Practical limitations to a positive deviance approach for identifying dietary patterns compatible with the reduction of cancer risk

Vossenaar, Marieke; Bermúdez, Odilia I.; Anderson, Annie S.; Solomons, Noel W.

doi:10.1111/j.1365-277x.2010.01056.x

Cited by 7 publications

(2 citation statements)

References 23 publications

(36 reference statements)

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“…A total of 68% of those studies use mixed methods, 21% use quantitative methods, and 11% used qualitative methods. The normal PD approach covered studies that tackled issues including health care–associated infections (de Macedo et al, ; Marra et al, ), enhancing health outcomes of women in disadvantaged circumstances (Long et al, ), cancer prevention (Vossenaar et al, ; Vossenaar, Bermúdez, Anderson, & Solomons, ), child marriage (Lackovich‐Van Gorp, ), child rearing (Aruna, Vazir, & Vidyasagar, ), infectious disease control (Babalola, ; Babalola et al, ; Nieto‐Sanchez, Baus, Guerrero, & Grijalva, ), improving pregnancy outcomes (Ahrari et al, ), counselling for family planning (Kim, Heerey, & Kols, ), child malnutrition (Aday, Hyden, Osking, & Tomedi, ; Bolles, Speraw, Berggren, & Lafontant, ; Guldan et al, ; Kanani & Popat, ; Merchant & Udipi, ; Merita, Sari, & Hesty, ; Roche et al, ; Sethi, Kashyap, Seth, & Agarwal, ; Shekar, Habicht, & Latham, ; Shekar, Habicht, & Latham, ; Wishik & Van Der Vynckt, ), neonatal mortality (Marsh et al, ), and managing medico‐social problems through self‐care (Gidado, Obasanya, Adesigbe, Huji, & Tahir, ).…”

Section: Positive Deviancementioning

confidence: 99%

Positive deviance, big data, and development: A systematic literature review

Albanna

Heeks

2018

E J Info Sys Dev Countries

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Positive deviance is a growing approach in international development that identifies those within a population who are outperforming their peers in some way, eg, children in low-income families who are well nourished when those around them are not. Analysing and then disseminating the behaviours and other factors underpinning positive deviance are demonstrably effective in delivering development results. However, positive deviance faces a number of challenges that are restricting its diffusion.In this paper, using a systematic literature review, we analyse the current state of positive deviance and the potential for big data to address the challenges facing positive deviance. From this, we evaluate the promise of "big data-based positive deviance": This would analyse typical sources of big data in developing countries-mobile phone records, social media, remote sensing data, etc-to identify both positive deviants and the factors underpinning their superior performance. While big data cannot solve all the challenges facing positive deviance as a development tool, they could reduce time, cost, and effort; identify positive deviants in new or better ways; and enable positive deviance to break out of its current preoccupation with public health into domains such as agriculture, education, and urban planning. In turn, positive deviance could provide a new and systematic basis for extracting real-world development impacts from big data. KEYWORDS big data, developing countries, machine learning, mobile data, positive deviance, systematic literature review 1 | INTRODUCTIONMany development practitioners continue to use a traditional "needs-based" approach to development, involving top-down identification of needs and problems, and the external imposition of solutions that meet those needs. This type of approach can work well in addressing specific technical challenges. But it works much less well where development requires learning and behavioural change by beneficiary groups, something which necessitates much greater knowledge of and engagement with beneficiary communities (Nel, 2018;Pascale, Sternin, & Sternin, 2010;Saïd Business School, 2010;Singhal, 2011). As a result, more bottom-up "asset-based" approaches have come into existence, which capitalize on a community's inherent assets and capabilities-including knowledge-in solving development problems. Positive deviance (PD) is one such assetbased approach. It is based on the observation that in every group or community, a few individuals use uncommon practices and behaviours to achieve better solutions to problems than their peers who face the same challenges and barriers (Pascale et al., 2010). Those individuals are referred to as "positive deviants" (PDs), and adopting their solutions on a wider basis is referred to as the PD approach.The term "positive deviance" was first used in 1976 to describe a practical strategy for the design of food supplementation programmes in Central America, a strategy that was derived endogenously rather than exogenously through identify...

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Section: Positive Deviancementioning

confidence: 99%

Positive deviance, big data, and development: A systematic literature review

Albanna

Heeks

2018

E J Info Sys Dev Countries

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“…In Mexico, an estimated 191,000 new cases of cancer are diagnosed annually ( AMLCC, 2023 ). A concordance analysis of selected WCRF/AICR recommendations for cancer prevention, which included 790 Mexicans aged 18–70 years, found that no participants adhered to the recommendations ( Vossenaar et al, 2010a ). In the same Mexican population, it was reported that no participants met the WCRF/AICR recommendations of body mass index (BMI) or daily intake of refined sugar ( Vossenaar et al, 2010b ).…”

Section: Introductionmentioning

confidence: 99%

Cancer prevention recommendations: awareness in a Mexican public hospital

Trujillo Rivera,

Sampieri,

Trujillo Rivera

et al. 2024

PeerJ

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Background The recommendations of both the World Cancer Research Fund (WCRF) and the American Institute for Cancer Research (AICR) for the prevention of cancer are important public health tools. These recommendations for the prevention of specific cancers are related to body weight maintenance; physical activity; foods and drinks that promote weight gain; plant foods; foods of animal origin; alcoholic beverages; preservation, processing, and preparation of food; food supplements; and breastfeeding. Methods This study was a descriptive, cross-sectional, retrospective study. All patients provided written informed consent prior to enrollment in the study. Stratified random sampling was carried out with a convenience sample size of ≥280 participants. The characteristics of the participants were investigated using validated questions. Knowledge about the WCRF/AICR recommendations for the primary prevention of cancer was determined using 14 multiple choice questions validated in this study. Group A included participants who answered that cancer can be prevented and that lifestyle is the main factor related to the onset of cancer; the remaining participants were assigned to Group B. The χ2 test and Mann‒Whitney U test were used to determine differences in the groups. A p-value of ≤0.05 was considered statistically significant. A multiple linear regression analysis with gamma response was performed to assess the knowledge score. Results A total of 289 participants were included; 168 (58%) participants were in group A, and 121 (42%) participants were in group B. Using a 0 to 14 scale, the median (P25, P75) number of correct answers was 11 (10, 12). There was no evidence of a difference between groups in sex, relationship status, literacy skills, years of education, occupation, monthly income per person, and BMI. Most of the participants reported that they did not consume tobacco (n = 259/289) or alcohol (n = 261/289) in the week prior to completing the survey. Discussion Most of the participants (58%) considered cancer preventable and agreed that lifestyle factors were the most important factors in cancer development. The results also showed a high level of public awareness of some evidence-based associations between cancer and lifestyle factors, such as tobacco use. Some confusion among the public on other risk factors was also identified: waist circumference, a variable related to excess weight, was not identified as a risk factor for cancer by most of the participants, but the consumption of foods and beverages high in calories was identified as a risk factor by the majority of participants. Awareness of cancer protective and risk factors may lead to positive behavioral changes and eventually reduce the burden of cancer.

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