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• Published: 06 December 2017

Healthy food choices are happy food choices: Evidence from a real life sample using smartphone based assessments

• Deborah R. Wahl 1   na1 ,
• Karoline Villinger 1   na1 ,
• Laura M. König   ORCID: orcid.org/0000-0003-3655-8842 1 ,
• Katrin Ziesemer 1 ,
• Harald T. Schupp 1 &
• Britta Renner 1  

Scientific Reports volume  7 , Article number:  17069 ( 2017 ) Cite this article

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Research suggests that “healthy” food choices such as eating fruits and vegetables have not only physical but also mental health benefits and might be a long-term investment in future well-being. This view contrasts with the belief that high-caloric foods taste better, make us happy, and alleviate a negative mood. To provide a more comprehensive assessment of food choice and well-being, we investigated in-the-moment eating happiness by assessing complete, real life dietary behaviour across eight days using smartphone-based ecological momentary assessment. Three main findings emerged: First, of 14 different main food categories, vegetables consumption contributed the largest share to eating happiness measured across eight days. Second, sweets on average provided comparable induced eating happiness to “healthy” food choices such as fruits or vegetables. Third, dinner elicited comparable eating happiness to snacking. These findings are discussed within the “food as health” and “food as well-being” perspectives on eating behaviour.

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Introduction.

When it comes to eating, researchers, the media, and policy makers mainly focus on negative aspects of eating behaviour, like restricting certain foods, counting calories, and dieting. Likewise, health intervention efforts, including primary prevention campaigns, typically encourage consumers to trade off the expected enjoyment of hedonic and comfort foods against health benefits 1 . However, research has shown that diets and restrained eating are often counterproductive and may even enhance the risk of long-term weight gain and eating disorders 2 , 3 . A promising new perspective entails a shift from food as pure nourishment towards a more positive and well-being centred perspective of human eating behaviour 1 , 4 , 5 . In this context, Block et al . 4 have advocated a paradigm shift from “food as health” to “food as well-being” (p. 848).

Supporting this perspective of “food as well-being”, recent research suggests that “healthy” food choices, such as eating more fruits and vegetables, have not only physical but also mental health benefits 6 , 7 and might be a long-term investment in future well-being 8 . For example, in a nationally representative panel survey of over 12,000 adults from Australia, Mujcic and Oswald 8 showed that fruit and vegetable consumption predicted increases in happiness, life satisfaction, and well-being over two years. Similarly, using lagged analyses, White and colleagues 9 showed that fruit and vegetable consumption predicted improvements in positive affect on the subsequent day but not vice versa. Also, cross-sectional evidence reported by Blanchflower et al . 10 shows that eating fruits and vegetables is positively associated with well-being after adjusting for demographic variables including age, sex, or race 11 . Of note, previous research includes a wide range of time lags between actual eating occasion and well-being assessment, ranging from 24 hours 9 , 12 to 14 days 6 , to 24 months 8 . Thus, the findings support the notion that fruit and vegetable consumption has beneficial effects on different indicators of well-being, such as happiness or general life satisfaction, across a broad range of time spans.

The contention that healthy food choices such as a higher fruit and vegetable consumption is associated with greater happiness and well-being clearly contrasts with the common belief that in particular high-fat, high-sugar, or high-caloric foods taste better and make us happy while we are eating them. When it comes to eating, people usually have a spontaneous “unhealthy = tasty” association 13 and assume that chocolate is a better mood booster than an apple. According to this in-the-moment well-being perspective, consumers have to trade off the expected enjoyment of eating against the health costs of eating unhealthy foods 1 , 4 .

A wealth of research shows that the experience of negative emotions and stress leads to increased consumption in a substantial number of individuals (“emotional eating”) of unhealthy food (“comfort food”) 14 , 15 , 16 , 17 . However, this research stream focuses on emotional eating to “smooth” unpleasant experiences in response to stress or negative mood states, and the mood-boosting effect of eating is typically not assessed 18 . One of the few studies testing the effectiveness of comfort food in improving mood showed that the consumption of “unhealthy” comfort food had a mood boosting effect after a negative mood induction but not to a greater extent than non-comfort or neutral food 19 . Hence, even though people may believe that snacking on “unhealthy” foods like ice cream or chocolate provides greater pleasure and psychological benefits, the consumption of “unhealthy” foods might not actually be more psychologically beneficial than other foods.

However, both streams of research have either focused on a single food category (fruit and vegetable consumption), a single type of meal (snacking), or a single eating occasion (after negative/neutral mood induction). Accordingly, it is unknown whether the boosting effect of eating is specific to certain types of food choices and categories or whether eating has a more general boosting effect that is observable after the consumption of both “healthy” and “unhealthy” foods and across eating occasions. Accordingly, in the present study, we investigated the psychological benefits of eating that varied by food categories and meal types by assessing complete dietary behaviour across eight days in real life.

Furthermore, previous research on the impact of eating on well-being tended to rely on retrospective assessments such as food frequency questionnaires 8 , 10 and written food diaries 9 . Such retrospective self-report methods rely on the challenging task of accurately estimating average intake or remembering individual eating episodes and may lead to under-reporting food intake, particularly unhealthy food choices such as snacks 7 , 20 . To avoid memory and bias problems in the present study we used ecological momentary assessment (EMA) 21 to obtain ecologically valid and comprehensive real life data on eating behaviour and happiness as experienced in-the-moment.

In the present study, we examined the eating happiness and satisfaction experienced in-the-moment, in real time and in real life, using a smartphone based EMA approach. Specifically, healthy participants were asked to record each eating occasion, including main meals and snacks, for eight consecutive days and rate how tasty their meal/snack was, how much they enjoyed it, and how pleased they were with their meal/snack immediately after each eating episode. This intense recording of every eating episode allows assessing eating behaviour on the level of different meal types and food categories to compare experienced eating happiness across meals and categories. Following the two different research streams, we expected on a food category level that not only “unhealthy” foods like sweets would be associated with high experienced eating happiness but also “healthy” food choices such as fruits and vegetables. On a meal type level, we hypothesised that the happiness of meals differs as a function of meal type. According to previous contention, snacking in particular should be accompanied by greater happiness.

Eating episodes

Overall, during the study period, a total of 1,044 completed eating episodes were reported (see also Table  1 ). On average, participants rated their eating happiness with M  = 77.59 which suggests that overall eating occasions were generally positive. However, experienced eating happiness also varied considerably between eating occasions as indicated by a range from 7.00 to 100.00 and a standard deviation of SD  = 16.41.

Food categories and experienced eating happiness

All eating episodes were categorised according to their food category based on the German Nutrient Database (German: Bundeslebensmittelschlüssel), which covers the average nutritional values of approximately 10,000 foods available on the German market and is a validated standard instrument for the assessment of nutritional surveys in Germany. As shown in Table  1 , eating happiness differed significantly across all 14 food categories, F (13, 2131) = 1.78, p  = 0.04. On average, experienced eating happiness varied from 71.82 ( SD  = 18.65) for fish to 83.62 ( SD  = 11.61) for meat substitutes. Post hoc analysis, however, did not yield significant differences in experienced eating happiness between food categories, p  ≥ 0.22. Hence, on average, “unhealthy” food choices such as sweets ( M  = 78.93, SD  = 15.27) did not differ in experienced happiness from “healthy” food choices such as fruits ( M  = 78.29, SD  = 16.13) or vegetables ( M  = 77.57, SD  = 17.17). In addition, an intraclass correlation (ICC) of ρ = 0.22 for happiness indicated that less than a quarter of the observed variation in experienced eating happiness was due to differences between food categories, while 78% of the variation was due to differences within food categories.

However, as Figure  1 (left side) depicts, consumption frequency differed greatly across food categories. Frequently consumed food categories encompassed vegetables which were consumed at 38% of all eating occasions ( n  = 400), followed by dairy products with 35% ( n  = 366), and sweets with 34% ( n  = 356). Conversely, rarely consumed food categories included meat substitutes, which were consumed in 2.2% of all eating occasions ( n  = 23), salty extras (1.5%, n  = 16), and pastries (1.3%, n  = 14).

Left side: Average experienced eating happiness (colour intensity: darker colours indicate greater happiness) and consumption frequency (size of the cycle) for the 14 food categories. Right side: Absolute share of the 14 food categories in total experienced eating happiness.

Amount of experienced eating happiness by food category

To account for the frequency of consumption, we calculated and scaled the absolute experienced eating happiness according to the total sum score. As shown in Figure  1 (right side), vegetables contributed the biggest share to the total happiness followed by sweets, dairy products, and bread. Clustering food categories shows that fruits and vegetables accounted for nearly one quarter of total eating happiness score and thus, contributed to a large part of eating related happiness. Grain products such as bread, pasta, and cereals, which are main sources of carbohydrates including starch and fibre, were the second main source for eating happiness. However, “unhealthy” snacks including sweets, salty extras, and pastries represented the third biggest source of eating related happiness.

Experienced eating happiness by meal type

To further elucidate the contribution of snacks to eating happiness, analysis on the meal type level was conducted. Experienced in-the-moment eating happiness significantly varied by meal type consumed, F (4, 1039) = 11.75, p  < 0.001. Frequencies of meal type consumption ranged from snacks being the most frequently logged meal type ( n  = 332; see also Table  1 ) to afternoon tea being the least logged meal type ( n  = 27). Figure  2 illustrates the wide dispersion within as well as between different meal types. Afternoon tea ( M  = 82.41, SD  = 15.26), dinner ( M  = 81.47, SD  = 14.73), and snacks ( M  = 79.45, SD  = 14.94) showed eating happiness values above the grand mean, whereas breakfast ( M  = 74.28, SD  = 16.35) and lunch ( M  = 73.09, SD  = 18.99) were below the eating happiness mean. Comparisons between meal types showed that eating happiness for snacks was significantly higher than for lunch t (533) = −4.44, p  = 0.001, d  = −0.38 and breakfast, t (567) = −3.78, p  = 0.001, d  = −0.33. However, this was also true for dinner, which induced greater eating happiness than lunch t (446) = −5.48, p  < 0.001, d  = −0.50 and breakfast, t (480) = −4.90, p  < 0.001, d  = −0.46. Finally, eating happiness for afternoon tea was greater than for lunch t (228) = −2.83, p  = 0.047, d  = −0.50. All other comparisons did not reach significance, t  ≤ 2.49, p  ≥ 0.093.

Experienced eating happiness per meal type. Small dots represent single eating events, big circles indicate average eating happiness, and the horizontal line indicates the grand mean. Boxes indicate the middle 50% (interquartile range) and median (darker/lighter shade). The whiskers above and below represent 1.5 of the interquartile range.

Control Analyses

In order to test for a potential confounding effect between experienced eating happiness, food categories, and meal type, additional control analyses within meal types were conducted. Comparing experienced eating happiness for dinner and lunch suggested that dinner did not trigger a happiness spill-over effect specific to vegetables since the foods consumed at dinner were generally associated with greater happiness than those consumed at other eating occasions (Supplementary Table  S1 ). Moreover, the relative frequency of vegetables consumed at dinner (73%, n  = 180 out of 245) and at lunch were comparable (69%, n  = 140 out of 203), indicating that the observed happiness-vegetables link does not seem to be mainly a meal type confounding effect.

Since the present study focuses on “food effects” (Level 1) rather than “person effects” (Level 2), we analysed the data at the food item level. However, participants who were generally overall happier with their eating could have inflated the observed happiness scores for certain food categories. In order to account for person-level effects, happiness scores were person-mean centred and thereby adjusted for mean level differences in happiness. The person-mean centred happiness scores ( M cwc ) represent the difference between the individual’s average happiness score (across all single in-the-moment happiness scores per food category) and the single happiness scores of the individual within the respective food category. The centred scores indicate whether the single in-the-moment happiness score was above (indicated by positive values) or below (indicated by negative values) the individual person-mean. As Table  1 depicts, the control analyses with centred values yielded highly similar results. Vegetables were again associated on average with more happiness than other food categories (although people might differ in their general eating happiness). An additional conducted ANOVA with person-centred happiness values as dependent variables and food categories as independent variables provided also a highly similar pattern of results. Replicating the previously reported analysis, eating happiness differed significantly across all 14 food categories, F (13, 2129) = 1.94, p  = 0.023, and post hoc analysis did not yield significant differences in experienced eating happiness between food categories, p  ≥ 0.14. Moreover, fruits and vegetables were associated with high happiness values, and “unhealthy” food choices such as sweets did not differ in experienced happiness from “healthy” food choices such as fruits or vegetables. The only difference between the previous and control analysis was that vegetables ( M cwc  = 1.16, SD  = 15.14) gained slightly in importance for eating-related happiness, whereas fruits ( M cwc  = −0.65, SD  = 13.21), salty extras ( M cwc  = −0.07, SD  = 8.01), and pastries ( M cwc  = −2.39, SD  = 18.26) became slightly less important.

This study is the first, to our knowledge, that investigated in-the-moment experienced eating happiness in real time and real life using EMA based self-report and imagery covering the complete diversity of food intake. The present results add to and extend previous findings by suggesting that fruit and vegetable consumption has immediate beneficial psychological effects. Overall, of 14 different main food categories, vegetables consumption contributed the largest share to eating happiness measured across eight days. Thus, in addition to the investment in future well-being indicated by previous research 8 , “healthy” food choices seem to be an investment in the in-the moment well-being.

Importantly, although many cultures convey the belief that eating certain foods has a greater hedonic and mood boosting effect, the present results suggest that this might not reflect actual in-the-moment experiences accurately. Even though people often have a spontaneous “unhealthy = tasty” intuition 13 , thus indicating that a stronger happiness boosting effect of “unhealthy” food is to be expected, the induced eating happiness of sweets did not differ on average from “healthy” food choices such as fruits or vegetables. This was also true for other stereotypically “unhealthy” foods such as pastries and salty extras, which did not show the expected greater boosting effect on happiness. Moreover, analyses on the meal type level support this notion, since snacks, despite their overall positive effect, were not the most psychologically beneficial meal type, i.e., dinner had a comparable “happiness” signature to snacking. Taken together, “healthy choices” seem to be also “happy choices” and at least comparable to or even higher in their hedonic value as compared to stereotypical “unhealthy” food choices.

In general, eating happiness was high, which concurs with previous research from field studies with generally healthy participants. De Castro, Bellisle, and Dalix 22 examined weekly food diaries from 54 French subjects and found that most of the meals were rated as appealing. Also, the observed differences in average eating happiness for the 14 different food categories, albeit statistically significant, were comparable small. One could argue that this simply indicates that participants avoided selecting bad food 22 . Alternatively, this might suggest that the type of food or food categories are less decisive for experienced eating happiness than often assumed. This relates to recent findings in the field of comfort and emotional eating. Many people believe that specific types of food have greater comforting value. Also in research, the foods eaten as response to negative emotional strain, are typically characterised as being high-caloric because such foods are assumed to provide immediate psycho-physical benefits 18 . However, comparing different food types did not provide evidence for the notion that they differed in their provided comfort; rather, eating in general led to significant improvements in mood 19 . This is mirrored in the present findings. Comparing the eating happiness of “healthy” food choices such as fruits and vegetables to that of “unhealthy” food choices such as sweets shows remarkably similar patterns as, on average, they were associated with high eating happiness and their range of experiences ranged from very negative to very positive.

This raises the question of why the idea that we can eat indulgent food to compensate for life’s mishaps is so prevailing. In an innovative experimental study, Adriaanse, Prinsen, de Witt Huberts, de Ridder, and Evers 23 led participants believe that they overate. Those who characterised themselves as emotional eaters falsely attributed their over-consumption to negative emotions, demonstrating a “confabulation”-effect. This indicates that people might have restricted self-knowledge and that recalled eating episodes suffer from systematic recall biases 24 . Moreover, Boelsma, Brink, Stafleu, and Hendriks 25 examined postprandial subjective wellness and objective parameters (e.g., ghrelin, insulin, glucose) after standardised breakfast intakes and did not find direct correlations. This suggests that the impact of different food categories on wellness might not be directly related to biological effects but rather due to conditioning as food is often paired with other positive experienced situations (e.g., social interactions) or to placebo effects 18 . Moreover, experimental and field studies indicate that not only negative, but also positive, emotions trigger eating 15 , 26 . One may speculate that selective attention might contribute to the “myth” of comfort food 19 in that people attend to the consumption effect of “comfort” food in negative situation but neglect the effect in positive ones.

The present data also show that eating behaviour in the real world is a complex behaviour with many different aspects. People make more than 200 food decisions a day 27 which poses a great challenge for the measurement of eating behaviour. Studies often assess specific food categories such as fruit and vegetable consumption using Food Frequency Questionnaires, which has clear advantages in terms of cost-effectiveness. However, focusing on selective aspects of eating and food choices might provide only a selective part of the picture 15 , 17 , 22 . It is important to note that focusing solely on the “unhealthy” food choices such as sweets would have led to the conclusion that they have a high “indulgent” value. To be able to draw conclusions about which foods make people happy, the relation of different food categories needs to be considered. The more comprehensive view, considering the whole dietary behaviour across eating occasions, reveals that “healthy” food choices actually contributed the biggest share to the total experienced eating happiness. Thus, for a more comprehensive understanding of how eating behaviours are regulated, more complete and sensitive measures of the behaviour are necessary. Developments in mobile technologies hold great promise for feasible dietary assessment based on image-assisted methods 28 .

As fruits and vegetables evoked high in-the-moment happiness experiences, one could speculate that these cumulate and have spill-over effects on subsequent general well-being, including life satisfaction across time. Combing in-the-moment measures with longitudinal perspectives might be a promising avenue for future studies for understanding the pathways from eating certain food types to subjective well-being. In the literature different pathways are discussed, including physiological and biochemical aspects of specific food elements or nutrients 7 .

The present EMA based data also revealed that eating happiness varied greatly within the 14 food categories and meal types. As within food category variance represented more than two third of the total observed variance, happiness varied according to nutritional characteristics and meal type; however, a myriad of factors present in the natural environment can affect each and every meal. Thus, widening the “nourishment” perspective by including how much, when, where, how long, and with whom people eat might tell us more about experienced eating happiness. Again, mobile, in-the-moment assessment opens the possibility of assessing the behavioural signature of eating in real life. Moreover, individual factors such as eating motives, habitual eating styles, convenience, and social norms are likely to contribute to eating happiness variance 5 , 29 .

A key strength of this study is that it was the first to examine experienced eating happiness in non-clinical participants using EMA technology and imagery to assess food intake. Despite this strength, there are some limitations to this study that affect the interpretation of the results. In the present study, eating happiness was examined on a food based level. This neglects differences on the individual level and might be examined in future multilevel studies. Furthermore, as a main aim of this study was to assess real life eating behaviour, the “natural” observation level is the meal, the psychological/ecological unit of eating 30 , rather than food categories or nutrients. Therefore, we cannot exclude that specific food categories may have had a comparably higher impact on the experienced happiness of the whole meal. Sample size and therefore Type I and Type II error rates are of concern. Although the total number of observations was higher than in previous studies (see for example, Boushey et al . 28 for a review), the number of participants was small but comparable to previous studies in this field 20 , 31 , 32 , 33 . Small sample sizes can increase error rates because the number of persons is more decisive than the number of nested observations 34 . Specially, nested data can seriously increase Type I error rates, which is rather unlikely to be the case in the present study. Concerning Type II error rates, Aarts et al . 35 illustrated for lower ICCs that adding extra observations per participant also increases power, particularly in the lower observation range. Considering the ICC and the number of observations per participant, one could argue that the power in the present study is likely to be sufficient to render the observed null-differences meaningful. Finally, the predominately white and well-educated sample does limit the degree to which the results can be generalised to the wider community; these results warrant replication with a more representative sample.

Despite these limitations, we think that our study has implications for both theory and practice. The cumulative evidence of psychological benefits from healthy food choices might offer new perspectives for health promotion and public-policy programs 8 . Making people aware of the “healthy = happy” association supported by empirical evidence provides a distinct and novel perspective to the prevailing “unhealthy = tasty” folk intuition and could foster eating choices that increase both in-the-moment happiness and future well-being. Furthermore, the present research lends support to the advocated paradigm shift from “food as health” to “food as well-being” which entails a supporting and encouraging rather constraining and limiting view on eating behaviour.

The study conformed with the Declaration of Helsinki. All study protocols were approved by University of Konstanz’s Institutional Review Board and were conducted in accordance with guidelines and regulations. Upon arrival, all participants signed a written informed consent.

Participants

Thirty-eight participants (28 females: average age = 24.47, SD  = 5.88, range = 18–48 years) from the University of Konstanz assessed their eating behaviour in close to real time and in their natural environment using an event-based ambulatory assessment method (EMA). No participant dropped out or had to be excluded. Thirty-three participants were students, with 52.6% studying psychology. As compensation, participants could choose between taking part in a lottery (4 × 25€) or receiving course credits (2 hours).

Participants were recruited through leaflets distributed at the university and postings on Facebook groups. Prior to participation, all participants gave written informed consent. Participants were invited to the laboratory for individual introductory sessions. During this first session, participants installed the application movisensXS (version 0.8.4203) on their own smartphones and downloaded the study survey (movisensXS Library v4065). In addition, they completed a short baseline questionnaire, including demographic variables like age, gender, education, and eating principles. Participants were instructed to log every eating occasion immediately before eating by using the smartphone to indicate the type of meal, take pictures of the food, and describe its main components using a free input field. Fluid intake was not assessed. Participants were asked to record their food intake on eight consecutive days. After finishing the study, participants were invited back to the laboratory for individual final interviews.

Immediately before eating participants were asked to indicate the type of meal with the following five options: breakfast, lunch, afternoon tea, dinner, snack. In Germany, “afternoon tea” is called “Kaffee & Kuchen” which directly translates as “coffee & cake”. It is similar to the idea of a traditional “afternoon tea” meal in UK. Specifically, in Germany, people have “Kaffee & Kuchen” in the afternoon (between 4–5 pm) and typically coffee (or tea) is served with some cake or cookies. Dinner in Germany is a main meal with mainly savoury food.

After each meal, participants were asked to rate their meal on three dimensions. They rated (1) how much they enjoyed the meal, (2) how pleased they were with their meal, and (3) how tasty their meal was. Ratings were given on a scale of one to 100. For reliability analysis, Cronbach’s Alpha was calculated to assess the internal consistency of the three items. Overall Cronbach’s alpha was calculated with α = 0.87. In addition, the average of the 38 Cronbach’s alpha scores calculated at the person level also yielded a satisfactory value with α = 0.83 ( SD  = 0.24). Thirty-two of 38 participants showed a Cronbach’s alpha value above 0.70 (range = 0.42–0.97). An overall score of experienced happiness of eating was computed using the average of the three questions concerning the meals’ enjoyment, pleasure, and tastiness.

Analytical procedure

The food pictures and descriptions of their main components provided by the participants were subsequently coded by independent and trained raters. Following a standardised manual, additional components displayed in the picture were added to the description by the raters. All consumed foods were categorised into 14 different food categories (see Table  1 ) derived from the food classification system designed by the German Nutrition Society (DGE) and based on the existing food categories of the German Nutrient Database (Max Rubner Institut). Liquid intake and preparation method were not assessed. Therefore, fats and additional recipe ingredients were not included in further analyses, because they do not represent main elements of food intake. Further, salty extras were added to the categorisation.

No participant dropped out or had to be excluded due to high missing rates. Missing values were below 5% for all variables. The compliance rate at the meal level cannot be directly assessed since the numbers of meals and snacks can vary between as well as within persons (between days). As a rough compliance estimate, the numbers of meals that are expected from a “normative” perspective during the eight observation days can be used as a comparison standard (8 x breakfast, 8 × lunch, 8 × dinner = 24 meals). On average, the participants reported M  = 6.3 breakfasts ( SD  = 2.3), M  = 5.3 lunches ( SD  = 1.8), and M  = 6.5 dinners ( SD  = 2.0). In comparison to the “normative” expected 24 meals, these numbers indicate a good compliance (approx. 75%) with a tendency to miss six meals during the study period (approx. 25%). However, the “normative” expected 24 meals for the study period might be too high since participants might also have skipped meals (e.g. breakfast). Also, the present compliance rates are comparable to other studies. For example, Elliston et al . 36 recorded 3.3 meal/snack reports per day in an Australian adult sample and Casperson et al . 37 recorded 2.2 meal reports per day in a sample of adolescents. In the present study, on average, M  = 3.4 ( SD  = 1.35) meals or snacks were reported per day. These data indicate overall a satisfactory compliance rate and did not indicate selective reporting of certain food items.

To graphically visualise data, Tableau (version 10.1) was used and for further statistical analyses, IBM SPSS Statistics (version 24 for Windows).

Data availability

The dataset generated and analysed during the current study is available from the corresponding authors on reasonable request.

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Acknowledgements

This research was supported by the Federal Ministry of Education and Research within the project SmartAct (Grant 01EL1420A, granted to B.R. & H.S.). The funding source had no involvement in the study’s design; the collection, analysis, and interpretation of data; the writing of the report; or the decision to submit this article for publication. We thank Gudrun Sproesser, Helge Giese, and Angela Whale for their valuable support.

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Deborah R. Wahl and Karoline Villinger contributed equally to this work.

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Department of Psychology, University of Konstanz, Konstanz, Germany

Deborah R. Wahl, Karoline Villinger, Laura M. König, Katrin Ziesemer, Harald T. Schupp & Britta Renner

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B.R. & H.S. developed the study concept. All authors participated in the generation of the study design. D.W., K.V., L.K. & K.Z. conducted the study, including participant recruitment and data collection, under the supervision of B.R. & H.S.; D.W. & K.V. conducted data analyses. D.W. & K.V. prepared the first manuscript draft, and B.R. & H.S. provided critical revisions. All authors approved the final version of the manuscript for submission.

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Correspondence to Deborah R. Wahl or Britta Renner .

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Wahl, D.R., Villinger, K., König, L.M. et al. Healthy food choices are happy food choices: Evidence from a real life sample using smartphone based assessments. Sci Rep 7 , 17069 (2017). https://doi.org/10.1038/s41598-017-17262-9

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[Databases of the chemical composition of foods in the era of digital nutrition science]

Affiliation.

• 1 Federal Research Centre of Nutrition, Biotechnology and Food Safety, 109240, Moscow, Russian Federation.
• PMID: 32986334
• DOI: 10.24411/0042-8833-2020-10058

By studying the chemical composition of foods, expanding the list of data on the content of nutrients, including minor biologically active substances, in the era of digital nutrition science, it became possible to create relevant systematic databases of the chemical composition of foods and rations in general. They allow us to solve various problems of modern society from the point of view of nutrition science. This review aim to analyze and generalize modern approaches to the formation and updating of databases of the chemical composition of food products from the standpoint of digital nutrition science. Results . This review considers the main provisions regarding creation of databases, directions for the development of food chemistry, discusses existing international programs for collecting and compiling data. The methods of systematizing data on the qualitative composition and content of biologically active and minor substances in products, as well as the problems associated with the development and metrological certification of highly selective highly sensitive analytical methods necessary to obtain reliable and reproducible data are considered. Conclusion . The development of digital nutrition science significantly increases the availability and quality of information on the chemical composition of foods, and allows it to be updated quickly. Further improvement of the quality of the data presented in the tables of chemical composition is associated with the establishment of stability and relationships between micro- and macro-components, their influence on the safety, stability of the chemical structure, the influence of the physic-chemical characteristics of the matrix on nutritive value of foods, determination of the content of specific minor components, development of relevant regulatory documents.

Keywords: databases of the chemical composition of food products; digital nutrition science.

Copyright© GEOTAR-Media Publishing Group.

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Conflict of interest statement

The authors declare no overt and potential conflict of interest related to the publication of this article.

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Survey tallies consumer attitudes toward lab-grown meat alternatives

Conventional beef, chicken and pork products perceived more favorably

In the latest Consumer Food Insights Report, Joseph Balagtas, professor of agricultural economics at Purdue University and director of the Center for Food Demand Analysis and Sustainability, gauged consumer perceptions of and willingness to try exotic and cultivated (or laboratory-grown) meats. (Purdue Agricultural Communications photo/Tom Campbell)

WEST LAFAYETTE, Ind. — Many consumers view conventional meats as both tastier and healthier than laboratory-grown alternatives, according to the  March  Consumer Food Insights Report.

The survey-based report out of Purdue University’s  Center for Food Demand Analysis and Sustainability  assesses food spending, consumer satisfaction and values, support of agricultural and food policies, and trust in information sources. Purdue experts conducted and evaluated the survey, which included 1,200 consumers across the U.S.

This month’s report explores consumer perceptions of and willingness to try exotic and cultivated meats. The report highlights differing responses to queries based on meat type: conventional (noncultivated) or cultivated. The researchers use the term “conventional” meat to describe meat that is sourced conventionally — bred and raised or hunted, slaughtered, and butchered. Cultivated meat is grown or cultivated in a laboratory from animal cells.

Focusing on familiar meats that Americans can find in any grocery store, such as beef and chicken, center researchers saw a big difference between the perceived taste and healthfulness of conventional versus cultivated versions of these meats. The conventional versions received a higher average rating in both aspects.

“We see similar results when evaluating consumers’ willingness to try conventional and cultivated meats in a restaurant setting,” said the report’s lead author,  Joseph Balagtas , professor of  agricultural economics  at Purdue and center director. For common meats, such as beef, chicken and pork, the researchers found that about 90% or more of consumers are willing to try conventional or noncultivated meats.

“The proportion of consumers willing to try the cultivated versions of these meats is around 30 percentage points lower, though it is still a majority, about 60%,” Balagtas said. “Given the fact that cell-cultured meat is not widely available, these results reflect consumer distrust of the unknown when it comes to food, which is a barrier for any novel food trying to break into the market.”

ARE CONSUMERS WILLING TO TRY EXOTIC OR CULTIVATED MEATS?

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How ai can bring more accuracy and speed to food and beverage development.

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Gary Iles is the senior vice president of marketing and business development at TraceGains .

In the food and beverage space, the companies that are most in tune with consumers’ demands—and the fastest to act on those demands—have a better chance of capturing the largest share of their markets.

Traditionally, creating new products (and tweaking the formulation of existing products) has been time-consuming, expensive and error-prone. First, research and development teams and marketers must extensively research trends and consumer demands, brainstorm ideas and get buy-in from executives. Then, food and beverage scientists must pinpoint the right blend of ingredients, concoct a prototype of the physical product, send the prototype to a lab for testing and wait for the results. One missed calculation at the formulation stage could put a company back at square one.

But moving forward, artificial intelligence can streamline that process. AI-driven product formulation and simulation stand to enhance companies’ ability to speedily bring new foods and beverages to market.

AI Can Help Companies With Market Research

Product formulation starts with market research. When companies understand what consumers want to see in their foods and drinks, they’re more likely to create products that people want to buy.

But traditional market research methods in the consumer packaged goods (CPG) space, namely, focus groups and surveys, require a lot of time and planning—and don’t necessarily produce accurate results. Why? It can be hard for people to know what kind of products they want, and that aside, they don’t always share their true thoughts. Still, focus groups, surveys and other traditional methods shouldn’t be done away with, as they can provide valuable insights and may be supplemented with artificial intelligence.

Artificial intelligence can help food and beverage companies better understand consumers’ preferences. AI can scrape online data, such as comments in online forums and on social media platforms, to give brands a snapshot of how consumers are talking about their products—and foods and beverages in general. From there, R&D and marketing teams can find commonalities between the data the AI brings to light and the data they get from focus groups and surveys.

The Role That AI Can Play In Food And Beverage Formulation

While market research is crucial, it’s only one part of the equation. Food and beverage companies first have to land on the right formulation. Then, any products they develop must undergo rigorous testing for safety and adherence to all applicable laws. This process can take weeks, and in the fast-paced market of today, every day counts.

AI can speed up food and beverage formulation by helping companies simulate products digitally rather than physically. Essentially, using AI, companies can make a digital twin for each new product, akin to how engineering companies leverage CAD software to model engines and other complex products before actually building them. For instance, say a company wants to develop a new plant-based protein bar. An AI tool can sift through the internet, examining different ingredient options and formulations, and then test multiple product concepts virtually. Rather than having to coordinate with a lab over the span of weeks to test products that might miss the mark formulation-wise, the company can get a relatively accurate picture of winning formulations—and then build only those products and send them for lab testing. AI won’t replace physical testing, but it can reduce the amount of physical testing new food and beverage products have to undergo for development, saving companies time and money.

Moreover, companies can use AI to comb through data from around the world to identify and vet the origins of ingredients and materials. With that knowledge, companies can more easily make sure they are working with well-understood, validated ingredients and materials.

Some food and beverage companies are already applying AI for formulation purposes. According to an article in Food Technology Magazine , a publication produced by the Institute of Food Technologists, “NotCo is wielding an AI-based platform it calls Giuseppe to help developers create plant-based versions of animal-based foods by analyzing products at the molecular level and providing alternative plant ingredients.” Another company, Spoonshot, is using AI “to leverage food science principles with data relating to the physical and chemical properties of ingredients and to understand how ingredient interactions impact a final recipe.” In the future, I predict that more food and beverage companies will leverage AI for product formulation purposes to meet consumers’ demands.

Food And Beverage Companies Will Still Have To Yield To The Realities Of Fragmented Global Supply Chains

Despite all the ways AI can help food and beverage companies streamline new product development, AI can only help to an extent. Brands will still have to yield to the realities of fragmented global supply chains, many of which use outdated processes and technology .

AI might tell a company that a certain ingredient is optimal, but the supply chains the company relies on may call that ingredient something else or may not have it at all. Even if the ingredient is available, it may be difficult or impossible for the company to obtain it due to costs and logistics.

When more supply chains update their technology and processes, food and beverage companies will be able to harness the full power of AI in product formulation—and stay ahead of the market.

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This Popular Artificial Sweetener Is Linked to Heart Attacks and Strokes, Research Shows

The sugar substitute is typically used in flavored waters, ice cream, and other low-calorie treats.

Korin Miller has spent nearly two decades covering food, health, and nutrition for digital, print, and TV platforms. Her work has appeared in Women's Health, SELF, Prevention, The Washington Post, and more.

Food & Wine / Getty Images

There are a lot of artificial sweeteners available for people who want to have less sugar in their diet, but one, in particular, has been getting a lot of attention lately — and not for a good reason. It’s called erythritol, and it’s been most recently linked to blood clots. 

New research published in the American Heart Association journal Arteriosclerosis, Thrombosis, and Vascular Biology analyzed data from two small groups of people — 10 who had a beverage with 30 grams of the artificial sweetener erythritol and 10 who had a drink with 30 grams of sugar after fasting overnight. Their blood was drawn before having the drink and 30 minutes later. The researchers discovered that people who had the erythritol drink had more than double the risk of developing blood clots than those in the sugar group. (Blood clots can form in blood vessels, which can then break off and travel up to the heart or brain, causing a heart attack or stroke.)

This isn’t the first time the safety of erythritol has been questioned. A 2023 study published in Nature Medicine linked the sweetener to a higher risk of stroke, heart attack, and death.  

It’s important to point out that the research isn’t conclusive, given that these studies are small. But the findings are definitely raising eyebrows. Here’s what you need to know about erythritol, plus what it’s commonly found in. 

What is erythritol?

Erythritol is a form of carbohydrate called a sugar alcohol, explains Keri Gans, R.D., author of The Small Change Diet . “It is a common replacement for table sugar,” she says. 

Erythritol, which is approximately 70% as sweet as sugar, per the National Institutes of Health, “is naturally found in small amounts in some fruits and fermented foods,” says Scott Keatley, R.D., co-founder of Keatley Medical Nutrition Therapy . “Unlike regular sugar, erythritol provides a sweet taste without contributing significantly to calories or impacting blood sugar levels,” he adds. 

Erythritol is classified by the U.S. Food and Drug Administration (FDA) as generally recognized as safe or GRAS, meaning it’s considered safe when it’s used as intended. 

What is erythritol in?

Erythritol is in a wide range of goods as a sugar substitute. “It is especially popular in low-calorie, sugar-free, keto, and diabetic-friendly products,” Keatley says. “Its main appeal lies in its ability to mimic the sweetness of sugar without the associated calories, making it a popular ingredient for those managing weight or blood sugar levels.”

It’s usually found in sugar-free varieties of ice cream, candy, cookies, cakes, gum, and fruit spreads, Gans says. “It is also commonly used in stevia and monk-fruit sugar alternatives,” she adds. 

These are some of the most common products you’ll find erythritol, per Keatley:

• Bai flavored waters
• Lily's Sweets, including sugar-free chocolate bars and baking chips
• Swerve Sweets low-carb and keto-friendly baking mixes
• DC24 daily care chewing gum
• Truvia sweetener 
• Swerve sweetener
• Halo Top ice cream
• Quest nutrition bars

How can you know if your food contains erythritol?

This involves some reading. “The FDA does not require a package’s Nutrition Facts Label to identify the specific type of sugar alcohol it contains,” Gans says. “However, it is required that the type of sugar alcohol be on the list of ingredients. “

Erythritol should be listed under its name, Keatley says. “It is not typically listed under any other name, making it relatively easy to spot,” he adds. 

While the latest findings on erythritol aren’t great, experts recommend putting them into perspective. “Everything — even food — has risks and rewards,” Keatley says. “A low/no-calorie sweetener is a game-changer for people who are with or at risk for diabetes, obesity, and PCOS.”

But, he says, “we see with this and other research like it that our body does react to these substances and we need to consume them in small amounts and with less frequency.” Most studies on erythritol look at 30 grams of the sweetener — which is a lot at once, Keatley points out. “But if someone were to have a couple of beverages, a baked good, and some ice cream sweetened with erythritol in the same day, the accumulation may be over 30 grams,” he says. 

Keatley agrees that it’s best to limit how much of the sweetener you have. “I do not think you need to avoid erythritol completely, but you should limit daily consumption,” she says. 

If you rely on artificial sweeteners for sweet foods, Keatley recommends that you “eat around.” 

“Having a little aspartame, sucralose, saccharin, stevia, and allulose means that you're not using the same pathways and are reducing your risk of side effects,” he says.    

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Harvesting at Soil Stewards Farm

Sandpoint Organic Agriculture Center

Harvesting at the Sandpoint Organic Agriculture Center

The Moscow Farmer’s Market

Office of Sustainability

via Office of the President

Physical Address: 851 Campus Dr. Moscow, ID 83844-3151

Phone: 208-310-5985

Email: [email protected]

What Vandals eat matters!

In 2020, food production and consumption accounted for 4.7% of our total emissions profile; this means that the food we ate emitted nearly as much carbon dioxide as the cars we drove to campus every day.

The 2022 Sustainable Solutions White Paper is proposing innovative ways to reduce our food waste and related carbon emissions, such as developing a donation program of non-spoiled food and creating a composting program to divert food waste from the landfill. Read the Sustainable Solutions White Paper .

Sustainability means not only addressing our emissions, but also supporting our community members who may not have easy access to healthy food. The University of Idaho has programs in place to help those experiencing food insecurity, such as the Vandal Food Pantry , the mobile food pantry and the Swipe Out Hunger program. Questions? Contact [email protected] or 208-885-6078.

Local Organic Agriculture

Soil stewards student farm.

The University of Idaho has its very own certified organic farm that produces sustainably grown produce. The Soil Stewards Farm provides students with the opportunity to learn and practice sustainable, small-acreage market garden production. Students who work on the farm gain valuable leadership skills and the scientific knowledge required to operate sustainable food production. The Soil Stewards Farm also gives Vandals affordable access to fresh organic food. Every Thursday from June to September, the farm sells its available produce. Community members can sign up for the CSA program, where customers can get a monthly subscription of fresh produce from the farm. Questions? Email [email protected] or visit the Soil Stewards Student Farm website .

Moscow Farmer’s Market

The Moscow Farmers Market takes place 8 a.m. to 1 p.m. every Saturday from May through October in downtown Moscow. The Farmers market is a great place to support local farmers and producers by stocking up on organic produce, meat, cheese, baked goods and other handmade products. Market shoppers can use their SNAP/EBT/WIC benefits or participate in the Double Up Food Bucks program. Read more about the market and its vendors.

Community Supported Agriculture (CSA)

• Soil Stewards Farm – University of Idaho
• Deep Roots Farm
• Hands and Hearts Farm
• Living Soil Microfarms
• Muddy Springs Farm
• Omache Farm
• Runner Bean Ranch
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Sandpoint Organic Ag Center

Located in Bonner County, the Sandpoint Organic Agriculture Center (SOAC) is the University of Idaho’s first USDA-Certified Organic program within the College of Agriculture and Life Sciences. The SOAC includes an organic fruit orchard, meeting facilities, dormitories for visiting faculty and students, a shop and a cider house. The SOAC provides a unique environment for students to experience hands-on learning on organic and sustainable crop production, pest management, soil health management, native plant landscapes, horticulture, organic food processing and marketing and food safety and nutrition. Learn more on the Sandpoint Organic Agriculture Center’s website .

Dairy Research

Did you know the state of Idaho is ranked as the third largest producer of dairy in the nation? The dairy industry is growing fast and is a major contributor to the health of Idaho’s economy. The University of Idaho is committed to providing expertise, resources and groundbreaking research to continue improving the sustainability and profitability of dairy for Idaho producers.

• U of I Dairy Center
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Idaho Eats Sustainability

Idaho Eats, the University of Idaho’s food service vendor, has its own sustainability commitments. 

Idaho Eats serves fair trade, USDA Organic and Rainforest certified coffee at multiple locations across campus. In addition, Idaho Eats partners with Moscow’s favorite, One World Coffee, which serves Landgrove Coffee, roasted locally in Troy, ID, with many varieties of beans, many of which are fair-trade, as well.

Sustainable, plant-based food like black bean burgers, plant-based meat and vegetable wraps are available throughout Idaho Eats dining locations. The Eatery, one of the dining centers on campus, offers a dedicated plant-based station that provides a variety of vegetarian and vegan meals for lunch and dinner using ingredients like lentils, garbanzo beans, tofu, roasted vegetables and more. Other plant-based eats are served in the Eatery and identified by the “Balanced U” icon system, specifically the vegetarian and vegan icons. The Eatery also offers an allergen-free station that serves food excluding the top 8 allergens.

Idaho Eats has partnered with the independent research company, HowGood, to understand the environmental and social impacts of the recipes we offer to the Vandal community. By leveraging these insights, we can identify and celebrate recipes that perform well based on HowGood’s eight standard metrics: greenhouse gas emissions, processing, water usage, biodiversity, animal welfare, soil health, land use and labor risk. High-performing recipes are highlighted in the Eatery’s digital menu screens with the “Best,” “Great,” and “Good” ratings. The icons inform Vandals of how sustainable their food is and support them in making dining decisions that are aligned with their values. 

• HowGood "Best" Rating – This recipe has an environmental and social impact better than 95% of food products.
• HowGood "Great" Rating – This recipe has an environmental and social impact better than 85% of food products.
• HowGood "Good" Rating – This recipe has an environmental and social impact better than 75% of food products.

Idaho Eats purchases from local enterprises from Fire House Ice, Idaho Ice, Moscow Co-op, Vandal Brand Meats, U of I’s Hydroponic Club and Moscow Rotary Club. Through Charlies Produce, Idaho eats purchases fruits and vegetables from the following local farms: Sunset Produce, Davidson Commodities, Northern Fruit Co. and Ostrom Mushroom Farms.

Explore the links below to see how Idaho Eats strives to provide sustainable food services to the Vandal community.

• Sustainability Commitments
• Dietary Accommodations
• Dietician Services
• Imperfectly Delicious Produce

Why Is This Important?

What we eat can have a large impact on the environment. According to a 2021 study by the Food and Agriculture Organization of the United Nations, the way we produce, process and package food accounts for more than one-third of global greenhouse gas emissions caused by human activity (see Crippa et al., 2021 in the Resources section below). Negative impacts of growing and processing food include pollution from the use of fertilizers and pesticides, methane emissions from livestock raising and rice cultivation, fluorinated emissions from refrigeration, carbon emissions from transportation and pollution and more carbon emissions from producing packaging for our food. There are also emissions from wasted food that is sent to the landfill and continues to emit greenhouse gases as it breaks down into organic material. Overall, the impacts of the food we eat are significant, but they can be reduced if we choose to eat food that is packaged responsibly, is produced closer to us and releases minimal emissions while being produced or grown. Eating responsibly can be good for the environment and also good for our health and economy.

In the U.S., not everyone has access to healthy, affordable food. Food insecurity, especially among college students, is a significant issue affecting every aspect of an individual’s life. In 2020, the UN estimated that between 720 and 811 million people went hungry, and high costs and low food affordability meant that billions could not eat healthily. As the global climate continues to warm and change, our food systems must be able to change with it and feed the billions of people who depend on it.

Ways You Can Help

At the University of Idaho, we believe all Vandals should have access to healthy, affordable food. You can help address food insecurity by donating to or volunteering with the Vandal Food Pantry and other local organizations.

Vandals can help reduce their food-related emissions by reducing their consumption of resource-intensive foods (see the resources below for more information). Vandals can also purchase products with minimal or plastic-free packaging and shop for local food produced at one of the many farms in the Palouse region.

If you would like to learn more about food, the following are great learning resources:

• Vandal food Pantry
• World Food Programme
• Food Systems & Hunger – World Food Programme
• Sustainable Livelihoods & Ecosystems – World Food Programme
• UN Sustainable Development Goal 2: Zero Hunger
• UN News: Food Systems & Greenhouse Gases
• The Environmental Impacts of Food Waste – US EPA
• Environmental Impacts of Food Production – Our World in Data
• Food and the Environment - FoodPrint
• Crippa et al., 2021 – Food systems are responsible for a third of global anthropogenic GHG emissions

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SEG grants fund summer internships, research projects

Summer Experience Grants

By | Kathy Hovis , A&S Communications

Hamid Rezaee ’26 spent this summer at Cornell Tech in New York City, working to refine a computer model that will help radiologists detect small cancer cells before they spread further in the body.

He was among the 119 students from the College of Arts & Sciences awarded Summer Experience Grants (SEG) this year. The grants help students pay for housing, food, transportation and other expenses while they undertake minimally-paid or unpaid summer internships or positions.

Rezaee, a computer science major, has spent the last two summers interning and conducting research in New York City, first with a startup aerospace company and now with a research team at Cornell Tech and Weill Cornell Medical Center.

“I’m well over 200 to 300 failed experiments at this point,” Rezaee said in July, quickly adding that that’s actually a good thing. “My task is to train this model to spot cancer cells using fMRI images of brain scans. And these can be as small as 4 pixels.”

He edits his model every day, “penalizing” the model if it makes a mistake, making refinements and then running the model every night. In the morning when he comes to campus, he discovers if it made fewer errors.

If all goes well, at the end of the summer or into the fall, the model will surpass other existing models for detection of the smallest cancer cells. And Rezaee will be included as an author on the paper that his supervisor, doctoral student Rachit Saluja (in Mert Sabuncu ’s lab at Cornell Tech), would write to introduce this new tool to researchers and radiologists.

“It would be amazing for me to contribute this to the medical community,” Rezaee said.

The experience wouldn’t be possible, he said, without the SEG grant, which helped provide funding for the metro, food and housing at St. John’s University.

“I wouldn’t have been able to accomplish any of this without the grant,” he said. 

Other students who used SEG funding to explore their futures this summer included:

• Isabella Riano ’25, who interned with a non-profit dedicated to helping immigrant children with legal representation
• Nika Makoviak ’25, who spent the summer in Los Angeles, working with actors and directors at the Stella Adler Academy of Acting
• Eva Farroha ’25 , who investigated an RNA binding protein complex at the National Institutes of Health (NIH) in Maryland
• Olivia D'Ambrosio ’26, who worked in Commonwealth Financial Network’s Anti Money Laundering team and special investigations unit
• Mnumzana Moyo ’26, who interned with Emzini weCode, helping high school students in Zimbabwe learn computer coding

Riano said the SEG funding took away the stress she was feeling about taking an unpaid internship in Manhattan and commuting from her family home on Long Island. “Going to the city is $20 one way and getting food and professional clothes…I wasn’t sure how I was going to finance everything,” she said. “The SEG grant allowed me to focus on my job without having a financial burden.”

Riano spent her days working with attorneys at Safe Passage Project and their clients, young children or teenagers facing deportation.

“A lot of them are unaccompanied minors (who) crossed the border, coming from a place of neglect, abuse and poverty or escaping gang violence,” she said. “They have suffered through trauma and violence and are taking the chance to come here for a better life.”

A government and American studies major with minors in Latino studies and migration, Riano plans to attend law school and has an interest in immigration law. She has worked with the Cornell Defender Program, a pre-professional program run by Cornell’s Office of Academic Diversity Initiatives for students interested in exploring family and criminal law. She also spent a semester studying in Australia, where she worked with a program helping people seeking asylum there. “I’ve learned to use this sadness in a healthy way – it inspires me and pushes me forward,” she said.

Riano said she’s been frustrated to learn it can take many years for child immigrants to receive employment papers and a green card. 

“I met 15 and 16-year-old girls from Honduras fleeing violence who talked about taking buses and cars and walking the whole way through Mexico and into the U.S.,” she said. 

Riano said she’s wanted to be a lawyer since middle school, but this summer work has helped her “better understand the kind of law I want to pursue.”

Makoviak, who is from Kyiv, Ukraine, said finding a summer internship as an international student is a complex process, requiring approval from several institutions.

“I knew I wanted to do something related to film/theatre production, so I wrote around 60 emails to different theatre and film production companies,” said Makoviak, who is studying government and performing and media arts. “SEG allowed me not only to cover my basic needs but make my dream real. When I saw that the Academy is located at Hollywood Boulevard, I got speechless.”

Makoviak worked as a production assistant under director Chris Thornton, on the play “Noises Off.”

 “Not only do I get to substitute actors at rehearsals (and practice my acting) but I also learn about set and prop design,” she said. “Most importantly, I learn a lot about directing and director-actor dynamics. Listening to Chris working with the actors is like being on a 3-4 hour lecture on directing.” 

Makoviak said the grant funding also allowed her to volunteer at short film festivals including LA Shorts and HollyShorts, where she met many passionate artists.

“This internship convinced me once more that it is crucial to follow your dreams,” she said.

Farroha, a biological sciences major with a concentration in computational biology who plans to attend medical school, worked in NIH’s National Heart, Lung, and Blood Institute last summer, so she chose to accept a position within the National Institute of Arthritis and Musculoskeletal and Skin Diseases branch this year.

“I saw similarities between my favorite course BIOMG 4400 and the lab's research interests,” she said. “I was hoping to use the skills I already had learned in class while also engaging in new techniques.”

The protein complex Farroha studied is responsible for the production of functional sperm and ovaries. When the complex is disrupted, she said, it results in infertility. 

 “My project was to see how mutations in DND1 at its RNA binding regions affect the functionality of the whole complex,” she said. “This involved using predictive AI software to determine intramolecular interactions, constructing 8 mutant cell lines and performing a variety of experiments.”

The summer experience heightened her interest in research as she moves toward medical school, Farroha said.

“Conducting a research project allowed me to engage in critical thinking and professionalism,” she said. “I also think research is super valuable for the presentation aspect, which directly translates to how important effective communication is in the doctor-patient relationship.”

D'Ambrosio, a government major, said her summer work offered the chance to work on a legal team while also  learning the intricacies of financial compliance.

“My role encompassed conducting due diligence reviews, managing regulatory responses and preparing detailed case reports,” she said. “I also conducted monitoring projects aimed at fraud prevention and analyzed transactional data to identify and address risk patterns impacting clients.”

For her capstone project, she collaborated with other interns, developing and presenting a new strategic initiative to the company’s board of partners.

“This experience has not only solidified my commitment to attending law school but has also strengthened my ambition to pursue a career that bridges finance and law, with a particular focus on financial compliance or corporate law,” she said.

The SEG funding was vital, she said, as the company is located in Boston, so housing and living expenses were steep. 

Moyo, a computer science major from Zimbabwe, said he never felt encouraged to pursue a tech career until he got to Cornell, “so volunteering at Emzini weCode was a chance for me to change that narrative for other youths in Zimbabwe so that they would be more informed about computer science when they get into college.”

Along with teaching students, Moyo conducted research aimed at enhancing the hands-on learning experience for first-time coders and created content and helped with administrative tasks for the organization.

“I found so much joy teaching students how to code,” he said. “I want to be involved in a career where I get to work with young people to help them realize their potential and reach for the power to express themselves through technology.”

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