example, a thorough analysis of 20 different studies with nearly 20, people revealed small and inconsistent differences in job attitudes when comparing generational groups. These beliefs can get in the way of how people collaborate with their colleagues, and have troubling implications for how we people are managed and trained. An emerging area of research in the field of Industrial-Organizational Psychology considers age-related beliefs from two different but intermingling angles. Work on age stereotypes looks at the content and impact of beliefs about people from another age group.

A stereotype about young people, for example, might be that they are narcissistic. A relatively newer concept called age meta-stereotypes looks at what we think others believe about us based on our age group. A young person, then, might worry that other people think they are narcissistic, even if the other people are not actually thinking this.

If both of these processes are occurring in an age-diverse workplace at the same time, employees are likely having knee-jerk thoughts about what other people must be like stereotypes while simultaneously assuming that the same people are making assumptions about them meta-stereotypes. Our research suggests that workplaces are brimming with age-related stereotypes and meta-stereotypes, and that these beliefs are not always accurate or aligned. In one survey of young , middle-aged , and older workers , people described the qualities that might be true of people in another age group their stereotypes.

They also described the qualities that other people might have about their own age group their meta-stereotypes. The pattern of their responses varied by age group.

Intergenerational Communication Across the Life Span

Broadly, these results demonstrate that older and younger workers believe others view them more negatively than they actually do. These cases confirm that neither age-related stereotypes or meta-stereotypes are accurate. Another undergraduate was asked to listen to the training and then perform the task. We varied whether each person — the trainer and the trainee — appeared to be old approximately 53 or young approximately 23 using photographs and voice-modifying software.

When trainers believed that they were teaching an older person how to do the computer task, they had lower expectations and provided worse training than when they believed they were teaching a young person. These results demonstrate that poorer training is a direct result of age stereotypes.

Generational Differences At Work Are Small. Thinking They’re Big Affects Our Behavior

A recently published study examined how people react to meta-stereotypes over the course of a work week. Importantly, these reactions can also impact interpersonal behaviors at work. Both threats and challenges led to conflict at work things like arguing or not getting along with colleagues and avoidance behaviors things like keeping to oneself and avoiding interacting with others.

We also considered the implications of meta-stereotypes for mentoring relationships in law and in medicine in another study that we recently presented at a conference with our colleagues. If there are not real and consistent differences between people of different age groups, but these stereotyping and meta-stereotyping processes end up creating artificial generational divides, what is a manager supposed to do? First, openly talking about these stereotypes and meta-stereotypes can be a great first step.

The Drosophila model established here indicates that the inheritance of altered histone modifications is a key mechanism in the propagation of lipotoxic cardiomyopathy across generations. Histone modifications are essential in regulating chromatin packaging and gene expression for proper development and cell function. In turn, metabolites serve as co-factors for chromatin modifying enzymes, allowing protein activity and gene expression to match the specific energy requirements We found that HFD, and potentially its maladaptive fluctuation in metabolites, can lead to changes in chromatin structure and gene expression that are transmitted to the next generation.

Indeed, a major finding presented here is the involvement of the PRC2 complex in regulating metabolism and heart function in response to a HFD, via H3K27me3 gene repression across generations. The increase in H3K27me3 global levels in the adult flies upon acute or parental HFD supports the hypothesis that HFD causes changes in the epigenome that have lifelong consequences.

In addition, we found that reduction of H3K27me3, either by overexpression of UTX or inhibition of EzH2, can prevent the deleterious effects of a parental HFD on heart function and metabolism. Importantly, the imposed metabolic state appears to be inherited by the next two generations as either a predisposition to metabolic imbalance and cardiac dysfunction, or a protection from HFD insult when bmm is overexpressed.

Moreover, we provide evidence that metabolic re-programming that leads to fat accumulation and cardiac lipotoxicity correlates with overall levels of H3K27me3 epigenetic marks, which can be reversed by genetic or pharmacological reduction of H3K27me3 levels. Our findings shed light on possible causes of obesogenic heritability and early adult onset of cardiovascular disease and diabetes, which appear to have their roots in the diet and overall metabolic state of the parents.

Just How Different Are Millennials, Gen Xers, and Baby Boomers at Work?

These findings provide new perspectives for tackling metabolic syndrome effects across generations and preventing lipotoxic cardiomyopathies. We obtained w flies used as controls in Figs. We used multiple drivers for each tissue type. Bergmann University of Massachusetts Medical School. This formulation was used for all experiments because it gave the strongest phenotype and the most reproducible results Male and female flies were collected after eclosion and aged for 5 days on NFD 40 flies per tube.

Each population was then placed on NFD see schematic in Fig. The offspring were raised on NFD. Additionally, 20 females and 20 males were placed on NFD and allowed to lay eggs for 3 days to create the subsequent generation. This protocol was repeated for 3 generations see Fig. Embryos were collected on agar plates following standard protocols Surgical dissection and exposure of hearts, high-resolution video microscopy, and analysis of movies for cardiac function measurements were performed according to published procedures Female flies were dissected in oxygenated artificial hemolymph in order to expose their hearts within the abdomen.

High-speed digital movies were recorded using HCImageLive software Hamamatsu and then analyzed in a group-blinded fashion for heart rate, arrhythmia, contractility, and fractional shortening using SOHA software For most of the experiments, a sample size of 15—20 flies was adequate. TAGs were measured as described by Diop et al.

The Triglyceride Reagent contains a Lipoprotein lipase that hydrolyzes the triglycerides present in the sample and produces glycerol, which is processed by a series of reactions ultimately producing a red-colored dye whose absorbance is proportional to the concentration of triglycerides present in the sample The 1—2-week-old female flies were dissected in oxygenated artificial hemolymph to expose the heart and surrounding fat tissue.

Images were analyzed using ImageJ 1. Primer sequences were as follows:.

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Gal4 -labeled hearts were mounted immediately after using Prolong Gold Molecular Probes. Images were acquired using an Apotome. Approximately 40 flies per sample were pulverized in liquid nitrogen, and histones were extracted. The recovered pellet was then re-suspended in 0. Densitometry quantification was achieved using ImageJ software. Heart dysfunction phenotypes partial conduction block, non-contractile cells in the heart, ostia defects were analyzed using the chi-square test and one representative experiment is shown. All data presented here are representative of at least two independent experiments.

The authors declare that the data supporting the findings of this study are available in the article and its Supplementary Information File. All other relevant data supporting the findings of this study are available from the corresponding author upon reasonable request. McCarthy, M. Genomic medicine at the heart of diabetes management. Diabetologia 58 , — Fall, T. Genome-wide association studies of obesity and metabolic syndrome.

Willyard, C. Heritability: the family roots of obesity. Nature , S58 Shankar, K.

Maternal obesity at conception programs obesity in the offspring. Barker, D. The maternal and fetal origins of cardiovascular disease. Community Health 46 , 8—11 Woo, M. Diabetes risk begins in utero. Cell Metab. Costa-Silva, J.

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Developmental origins of cardiometabolic diseases: role of the maternal diet. Front Physiol.

How to get along with Boomers, GenXers and Millennials - Mary Donohue - TEDxToronto

Intergenerational transmission of overweight among Finnish adolescents and their parents: a year follow-up study. Carone, B. Paternally induced transgenerational environmental reprogramming of metabolic gene expression in mammals. Cell , — Paneth, N. BMJ Clinical research ed. Sales, V.