As part of a process evaluation, we explored in semi-structured interviews theexperiences of 19 mothers who had taken part in a trial to reduce infantformula-milk intake and promote healthy weight gain, and reflections of threefacilitators who delivered the intervention and control group protocols. Mothersappreciated the nonjudgmental support provided during the trial, afterexperiencing stigma and receiving limited advice on how, how much, and how oftenformula-milk should be given. The information mothers had previously found,printed on formula-milk tins, or provided by family, friends, and healthprofessionals was often perceived as contradictory; the trial guidance alsoconflicted with social norms relating infant health positively with weight gain.For those recruited into the trial with older infants, who had already exceededthe recommendations, reducing formula-milk amounts was difficult. The findingshighlight the difficulties of addressing a highly stigmatized, complex socialpractice with an individual, behavioral intervention approach. Childhood obesity is a major public health challenge . EffortsBaby-Milk Trial aimed to evaluate the efficacy, cost-effectiveness,and acceptability of a theory-based, multicomponent behavioral intervention to reduceformula-milk intake based on the new WHO recommendations and prevent excess weight gainduring infancy ,the analysis was theoretically guided by social practice theories that aim tounderstand in what way everyday practices such as infant feeding are sociallyshared and shaped through time and space .Ten mothers from the intervention arm of the trial, and nine from the controlgroup, as well as three of the four female facilitators (research nurses) tookpart in this qualitative study. It seemed important to understand theexperiences of the women who got explicit guidance on healthy strategies forformula-feeding in the intervention arm, as well as of those mothers in theattention control group who received the same amount of contacts but onlygeneral guidance such as sterilizing bottles, feed preparation, and types offormula-milk. Mothers were recruited from the last wave of families that hadjust completed the trial protocol from an eligible pool of 58 trialparticipants, of whom 43 were contacted  and invited to thisqualitative study, and of whom 19 took part (44% response rate). Theparticipants had been initially recruited to the trial if identified asformula-feeding by research staff or health professionals . Our stuBetween July and October 2015, 22 semi-structured interviews were conducted inperson at a place of the participants’ convenience . Interviews were conducted on average one month after theintervention ended at the infant’s age of 7 months. The interviews with themothers were conducted by a female member of the trial team who was the trialmanager but had no previous personal contact with mothers before the interviews.The interviews with the facilitators were conducted by a female researcheroutside the trial team who had not met the facilitators before. Interviewslasted between 32 and 77 minutes, and all were audio-recorded and transcribedverbatim. Interview questions (see Online Supplementary File 1) included thewomen’s reasons for formula-feeding, their experience of formula-feeding priorto and during the trial, and their experiences and reflections on participatingin the trial. The facilitators were also asked to comment on these issues asthey had learned from the women during the trial, as well as their ownreflections on the trial design and delivering the intervention and controlgroup protocols.We conducted thematic analysis. We double-coded sample transcripts fromparticipants representing both the control and intervention groups, theniteratively developed a coding tree that covered categories of trialparticipation, feeding experience, support and information, and stigma. With thefinalized code book (see Online Supplementary File 2), the rest of thetranscripts were coded. Two researchers identified an initial set of themesbefore the outcome of the trial was known; a second wave of analysis togetherwith the rest of the research team explicitly explored potential explanations ofthe trial findings. Particular attention was placed on constant comparisonbetween cases  and on negative cases to ensure rigor in the analysis.All participants, including the facilitators, gave their informed writtenconsent for this qualitative study separate from trial ethical procedure.Ethical approval was granted by Cambridge South Research Ethics Committee(10/H0305/9).We identified three themes that describe the women’s experience of taking part in aformula-feeding trial. Theme 1 shows that the mothers we interviewed felt that theylacked support for bottle-feeding their infants, particularly in contrast to thesupport breastfeeding new mothers seemed to get in their view. Trial participationremedied this gap. Theme 2 explores the way in which the advice and information theydid receive outside the trial often seemed contradictory. The trial guidance seemedreliable and clinical measurements reassuring; however, the main trial messageintroduced similar contradiction, in particular, that weight gain might not benecessarily positive. Finally, Theme 3 describes the added challenge of beingrequired to feed reduced amounts of formula-milk when joining the trial with anolder infant.Baby-Milk Trial becausethey hoped for more support and information on infant formula-feeding. Whenasked about the positives about the trial, all women mentioned the personalizedsupport and attention they got as the main benefit of the trial, and how muchthey appreciated it.Most mothers decided to take part in the Q: How have you found taking part in the study?A: Really good. Loads of information, I wouldn’t really put any, haveanything sort of doubtful to say about it, really. I think [thefacilitator]’s been really good, and obviously another girl came withher to do some weigh-ins and stuff occasionally. But, yeah, no, I’vereally enjoyed it, loads of information, a lot of guidance as well, andshe made me feel quite sort of happy and content by always making sure,if I needed to call her or anything like that, she was always there, so,yeah. (Intervention Group Participant I)A: Yeah, very good, very interesting [taking part in the study], I likedit, yeah, because I had the support of [the facilitator] and she said tome “If you need me just send me an email or call me and I will bethere,” . . . so yeah, I liked it very much. (Control Group ParticipantC)This access to formula-feeding advice and support was in stark contrast to thewomen’s experience before entering the trial. Before their participation, theyrecounted relying on sparse information provided on leaflets and formula-milktins, or advice perceived as reluctantly given by midwives or health visitors.All mothers felt that the health professionals that they encountered outside thetrial were not only often too busy to give detailed advice but also reluctant toprovide support for infant formula-feeding if this could deter from attempts tobreastfeed. The trial facilitators , on the contrary, provided lots of advice and time.Q: . . . what was it that made you decide to take part?A: Well, . . . it was offering quite a lot of advice that I hadn’t beengiven by any other health . . . professionals . . . it’s very difficultbecause you’re led to believe that breastfeeding is best and that’s theway to do it, but obviously from my point-of-view, it didn’t happen, itwas bottle-feeding and it was like, “I don’t know how much to give,”when we left the hospital it wasn’t very clear, how often do I do it, doI feed on demand or do I do sort of set feeds, you know, and for afirst-time mum, it was just very confusing. To have something there thatcould offer that sort of support and advice and a bit of guidance, wasjust great, to be honest. (I)But no-one gave me anything, I know I didn’t end up bottle-feeding untiltowards the end but as soon as you go into hospital it’s likebreastfeeding-breastfeeding, there’s no advice and especially because ofthe Baby Friendly Initiative . . . They just don’t provide you with thesupport . . . you should be supporting those parents regardless of whatthey choose because it’s the baby’s health and wellbeing. (I)Mothers not only reported limited support from health professionals outside thetrial but also described experiencing negative reactions from others includingfriends and the public about their infant formula-feeding. In the interviews,mothers recounted frequently needing to justify why their infant wasformula-fed, and avoiding such experiences by feeding their infants before goingout.. . . it’s like other parents looking down on you, that arebreastfeeding, I found that that was a major thing. If I went to anybaby groups, I’d try and make sure that she’d already had a bottle.(I)I think for, the thing that really frustrates me is that everyone goes onabout “breast is best” and then when you bottle-feed they make you feela bit like you’ve let your baby down, a bit like you’re a failure, andthere’s all these like support groups, breastfeeding support groups inthe community, . . . and there’s not that for bottle-feeding . . . I’vehad negative comments from some friends who didn’t know the reasonbehind, I just said “oh I’m bottle-feeding” and it’s like “ooh, that’swhy he’s poorly at the moment” . . . they don’t know the story, and thenI have to say “well actually I didn’t really have the choice to do that”and they’re like “oh sorry.” (C). . . they [the midwives] were so brilliant about it, and even in thehospital, obviously you have to go [outside of the hospital] and get thebits and pieces you need, and we . . . took the stuff [bottles andformula] in, . . . they were absolutely fine, nobody turned their noseup, nobody gave you any dodgy looks, and back when I was younger, peoplewould. (C)Although they did not explicitly discuss this, part of their appreciation ofhaving been part of the trial could have been that they were recruited into a“legitimate” cohort of mothers  where breastfeeding is nolonger an option to be considered and bottle-feeding destigmatized. Althoughthis experience of stigma was prevailing in most interviews, it has to beacknowledged that not all participating mothers experienced stigma in theirinteraction with health professionals and highlighted their positive experienceduring interviews:Trial participants in the intervention group were taught about the WHO guidanceon healthy formula-milk amounts, to recognize infants’ satiety cues andtherefore not force infants to finish the bottle, and recognize that crying wasnot always due to hunger and therefore try water or a dummy to calm them. Thesedetailed instructions stood in contrast to the limited advice from elsewhereavailable to mothers. Instead, women recounted how they had used their ownexperience with previous children, or that of family and friends, to makedecisions about how to feed their infants before entering the trial. Theseshared experiences from other mothers seemed to offer them more tangible andpersonalized instructions, rather than the impersonal and generic advice thatthey gained from instructions on the tin or given on leaflets.In terms of, you know, bottle-feeding and what formulas and how much andall that kind of stuff, I mean the internet really has been a reallygood source. As I said, friends, my two best friends had exclusivelybottle-fed . . . so a combination of the internet and other friends andyour gut really. (C). . . this is the problem, I don’t think there’s a great deal ofguidance, obviously you get what’s on the tin which tells you a roughidea of how much you should be feeding your baby, but what I got wasconflicting information between the health visitor, a midwife and my GP,because I found it really hard to work out “do I stick to the tin” . . .’cos that’s what my midwife told me to do, “feed him every couple ofhours and make sure he doesn’t go no longer than this amount of time,”which was fine in the beginning and then the health visitor comes round“no, no, no, you should feed on demand ’cos he’s crying he’s hungry.” .. . Yeah, you do feel a bit in the dark and you’ve only got what’s, as Isay, the guidance on the tin and then guidance from the healthcareprofessionals that see you, but they don’t always think on the same hymnsheet . . . (C). . . from a feeding point of view, from the day we went for the firstmeeting he was having a lot more milk than he should have had, so [thefacilitator] suggested we cut him back just to see, to what they wantedfor the intervention group and I cut him back and he had a weight lossso the [regular] health visitor said you’ve got increase his milk up soI ended up increasing and I think at one point he was having 300mls morea day than they recommended. (I)However, participants did not only rely on informal lay advice from friends andfamily but also received information from other health professionals not relatedto the trial, but this advice was perceived to be not consistent. Although someadvised them to “stick to the tin [instructions],” others advised to feed inregular intervals, or to feed on demand, “’cos he’s crying he’s hungry”:Baby-Milk Trial also with the interventionguidance. A case in point is health visitors’ focus on tracking infants’ growthby weight. Any downward trajectory seemed to be problematic for health visitorsnot connected to the trial, and a trial participant explained that her healthvisitor had not approved of her infant’s weight loss after regulating down herfeeding amounts to follow the intervention guidance. Another woman recountedthat the facilitator agreed when another health professional queried the lowerfeeding amount and revised the feeding plan.It appears that this disparate advice often conflicted with each other, and oncethey entered the . . . when I left hospital with him, he was underweight and the hospitalwere saying, “You know, you’ve got to feed him on demand” and [thefacilitator] was saying to me “Well do you think you can feed him less,”but when I told her what the hospital said, she said “Well, we can’treally ignore the hospital.” (I)This also fits with some mothers’ responses to equate weight gain as a positiveoutcome. Mothers commented on the health of their infants in terms of theirregular weight gain, or shared in interviews their concerns for their infant’shealth when weight dropped or stagnated.I’m very, yeah, very positive about it, she’s been happy and healthy andbeen put on weight regularly. (C)This was for some related to their initial experience of failing to give theirinfants enough breastmilk—which had been assessed by the weight gained by theinfant.He doesn’t gain weight very quickly, he’s right at the bottom on thepercentiles and there was like one week where he lost weight when he wasill and I was really worried about him I was really struggling, I was ina lot of pain and that was the main issue actually, she wasn’t puttingon as much weight as they wanted her to and we’d got to kind of a crisispoint where . . . I was told by the breastfeeding lady that I needed togive her formula top-ups. (C)The more thorough measurements provided during the trial, including not justweight but length and head circumference, helped to reassure the mothers intheir worry about underfeeding , and alsoshowed the juxtaposition with health visitors’ focus on weight gain as a measureof health, as a mother happily recounted that her infant was “in proportion, sothat was nice because if I was just going to a health visitor . . . I would havejust thought he was underweight but he’s not, he’s just small.” (C)Healthy, term infants who were receiving formula-milk within 14 weeks of birthwere eligible for the trial. Initial challenges to recruit women to the trial asidentified by health visitors  led to the expansion ofrecruitment through general practitioners (GPs), facilitators at postnatalhospital wards, and via a mail-out using the National Health Service (NHS)database. On average, women entered the trial 10 weeks after their infant wasborn. The facilitators speculated that recruitment was mainly hampered bywomen’s reluctance to speak about formula-feeding and worries about beingjudged.I think initially, I think why we’ve had trouble recruiting orrecruitment has gone quite slowly is because people won’t talk aboutformula-feeding and therefore, you know, they’re worried about tellingtheir Health Visitor, they’re worried about . . . and so they don’t,they just think oh it’s another person that’s going to give them a hardtime maybe. (Facilitator F)Some mothers expressed regret that they would have preferred entering the trialstraight after the birth of their child to get support from the start, or thatthey wished they could have entered the trial with their first child. This wasbecause they would have appreciated personalized support straight from thestart, but some also realized that they were already exceeding the recommendedfeeding guidance. Decreasing feeding amounts did not seem to be an acceptableoption for most participants who had already overfed their infants by the timethey entered the trial. The solution was to stick to the feeding amount untilthe infant had caught up with the trial recommendations.I think had we been recruited onto the study earlier, then we might nothave been in that set routine and I might have been a bit more receptiveto changing things. (I)No, the only thing I thought it could have been, have improved for us isif they’d got to us earlier and I hadn’t already started feeding her toomuch, then I wouldn’t have had a problem following the guidelines fromthe beginning, . . . because I’d already started feeding her too much .. . she [my daughter] did not take kindly to being decreased, I think,so we just left it at the same until she caught up with how much it wassupposed to be, and then from that point we were on track and wefollowed the advice completely and it was fine, and it was good, becausewithout that, I would have kept increasing, increasing, increasing.(I)I mean we were feeding . . . quite a bit over what the [intervention]guidelines said, we were a bit like “oops!” So we did cut it downslightly without too much interference to [the infant], we didn’t stickto that first, I think it was three months we started, we didn’t stickto the guidelines, because he was a big baby, and [the facilitator] hadsaid, you know, as a big baby he might need a bit more, and I wasreluctant to drop it right down. (I)From the facilitators’ perspective, it also made it difficult to introducefeeding amounts that had already been exceeded. They knew that many women feltregret to formula-feed their infants and worried about the health impact fortheir children; the facilitators were cautious to add another worry—to beoverfeeding. Instead, they were keen to support the women in a positive way, notto call out overfeeding in a judgmental way and damage—often quiteanxious—mothers’ confidence, “you almost feel that they’re being bruised,” andto establish a good rapport with the mothers.So, we never forced anything on parents, and I think that was the nicething with the intervention, nothing was forced upon the parents, butyet they had the information at hand. So if they wanted it they could doit. (F). . . certainly the first year I did this job it was getting the balanceof trying to encourage them to follow these new guidelines and trying tosort of express how important this issue is with formula-feeding,without adding to their guilt at formula-feeding in the first place. Ididn’t want them to go away thinking “oh, it’s just somebody else who’stelling me in a round about way that I’m not doing the best for mybaby.” So it was, sometimes I used to come away from the baselinesthinking “have I encouraged or pushed this mum enough, could she havedone better or have I been too laidback” . . . (F)I think it’s very important to have a good rapport with the mothers, Ithink actually they’re quite vulnerable . . . I kind of said to one ofmy colleagues that you almost feel that they’re being bruised becausethey’ve tried breastfeeding and it hasn’t worked and then they’re madeto feel guilty about that and by the time they get to us you kind ofthink, you know, they’re almost, they just want someone to listen tothem and hear their experiences. So, I think having a non-judgmentalapproach is paramount. (F)Although they might have not reinforced the intervention guidance strictly, thefacilitators were trained to recognize that it was important to negotiatefeeding practices and bring the mothers on board with the intervention guidance.By allowing for this negotiation of the intervention guidelines, however, thefacilitators might have inadvertently supported the view that straying from theguidelines was fine, and at times, this might have been perceived thatfacilitators condoned excess weight gain.All participants in our study reported the trial participation as a positiveexperience, and this was in contrast to previous negative experiences asformula-feeding mothers. They shared various experiences of not getting help,support, or information about formula-feeding not only because health visitorsor midwives would be too busy but also because this could discouragebreastfeeding. Nonetheless, the women reported a variety of information sources,which tended to include advice from friends and family, and from healthprofessionals they encountered in the regular health care system. However, thisadvice was disparate and often considered contradictory. Weight gain seemedmainly discussed as a positive outcome by other health professionals withoutattention to excess weight gain. For some women, recruitment into the trial whentheir infant was older meant that women had already exceeded feeding guidelinesand reducing feeding amounts were difficult to achieve for both mothers and thefacilitators. Mothers’ experiences of stigma exacerbated the facilitators’challenge to correct feeding practices sensitively.The trial was effective in improving the psychological determinants set out inSocial Cognitive Theory that framed the intervention  andmaternal attitudes to infant feeding and growth. It was also effective inreducing milk intakes (the target behavior) and weight gain in the first 6months of life . HoweverThe results of this study echo previous studies on negative experience ofinfant formula-feeding mothers  includinThis experience of stigma might have been an underlying barrier torecruitment, and being recruited with older infants, in turn, became abarrier to following the intervention guidance . Furthermore, the interventionfacilitators were highly aware that the women felt stigmatized, or at leastinsecure about formula-feeding, and went cautiously into the trialinteractions, emphasizing their supportive, nonjudgmental role within thetrial. Getting positive, nonjudgmental attention and recognition from theseresearch nurses stood out as the most positive experience to all women, evenfor those in the control group who did not receive specific advice onamounts of formula-milk but general advice about sterilizing bottles, feedpreparation, and types of formula-milk. This is also reflected in the hightrial retention rate, and the high engagement with the intervention. As theinterviews with both trial groups showed, feeding was central to theirexperience of raising their infants, and their own and others’ perceptionsof their ability as mothers. However, the women’s anxieties were stillpresent in most interactions, and messages given by the facilitators, forexample, on negative outcomes of overfeeding, might not have been firmenough out of concern to worry these new mothers who already displayedanxiety over their infants’ welfare. It might be argued that theintervention facilitators’ role also included providing pastoral care aswell as delivering the intervention messages. It seems vital to understandthese complex mechanisms underlying both the practice of infant feeding andthe practice of participating in an intervention, and exemplifies critiquesof the limited ambition of “complex interventions” to truly account forcomplexity .Although its approach was that of a complex intervention , infant excess weight gainas a problem. Strong societal norms that connect infants’ weight gain withhealthy growth seem to underline this in both lay and professional practice,and future interventions should seek to change these wider determinants ofinfant feeding in addition to supporting individual families. In what waythese norms, however, can be disentangled from ambitions and anxieties ofbeing “a good mother” (Moreover, feeding practices had been developed with the help of limited,disparate, and often conflicting advice given outside the intervention fromother health professionals, friends and family; perhaps most impactful forthe intervention result was a general emphasis of infants’ weight gain aspositive without explicit recognition of  mother” , seem chThis qualitative study could explore experiences of participants of a healthyformula-feeding trial by inviting some of the participating mothers to reflecton their own practices and potential change as well as the delivery of thetrial. Taking a wider theoretical perspective beyond testing the trialintervention’s psychological framing helped to understand underlying mechanismsthat disrupted the delivery such as experiences of stigma and self-reliance.Some of the trial’s challenges also turned into opportunities for thisqualitative study. The recruitment into the trial of participants with olderinfants challenged their adherence to the intervention guidance, as discussedabove; however, for this qualitative study, it enabled us to compare theirexperiences of infant formula-feeding before and after entering the trial.There were also limitations to this study. The overall backdrop of addressing andinvestigating a stigmatized practice—infant formula-feeding—also shaped thisqualitative study. The interviewers felt as cautious as the interventionfacilitators during their interactions to sensitively probe into transgressionsand challenges of the new mothers. Research in this area is still scarce, andlonger term research designs with time to develop rapport and trust couldprovide more in-depth insights into feeding practices. More sophisticatedqualitative research designs that go beyond, for example, small interview orfocus groups studies could greatly enhance the understanding of participants’experiences , and infThis qualitative study could explore in depth the trial participants’ andfacilitators’ experiences and reflections on participating in a behavioralintervention, and contribute to a growing understanding of how social factors canshape behavioral interventions in unanticipated ways. Lessons learned from thisstudy are informative for future interventions. Addressing a highly stigmatizedsocial practice, the intervention facilitators seemed to have inhabited a role ofproviding pastoral care, and delivering the program, therefore, included a degree ofpermissiveness. Moreover, the mothers’ practices seem to have been shaped byimplicit and explicit societal norms that relate an infant’s health with weightgain, which stood in conflict with the premise of the intervention guidance whosemessage of “excess weight” seemed attenuated. The psychological behavior changeframework employed in the intervention could not address this complexity adequately.Most notably, the most positive outcome of the trial participation for the mothers,probably not captured in the trial’s quantitative outcome measures but a centralfinding in this qualitative study, was the personal and nonjudgmental support theyreceived.Baby-Milk Trialmanaged to achieve changed feeding practices at least indicates an opportunity to doso.This most appreciated element of the trial might clearly be difficult to scale-upinto routine practice. However, our participants’ experiences clearly highlightedthe need to receive nonjudgmental information and support right from the birth oftheir infants to develop healthy ways of formula-feeding. Formula-feeding mothersshould not be ignored if excessive formula-milk amounts are recognized to contributeto childhood obesity, and new mothers should certainly not be stigmatized at a timeof great anxiety, uncertainty, and vulnerability. Arguably, this is a controversialproposition and some might argue that providing formula-feeding support mightdiscouraged breastfeeding. Yet, in other public health fields such as the preventionof sexually transmitted diseases and teenage pregnancy, the public health stancefavors harm reduction, the provision of advice and condoms, without fearing todiscourage abstinence . A solutClick here for additional data file.Supplemental material, Suupplementary_Material for Toward Understanding HowSocial Factors Shaped a Behavioral Intervention on Healthier InfantFormula-Feeding by Cornelia Guell, Fiona Whittle, Ken K. Ong and RajalakshmiLakshman in Qualitative Health Research


Incidence rate of cancer is increasing worldwide, with longer life expectancy being one of the main causes. Yet, between 30% and 50% of cancer cases are preventable, and early detection contributes to a better prognosis. This makes health communication strategies essential. Facebook, the world’s most used social networking site in 2017 and 2018, can be a useful tool for disseminating powerful messages on health promotion, prevention, and early detection.We aimed to (1) offer ways of optimizing health messages about cancer on Facebook, focusing on topics, such as risk factors, prevention, treatment, early diagnosis, and cure, and (2) investigate which aspects of these messages generate greater engagement.To verify what generates greater engagement in topics related to cancer on Facebook, we analyzed 16 Brazilian pages with the main theme of cancer. We performed a manual analysis of texts, content, and engagement rates. Finally, we developed a software program to operationalize the analysis of Facebook posts. The tool we devised aims to automate the analysis of any Facebook page with cancer as the main theme.We analyzed 712 posts over a 1-month period. We divided the posts into the following 8 categories: “Testimonies or real-life stories,” “Solidarity,” “Anniversaries,” “Science and health,” “Events,” “Institutional,” “Risk factors,” and “Beauty.” The pages were also organized into groups according to the type of profile to which they belonged .The results showed that the categories generating greater engagement in Brazil were not those with the highest percentage of cancer-related content. For instance, in the “Informative” group the “Testimonies or real-life stories” category generated an engagement of 79.5%. However, only 9.5% (25/261) of the content within the relevant time period dealt with such topics. Another example concerns the category “Science and health.” Despite being the one with the highest number of posts , it scored 5th in terms of engagement. This investigation served as the basis for the development of a tool designed to automate the analysis of Facebook pages. The list of categories and keywords generated by this analysis was employed to feed the system, which was then able to categorize posts appearing on a Facebook page. We tested the system on 163 posts and only 34 were classified incorrectly, which amounts to a 20.8% error rate (79.2% accuracy).The analysis we conducted by categorizing posts and calculating engagement rates shows that the potential of Facebook pages is often underutilized. This occurs because the categories that generate the greatest engagement are often not those most frequently used. The software developed in this research may help administrators of cancer-related pages analyze their posts more easily and increase public interest as a result. Cancer is an umbrella term encompassing a group of >200 diseases that have in common the disordered growth of cells invading tissues and organs . The numFor prevention purposes, it is important to reiterate that changes in lifestyle and habits of the population may reduce the likelihood of disease onset. As reported by Anand et al, “Only 5%-10% of all cancer cases can be attributed to genetic defects, whereas the remaining 90%-95% have their roots in the environment and lifestyle. The lifestyle factors include cigarette smoking, diet , alcohol, sun exposure, environmental pollutants, infections, stress, obesity, and physical inactivity” .Cancer Research UK, some types of cancer can be treated much more easily if detected early, for example, bowel, breast, ovarian, and lung  Get to know @Toda Poesia at [link].Translated from PortugueseThe mistake arguably happened because the word “day” appears 2 times and it is the only word in this post that also appeared in the keyword list. After this error, we may consider including the word “project” in the “Institutional” category as several publications from “Acubens, cancer museum” in this category contain this word.With respect to content analysis, one of the limitations concerned the fact that we restricted the study to pages produced in Brazilian Portuguese. We did this out of interest in gaining a better understanding of what is produced on social media about cancer in Brazil and what generates engagement among Brazilians. However, future studies should analyze more broadly the content generated in other countries and languages.With respect to the software, one limitation concerned the difficulty in choosing the words for each category, as some of them could belong to more than one. In many cases, we had to make choices based on the evaluative criteria of the researchers. However, it may very well be that people with different experiences and writing styles could have classified words in other categories. Another limitation, already mentioned above, may be that the software does not understand the context and, therefore, is unable to capture irony, jokes, ambiguous wording, or figurative language. Moreover, the system is not able to recognize common typing errors.Despite these limitations, our software could be of help to many research groups and Facebook page administrators wishing to gain a better understanding of what their audience wants and what generates engagement. Other features of the software, such as the “Heat map,” will also be of great value in this process.Categorizing posts and calculating engagement rates revealed that the potential of Facebook pages is often underutilized. This may be because the categories generating the greatest engagement are not those used most frequently. In contrast, we have noticed that in some cases, the most attractive category in terms of engagement is among the least published. For instance, it is worth noting that many pages had only a few posts in the “Science and health” category, despite this being one of the most popular. Indeed, along with “Risk factors,” “Science and health” comprises the most relevant categories for public health issues, such as cancer prevention, early diagnosis, and well-being. Given that a high number of cancer cases are related to environmental and lifestyle issues, it is crucial to talk more about prevention and risky behaviors on social media.However, this study shows that personal pages and the “NGOs” group did not produce any messages about “Science and health.” The “NGOs” group also failed to produce any content on “Risk factors”. Our results suggest that NGOs should include more information about science, health, and risk factors and also set out to promote them more vigorously.Within the “Hospital or foundation” group, the category “Science and health” was the one that generated the highest weighted average engagement. However, only 18.3% (20/109) of the posts within this group of pages fell into this category. Our suggestion is that page administrators of hospitals or foundations give more space to this subject.The software developed in this study may certainly help research groups interested in studying cancer-related topics. In addition, the keyword dictionary on cancer could help people who are interested in delving deeper into this topic. Moreover, researchers and groups willing to create new categories and dictionaries could take advantage of our tool to gain a better understanding of what type of content engenders greater engagement among target audiences, thereby collecting information to produce more attractive Web-based content.


Nearly 2 million traumatic brain injuries occur annually, most of which are mild (mTBI). One debilitating sequela of mTBI is cognitive fatigue: fatigue following cognitive work. Cognitive fatigue has proven difficult to quantify and study, but this is changing, allowing models to be proposed and tested. Here, we review evidence for four models of cognitive fatigue, and relate them to specific treatments following mTBI. The evidence supports two models: cognitive fatigue results from the increased work/effort required for the brain to process information after trauma-induced damage; and cognitive fatigue results from sleep disturbances. While there are no evidence-based treatments for fatigue after mTBI, some pharmacological and nonpharmacological treatments show promise for treating this debilitating problem. Future work may target the role of genetics, neuroinflammation and the microbiome and their role in complex cognitive responses such as fatigue. With some 1.8 million traumatic brain injuries (TBIs) occurring annually in the USA , the incet al. investigating the prevalence of fatigue across time in mTBI, found the prevalence of fatigue to be initially 68% (1 week post-mTBI) and to decrease to 38% over the next 3 months, with severity correlating with prevalence ) does nevalence , whetherevalence ,19. ThusThe aim of this paper is to review current models of cognitive fatigue after mTBI, as well as current treatments. In the following review, we will begin with an overview of the problem of fatigue in mTBI, then we will move into a description of the major models that have been proposed to account for fatigue in mTBI, and we will conclude with a section on potential treatments for fatigue in mTBI, with available evidence. A systematic review was performed to identify studies of mTBI and fatigue using PubMed from its inception through 16 May 2016 using MeSH terms and keywords. No language, type of study or date restriction was applied in the initial search. All citations were examined and nonrelevant studies were excluded based on their titles and abstracts. Studies were additionally excluded if they were animal studies or case reports. Manuscripts of all potentially included studies were obtained, and those with a focus on TBI and dimensions of fatigue, models of fatigue, or treatment were read and incorporated into this review as appropriate. See In the last century, researchers have had great difficulty in both defining and assessing fatigue , despiteWhile this proliferation of measures reflects a recognition of fatigue as a major clinical problem in many conditions, the information derived from these self-report scales depends on the information collected, and is influenced by the scale developer's conceptualization of fatigue, the targeted clinical population and the responder's interpretation of the questions asked . TherefoFatigue has been defined as ‘a subjective lack of physical and/or mental energy that is perceived by the individual or caregiver to interfere with usual and desired activities’ . While tIn fact, fatigue has been acknowledged to be a multidimensional concept by the World Health Organization's International Classification of Functioning, Disability and Health (1976). This is because fatigue interacts with brain injury or disease to affect body function and structure, as well as the activity and participation of the patient. Many subtypes of fatigue have been identified, including cognitive fatigue, physical fatigue, emotional fatigue and stress fatigue . This paTo further focus this review, we will concentrate on primary fatigue rather than fatigue that is secondary to some other factor. Secondary fatigue is fatigue that is due to, for example, poor sleep quality or chronic inflammation. In contrast, primary fatigue is due to the brain injury itself, and is not due to some intermediate factor. For instance, fatigue has been found to contribute uniquely to disability status and headache severity among adults with chronic TBI in the community, independent of injury severity, executive dysfunction and depression ,38. Becaet al. [One attempt to grapple with this amorphous construct has been to classify fatigue as either physical  or cognitive . In this review, we will concentrate on cognitive fatigue. Kluger, Krupp & Enoka  propose et al.  found evAlthough fatigue has a strong subjective element, subjective, self-report measures are notoriously prone to bias. There have, therefore, been several attempts to examine cognitive fatigue objectively, generally by inducing cognitive fatigue and then examining behavioral performance , and for that reason, we focus on it here. For example, Ziino and Ponsford [change in performance on the C-SAT from before to after performance of the vigilance task [In the TBI literature, the Ponsford ,43 publiPonsford , no suchnce task ). For exnce task  reportednce task . Self-rence task  supportence task ,47. ThusCorrelations between cognitive fatigue and behavioral performance are encouraging because we intuitively expect to find them. When we are cognitively fatigued, we feel more sluggish and less sharp. It therefore follows that cognitively fatigued individuals should take more time to respond and make more errors. When such correlations are reported, we are reassured and our notions of fatigue are supported; when such correlations are not found – and the literature on fatigue is rife with such null effects dating back to 1904  – it poiResearch into fatigue in mTBI has attributed fatigue to several factors. These fall into several categories, and while there are currently few formal models of fatigue, these categories serve as a starting point for the creation of models of fatigue. In this section, we have grouped the research we reviewed into studies that have proposed that fatigue is the result of increased effort, that fatigue is an indication of neuro-inflammation, that fatigue is due to psychological risk factors and that fatigue is a function of sleep disturbances.et al. [et al. [The idea that fatigue is an indication of increased effort following mTBI derives from the idea that a TBI, even a mild one, causes structural damage to the brain that disrupts the cognitive system. This disruption results in inefficient information processing, which means that the brain must expend more energy (effort) in order to perform a given amount of cognitive work. In its simplest form, this line of thinking then proposes that, because the brain is constantly working harder, it is prone to fatigue (in much the same way that an overworked muscle becomes fatigued). This was, for example, the view of Van Zomeran et al. , who suget al. ,42,49 ha [et al.  found thThe idea that the brain must work harder following mTBI is supported by several lines of evidence. For example, studies measuring cortical activation using electroencephalography (EEG) have shown that fatigue (in HCs) is associated with changes in θ-band activity, and also with changes in the location of α power . These ret al. [These fMRI studies have shown that persistent post-concussive symptoms are associated with increased activation in attentional areas such as the anterior cingulate cortex (ACC) and with decreased activation in the ‘default network’ (DN), an interconnected group of brain structures that are hypothesized to be part of a functional system . Increaset al. , who fouet al. [A variant of this idea was proposed by McAllister et al. , who fouet al. [et al. proposed that TBI results in structural damage and that the brain must work harder in order to overcome inefficiencies in information processing. Dobryakova et al. went on to observe that the striatum of the basal ganglia is implicated in fatigue following brain damage (as well as brain disease) [et al. [et al. [A more recent variant of this idea is was proposed by Dobryakova et al. , who suget al. . As withdisease) . For exa [et al.  demonstr [et al. ,65. Thus [et al.  therefor [et al. .Taken together, the studies reviewed above show that mTBI can result in measurable, persistent damage to the brain, that the brain has to ‘work harder’ (as shown by increased activation) following a mTBI and that fatigue is associated with areas in the brain implicated in the processing of reward and motivation.+/K+ ATPase activity [Several studies have investigated the link between neruo-inflammation and fatigue. This is because it is now known that the CNS generates inflammatory mediators in response to injury. These mediators include pro-inflammatory cytokines, prostaglandins and free radicals, which in turn induce chemokines and adhesion molecules, recruit immune cells and activate glial cells (for a review see ). Indeedactivity . Pro-infactivity . In seveactivity . These dactivity .et al. found that fatigue does not appear to be due to neuro-inflammation as measured by C-reactive protein levels in mTBI [However, while fatigue may well be associated with neuro-inflammation, particularly after severe trauma, pro-inflammatory cytokines are unlikely to underlie chronic fatigue following mTBI. This is because one would expect inflammation to be proximal to the injury (rather than chronic) , and als in mTBI .There is a clear need for increased research in the area of neuro-inflammation in mTBI. Based on the current literature, it is difficult to determine the extent to which fatigue in mTBI is related to neuro-inflammation. It may be that following even a mTBI, levels of pro-inflammatory cytokines are chronically elevated, leading to chronic fatigue. Alternatively, it may be that fatigue associated with neuro-inflammation is confined to the acute and subacute period of recovery , and that chronic fatigue in mTBI is due to a different cause. Further work is required to adjudicate between these possibilities.Fatigue has also been conceived of as a psychological process that protects the cognitive system from exhaustion. Thus, central physical fatigue has been proposed to be a mechanism designed to prevent the body from over exertion, which might eventually lead to upsetting homeostasis and causing irreparable damage to muscles and organs . In a siet al. [A rather different conception of fatigue is that it is related to modifiable psychological risk factors. For example, individuals who have sustained mTBI but who are psychologically resilient report less fatigue than individuals who have mTBI but who are less resilient . Similaret al.  found thet al. , which iThis conflation of ideas – mental fatigue, sleep, attention and alertness – is not specific to the BNI. On the contrary, it is found (to a greater or lesser extent) in virtually all the instruments that have been developed to assess fatigue. And this conflation of ideas is one very plausible reason why fatigue scores are so often correlated with other measures, such as depression or, in the research cited above, resilience. Indeed, the resilience questionnaire used  includeSleepiness is generally caused by not enough proper, restful sleep or a lack of stimulation, and results in the need for increased sleep. Fatigue is usually a more chronic condition than sleepiness. People who suffer from fatigue feel they lack motivation and energy. Even though fatigue and drowsiness are not the same, drowsiness or the desire to sleep, is a common symptom that accompanies fatigue. Apathy may also accompany fatigue. However, sleep disorders such as sleep apnea , narcolepsy (with or without cataplexy), periodic limb movement disorder, post-traumatic hypersomnia and parasomnias may also occur after a TBI. Potential causes include injury to brain regions associated with sleep-wake regulation and/or disruption of circadian timing of sleep [It is important to distinguish between actual sleep disorders that can occur after TBI, and the subjective experience of fatigue. Sleep disturbances are frequently identified following TBI, affecting 30–70% of persons, and often occur after mTBI . Insomniof sleep . SecondaDiagnosis of sleep disorders after TBI is made using polysomnography, multiple sleep latency testing or actigraphy. Treatment is based on the specific disorder, and may include the use of medications, continuous positive airway pressure, or behavioral modifications. It has been reported, however, that treatment of sleep disorders in individuals with TBI often does not improve sleepiness or cognitive functioning . Individcause, not a consequence, of anxiety, depression and daytime sleepiness, which in turn may exacerbate fatigue by affecting cognitive functioning. This model proposes that to alleviate fatigue, each factor must be addressed individually.Importantly, while insomnia and fatigue often co-occur following a TBI (9–22%), and are both associated with poorer quality of life, they are affected independently by a variety of factors, especially psychopathology and sleep quality . While iet al. [et al. have shown that the MFIS and the PSQI share some common variance, it may be that both poor sleep and cognitive fatigue proceed from the same cause, or it may be that one causes the other. In other TBI populations, it appears that poor sleep quality or insomnia is not the cause of fatigue. The use of targeted statistical approaches  and careful use of neuropsychological instruments (that do not contain items that assess overlapping constructs) are required to establish whether this is also the case in mTBI.Very little of the research that has been conducted on the relationship between sleep and cognitive fatigue in TBI has specifically investigated mTBI. One exception is Schiehser et al.  who inveIn the above, we have reviewed four ways that researchers have attempted to understand cognitive fatigue in mTBI. This is not an exhaustive list of models of fatigue, but rather this is one way to organize the research reviewed here. Broadly, this research can be understood as linking fatigue to an increase in the effort necessary to perform cognitive work, linking fatigue to neuro-inflammation, linking fatigue to psychological processes or linking fatigue to sleep quality. Of these models, there appears to be little support for the idea that chronic fatigue in mTBI is due to neuro-inflammation, though it is entirely possible that fatigue experienced during the acute and subacute periods may be at least partially due to this cause. However, this conclusion may change as more research is undertaken to better understand the relationship between neuro-inflammation and fatigue in mTBI. The idea that fatigue in mTBI is linked to psychological processes such as resilience also represents an area where more research could produce illuminating results. However, until more research is conducted, it is not possible to rule out the possibility that the linkage between psychological processes and fatigue is due to the fact that the instruments used to assess fatigue and psychological processes such as resilience both contain items that assess common constructs.et al. one would predict that improved sleep quality would result in reduced cognitive fatigue, and, to foreshadow a section below, Ouellet and Morin have provided partial support for this by showing that improving sleep habits resulted in less general and physical fatigue [Although fatigue and sleep problems appear to be relatively independent in individuals with more severe TBI, in mTBI it has been shown that sleep quality predicts cognitive fatigue . This is fatigue . Thus, mIn the research reviewed here, the model with perhaps the most support was the model linking fatigue to an increase in the effort necessary to perform cognitive work. Unlike some of the other models that rely on correlations of two self-report measures, this model links self-reported fatigue to objectively measured changes in the brain. This is a strong advantage, since there is often overlap in the constructs assessed by self-report instruments that are designed to assess such things as, for example, ‘fatigue’ and ‘resilience’ (see above). As with the other models, more work needs to be done to support this model, yet of the four models reviewed here, it is our view that this model represents the most promising way forward.There has been relatively little work done to develop interventions for fatigue following TBI in general, and mTBI in particular, and at this time there are no evidence-based treatments with sufficient evidence to be recommended or contraindicated for posttraumatic brain injury fatigue ,87. In aSeveral treatments have been described to help address posttraumatic fatigue and are reviewed below. These include pharmacological, cognitive and behavioral interventions.et al. [As has been described, TBI may result in long-lasting postconcussive symptoms, such as cognitive fatigue and concentration difficulties, and this is often the main impediment in returning to work or school. While there is currently no effective treatment for chronic cognitive fatigue, methylphenidate is the most common medication that has been used to help combat cognitive fatigue and enhance cognitive function in this population. This treatment is based on the notion that TBI results in a need for increased effort on the part of an individual to maintain pre-injury levels of performance and help overcome attentional difficulties and slowed processing speed (see above). Moreover, because methylphenidate is a dopamine agonist, it results in an increase in the levels of dopamine in the brain , suggesting a link between dopamine levels and fatigue in TBI . Johansset al.  found thet al.  also treOther medications may help treat an underlying sleep disorder, and in turn, lead to improvements in cognitive functioning. Modafinil is a wake-promoting drug and an example of a smart drug that has been used like a nootropic (cognitive enhancing drug). It has been used for treating excessive sleepiness associated with narcolepsy, obstructive sleep apnea and shift-work disorder. Perhaps because it is common to conflate sleepiness and fatigue, Modafinil has also been used as a potential treatment for fatigue in individuals with TBI, but without success. One randomized controlled study  showed nMelatonin has been shown to improve latency to sleep, sleep efficiency, morning alertness and arousal, and quality of life in chronic patients with insomnia over the age of 55 ,97. OnlyTo summarize, three broad classes of medications have been used to help reduce fatigue in TBI: those designed to help with attention/concentration, those designed to help with cognition generally and those designed to help with sleep. Of these, only methylphenidate, a dopamine agonist, has been found to affect fatigue. Medications that help with sleep have not been found to reduce fatigue, and nootropic medications  have produced mixed results. This pattern of results underscores other evidence that fatigue in TBI is independent of sleep quality, and suggests instead that fatigue may be related to dopaminergic areas of the PFC.Several randomized controlled studies have been identified examining nonpharmacological interventions for fatigue management after TBI and other brain injuries  ,100. Theet al. point out the need to help patients to regulate their lifestyle ‘to live within cognitive and physical limitations’ (p. 231). Strategies include reducing work hours, pacing activities, reducing the demands of activities, taking frequent rest breaks, reducing distraction and avoiding situations that require multitasking. They endorse the use of general cognitive behavior therapy techniques to address psychological issues related to making such changes in lifestyle. Ouellet and Morin indicate that any effective intervention approach should involve multiple components, including biological, psychological and social. They suggest that a combination of gradual physical reconditioning, cognitive restructuring, cognitive retraining, anxiety-reducing techniques and education around proper energy management techniques, with a gradual increase in social or occupational activities, could prove beneficial. Using a single-case experimental design, they tested the efficacy of a cognitive-behavioral therapy for insomnia in individuals with mild to severe TBI in an outpatient rehabilitation center [There is some evidence to suggest that cognitive behavioral therapy (CBT), alone or in conjunction with other treatments, may be helpful in reducing postinjury fatigue and is worthy of further study ,101–103.n center . The proRees and Bellon treated 20 patients with persistent post concussive symptoms 1 year after mTBI (ages 18–52). No participant had had a prior TBI. Each subject participated in individual client centered counseling and CBT for 2 hours every 2 weeks for 6 months, then for up to 2 hours monthly for 18 months. The intervention included education, client centered therapy and CBT which involved sharing information about post concussion difficulties; using PCS questionnaires to identify PCS; rank ordering symptoms by participants to drive counseling, problem solving and symptom validation; development of compensatory strategies for prioritized symptoms; sharing information about mood states and their impact on behavior; discussion and feedback; developing ability to attend, persist at tasks and set appropriate goals; and development of strategies to improve participation in physical, cognitive and social activities. At baseline, 100% of the sample reported physical fatigue and cognitive fatigue, as well as difficulty making decisions and anxiety. At 2 years follow-up, there was a significant reduction in physical fatigue (endorsed by 40% of the sample) although cognitive fatigue remained a problem (endorsed by 90% of the sample). Difficulty making decisions and anxiety also remained problematic. On the Beck Depression Inventory, significant reductions were noted on a number of items, including loss of energy, changes in sleeping pattern and tiredness/fatigue. This study suggested that CBT in combination with client-centered therapy was an effective intervention for individuals with PCS associated with mTBI, although some symptoms, including cognitive fatigue, irritability, poor frustration tolerance and feeling overwhelmed were not affected. More work was recommended given the lack of a control group in this study.et al. provided a cognitive behavioral intervention specifically designed for managing social anxiety following acquired brain injury at least 12 months prior to beginning therapy (no further details provided) in 12 individuals with evidence of social anxiety or social phobia. These individuals were allocated to a treatment group or a waitlist group, using a case–control procedure. The core CBT methods in the treatment program included relaxation, cognitive strategies, graded exposure and assertiveness skills training. Participants were seen for one hour per week for 9–14 weeks. Therapy was modified  by having shorter sessions with more frequent breaks, frequent repetition of information and use of visual aids, session summaries and audio tapes; simplified cognitive strategies were also used. Outcome measures included The Social Phobia and Anxiety Inventory [Hodgson nventory , the Hosnventory , a self-nventory  and the Various measures of fatigue have been reported to improve after a course of CBT, although they vary among studies. By the very nature of this type of therapy, psychological processes that might be affecting a person's behavior are explored; in this case, the role of fatigue as a signal either indicating too much effort is leading to frustration or as a preemptive protective factor can be explored. In addition, the role of resiliency and other modifiable psychological risk factors are considered.Mindfulness-based interventions are aimed at reducing psychological symptoms of distress and enhancing quality of life, and have been applied in various settings in both mental healthcare and somatic healthcare. Mindfulness-based stress reduction (MBSR) is an educational program designed to improve attention and cognitive flexibility, increase brain neural connectivity, and help individuals to better cope with their difficulties . It has et al. hypothesized that, compared with a waitlist group, patients randomly assigned to the MBSR program would experience improvement at 8 weeks in their assessment of cognitive fatigue, measured using the MFS and neuropsychological measures of processing speed, attention and working memory. Their results supported this hypothesis, with reductions in self-reported cognitive fatigue and improvements in psychomotor functioning  relative to waitlist controls (who received no active treatment). These results are encouraging, and suggest that MBSR may represent an effective means to reduce fatigue after mTBI. However, because the MFS includes questions that assess attention/concentration, cognitive functions such as memory and processing speed, sleep and emotional control, it is not clear to what extent MBSR is able to specifically reduce mental fatigue.Returning to cognitive fatigue in TBI, Johansson, Bjuhr & Rönnback  used an et al. [Theadom et al.  note fouet al. . Communiet al. : interveBjörkdahl and colleagues  evaluateUse of bright blue light may reduce post-TBI fatigue because light exerts nonvisual effects, including acute alerting effects, on many biological functions. Use of light therapy has been associated with reduced sleepiness, increased vigilance performance and improved mood in both healthy and patient populations . Blue liThe use of interventions aimed at increasing physical activity has not generally been found to be helpful in improving subjective ratings of fatigue . Howeveret al. [A few studies have examined the effectiveness of EEG biofeedback  and tranet al.  determinet al. [More generally, Cantor et al.  concludeThere is also evidence to suggest that by treating specific sleep disorders, individuals with TBI show significant reductions in psychiatric symptoms of PTSD and depression, as well as on ratings of quality of life , suggestCounseling/education and early interventions can also be helpful in improving recovery in individuals who report moderate to severe sleep disorders following mTBI in combination with moderate to severe headache, dizziness and psychiatric symptoms . AnotherMethylphenidate and bright blue light have shown some promise in alleviating mental fatigue;Very limited work suggests that CBT and MBSR may help reduce mental fatigue;There is equivocal evidence that cranial electrotherapy stimulation may reduce mental fatigue;In general, it is important to provide evidence-based treatment and rehabilitation services early in the recovery period, even when the etiology of the fatigue not clearly understood. These should address other, modifiable risk factors .Overall, while there are no evidence-based treatments for post-TBI fatigue, the extant literature suggests the following:Clearly, far more work needs to be done to better understand the mechanisms underlying these treatments. It will also be important to investigate the long-term effects of these treatments and whether there is sustained improvement once treatment has ended. As this research is done, and the mechanisms are better understood, it is to be hoped that more effective treatments for mental fatigue following mTBI will be developed.Over the past decade, there have been important advances in the study of cognitive fatigue generally, and in TBI in particular. The tools of cognitive neuroscience, such as fMRI, have allowed us to assess brain function and dysfunction in ways that were once simply impossible. As we look to the future, we will move beyond studies investigating the neural substrates of cognitive fatigue and bring to bear advances in other domains of clinical science. These include the influence of, for example, genetics, neuroinflammation and the microbiome on behavior and how factors such as these may interact with brain function to produce complex cognitive responses such as fatigue. As our understanding of the complexity of the cognitive system grows, we will require increasingly multidisciplinary and collaborative groups to fully investigate our hypotheses.It is also to be hoped that as our scientific questions grow to include a broader range of systems, our approach will become more translational. That is, as our understanding of fatigue becomes deeper, we should begin to be able to predict the treatments that will effectively treat fatigue, and also to be informed by the relative effectiveness of different treatments. One example of this is the use of a dopaminergic agonist (methylphenidate) to help treat fatigue. In as much as this is an effective treatment for many people, it supports the idea that the dopaminergic system in the brain is associated with fatigue; however, in as much as it does not help all individuals with cognitive fatigue to the same degree, this suggests that fatigue may also be due to factors beyond the dopaminergic system. This type of cyclical information flow between the lab and the clinic will refine and enhance our ability to treat fatigue in mTBI in the future.Fatigue is a common, persistent consequence of TBI of any severity, including mTBI. Despite this, to-date fatigue has been inadequately characterized, assessed and managed. Fatigue clearly detracts from quality of life, interferes with the ability to work, interacts with psychiatric symptoms and exacerbates problems with social functioning. Of the models that have been proposed to account for fatigue, the two with the most support are: that fatigue in mTBI results from the increased effort that the brain must expend in order to process information following injury, or that fatigue in mTBI results from sleep disturbances. These models are, of course, not mutually exclusive. The application of the methods of cognitive neuroscience to the study of fatigue has resulted in important advances in our ability to test hypotheses about the causes and effects of fatigue. It is to be hoped that we are finally beginning to gain a better understanding of the etiology, precipitants and risk factors of fatigue. This is critically important work, in as much as it will enable the development of effective treatments, which will benefit the many thousands of individuals who struggle with fatigue on a daily basis.Cognitive fatigue is a significant problem for many individuals who have sustained a mild TBI (mTBI).There are multiple types of fatigue that individuals with mTBI experience, including cognitive and physical fatigue.Here, we group the research on cognitive fatigue in mTBI into four categories, or models of fatigue: 1) fatigue as an indication of effort, 2) fatigue as an indication of neuro-inflammation, 3) fatigue as an indication of psychological processes, 4) fatigue as an indication of sleep problems. Of these models, models 1 and 4 have the most support.While there are no evidence-based treatments for fatigue, research has been conducted into treatments in several domains.Medications: the efficacy of three broad classes of medication have been investigated to help reduce fatigue in TBI: those designed to help with attention/concentration, those designed to help with cognition generally, and those designed to help with sleep. Of these, only methylphenidate, a dopamine agonist, has been found to affect fatigue.Therapeutic interventions: the efficacy of cognitive behavioral interventions, mindfulness-based stress reduction, education/symptom management strategies, working memory training are reviewed. Reductions in fatigue have been reported, but these reductions are not always easy to interpret because of the instruments used to assess fatigue.Other nonpharmacological interventions: the efficacy of light therapy, physical exercise and brain biofeedback/stimulation are reviewed. These are promising approaches that may prove useful in alleviating fatigue in the future.In general, it is important to provide evidence-based treatment and rehabilitation services early in the recovery period, even when the etiology of the fatigue is not clearly understood. These services should address other, modifiable risk factors .Future research should investigate influence of factors such as genetics, neuroinflammation and the microbiome on behavior, and how factors such as these may interact with brain function to produce complex cognitive responses such as fatigue.


This article has critical problems with conception, reported data, and results interpretation. We believe it is important to inform your readers, and the community of researchers and practitioners working to reduce LD incidence, of these issues.In their recent article, MacIntyre et al.4, and adequate resources to investigate and report when cases are suspected to have a shared exposure. The authors did not provide evidence that the degree of clustering in these cities is statistically unlikely to occur by chance alone, accounting for this detection bias. In addition, large cities—by definition, small geographic areas—have large numbers of people with underlying conditions that can increase the risk of LD. It is thus expected that LD outbreaks would be more likely to occur and be detected in cities with large at-risk populations than in rural areas.The authors claim that the degree of geographic and temporal clustering of LD outbreaks in NYC and Sydney is “unusual” as compared with other jurisdictions. However, the authors did not consider detection bias and underlying population characteristics of cities as likely alternative explanations. LD outbreaks in NYC are likely more completely detected and reported than in other jurisdictions because of complete and timely case notification via electronic laboratory reporting, automated cluster detection processesLegionella within complex building water systems (i.e. within the building), with no linkage to the municipal water distribution system. Similarly, the terms “rolling epidemic”  and “rolling outbreak” strongly imply that the outbreaks were linked, but the authors present no evidence this is the case.The use of phrases such as “contamination of potable water” and “potable water supply is a more common source in US outbreaks” is inaccurate when referring to LD cases occurring in NYC. This phrasing implies that outbreaks in NYC have been linked to the municipal water distribution system, which is incorrect. For buildings in NYC where more than one case has occurred among tenants within 12 months, water testing has sometimes shown evidence of amplification of A total of 32 outbreaks were reported in NYC from July 2003 to November 2012, and of these, only 5 (16%) were due to cooling towers. Figure 4 shows the source of these different outbreaks, with most being caused by contamination of potable water.”). If the Figure 4 caption is accurate, then these results are clearly misrepresented in the text, and the implications of these data are quite different, as New York State, including New York City, has a total population of ~20 million people and includes 62 counties over ~55,000 square miles, with thousands of public water systems; New York City, by itself, has a total population of ~8.6 million people, includes 5 counties over ~304 square miles, and has one municipal water system. To clarify, the authors should have provided a linelist for each outbreak in Figure 4, including variables such as data source, outbreak timing, number of persons affected, and outbreak source.Figure 4 and related text conflate data from New York State with data from New York City. The Figure 4 caption indicates that these are New York State data, while the text referring to Figure 4 indicates the data are from New York City (“5 It should be noted that the strains identified as the source in outbreak 1 (South Bronx) and outbreak 2 (Morris Park) are not identical strains.5 Thus, these outbreaks are not linked by epidemiological or laboratory data and represent separate events.Furthermore, the article contains self-contradictory language. As one example, in the discussion, climate change is said to be a long-term effect and have little impact on LD cases, but this is followed by stating that “slightly warmer temperatures” support rolling outbreaks due to unseasonably warm weather. The authors have not performed the necessary data collection or analyses to support such conjecture. As another example, the results for outbreak 2 in Morris Park state that “the strain found in the cooling tower at the Bronx Psychiatric Centre matched samples taken from four patients.” However, the discussion asserts the opposite, i.e., that “no data have been reported on matching to date on the remaining outbreaks” other than the Opera House Hotel outbreak. The latter is incorrect as matching data were provided by Lapierre et al., which showed that clinical strains obtained from outbreak 2 in Morris Park did match by whole genome sequencing.5 is uncited.Finally, the authors provide no analysis or citations to support their assertions that: “in relation to the Bronx, the Opera House Hotel and Morris Park outbreaks, it is unusual for so many cooling towers to be contaminated at one time” and “the reporting standards are generally good in both countries.” Key references presented to support points of discussion are not peer-reviewed while relevant peer-reviewed literatureHealth department practitioners who originally collect, analyze, and report on communicable disease data are well-positioned to provide meaningful local context and interpretation. We strongly encourage researchers to reach out to health department practitioners when conceiving articles using such data, and journal editors to invite such practitioners to serve as peer reviewers for such articles prior to publication