The present study investigated how well self-report is reflected by cognitive-neurophysiological and actigraph measures, which we have previously shown to discriminate between ADHD persisters, remitters and controls using parent-report  frequency, event-related potential (ERP) and actigraph measures were obtained from 108 adolescents and young adults with childhood ADHD and 167 controls.Participants reported lower levels of ADHD symptoms and impairments than parents (p < 0.05) and the ADHD persistence rate based on self-report was low at 44%, compared to the persistence rate of 79% previously reported based on parent-report. Regression analyses showed that the objective measures distinguished poorly between ADHD persistent and remittent groups based on self-report, in contrast to findings based on parent-report , although the measures differentiated well between ADHD persisters and controls. Correlation analyses revealed that self-reported impairment significantly correlated with fewer of the objective measures, despite parent- and self-reported symptoms showing similar correlations with the measures.The findings show that self-reported ADHD outcome is not as well reflected by cognitive-neurophysiological and movement correlates as we previously found for parent-reported ADHD. ChildhoPrevious research suggests modest agreement between self- and parent-ratings of ADHD symptoms in adolescents and young adults (r = 0.16–0.30) . Young iOverall, existing research is limited, yet suggestive evidence is emerging that self-report of ADHD may have lower validity than parent-report. Population-based and clinical ADHD studies have found that self-reported ADHD symptoms show weaker associations with poor school achievement in adolescence  and majoWhile studies converge in suggesting that self-report of ADHD shows lower validity than parent-report, no studies have compared the validity of source informants using cognitive-neurophysiological and movement correlates of ADHD. Objective measures could be used to examine how well each informant report of ADHD is reflected by cognitive-neurophysiological and movement data.We previously reported findings from a prospective study that successfully discriminated between ADHD persistent, remittent and control groups on cognitive-electrophysiological and actigraph measures . The ADHWe now examine ADHD persistence and remittance based on self-report in young adulthood using the same sample as our previous study . The aimThe main aims of the present study are to examine (i) whether self- and parent-report of ADHD differ in severity; (ii) how well the objective data discriminate between ADHD persisters, remitters and controls based on self-report of ADHD using DSM-IV criteria and (iii) the pattern of correlations between self-reported ADHD symptoms and impairments and the objective data.Based on DSM-IV , individuals are diagnosed with ADHD if they display at least six symptoms in either the inattentive or hyperactive-impulsive domains, and experience symptoms and impairment in at least two settings. In the revised DSM-5 criteria, individuals aged 17 or older only require the presence of five symptoms and the presence of symptoms in at least two settings, rather than impairments from symptoms in two settings. Thus, we run additional analyses to investigate whether the objective data discriminate better between ADHD groups, based on self-report, using the revised DSM-5 criteria of displaying at least 5 ADHD symptoms.22.1The sample consists of 275 participants, followed-up on average 5.8 years (SD = 1.1) after initial assessments. At follow-up, participants were on average 18.0 years of age (age range: 11.1–25.9). 17 individuals were between 11 and 13 years, 79 individuals were between 14 and 16 years, 116 individuals were between 17 and 19 years and 63 individuals were 20 years and older. 108 participants had a diagnosis of DSM-IV combined type ADHD in childhood  and 167 were controls .Participants with ADHD were initially recruited from ADHD clinics in south-east England . DiagnosAt follow up, eight controls met ADHD criteria based on self- (n = 2) or parent- (n = 6) ratings on the Barkley Informant Rating Scale, and eight participants had missing self- or parent-ratings of impairments. These participants were excluded from analyses.2.2Participants were scheduled for a follow-up clinical interview and cognitive-electroencephalogram (EEG) assessments at the research center where initial assessments took place. A 48-h ADHD medication-free period was required. The total length of the test session, including breaks, was approximately 4 h.2.3The Diagnostic Interview for ADHD in adults (DIVA) is a semi-structured interview evaluating the DSM-IV criteria for adult and childhood ADHD symptoms and impairment  (e (BFIS) . This 10Participants were classified as ADHD persistent at follow-up based on DSM-IV criteria; if they scored ‘yes’ on ≥ 6 items in either the inattention or hyperactivity-impulsivity domains, and if they scored ≥2 on two or more areas of impairments.Barkley Informant Rating Scale  were administered to derive an IQ estimate  (61–0.79) .The Fast Task (ast Task . The basast Task .The cued flanker Continuous Performance Task (CPT-OX) ((CPT-OX) . This CP2.4EEG was recorded from 62 channels DC-coupled recording system (extended 10–20 montage), with a 500 Hz sampling-rate, impedances kept under 10 kΩ and FCz as the reference electrode. The electro-oculograms (EOGs) were recorded from electrodes above and below the left eye and at the outer canthi.The EEG data were analyzed using Brain Vision Analyzer (2.0) . After down-sampling the data to 256 Hz, the EEG data were re-referenced to the average and filtered offline with digitally band-pass  Butterworth filters. Ocular artifacts were identified using Independent Component Analysis (ICA) . The ext2.5The CNVs were analyzed as mean amplitudes 1300–1650ms following cues over the central electrode (Cz). The cue-P3 had a parietal maximum and was defined as the most positive peak 250–600ms following cue trials at electrode Pz. The nogo-P3 was defined as the most positive peak 250–600ms following no-go trials at electrode Cz.2.62) by computing the mean activity of electrodes  in the delta (0.5–3 Hz), theta (4–7 Hz), alpha (7–12 Hz) and beta (12–30 Hz) bands using the Fast Fourier Transform (FFT). We analyzed the frontal location only, to be consistent with our previous analyses  removed. We also re-ran the analyses using groups based on DSM-5 criteria of having five, rather than six, ADHD symptoms. Cohen's d effect sizes are presented with means, SDs and test statistics for the group analyses; 0.2 is considered a small effect, 0.5 a medium effect and 0.8 a large effect.We ran regression models with dummy variables to identify which measures showed an effect of group (ADHD persisters vs ADHD remitters vs controls), with controls as the reference group. Post-hoc Pearson correlations were conducted on the objective measures to examine their associations with DIVA ADHD symptom scores and clinical impairment, within those with childhood ADHD, with age and gender included as covariates.We ran additional analyses to investigate whether the combination of information from self- and parent-reports is better reflected by the objective measures compared to only using parent-report. We compared profiles of individuals with both self- and parent-reported ADHD (concordant group), individuals with only parent-reported ADHD (discordant group) and controls on the objective measures and reports of impairment. We did not examine individuals with only self-reported ADHD as this group of individuals was too small (n = 17).We re-ran all analyses covarying for IQ to examine its potential effects. All cognitive and EEG measures were skewed and log-transformed to normal in STATA version 10 . Genetic relatedness between the sibling pairs was controlled for by using the ‘robust cluster’ command in STATA.3Based on self-reports of symptoms and impairment, 44% of individuals with childhood ADHD continued to meet DSM-IV levels of ADHD and were classified as ADHD persisters. As reported previously , 79% of z = 0.31, p = 0.76).At follow up, based on self-report, ADHD persisters, remitters and controls did not differ in age, but there were significantly more males in the remitted group than the control group . The folAlmost half (47%) of the participants were under medication treatment for ADHD at the time of the follow-up assessment. The proportion of participants on medication at follow up did not differ between persistent and remittent groups based on either self-report  or parent-report .3.1The average number of self-reported inattentive symptoms  was significantly lower (t (107) = 6.85, p < 0.001) than the number of parent-reported symptoms . Self-reported hyperactive-impulsive symptoms  was significantly lower (t (107) = 3.54, p < 0.001) than parent-reported hyperactive-impulsive symptoms . Self-reported impairment was significantly lower (t (105) = 4.67, p < 0.001) for self-report  than parent-report . There was a significant correlation between self- and parent-reported ADHD symptoms , as well as impairments .3.2ADHD persistent-control group differences were observed on all measures except for EEG delta, theta and beta activity, and movement count (p > 0.05). After controlling for IQ, there were no longer significant ADHD persistent-control differences on DSF, RTV (from CPT-OX) and alpha activity . Control3.3ADHD remittent-control group differences were observed on the same measures that distinguished ADHD persisters from controls, except for cue-P3. After controlling for IQ, ADHD remittent-control group differences remained only for RTV (Fast Task), CE and OE, and the effect sizes were reduced .When we re-ran the analyses with females removed a significant ADHD remittent-control difference in EEG beta activity emerged, and there were no longer significant differences on CNV and DSF between remitters and controls (p > 0.05). The results did not change for the remaining variables.3.4A marker of remission refers to a measure that distinguishes ADHD remitters from persisters, but not from controls. In this study, ADHD persisters and remitters only significantly differed on RTV (Fast Task). However, as the measure also distinguished ADHD remitters from controls (p < 0.05) , it does3.5When ADHD status was based on self-reports using the DSM-5 symptom criterion of 5 rather than 6 symptoms, three individuals were re-classified as ADHD persisters, from being ADHD remitters according to DSM-IV. The group-based analyses based on DSM-5 criteria showed the same results as when groups were based on DSM-IV criteria, with the exceptions that significant ADHD remittent-control group differences emerged on the nogo-P3, intensity movement count and beta activity, and there was no longer a significant ADHD persistent-control group difference on nogo-P3 .When ADHD groups were based on parent-reports using the DSM-5 criterion, the same individuals were classified as ADHD persisters and remitters as when DSM-IV criteria were used.3.6Self-reported ADHD symptoms at follow up correlated significantly with RTV (CPT-OX & Fast Task), OE, delta, theta and alpha activity and movement count. Self-reported ADHD impairment correlated significantly only with RTV (Fast Task) and cue-P3 amplitude . After c3.7The concordant ADHD group (meeting ADHD criteria according to both informant reports) and discordant group (meeting ADHD criteria according to parent report only) both significantly differed from controls and not from each other on: IQ and twelve objective measures, including digit span (backward & forward), RTV (Fast Task & CPT-OX), CE, OE, No-go P3, CNV, alpha activity and movement intensity . The pat4Our follow-up study of 108 adolescents and young adults with a childhood ADHD diagnosis and 167 controls revealed that ADHD persistence and remittance based on self-report is poorly differentiated by the objective measures, as opposed to groups defined by parent-report . AlthougIndividuals with persistent ADHD showed significant impairments on nearly all objective measures, suggesting that ADHD persisters defined by self-report show similar profiles to ADHD persisters defined by parent-report. However, individuals who reported themselves as ADHD remittent showed similar profiles of underlying impairments as individuals who reported themselves as persistent. In contrast, when ADHD outcome was based on parent-reports , ADHD peThe analyses on continuous measures of ADHD symptoms revealed that self- and parent-reports showed similar patterns of associations with the objective measures, suggesting a quantitative difference between self- and parent-reported symptoms, as they differed in mean severity. Self-reported impairment correlated significantly with fewer objective measures than parent-reported impairment, suggesting a qualitative difference between the informants despite the moderately strong correlation  between them. This suggests that individuals evaluate their level of impairment based on other factors than their parents. Further investigations into self-reported impairment and its correlates would be beneficial in order to understand on what basis young individuals estimate their levels of impairment.It is important to acknowledge that there were notable discrepancies in results depending on which informant was used. The ADHD persistence rate based on self-reports was almost half the persistence rate based on parent-report. Furthermore, whereas several markers of remission were identified when ADHD status was based on parent-reports , no markTaken together with other research showing rater effects on ADHD prevalence rate at follow-up  and heriA limitation of this study is the wide age range of the sample. Although age was controlled for in the quantitative analyses and there were no significant group differences on age, it would be important to investigate the validity of self- vs parent-report using a narrower age group, in particular individuals in their transition into young adulthood. Furthermore, only cases diagnosed with ADHD combined type in childhood were included in the sample in order to reduce heterogeneity in the sample. Thus, findings may not generalize to other presentations of ADHD. Moreover, we acknowledge that the term ‘remitters’, when based on self-reports, does not necessarily reflect a group of individuals who have remitted from self-reported ADHD, as self-reports were not obtained in childhood. Furthermore, although we found that self-report of ADHD outcome was not well reflected by objective measures, it is possible that self-report is better captured by other measures not included in our study.In summary, this is the first study to suggest that self-report of ADHD outcome in adolescents and young adults is not as well reflected by cognitive-neurophysiological and movement data as parent-report. Our findings also demonstrate that there can be considerable inconsistencies in research findings based on the informant source used, which is important for researchers to acknowledge. For clinicians the findings suggest that during the follow-up of children with ADHD, care should be taken to continue to gather reports from multiple informants including parents.Ebba Du Rietz was involved in forming the research questions, executed the statistical analyses and wrote up the report. Dr Celeste Cheung contributed to the planning of the study design, collected the data and provided support during analysis and writing of the report. Professor Jonna Kuntsi played a key role in planning the study design and research questions, and provided input for interpretation of results and the write up of the report. Professor Philip Asherson also contributed with his input regarding the research questions, interpretation of results and writing of the report. Dr Grianne McLoughlin, Professor Daniel Brandeis and Professor Banaschewski contributed by giving input on data interpretation and on the writing of the report. All authors have approved the final article.This project was supported by generous grants from Action Medical Research and The Peter Sowerby Charitable Foundation (grant GN1777 to J Kuntsi). Initial cognitive assessments of the ADHD and control groups in childhood, and the recruitment of the control sample were supported by UK Medical Research Council grant G0300189 to J Kuntsi. Initial sample recruitment of the ADHD group was supported by NIMH grant R01MH062873 to SV Faraone. E Du Rietz is supported by a doctoral studentship from UK Medical Research Council. The funding sources had no involvement in decisions regarding study design, data collection, analysis, interpretation of data or in writing of the report.Professor Banaschewski has served as adviser or consultant for Bristol Myers-Squibb, Develco Pharma, Lilly, Medice, Novartis, Shire, and Vifor Pharma; he has received conference attendance support and conference support or speakers honoraria from Janssen McNeil, Lilly, Medice, Novartis, and Shire and has been involved in clinical trials conducted by Lilly and Shire. Professor Asherson has acted in an advisory role for Shire, Janssen-Cilag, Eli-Lilly and Flynn Pharma. He has received education or research grants from Shire, Janssen-Cilag and Eli-Lilly. He has given talks at educational events sponsored by the above companies. Ebba Du Rietz, Dr Celeste Cheung, Dr Grainne McLoughlin, Professor Dr Daniel Brandeis and Professor Jonna Kuntsi report no biomedical financial interests or potential conflicts of interest.


In the present investigation, a total of 42 polymorphic InDel markers were used for differentiating 188 rice landraces and two local varieties of Chhattisgarh, India into indica and japonica related genotypes based on ‘InDel molecular index’. Frequency of japonica alleles varied from 0.11 to 0.89 among landraces. Results revealed that 104 rice landraces have indica type genetic architecture along with three tested indica cultivars Swarna, Mahamaya and Rajeshwari. Another 60 landraces were placed under ‘close to indica’ type. It was found that three rice landraces i.e. Kalajeera, Kapri, Tulsimala were ‘close to japonica’ type and 21 landraces were ‘intermediate’ type. The result from the calculation of ‘InDel molecular index’ was further verified with STRUCTURE, AMOVA, PCA and cluster analysis. Population structure analysis revealed two genetically distinct populations within the 190 rice landraces/genotypes. Based on AMOVA, ‘intermediate’ type, ‘close to japonica’ type and Dongjinbyeo (a japonica cultivar from Republic of Korea) displayed significant genetic differentiation  from ‘indica’ and ‘close to indica’ groups. The PCA scatter plot and dendrogram demonstrated a clear pattern of two major group differentiations. ‘Close to japonica’ type and ‘intermediate’ type landraces/genotypes were grouped with Dongjinbyeo and formed a separate cluster at 30% Jaccard’s similarity level from rest of the landraces/genotypes which were ‘close to indica’ or ‘indica’ type. Such a significant genetic differentiation among the locally adapted landraces could be exploited for the development of rice varieties introgressing higher yield potential and better plant types of japonica type as per the need of consumers and rice traders.Rice has been cultivating and utilizing by humans for thousands of years under diverse environmental conditions. Therefore, tremendous genetic differentiation and diversity has occurred at various agro-ecosystems. The significant  Oryza sativa L.) is one of the most important food crops in the world and supports the requirement of staple food for almost half of the world’s population. It is cultivated in about 163.2 million ha of land and produced 751.9 million tons (in form of paddy) worldwide  and ΔK [b] against number of cluster (K) from the STRUCTURE simulation summary.(TIF)Click here for additional data file.S2 Fig(TIF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.


Two studies examined peoples' reasons for not monitoring their progress toward their personal goals—a phenomenon that has been termed “the ostrich problem” (Webb et al.,  For example, sometimes people avoid looking at their bank balance, do not weigh themselves, ask their boss for feedback on their work, or their partner whether they are happy in the relationship. People may not monitor their progress because they are busy or because so doing is not possible, but in some cases they may actually be motivated to avoid or ignore information about their goal progress—a phenomenon that has been referred to as “the ostrich problem” , avoiding information that suggests that progress is poor can guard against further decreases in commitment and prevent disengagement  the perceived accuracy and (b) value of the information that is available, (c) the difficulty of obtaining the information, d) the trade-off between the costs and benefits of monitoring progress, (e) the extent to which the person felt that they would be able to understand the information, (f) whether information on goal progress was deemed to be likely to have a negative impact on motivation and/or (g) demand unwanted action or (h) a change in beliefs. The questions also assessed: (i) affect associated with the target goal, (j) affect associated with progress toward the target goal, and (k) perceived control over goal attainment.Study 1 asked a relatively large sample of participants to think of an occasion when they avoided monitoring their goal progress and to indicate the extent to which each of the statements explained why they did so. Factor analysis was used to organize the reasons before we identified which were most strongly endorsed. Study 2 adopted a prospective design in which participants were offered the opportunity to obtain information about their progress toward a personal goal. However, before participants were offered this opportunity, they rated their beliefs about obtaining information on their goal progress by indicating the extent to which they agreed with each of the statements developed in Study 1. We then examined which beliefs best predicted whether or not participants eschewed the opportunity that they were offered to obtain information on their goal progress.N = 288 participants completed an online questionnaire in response to a request sent to a list of research volunteers at a large university in the UK. Participants were offered the chance to win a £50 Amazon voucher in return for their time. There were relatively equal numbers of males (52%) and females (48%) (1 participant preferred not to specify their gender). Participants were aged between 18 and 66 years .In Studies 1 and 2 participants were informed that they could withdraw from the study at any time by closing their browser, and that their responses would remain anonymous . Participants indicated that they agreed to take part in the study by selecting the “I agree” option on the introductory page of the questionnaire. All studies reported here were carried out in accordance with the British Psychological Society's Code of Human Research EthicsParticipants were asked to think of a situation in which they were at least somewhat uncertain about their progress toward a particular goal and where they did not pay much attention to information on their progress  or did not seek information on their progress when they could have . They were then asked to briefly describe: (a) the goal that this situation applied to and (b) how they did not pay much attention to information about their progress or did not seek information about their progress when they could have.Participants were then asked to think about the reasons why they did not monitor their progress toward the stated goal and to rate the extent to which 74 statements reflected these reasons on a 7-point scale anchored by “strongly disagree” and “strongly agree”. Table The goals that participants reported avoiding monitoring related to physical activities or health , money and finances , work or study , relationships and social goals , or other goals . The descriptions of 58 participants (20%) did not reflect situations where they did not pay attention to, or seek information on their progress  and so these participants were excluded from subsequent analyses.df = 2701, p < 0.001) indicated that the correlation matrix was appropriate for factor analysis , and Bartlett's test of sphericity  perceived behavioral control over goal attainment.Factor 4 had high loadings from statements reflecting the idea that “There were relatively few cross loadings (just six items loaded >0.30 on more than one factor) and all of the factors proved internally reliable . Scale scores were computed by averaging items loading on the relevant factorr = 0.17, minimum r = −0.29, maximum r = 0.55) supporting the discriminant validity of the factors. Only one correlation exceeded Cohen's (r > 0.50); this was between Factor 2: Information on goal progress was believed to be inaccurate and Factor 8: Information on goal progress was difficult to obtain and/or understand (r = 0.55). This correlation is intelligible as each of these factors represented the challenges of obtaining and interpreting information on goal progress. However, the correlation is not so high as to suggest that these factors measure the same construct .Table  Cohen's  criteriaF = 49.99, p < 0.001, eta2 = 0.68. Pairwise comparisons (with Bonferroni adjustment) were used to identify which reasons were differentially endorsed  or (b) undesired action . The next most strongly endorsed reasons for not monitoring were: (c) that progress was likely to be poor , and (d) that thinking about and/or working on the goal was associated with negative emotions .In order to investigate which reasons for not monitoring goal progress were most strongly endorsed by participants, we computed descriptive statistics . Participants also reported that feeling negatively about their goal and/or their progress toward that goal discouraged them from monitoring their progress. Reasons that were more cognitive  were less strongly endorsed, as were structural reasons for not monitoring . These findings provide an initial suggestion that the reasons people have for not monitoring may be more emotional, rather than practical in nature.The findings of Study 1, while informative, are based on participants' retrospective reports of why they did not monitor their progress. It may therefore be that participants more strongly endorsed emotional reasons for not monitoring their progress not because such reasons actually motivated their behavior, but because emotional reasons tend to command more attention  progress monitoring . We then investigated whether variations in the strength of these factors predicted: (a) whether participants accessed the progress calculator, and (b) the frequency with which they monitored their progress toward the goal of losing weight by self-weighing. For comparison with Study 1, we also examined the extent to which participants endorsed each of the reasons that might explain why they did not monitor their goal progress. Finally, we investigated whether participants who weighed themselves less frequently (and thus might be assumed to avoid monitoring their progress) endorsed these reasons to a greater extent than participants who weighed themselves more frequently.n = 134), and/or if they answered at least one of these test questions incorrectly (n = 64). This left n = 634 participants—451 females (73%), 166 males (27%), and 3 (< 1%) who identified their gender as “other.” Fourteen participants (2%) did not report their gender. Data on the age of two participants was excluded because they reported that their age was either 1 or 95. The remaining participants were aged between 18 and 66 years .An email was sent to a list of volunteers at a large university in the UK, inviting people who were currently trying to lose weight to complete a survey about their thoughts and feelings about so doing. Eight hundred and thirty-two people volunteered for the study and were offered the chance to win one of two £50 Amazon vouchers. Test questions (that instructed participants to select a particular response) were randomly placed in the survey to ensure the integrity of the data. Participants were excluded if they indicated that they were only thinking about losing weight but were not currently working on the goal . They also indicated how frequently they weighed themselves using a scale developed by Klos et al. : 1 = DaiNext, participants answered questions designed to assess each of the 10 reasons identified in Study 1 as reasons why people might not monitor their goal progress. Where possible, these questions were based on the 4 statements that had the highest loadings on each factor, but were adapted to refer to how participants currently thought or felt about their weight loss goal . For example, the statement “My progress was slower than I would have liked it to be” was rephrased to “My progress toward my weight loss goal is probably slower than I would like it to be.” These statements are presented in Table Following this, participants provided demographic information. They were then told that they had reached the end of the questionnaire, but that they had the option of using an online tool that could indicate whether they were on track to achieving their weight loss goal. Participants were told that, in order to calculate their progress, they would have to input their desired weight, current weight, the number of minutes of physical activity that they undertook each week, and what food they ate on an average day. Participants were informed that this would take around 10 minutes and that, based on this information, the calculator would assess whether they were on track to achieving their goal. Our primary dependent variable was whether participants accessed the progress calculatordf = 780, p < 0.001, suggesting that the data was suitable for analysis. Principal factor extraction with direct quartimin rotation was therefore performed through SPSS on the 40 items. Ten factors were extracted  = 459.68, p < 0.001, partial eta2 = 0.42. Pairwise comparisons (with Bonferroni adjustment) indicated that, overall, participants felt most strongly that: (a) information on goal progress would demand a change in beliefs . The next most strongly endorsed beliefs were that: (b) information would demand undesired action , (c) progress is poor , and (d) thinking about and/or working on the goal was associated with negative emotions . Participants less strongly endorsed the belief that discovering that their progress was poor would reduce their motivation and effort , that information about their progress was likely to be inaccurate , that information about their progress was difficult to obtain and/or understand , that the information was unlikely to be useful , or that they lacked control over goal attainment . Participants also did not believe that discovering that they were making good progress would reduce their motivation or effort .Table S.E. = 0.09 p = 0.04, odds ratio = 0.82], when they did not think that it would be useful to have information about their goal progress , or when they felt that they had more control over their weight loss .To examine which of the factors predicted whether participants' declined the opportunity to use the progress calculator, we conducted a logistic regression with avoidance of the progress calculator  as the dependent variable and the 10 factors as the predictors. The results of this analysis are presented in Table B = −0.21, t = 3.29, p = 0.001, C.I. = 0.09–0.34], but they weighed themselves more frequently when they felt that information about goal progress would demand undesired action . As with the progress calculator, participants weighed themselves less frequently when they did not feel that information about their goal progress would be useful , and felt that they had more control over their goal attainment .We also examined which of the factors predicted whether participants would weigh themselves as a means of assessing their progress toward their goal of losing weight , even when they would prefer not to make changes to these behaviors.Participants were less likely to weigh themselves or, to take the opportunity to monitor their progress if they felt that information about their progress was unlikely to be useful and if they felt greater control over their goal attainment. Finally, endorsing the belief that information about goal progress was likely to be inaccurate was associated with declining the opportunity to use the progress calculator, but was not associated with the frequency of self-weighing, perhaps because the information obtained from self-weighing is considered to be objectively accurate.Research suggests that there are a myriad of different reasons why people do not monitor their progress toward their personal goals. In order to identify the conceptual structure of such reasons and which reasons explain why people do not monitor their goal progress, we developed a set of statements that reflect possible reasons. We then asked two large samples of participants to indicate the extent to which each reason explained a recent instance in which they did not monitor their goal progress (Study 1) or reflected their beliefs about monitoring their progress toward their goal of losing weight (Study 2). Study 2 also provided participants with an opportunity to obtain information about their progress and examined which beliefs predicted whether they would decline that opportunity.Study 1 identified 10 reasons why people did not monitor their goal progress, including that thinking about and/or working on the goal was associated with negative emotions, that information on progress was not perceived to be useful, and that discovering that progress was poor would have reduced motivation and effort. Study 2 revealed that participants who were trying to lose weight avoided monitoring their progress toward this goal  when they felt that information on their progress was unlikely to be useful. This finding is consistent with previous research showing that people are more likely to seek information that they believe will help their goal progress . To overcome this limitation, Study 2 adopted a prospective design that allowed us to assess which factors predicted a behavioral and a self-report measure of the avoidance of monitoring. Our finding that some of the factors that best predicted why participants avoided monitoring—e.g., that information on progress monitoring was considered to be of little use, that participants felt in control of their goal attainment—were not always those that were most strongly endorsed as explanations for their lack of monitoring by the participants themselves, suggests that peoples' explanations of why they do not monitor their goal progress may not accurately reflect why they actually avoid monitoring their progress. Self-presentation concerns aside, it is possible that some people may not be aware of their actual reasons for avoiding monitoring. In support of this idea, Mintz et al.  found thAnother possible explanation for why the most strongly endorsed reasons for not monitoring in Study 1 did not predict the lack of monitoring in Study 2 may be that the a posteriori thought processes that were activated in Study 1, when participants were asked to explain why they avoided monitoring, are different to those that were invoked in Study 2, when participants were asked to consider whether they wanted information on their goal-progress in a specific situation. Specifically, the procedure of Study 1 may have led participants to focus on their motivations, while the procedure of Study 2 may have led participants to focus more on the quality of the information that was available on their progress and the current state of their goal pursuitThe correlational nature of Study 2 is also a limitation, and prevents us from drawing strong conclusions about the extent to which holding particular beliefs is causally related to people not monitoring their goal progress. However, the relationships we found are consistent with experimental research, such as that showing that the perceived usefulness of feedback influences whether or not it is accessed .The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Attention-deficit/hyperactivity disorder (ADHD) has been found to be comorbid with obesity in adults, but the association in children is uncertain. Because the underlying mechanism of comorbidity in children has not been researched sufficiently, this study aims to explore the associations among ADHD, abnormal eating, and body mass index (BMI), as well as the mediating effect of depression in children. We conducted a cross-sectional study of 785 primary students in China. The parent-report version of ADHD Rating Scale-IV (ADHDRS-IV), the Child Eating Behaviour Questionnaire (CEBQ) and the Children’s Eating Attitude Test (ChEAT) were used to identify ADHD symptoms and abnormal eating. The Child Behavior Checklist (CBCL) was applied to assess depression. Structural Equation Modeling was carried out to clarify the associations between ADHD symptoms, depression, abnormal eating, and overweight of students. We found that ADHD positively contributed to emotional eating and Bulimia Nervosa symptoms. However, neither emotional eating nor Bulimia Nervosa symptoms was related to BMI in children. We also found that ADHD significantly contributed to depression, and depression directly predicted emotional eating. In conclusion, ADHD increased the risk of abnormal eating in children, while no significant relationship existed between ADHD and BMI. Comorbid depression raised the risk of emotional eating, rather than Bulimia Nervosa symptoms. It has been suggested that individuals with ADHD may have an elevated risk for obesity, which comes from studies of adults and youth in both clinical and population-based settings6. However, when looking at a younger age in children, the comorbidity between ADHD and obesity has not been examined sufficiently, especially with the lack of data based on population. A study based on a small sample of clinical data confirmed that ADHD would increase the risk of obesity in boy ADHD patients7. Another study based on a national survey with 62887 children and adolescents aged 5 to 17 years suggested that children with ADHD had 1.5 times the odds of being overweight, after adjustment for age, gender, and other demographic information8. A recent meta-analysis study revealed that adolescents with ADHD only have 1.1 times of odds of being overweight9. In that national survey, a doctor-diagnosed ADHD was used to determine ADHD status, therefore, the finding is based on ADHD patients as well. Few studies have been done in children based on general population.Attention-deficit/hyperactivity disorder (ADHD) is a disorder of inattention, impulsivity, and hyperactivity that affects 8% to 12% of children worldwide10. A recent meta-analysis study demonstrated that there are significant overlapping neurobehavioral circuits in ADHD, eating disorder, and obesity in pediatric populations11. Research has mainly examined ADHD as a risk factor for obesity13. A prospective study indicated that inattention-hyperactivity symptoms at 8 years old were associated with indices of obesity at 16 years old, after adjustment for gender and baseline BMI, rather than the opposite14.Furthermore, the potential underlying mechanisms between ADHD, eating disorder, and obesity has not been examined sufficiently15. An updated meta-analysis study indicated that people with ADHD are 3.8 times more likely to present with any eating disorder as a comorbid diagnosis, and the risk increased to 5.7 times for Bulimia Nervosa16. Bulimia Nervosa is characterized by recurrent episodes of binge eating, and recurrent inappropriate compensatory behavior in order to prevent weight gain17. Community-based studies suggested that Bulimia Nervosa symptoms partially explained the associations between ADHD and obeisty19. In addition, emotional eating has been defined as eating in response to a range of negative emotions such as anxiety, depression, and loneliness to cope with negative affect emotional eating21. Emotional eating is highly correlated with other eating disorders, like Bulimia Nervosa symptoms, since both of them are related to emotion-focused coping, maladaptive coping strategies, and a strong aversion to negative feelings and stimuli24. It has been suggested that ADHD symptoms and impulsivity predicted both emotional eating and binge eating in adult women, and such abnormal eating behaviors were, in turn, positively associated with BMI25. Similar results have been replicated in males26. In addition, adult patients with Bulimia Nervosa and childhood ADHD were more impulsive than patients with Bulimia Nervosa alone, and these patients also displayed more severely disordered eating patterns27. ADHD inattention symptoms, depressive symptoms and trait-impulsivity in obese women patients highly predicted their binge eating behaviors28.With better insight into the potential mechanism of comorbidity, abnormal eating such as Bulimia Nervosa and especially impulsivity-induced eating, is considered to be an important mediator for the association between ADHD and obesity29. In another study, both boys and girls with ADHD displayed more Bulimia Nervosa symptoms than controls30. Conversely, an inconsistent outcome indicated that no significant differences in rates of Bulimia Nervosa symptoms were identified in children with ADHD when compared to the sex-matched control group31. This might be explained by the fact that full Bulimia Nervosa syndrome is not that common in the pediatric group.Considering the sample of children and adolescents, ADHD comorbidity of Bulimia Nervosa symptoms has been discussed in few studies, but the findings are confounding. A study suggested that childhood ADHD diagnosis predicted eating pathology in female adolescents32. However, to our knowledge, no study has examined the relationship between ADHD and emotional eating in children.It was said that children/adolescents with oppositional defiant disorder (ODD) symptoms showed increased eating in response to external cues, even though binge eating and ADHD symptoms were not associated with disordered eating behaviors in overweight and obese children/adolescents33. The study was carried out based on community mental health clinics, and the effect of binge eating was excluded from the model, so little is known about the mediating effect of abnormal eating on the association between ADHD and obesity. Therefore, the first purpose of this study is to clarify the relationships among ADHD, abnormal eating , and BMI in children at the population level.To date, the evidence regarding the relationships among ADHD, abnormal eating, and overweight is extremely limited in a sample of children. To our best knowledge, only 1 recent study showed that adolescents diagnosed with ADHD showed more binge eating problems, and after adjusting for binge eating, the relationship between ADHD and BMI z-scores was attenuated35. A review of studies in community samples has reported that the rate of depression in youth with ADHD is 5.5 times higher than in youths without ADHD, with rates ranging from 12% to 50%36. Children/adolescents with symptoms of depression showed emotional and binge eating37. Those with ADHD and comorbid depression had significantly increased risk for substance abuse and suicide compared to children with ADHD or depression alone37. Obese women with both of ADHD and eating disorders have higher rates of substance abuse; moreover, inattention symptoms combined with depression predict binge eating28. However, little is known about the role of depression between ADHD and eating problems, even though emotional eating and Bulimia Nervosa symptoms are highly correlated with mood. A preliminary study had explored the relationship among them, but the effect of depression was often excluded from the analysis models. For instance, in a clinical sample of severely obese adolescents aged 12 to 17 years, ADHD symptoms were significantly associated with Bulimia Nervosa symptoms after controlling for depressive symptoms38. Thus, the third purpose of this study is to identify the mediating effect of depression between ADHD and abnormal eating in children.Except for abnormal eating, ADHD is associated with a broader range of psychiatric comorbidity, e.g., depression is a common internalizing disorderP < 0.0001). The behaviors of emotional undereating in boys (mean = 9.2) was also slightly higher than girls . There were no gender differences in Bulimia Nervosa symptoms, emotional overeating behaviors, and depression. The results indicated that 98 children (12.9%) were considered obese and 150 children (19.7%) were considered overweight in the sample. There were more boys than girls in both the overweight and obesity classifications . Children in obesity/overweight group have a slightly higher ADHD score (mean = 14.3) than children in normal weight group . Children in obesity/overweight group have more Bulimia Nervosa symptoms (mean = 1.3) than normal weight group (mean = 1.1), but the difference is not statistically significant. Similarly, there are no significant differences in emotional overeating/undereating and depression symptoms within two groups.This study mixed a sample with different socioeconomic strata from China. Table P < 0.0001), emotional overeating , emotional undereating , and depression . Bulimia Nervosa symptoms was positively correlated with emotional overeating as well . Emotional undereating was positively correlated with depression . Emotional overeating is highly correlated with emotional undereating as well . No significant correlation was found between BMI and ADHD or abnormal eating.The results in Table β = 0.41, P < 0.001) and Bulimia Nervosa symptoms  in children. However, neither emotional eating  nor Bulimia Nervosa symptoms  was related to BMI. The proposed Model 1 represents an excellent fit to the data (GFI = 0.994). The details are provided in Table In Fig. β = 0.43, P < 0.001), rather than bulimia . ADHD significantly contributed to depression . It suggested that ADHD not only contributed to abnormal eating directly, but also had an effect on emotional eating through depression when two symptoms were comorbid. Similar to model 1, neither emotional eating  nor Bulimia Nervosa symptoms  was related to BMI. SEM model 2 also demonstrated a good fit to the data (GFI = 0.963). The loading factors for the 2 variables of emotional eating were 0.73 to 0.65.In Fig. 15. The current study indicated that ADHD symptoms in children contributed to their Bulimia Nervosa symptoms. Impulsivity might be the cause of ADHD comorbidity with Bulimia Nervosa symptoms, since impulsivity is considered to be a central symptom for both disorders30. Impulsive symptoms such as interrupting, intruding, and difficulty waiting one’s turn are part of the diagnostic criteria for the Combined Type of ADHD, which has been conceptualized as a problem of inhibition and impulse control. Impulsive personality traits are thought to be central to Bulimia Nervosa, and up to 40% of individuals with Bulimia Nervosa show multi-impulsivity symptoms in other life domains beyond eating, such as risky sexual behavior, stealing, and drug abuse39. Even though a study with a small sample of college students indicate that impulsivity hasn’t mediated the relationship between ADHD and binge eating disorder40, impulsivity has been shown to predict the onset of Bulimia Nervosa symptoms 9 months later, among adolescent girls in a community sample41. Therefore, impulsivity and lack of inhibition in children with ADHD may play a role in triggering Bulimia Nervosa42. Additionally, some genic feature might be the cause of the relationship. It had been suggested that the dopaminergic genes, especially the dopamine receptor D4 (DRD4), have been associated independently with both binge eating and ADHD43. Reward Deficiency Syndrome caused by abnormalities of dopaminergic genes could be a transdiagnostic feature between ADHD, eating disorder, and obesity45.Even though an eating disorder has been demonstrated to be an important mediating factor between ADHD and obesity in adults, the evidence is very limited in children46. A speculated mechanism is that the stress and negative emotion faced by children with ADHD increased the risk of emotional eating behaviors, because individuals engage in emotional eating only when they are experiencing negative emotions47. Emotional eating is associated with a range of emotional problems, such as low self-esteem, social anxiety, and feelings of inadequacy48. Children with ADHD often suffer from low social recognition, poor school achievement, and high accompaniment with mood disorders, which may contribute to emotional eating49. Meanwhile, those children probably perceive subjectively greater stress that may result in anxiolytic quality of eating50.In addition, a unique finding in the present study was that ADHD can predict emotional eating behaviors in children, including both emotional overeating and undereating. Some people eat less in the face of strong emotions, but some may turn to impulsive or binge eating to struggle with emotional distress. To our best knowledge, only 1 study examined the relationship between ADHD and emotional overeating, but no specific interpretation was discussed. A nationwide twin study suggests that children with ADHD show significant higher prevalence of restrictive eating behaviors than their counterparts, especially for girls51. Our present study clarified the mediating effect of depression between ADHD and eating behaviors. As expected, we found that depression mediated the relationship between ADHD and emotional eating in children, rather than ADHD and bulimia. Depression has long been documented as a significant comorbid condition of eating disorders among female adolescents52. It has been suggested that the presence of depressive symptoms and ADHD inattention symptoms can predict the present of binge eating in obese women28. Depressive symptoms would predict eating disorders in 13 to 18-year-old girls over a 4-year period, but not the reverse53. One finding in our study indicated that children with ADHD who are comorbid with depression would have an increased risk of emotional eating. To summarize shortly, the complex relationships between ADHD and eating disorder not just rely on single factors , but the interactions among these factors might interpret the associations. It has been suggested that not only ADHD neuropsychological functioning could alter information processing for food-related decision making, but also changes in nutritional or emotional state promoted by eating disorder could make ADHD individuals more prone to disinhibition16.Given emotional eating is closely related with emotional problems, ADHD is highly comorbid with emotional disorders, especially depression54. To date, only a few studies based on ADHD patients demonstrated that ADHD could increase the risk of obesity in children8 and none of these were carried out at the population level. The close relationship between ADHD and eating disorders in children potentially increase the risk of obesity when they are grown. Obesity has been found to be a long-term consequence of binge eating disorder in epidemiological studies55. Another interpretation is that the median age for the onset of an eating disorder is between 12 and 13 years of age56; this means children who are comorbid with ADHD and eating disorders might take a long time to become obese.Taking BMI into consideration, although the relationships between ADHD and eating disorders have been confirmed in this study, no significant relationship among ADHD, eating disorder and BMI was established in children. This finding is consistent with a previous study in which the diagnosis of ADHD was not associated with any of the obesity trajectories  in the general pediatric population (age ranged from 9 to 16 years)The current study is a cross-section design, so a longitudinal study is needed to explore the causality among ADHD, abnormal eating, and BMI, even though the method of SEM is suggested to be a good method to explore the causal relationship for cross-sectional data. ADHD was assessed with the parent-reported questionnaire, rather than an interview by a professional. In addition, except for abnormal eating and depression, multi-factors related to both ADHD and BMI should be taken into consideration to construct a SEM model, such as sleep problems and screen time.This study was approved by the medical ethics committee of Fudan University . The corresponding author confirms that this study was performed in accordance with the approved social experiment guidelines and regulations. Informed consent was obtained from legal parents of all participating students. A total of 785 primary students, aged 9 to 13 years , and their parents were recruited by stratified random sampling (from third grade to fifth grade) of 3 primary schools in Shanghai, China. Among the sample, 409 (52.1%) were boys  and 376 (47.9%) were girls .Both the student self-reported questionnaire and parent-filled questionnaire were used in this study. The 2 questionnaires were matched by student identification (ID). The specific assessment instruments covered in the 2 questionnaires were reported as follows:57. The ADHDRS-IV is an 18-item ADHD assessment scale, and it consisted of 2 subscales, inattention and hyperactivity-impulsivity, each containing 9 items. Each item was mapped onto 1 of the 18 Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV) symptoms of ADHD. Parents were required to rate the frequency of each of the ADHD symptoms, which occurred over the previous 6 months, on a 5-point Likert scale that ranged from 0 to 4 . The sum of all the scores on the18 items resulted in a total score that ranged from 0 to 54. The reliability and validity of the home version of ADHDRS-IV had been verified in a sample of Chinese children aged 6 to 17 years58. Cronbach’s alpha was 0.92 for the ADHDRS-IV in this sample.The parent-report version of the ADHD Rating Scale-IV (ADHDRS-IV) was used to assess ADHD symptomsEmotional eating59. It has been shown to have a robust factor structure and good internal reliability60. Two subscales involving emotional overeating and emotional undereating were used in our present study. Parents were asked to rate their child’s eating behavior on a 5-point Likert scale that ranged from 1 to 5 . Sample scale items included, for example, “My child eats less when s/he is angry; my child eats more when s/he is happy; my child eats more when worried; and my child eats more when annoyed.” Cronbach’s alpha was 0.86 for both subscales of emotional overeating and emotional undereating.The Child Eating Behaviour Questionnaire (CEBQ) is a parent-report questionnaire designed to assess variation in eating styles among childrenBulimia Nervosa symptomsTwo separate scales were used to assess abnormal eating behaviors:61. The psychometric properties and the application of ChEAT in different cultures have been certified in previous studies65. The ChEAT contained 26 items which were rated on a 6-point Likert scale that ranged from 0 to 3: always (3), very often (2), often (1), sometimes (0), rarely (0), and never (0). A subscale of Bulimia Nervosa was also used in this study. Sample scale items included, for example, “I have gone on eating binges where I feel that I might not be able to stop” and “I give too much time and thought to food.” The Cronbach’s alpha for the bulimia nervosa subscale was 0.67.The Children’s Eating Attitude Test (ChEAT), a modified version of the Eating Attitudes Test (EAT) is a self-reported questionnaire filled out by children themselves67. The subscale of depression contained 17 items. Sample scale items included, for example, “Deliberately harms self or attempts suicide; Cries a lot; and Worries.” Each item was rated on a 3-point Likert scale that ranged from 0 to 2 . The Cronbach’s alpha for the depression subscale was 0.75.The parent of each participant completed the Chinese version of the Child Behavior Checklist for ages 4 to 18 years (CBCL/4–18). The CBCL is a very common tool because its psychometric properties and Chinese version have been certified in previous studies2 [m2]) measured with the participant wearing indoor clothing and standing in stocking feet. The height and weight were measured by a healthcare provider in the school hospital. Specific age and gender BMI cut-off points were used to define overweight and obesity according to the International Obesity Task Force (IOTF) Body Mass Index Cut-Offs68.Body Mass Index (BMI) was calculated from height and weight  9.3 . Partial correlation analysis was used to examine the correlation between ADHD, abnormal eating, and depression. The relationship between ADHD symptoms, emotional eating, Bulimia Nervosa symptoms, and BMI was analyzed by using Structural Equation Modeling (SEM).


The term “landrace” has generally been defined as a cultivated, genetically heterogeneous variety that has evolved in a certain ecogeographical area and is therefore adapted to the edaphic and climatic conditions and to its traditional management and uses. Despite being considered by many to be inalterable, landraces have been and are in a constant state of evolution as a result of natural and artificial selection. Many landraces have disappeared from cultivation but are preserved in gene banks. Using modern selection and breeding technology tools to shape these preserved landraces together with the ones that are still cultivated is a further step in their evolution in order to preserve their agricultural significance. Adapting historical landraces to present agricultural conditions using cutting-edge breeding technology represents a challenging opportunity to use them in a modern sustainable agriculture, as an immediate return on the investment is highly unlikely. Consequently, we propose a more inclusive definition of landraces, namely that they consist of cultivated varieties that have evolved and may continue evolving, using conventional or modern breeding techniques, in traditional or new agricultural environments within a defined ecogeographical area and under the influence of the local human culture. This includes adaptation of landraces to new management systems and the unconscious or conscious selection made by farmers or breeders using available technology. In this respect, a mixed selection system might be established in which farmers and other social agents develop evolved landraces from the variability generated by public entities. As the environment changes annually and as the landrace becomes ‘contaminated’ with few genotypes of other landrace(s), or cultivar(s) it will continuously adapt itself” and “an allochthonous landrace is an autochthonous landrace of a foreign region recently introduced into the region concerned. This will be a rare type, as after its introduction it frequently becomes contaminated with a few genotypes of the autochthonous landraces or locally grown cultivar(s). Depending on the number of generations of after growth and on the frequency of seed change, it may become an autochthonous landrace.” Nevertheless, in his review Widely used in the literature, the term “landrace” encompasses a range of different concepts that have varied over time depending on prevailing trends in the use and conservation of genetic resources. After an initial period in which it was considered important to conserve landraces to maintain biodiversity, nowadays there is an increasingly promoted commercial message that holds that landraces are generally endowed with superior nutritional and sensory properties (“a flavor of the past” belief), and this has influenced the concept of landrace. For many years after More recent approaches to the concept of landrace again incorporate elements related to the mechanics of its evolution. Finally, in an excellent review, in situ conservation.Zeven points out that landraces are continually evolving and also continually mixing with other landraces or cultivars on a genetic level. Natural and artificial selection together with migration resulting from the exchange of seeds can contribute to creating different landraces (populations), as well as groups of interrelated landraces (which could be considered as metapopulations). Therefore, landraces should be viewed as evolving entities in contrast to modern cultivars, which are expected to be maintained true to type according to Union for the Protection of New Varieties of Plants (UPOV) rules. In this respect, We propose a more inclusive definition of landraces as plant materials consisting of cultivated varieties that have evolved and may continue evolving, using conventional or modern breeding techniques, in traditional or new agricultural environments within a defined ecogeographical area and under the influence of local human culture. This includes adaptation of landraces to the management systems and the unconscious or conscious selection made by farmers or breeders with available technology. This coevolution has been modeling landraces as a result of several factors: the initial genetic variation; the generation of new variation through mutation, migration, recombination, and crossing with other populations; the soil, climate, and other ecological conditions of the region of cultivation; and the influence of humans, which includes cultivation techniques (evolving over time) and preferences . This definition emphasizes the role of humans in the evolution of landraces because human intervention has been a key factor (in fact humans and cultivated plants have constituted a symbiotic system since the Neolithic period).As a consequence of this coevolution, populations that have not undergone organized genetic improvement meet It is an undeniable fact that genetically improved varieties have become predominant throughout most of the world. This predominance has been made possible by high energy inputs in crop production  and heavy investment in research and genetic improvement. To the extent that these factors molded similar environments, the same or only slightly different varieties could be cultivated in more places. With the loss of farmer specialization in propagating their landraces, professional breeders can obtain returns on investments from developing new varieties. Legislation on protection of cultivars and seed trade also favor improved cultivars by demanding homogeneous materials for each variety commercialized. However, the main reason for genetic erosion is the inability of unimproved landraces to compete against improved varieties. Cultivated germplasm has evolved since Neolithic times, so it should not surprise us that this has continued into the modern times; and in some cases it has sped up dramatically as in the development of improved varieties for widespread use.Nevertheless, these improved varieties have drawbacks: (a) cultural ties with consumers are weak or non-existent , (b) growing them requires large investments in energy (the extreme case being high-tech greenhouses), and (c) methods of distribution  can lower sensorial quality. On the other hand, materials that meet the narrow definition of landraces also suffer from serious drawbacks such as low yields and vulnerability to new pests introduced in new areas as a consequence of globalization.Given our society’s growing concern for the environment  and growing interest in identity issues , the ecological aspects of traditional varieties (aspects related to the milieu) can represent values appreciated by consumers and therefore be used as tools for development and progress by farmers. Thus, there is a need for a less orthodox conceptualization of landraces, one that is based on values that continue to be interesting in modern societies, such as adaptation to the environment, need of reduced inputs, cultural values, and diversity as a consequence of local adaptation, etc.Our proposal aims to modify the concept of landrace delineated by Given that adaptability to particular environments, general resilience, cultural value, tolerance to local stresses, sensorial value, etc. are traits often controlled by multiple genes, the most reasonable material for initial development of new generations of local cultivars consists of historical landraces, found in seed banks or under local cultivation.Our proposal involves extending the concept of landraces beyond their currently recognized value as a reservoir of genes. We propose to use these materials, study their potential, and correct their defects with available technology. The first wave of transformations that candidate landraces might undergo are the introduction of monogenic traits, such as resistance to pathogens, although this might create a “boom and bust” phenomenon. Globalization has allowed pests and pathogens to circulate freely, so farmers cultivating historical landraces often have to apply many phytosanitary treatments or risk losing their entire crop, making it impossible to meet the goals of keeping inputs to a minimum and using minimally aggressive agricultural practices. Problems related to traditional methods, such as linkage drag in backcrossing (introducing undesirable genes linked to the gene introduced mainly when the donor is a wild plant), can be overcome by biotechnological approaches available today  and otheOn a small scale, and still fundamentally through backcrossing or classical selection, new cultivars have already been obtained from landraces. In Spain, for example, with this aim of local and cultural adaptation, new improved materials have been developed from landraces in tomatoes , beans , onions In this new view, intravarietal heterogeneity can be replaced by a large number of landraces with different traits that fit in together with the different environmental characteristics encompassed in the local cultural sphere. For example, different landraces with similar sensory profiles and yields, adapted to the needs of local cuisine, but with different degrees of earliness to allow scaled sowing or to allow for yearly variations in the weather, especially in moisture content of the soil for sowing, might be developed. Thus, we could even consider using landrace hybrids, whether between two landraces or between a landrace and a single inbred line.Figure 1).Before the advent of scientific breeding techniques, landraces evolved together with the farmers that managed them within their cultures  in the soil and climatic conditions in which the evolutionary process occurred. Large-scale breeding and better control over environmental factors, together with the availability of vast amounts of energy and global food distribution systems, have transformed landraces into new types which generally can be classified in different categories: (a) generalized, universally embraced, commercial cultivars of extremely homogeneous materials that are no longer bound to a particular local culture, which are managed by breeding corporations, (b) cultivars that we continue to refer to as landraces, which include a blend of “unselected” varieties that have continued to evolve “on farm,” but that are usually heavily introgressed from genetically improved varieties or other “landraces” with which they have been crossed, (c) “unselected” landraces, which in some cases have remained more or less free of introgression, in which evolution has been suspended by conservative selection (heirlooms or vintage varieties in the strictest sense), and (d) varieties that maintain their character as garden varieties, easily confused with the “landraces” described in (b). Thus, the evolution of landraces can take different paths, some of which lead to products that conserve the spirit of landraces before the advent of scientific selection , we need to manage this coevolution. This task cannot be relegated to farmers dedicated to cultivating landraces with traditional techniques in relatively isolated sites. This unrealistic vision is rooted in a conservative ideology that does not take evolution into account. We need to design participative strategies in which, just as society has moved toward a division of labor with increasing specialization, various social agents participate in the evolution of the landraces. The burden of this task cannot be placed only on farmers, because farmers have also become specialists with their own niche in our knowledge-based societies that tend to distribute responsibilities among various agents. In this respect, participatory plant breeding (PPB), preferably implemented through public-private partnerships (PPP), could play an important role in the evolution of landraces in order to respond to the challenges and demands of the different stakeholders in the marketing chain going from producer to consumer.in situ or ex situ. It is important to identify varieties with traits that have added value in today’s society , recognizing that the adaptation to the local environment is already the defining characteristic of these materials . Territories without local varieties should be able to seek out landraces from other territories that would become allochthonous according to The first step in managing the evolution of landraces should be filtering by the local cultures and societies that are the depositories of these materials. These societies should evaluate the plant genetic resources linked to their histories that are extant Figure 2). This merely means using cultivation techniques that seem most reasonable and accepted by a given society. Nowadays in advanced Western societies, this means low-input agriculture, with minimal agrochemical intervention. In the future, other approaches might be considered more rational. Based on this assessment, technology centers and experimental stations should be put in charge of characterizing the materials and determining their commercial potential in close collaboration with farmers, who need to be involved in these processes.The second step is to evaluate the landraces’ potential, considering rational cultivation techniques used in a certain place and time . In our opinion it is essential to take full advantage of all available tools from classic breeding and biotechnology. As stated above, landraces should be defined by their essence, not by the methods used to obtain them. This approach requires the intervention of institutions that generate unselected materials, introducing variability for the traits that need to be modified. Again, farmers must serve as the final filter for a large number of new candidate varieties that technological centers and experimental stations can provide.The third step is to correct the varieties’ weaknesses without undermining their strengths . Dealing with this point requires imagination and generosity. Registries of conservation varieties represent an attempt to provide a legal framework for these materials, but further developments are needed to take into account the inherent heterogeneity of landraces.One last point that must be resolved is the ownership of the landraces, their certification, and their maintenance until they are replaced by newly evolved types  (The review of FC and JP conceived the project and supervised the manuscript. FC, JS, JC, and JP drafted the manuscript and contributed to discussions. JS and JC designed and drew the figures.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


This qualitative study explored siblings’ perceptions of the impact a sibling diagnosed with ADHD has within the family system. Specific focus was placed on the different ways these different sibling cohorts were parented. Participants constituted eight adult females with a mean age of 20 years from different cultural and socio-economic backgrounds in the province of Gauteng, South Africa. Data was collected using semi-structured interviews and was analysed thematically. The four themes that emerged from the interviews include differential parental treatment, rejection, discrepancy with discipline, and the parentified child. Specifically, the results of this study revealed feelings of differential parental treatment and discipline that took place in the home and rejection experienced by the non-ADHD sibling. There was also a common theme of a parentified child, who had to carry a burden of caring for their sibling with ADHD. The non-diagnosed siblings perceive themselves to be particularly negatively impacted. The results are discussed in light of the previous empirical studies, and recommendations are made. Attention deficit hyperactivity disorder (ADHD) is one of the most common and challenging childhood neurobehavioral disorders globally. ADHD is known to negatively impact children, their families, and the community ,2. A larHaving taken the above research into account, the authors of this study aimed at paying particular attention to the non-ADHD sibling in the hopes of promoting positive outcomes for the development and relationships of these individuals and their families.Although the impacts of ADHD behaviours have been widely reported from the perspectives of children and adolescents diagnosed with ADHD, educators, and from parents’ perspectives ,11,12,13It is, however, acknowledged that there are few studies conducted from Euro-Western countries which explore the perspectives of siblings living with children diagnosed with ADHD. The relationships between the siblings may be affected when there is a child with ADHD. Indeed, an earlier study  investigGiven the paucity of research on how a child with ADHD may affect the family ecosystem , it is crucial to explore the perceptions of the siblings living with children diagnosed with ADHD in order to understand the impact of their siblings’ behaviours and how it can be managed. It is believed that the more research is conducted on siblings’ perceptions, the more awareness it will generate, and will thus encourage more support from organizations and other social spheres. Relationships between siblings and other members of the family may be negatively affected, particularly when there is a child with ADHD. Siblings of ADHD children have reported feeling ill-treated through violent and aggressive behaviours, and manipulation. For instance, jealousy is often experienced by siblings because of the amount of attention given to the ADHD child by their parents .In another study, Mikami and Pfiffner  exploredIt is imperative that the African context be explored, given that the majority of the countries in Africa experience a low human development index . Therefo(1)What is the experience of a sibling living with a sibling diagnosed with a mental disorder such as ADHD?(2)What are the participants’ perceptions of the relationship they have with the caregiver(s) and the sibling diagnosed with ADHD?(3)What did the participants observe regarding parenting in the home while living with a sibling with ADHD?The main research question that drove the study was “what are the perceptions of non-ADHD siblings of the impact of a sibling diagnosed with ADHD on the family system?” This question was unpacked with the following sub-questions:This study applied a qualitative method of investigation. Given the nature of the study, a phenomenological research design was deemed appropriate, as participants’ lived experiences were essential ,23.The participants were accessed through convenience sampling. Snowball sampling was also used to access additional participants known through word of mouth. Criteria for participation in the study included individuals in early adulthood (between the ages of 18 and 30), with a reasonable degree of fluency in English. The participant’s age was imperative, as the researchers required a comprehensive and in-depth response to the possible sensitive nature of the topics raised. The quality of the data was therefore determined to a large extent by the participant’s ability to accurately recall past exposures. In order to prevent recall bias, participants were blinded to the study hypothesis. Additionally, a requirement was that all the participants had to have resided with a sibling who was diagnosed with ADHD, as well as a caregiver or parent in the same household. The participants were not reimbursed for participating in the study. They were met on university campus at a time and place of their convenience. No formal testing took place to screen the participants for ADHD themselves. The authors relied on the feedback received from the participants, and they acknowledge that while the possibility exists that the participants may have had ADHD symptoms, this is unlikely to have been the case. Furthermore, participants were required to disclose any concerns they had regarding their own behaviour in terms of ADHD.n = 5), while the least number of participants,  were within the older age range of 20–29 years. The overall mean age of the sample was 20 years. The participants in the current study comprised eight females between 18 and 30 years old. While attempts were made to gather perspectives of the male sibling, the research was not successful in this regard. The majority of the participants were aged 18 years  (Project Identification Code: MACC/14/002 IH). Permission was also sought from the Heads of the School from the Faculty of Humanities. A message regarding the study was then sent out to the first year psychology students. All participants were briefed of their rights to confidentiality: that they could choose to participate or not to participate in the study, and would not be disadvantaged in any way. Permission to audio-record the interview was also granted by the participants. They were informed that their anonymity would be ensured in the reporting of the results.(1)Can you tell me what the relationships were like within your family system?(2)How did you perceive your caregiver/parent response to the diagnosis of your ADHD sibling?(3)Can you tell me what your role was as a sibling, after the diagnosis of your ADHD sibling?A semi-structured interview was used for the data collection. Open-ended questions were posed to the participants, some of them being:This study was premised on the assumption that the experiences of the non-ADHD siblings could best be understood through interaction . The intRecorded interviews were transcribed verbatim, and a thematic analysis was conducted to analyse the qualitative data gained from the semi-structured interviews ,23. ThemThe results of the present study are presented concurrently with the discussion. The following themes that relate to the non-ADHD sibling’s perceptions of the impact a sibling diagnosed with ADHD has on the family system emerged from the data; namely, differential parental treatment that took place in the home, rejection faced by the non-ADHD sibling, a discrepancy in terms of discipline, and the phenomenon of the parentified child.got more attention”. In addition, resources were provided for their sibling but not for them, despite the fact that they, too, needed extra help. Some of the excerpts indicated that:He got more attention.”“He always got more attention because he wanted more attention.”“Everything revolved around my brother and it almost was like it had to go his way.”“My needs would always be ignored.”“There were times when we were shopping for stuff for me and if my brother got tired or bored they would have to go home. This made me feel jealous in a way and cheated out of a lot of things because he had ADHD and I didn’t. It was unfair to me.”“It emerged from the analysis that there was differential parental treatment in the forms of attention provided to children and inconsistent disciplinary methods at home. The results of the present study demonstrated within the non-ADHD siblings feelings of not getting adequate attention and that their sibling with ADHD “had four different tutors, one for each subject”. Participant 4 reported that her parents “would brush off” what she needed, yet they would do everything for her sister. This in turn affected the relationship between the non-ADHD sibling and the parent(s).Participant 2 felt that she could have benefitted from additional support such as a tutor, but her parents insisted she did the work on her own. However, her brother “The tendency for parents to inadvertently give more attention to the diagnosed child is consistent with previous studies. Research has revealed reduced parental attention paid to the child without ADHD ,26. Simia little sad and a bit angry”. Participant 6 stated that she “felt a bit bitter” towards her parents for always defending the brother and taking his side. She said that she developed this attitude:Just go help your son; he needs you more than me.”“The results revealed a consistent theme of rejection resulting from the lack of or absence of attention from the parents because their siblings with ADHD needed the assistance and support, for they were the ones with the disorder. For instance, Participant 8 expressed that when all the attention was on her sister and she was not considered, it made her feel “Because of my addictive personality I became very addicted. I think it is because of all the rejection I felt from my mom.”“Participant 7 reported that her feelings of rejection were so severe that she started to abuse drugs and alcohol in order to fill the void in her life:I would just go and hide and cry and stuff. I remember there was this one little cupboard on the floor in my mom’s room that did not have anything in it. This used to be my crying spot. So I would just go and retreat in there.”“In addition to this, Participant 6 stated that she remembered that:These findings are consistent with previous studies conducted in developed Euro-Western countries. Research indicates that while siblings are likely to vary from one to another, the perception of the absence of parental attention is commonly experienced ,25,26. They are more lenient with her and when she performs or has a tantrum because they are disciplining her, they just take away the discipline and the threats.”“They just take away the discipline.”“…when you punish her you take away again the punishment (sic) whereas with us when we are punished, we are punished. There is no going back.”“They make excuses for the naughty behaviour.”“When I was in Grade 1, I had to do a minimum of an hour of homework every day and even if I did not have homework to do my parents made stuff for me to complete. My brother, on the other hand, would finish only half of the required work and when he did not want to do anymore mom or dad would do the rest for him.”“One of the main concerns that were expressed by several of the participants in the current study was the fact that the ADHD child would receive few consequences for bad behaviour when it came to homework and chores. Participants reported that their sibling with ADHD could do things that they were never allowed to do when they were young, purely as a result of the ADHD diagnosis. For example:Many of the participants expressed that they would speak to their parents about the discrepancy in the way in which they were disciplined and would mention that they could see that there was a significant difference in the way in which they were being treated. However, the parents would often create an excuse or try and justify their own behaviour. This resulted in an angry, irritated, and often frustrated sibling. These results seem to mirror those which demonstrated that the siblings of ADHD children feel victimized and unnoticed by the parents . The parIt can then be said that the effects the participants felt negatively impacted the parent-child relationship and altered the child’s perceptions towards the caregiver that was instilling authority. Furthermore, this hindered the non-ADHD individual’s development, as the relationships within different parts of the microsystems were not working together for the good of the child.I took on the motherly role and disciplined my brother. I was always the disciplinarian with him, even now.”“I was the one who took care of things. I was the one who gave her medicine.”“At first I was a little bit annoyed and irritated about it because now I had more responsibility, making sure that she is taking her tablets and stuff like that. And I also helped him with his homework and stuff so, whenever we had to do the homework and helping out with stuff it just took hours.”“I had an obligation to look after my ADHD sibling and do what the parent could not. I had to take her to her room and take care of her in order to protect her sister from the violence in the home.”“The last theme that emerged from the analyses involved the parentified child. Most of the non-ADHD siblings reported that their parents expected them to play with and supervise their siblings with ADHD. Amongst the caretaking activities were giving medication and helping with homework, as illustrated by the following excerpts:Based on the excerpts above, it can be seen how participants in the current study were involuntarily made to assume the responsibilities of their caregivers by taking care of their siblings diagnosed with ADHD. Earley and Cushway  define pWith this being said, it goes against the pivotal point that Bronfenbrenner  so clearLike any other study, it is important to acknowledge the limitations of this study. Obtaining information across ecological levels is logistically complex , and wasHowever, the fact that this current study focused on sibling’s perceptions of living in a home with an ADHD sibling, within a South African context, suggests that this study is highly relevant due to the high prevalence of children diagnosed with ADHD in South Africa . The resFurthermore, it is recommended that a larger study with participants from different socio-economic backgrounds be conducted. The fact that the participants are from middle to upper social-economic background may limit generalisation of the results to the population of South Africa. Nonetheless, they are still applicable to the upper-class population.Another major limitation to this study is the fact that only females were interviewed. While the authors did try and include males, two of the participants interested had ADHD and had to be excluded from the study. The female participants that did take part in this study may have viewed their roles quite differently from a male subject. Thus, one has to be cautious when interpreting the results and making sweeping statements or generalisations. Additionally, it is recommended that increased support be offered to family members who have a child that is diagnosed with ADHD. This might be in the form of classes, support groups, and information booklets. This is due to the fact that once a child is diagnosed with ADHD, it is not only the child that needs treatment, but the whole family should receive counselling and education on issues such as those raised in this study. This may include parenting skills appropriate to the situation and inculcating an awareness in the parents of possible effects on the ADHD child’s siblings. The findings of the research therefore signify that the ADHD sibling does indeed have an impact on the family system, and these impacts are consistent with those reported in the literature. The four themes that emerged from the interviews—namely, differential parental treatment, rejection, discrepancy with discipline, and the parentified child—confirmed that the non-ADHD siblings perceived a difference in the way in which they were treated by their parents, compared to their ADHD sibling. Additionally, it was evident from the way in which the participants articulated their concerns that they perceived themselves to be a hindrance to their parents, because their ADHD siblings needed the assistance and support, as they were the ones with the disorder. The perception was thus rejection. Furthermore, in terms of discipline, all the participants felt that there was a discrepancy, as the ADHD sibling faced fewer consequences and punishment.The non-ADHD siblings reported that they felt they had a particular role to play in terms of caring for their sibling with ADHD, and many felt it was their responsibility to ensure that their sibling was attended to. However, despite the challenges that these participants faced, most of them found a way to deal with their sibling with ADHD and accommodate their needs.