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American Journal of Lifestyle Medicine logoLink to American Journal of Lifestyle Medicine
. 2016 Aug 19;10(6):369–376. doi: 10.1177/1559827616661690

Theory-Based Interventions for Long-Term Adherence to Improvements in Diet Quality

An In-depth Review

Melissa J Vilaro 1, Daniel Staub 1, Changjie Xu 1, Anne E Mathews 1,✉
PMCID: PMC6124976  PMID: 30202295

Abstract

Many interventions aim to improve dietary patterns but not all are able to maintain these changes long term. Interventions informed by theory may facilitate dietary behavior changes and maintenance of these changes for longer periods of time. PubMed and PsychInfo were searched for theory-based interventions with long-term assessments of fruit and vegetable (FV) and fat intake. We identified 335 unique titles; 20 were included for review. Most interventions (65%) were based on social cognitive theory. Assessments of FV and fat ranged from 12 to 72 months postrandomization, and 15 studies reported significant intervention effects. Only 6 studies directly tested theory in relation to diet and of those, significant findings indicated self-efficacy, motivation for dietary change, perceived competence to eat more FV and less fat, and multiple processes of change were associated with long-term maintenance of healthy eating. Overall, this review indicates that theory-informed interventions are generally successful for long-term improvements in diet quality, although such improvements are often modest. Most studies did not directly measure theoretical constructs in relation to diet outcomes, thus limiting our ability to describe how theory-based interventions specifically promote long-term diet change. Recommendations for future research and practical recommendations for long-term maintenance of diet change are discussed.

Keywords: diet quality, behavioral theory, maintenance, fruit and vegetable intake, dietary fat

‘Interventions that purposefully incorporate theory-based strategies have been recommended for improving dietary behaviors both initially and in the long term.’

Long-term maintenance of positive changes in nutrition habits remains elusive for many people. Although numerous research trials have focused on dietary modification, relatively few have incorporated long-term follow-up and reported successful outcomes with regard to maintenance of behaviors. To support persistent behavior change, the use of theory-based approaches is recommended,1 yet little is known about how theory may directly contribute to the long-term effectiveness of diet interventions.

Interventions that purposefully incorporate theory-based strategies have been recommended for improving dietary behaviors both initially and in the long term.2,3 However, the literature remains equivocal in this area, with some suggesting that commonly used theories, including social cognitive theory (SCT) and the transtheoretical model (TTM), are unlikely to enhance intervention effectiveness for diet change.4 In contrast, a recent systematic review found interventions informed by theory were more successful in improving diet compared with those not utilizing theory2; however, the authors did not specifically examine the long-term impact of such interventions. Several theoretical elements, including self-monitoring, self-efficacy, and goal setting, have been identified as integral features shared by many diverse theories and have been linked to successful diet outcomes.5,6 An examination of theory-based interventions targeting long-term improvements in diet quality, including key components for achieving target outcomes, may provide insight into successful strategies for maintaining behavior change.

The purpose of this review was to identify and describe the components of theory-based interventions capable of generating long-term improvements in diet quality. We focused on studies that sought to improve markers of fruit and vegetable (FV) and fat intake, as these changes are recommended by nearly every major health organization and are primary components of most chronic disease prevention programs. Moreover, a recent analysis of diet quality of US adults from 1999-2012 noted improvements in several dietary components (whole grains, fish, sugar sweetened beverages), but no observed change in total FV or saturated fat intake over the same period of time.7 This null finding for FV and fat highlights the need to identify and analyze interventions capable of achieving sustained improvements in these diet patterns.

Method of Review

We searched the online databases PubMed and PsychInfo for theory-based behavioral lifestyle interventions with a focus on long-term change in dietary patterns as a component of the intervention. The search was conducted on June 9, 2016. For the purpose of this review, long-term was defined as follow-up point(s) ≥12 months postrandomization, irrespective of intervention length. Articles were searched using the following terms: intervention OR program; long-term OR maintenance; diet quality OR diet pattern OR behavior; and theory. After removal of 29 duplicates, a total of 335 unique articles were identified. We further limited articles to those that explicitly stated a behavioral theory as a basis of the intervention and reported change in a dietary outcome among adults with no history of eating disorders. Titles and abstracts were independently reviewed by the four authors, leading to the subsequent exclusion of 305 articles due to lack of compliance with the specified criteria or because they were a review, editorial, or methods paper, or cross-sectional/qualitative in nature. In addition to the 30 remaining articles, 7 articles identified outside of the search were admitted after searching references from relevant papers, particularly a review by Chapman.8 Finally, articles that did not report changes in both FV and fat (total and/or saturated fat) intake and those published prior to 2000 were excluded, thus yielding 20 articles for review. All eligible studies were in the form of randomized controlled trials (RCTs) or cohort randomized trials. Studies with interventions targeting multiple lifestyle behavioral outcomes (physical activity, smoking cessation, etc), as well as those with multiple dietary outcomes in addition to FV and fat intake (fiber, sodium, etc), were admitted for review. However, this review only reports on the outcomes of interest.

Results

The search process identified 20 unique studies with theory-based interventions and assessments of FV and fat intake at periods ≥12 months after randomization. Across all studies, the total number of participants was 28 743 (range 77 to 5407 participants), and intervention lengths ranged from 2 weeks to 48 months. Nearly all studies assessed diet outcomes immediately postintervention. Six studies conducted follow-up assessments at more than 1 long-term time point, with the longest follow-up at 72 months postrandomization. Table 1 provides an overview of the characteristics of included studies.

Table 1.

Characteristics of Studies Included in the Review.

Theory No. of Articles (%) Study Intervention Length (Months) Follow-up (Months Postrandomization) Diet Assessment Method Setting Participants Intervention
Combination 6 (30)
 SCT, TTM, SS, SEM Campbell et al15 18 18 FFQ United States; rural worksite 859 female adults; ≥18 years IL; computer modules + peer support
 SCT, TTM Kristal et al18 12 12 FFQ; 24-hour recall United States; HMO participants 1459 adults; 18-69 years IL; self-help program via print materials, diet
 SCT, SEM Lin et al19 18 18 24-hour recall United States; multisite; research centers 810 adults with hypertension; ≥25 years; BMI 18.5-45 kg/m2 IL + GL; in-person meetings
 SCT, TTM McCarthy et al20 2 12 FFQ United States; community 366 African American female adults GL; in-person meetings with supervised exercise
 SCT, TTM Steptoe et al24 0.5 12 FFQ England; primary care center; urban, low-income community 271 adults; 18-70 years IL; 2 brief in-person counseling sessions + printed materials
 SCT, HBM, TTM Toft et al26 6 12, 36, 60 FFQ Denmark; urban community 9415 adults IL + GL; in-person meetings
SCT Only 7 (35) Hageman et al16 12 12, 18 FFQ United States; rural community 289 female adults; prehypertension; 40-69 years IL; in-person + phone OR newsletters
Mosher et al21 10 12 FFQ United States and Canada; home-delivered 519 adults; breast and prostate cancer history IL; workbook + tailored newsletters
Pakiz et al22 12 12 24-hour recall United States; university research center 77 adults; 18-80 years; high risk for recurrence of colorectal adenomas IL; telephone counseling
Peters et al11 12 12 24-hour recall United States; university research center 86 postmenopausal female adults; 50-72 years; BMI ≥18 and <30 kg/m2 GL; weekly sessions tapering to monthly sessions +newsletters
Pierce et al23 48 48, 72 24-hour recall United States; multisite; research centers 3008 female adults; history of breast cancer; 18-70 years Telephone sessions + cooking classes + newsletters
Stevens et al25 2.5 12 FFQ United States; HMO primary care offices 616 female adults; 40-70 years IL; computer modules and telephone
Winett et al27 3 16 FFQ United States; multisite church-based centers 1071 adults; BMI > 25 kg/m2 IL; internet-based program with church environmental supports
TTM 5 (25) Johnson et al17 9 12, 24 Stages of Change United States; home-delivered; Stages of Change 1277 adults; BMI 25-39.9 kg/m2 IL; assessments with feedback and TTM stage and tools
Kattelmann et al12 2.5 15 FFQ United States; 13 college campuses 1639 college students; 18-24 years IL; internet and email
Prochaska et al32 12 12,24 Diet Behavior Questionnaire United States; home-delivered; primary care offices 5407 adults IL; 3 computer reports with TTM stage and tools
Racette et al10 12 12 NIH FVS and KFFBQ United States; worksite 151 adults IL + GL; assessments with feedback + group meetings
Riebe et al9 6 24 24-hour recall United States; university research center 144 adults; ≥18 years; BMI 27-40 kg/m2 GL; in-person meetings with supervised exercise
SDT 1 (5) Brown et al14 12 12,18 FFQ US; SHARE study; recruited in Catholic churches 801 adults; ≥18 years; Hispanic/Latino or non-Hispanic white IL; partner enrollment; combination of self-help; in-person workshop; 5 phone calls; newsletters
TPB 1 (5) Griffin et al13 12 12 Plasma vitamin C + FFQ England; ADDITION-Plus study; recruited from primary care 478 adults; 40-69 years; new type 2 diabetes IL; 7 in-person meetings + 4 phone calls
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Abbreviations: BMI, body mass index; FFQ, Food Frequency Questionnaire; GL, group level; HBM, health belief model; HMO, health maintenance organization; IL, individual level; KFFBQ, Kristal Fat and Fiber Behavior Questionnaire; NIH FVS, National Institutes of Health Fruit and Vegetable Screener; SCT, social cognitive theory; SDT, self-determination theory; SEM, social ecological model; SS, social support; TPB, theory of planned behavior; TTM, transtheoretical model.

Overall, 15 studies demonstrated a significant intervention effect (between-group differences) for either FV and/or fat at 1 or more long-term follow-up. Three studies did not report a significant intervention effect for either FV or fat but rather reported a significant change from baseline, indicating a within-group difference at a long-term follow-up.9-11 Two studies12,13 did not report significant findings for FV or fat outcomes at any long-term follow-up (Table 2).

Table 2.

Significant Improvements in Fruit and Vegetable or Fat Intake at Long-Term Follow-up Time Points by Theory.

12 Months 16 Months 18 Months 24 Months 36 Months 48 Months 60 Months 72 Months
Fruit and vegetable
Theory
 Combination (SCT + other) Steptoe,a,b Kristal,a,b Toft,a,c McCarthya Winetta Campbell,a Lina,b Tofta Tofta,c
 SCT Mosher,a Peters,b Pakiz,a Pierce,a Stevensa,b Haegmana Piercea Piercea
 SDT Browna
 TTM Proschaska,a,b Racette,b Johnsona Proschaska,a,b Johnsona
Fat
Theory
 Combination (SCT + other) Steptoe,b Kristal,a,b Toft,b McCarthyb Linb Toftb Tofta,b
 SCT Mosher,a Peters,b Pakiz,a Pierce,a Stevensa,b Haegmana Piercea Piercea
 SDT Browna
 TTM Riebe,b Proschaska,a,b Racette,b Johnsona Riebe,b Proschaska,a,b Johnsona
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Abbreviations: SCT, social cognitive theory; SDT, self-determination theory; TTM, transtheoretical model.

a

Difference between intervention and control group at time point (between-group difference).

b

difference from baseline at timepoint (within-group difference).

c

Vegetable only.

Long-Term Changes in Fruit, Vegetable, and Fat Intake

Fifteen studies reported significant between-group differences for increased FV intake at 1 or more long-term follow-up, indicating a successful intervention effect14-27 (Table 2). Of the 5 studies that did not achieve long-term intervention effects for FV increases: Kattelmann et al12 reported significant between-group differences at a 3-month assessment, although those findings had attenuated by the long-term follow-up; Griffin et al13 had a usual care control group that may have obscured significant findings; Riebe et al9 reported unexpected findings with a significant decrease in FV intake at 24 months; and both Peters et al11 and Racette et al10 had significant increases in FV from baseline but not compared with a control group. About half of the studies in this review (8 studies) reported intervention effects for FV intake that extended beyond 12 months. Two studies measured and were successful at maintaining an increase in FV intake at 36 months or more23,26; however, while Toft et al26 reported a significant intervention effect for FV at 36 months, the differences only remained for vegetables at the 60-month follow-up. Of the 4 studies with multiple follow-up time points, only Pierce et al23 reported regression toward baseline intake values. However, this study utilized the longest follow-up period of all studies and achieved recommended levels of intake for FV at all long-term time points.

Regarding dietary fat, 10 studies had significant intervention effects for reducing intake of total fat or saturated fat as a result of a theory-based intervention (Table 2). The distribution of significant long-term findings for reductions in dietary fat was similar to those of FV findings. However, changes in fat were less likely to be reported as intervention effects (between-group differences) and more commonly were reported as differences from baseline to follow-up.

Theoretical Aspects of Long-Term Diet Change

A majority of interventions (65%) in this review utilized SCT,28 either alone (7 studies) or in combination with at least 1 other theory (6 studies). The TTM29 was the next most prevalent theory (5 studies), while self-determination theory (SDT)30 and the theory of planned behavior (TPB)31 were the basis of 1 study each (Table 1). In this issue, a brief description of these theories is provided by Joseph et al.3 Of the 18 studies with significant changes at any long-term follow-up, 10 explicitly linked theory or a theoretical construct to outcome success in their results or in the discussion of the results* and 6 directly tested theoretical constructs in relation to diet outcomes.9,14,17,18,21,32

Social Cognitive Theory–Based Interventions

SCT was the theory most frequently cited out of all interventions that achieved significant long-term intervention effects for FV or fat (12 of 15 studies). SCT-based interventions primarily focused on components such as goal-setting, self-efficacy, addressing barriers, knowledge of risks and benefits, and motivation. Among all studies utilizing SCT, only that of Mosher et al21 explicitly tested any theoretical construct and found that changes in self-efficacy were associated with improved diet. Only 3 out of 7 studies using a theory other than SCT14,17,32 reported significant between-group differences at a long-term follow-up.

Transtheoretical Model–Based Interventions

Four TTM-based interventions reporting significant intervention effects9,17,18,32 explicitly stated that theory played a role in the intervention’s success and also directly measured a component of the theory. Johnson et al’s17 individually tailored, stage-based intervention was successful for moving intervention participants (in preaction stage at baseline) to action or maintenance for consuming recommended amounts of FV and fat. Prochaska et al32 had similar findings with a multi-behavior, stage-based intervention, showing treatment effects for moving participants to action or maintenance for reducing fat and increasing FV consumption. Kristal et al18 delivered an intervention based on TTM and SCT and measured participants’ movement through stages of dietary change for fat and FV. In contrast to Johnson et al17 and Proschaka et al32 who used behavioral criterion when measuring stage (eg, readiness to consume less than 30% energy from fat or five servings of FV per day), Kristal et al18 measured stage of change as a “measure of cognitive and behavioral engagement in the diet change process” with self-reported ratings of “very low, low, in the middle, high or very high” consumption of fat or fruits and vegetables and found significant intervention effects for FV and fat but only for those already in action or maintenance, and not preaction stages. Riebe et al9 measured decisional balance, processes of change, and self-efficacy in relation to dietary outcomes and found a significant reduction from baseline to follow-up for saturated fat intake but, similar to Kristal et al,18 found that changes were larger for those already in action stages. Additionally, Riebe et al9 found a significant increase in FV intake from 5.4 servings per day at baseline to 5.7 servings per day at 6-month follow-up. However, at 12 and 24 months, FV intake significantly decreased below baseline levels to 4.9 and 4.4 servings per day, respectively.

Theory of Planned Behavior– or Self-Determination Theory–Based Interventions

Only 1 study in this review utilized TPB, and the authors did not report any long-term change in FV or fat.13 The 1 study that based its intervention on SDT reported an intervention effect for both fat and FV and also directly tested constructs in relation to the theory. Specifically, changes in lack of motivation for dietary change and perceived competence to eat more FV were significant among the treatment group. In this study, there was an intervention effect for both FV and fat; however, authors described that it is more likely that the intervention prevented a decline in the treatment group rather than encouraged an increase.

Discussion

The current article provides an in-depth review of recent theory-based interventions that facilitated maintenance of long-term changes in FV and/or fat consumption. Of the 20 articles in this review, 18 reported significant findings for either FV and/or fat at 1 or more long-term assessments; however, only 15 described intervention effects signaling that the theory-based intervention played a role in promoting dietary changes. Only half of the studies referenced theory in the discussion of their findings or described findings in relation to the theory used, and even fewer studies9,14,17,18,21,32 (6 studies) explicitly measured a theoretical construct and analyzed it in relation to a dietary outcome measure. Additionally, even when theory was explicitly measured, the theory as a whole was not evaluated (ie, only selected constructs of the theory directly tested).

With regard to theory, SCT, either alone or in combination with other theoretical models, was by far the most prominent theoretical basis for interventions. Despite the prevalence of SCT-based interventions in this review, only 1 study directly measured any construct related to the theory. Mosher et al21 based the FRESH START intervention on SCT, which has a number of core constructs including self-efficacy, self-regulation, outcome expectations, and observational learning among others.33 Even though it was the authors’ stated purpose to focus specifically on self-efficacy due to it being one of the primary constructs in SCT and due to the lack of other research formally evaluating self-efficacy as a mediator of the effects on diet, self-efficacy alone does not comprise the theory. Therefore, identifying relationships between individual constructs and diet outcomes may be useful for making recommendations regarding the construct measured, but interpretations regarding the use of the whole theory should be based on more inclusive evaluations. This limits our ability to draw conclusions about the specific impact of theory on long-term diet changes.

Studies utilizing TTM were the most consistent regarding overall testing of theory in relation to diet change. Out of 4 TTM-only studies with significant long-term diet outcomes, 3 studies explicitly measured stage of change.9,17,32 The fourth study created an intervention that addressed multiple stages of TTM, but it neither individually tailored the intervention nor measured stages of participants.10 Another study18 utilized a combination of TTM and SCT for their intervention and measured movement through TTM stages but no SCT constructs. Common components of TTM-based interventions cited in this review included goal setting, stimulus control, relapse prevention, stage-tailored communications, and enhancing motivation. Only Riebe et al9 measured multiple constructs of TTM in addition to stage of change for dietary behavior and reported significant relationships between 4 distinct constructs and the ability to maintain dietary fat at less than 25% total intake at 2 years. However, this study did not report a significant intervention effect for either fat or FV and actually found lower intake of FV at long-term follow-up.

Several limitations of this review are noted. Although most studies reported significant long-term diet change, very few reported participants achieving and maintaining recommended intakes. Current dietary guidelines recommend limiting saturated fat to less than 10% of total energy intake per day.34 Many of the studies in this review reported a reduction in total dietary fat as an outcome variable. Only 2 studies14,16 specifically noted a significant reduction in saturated fat, and only 1 study16 discussed findings in relation to meeting the current recommended intake of less than 10% of total energy from saturated fat. Based on supplemental data, Brown et al14 likely achieved recommended intakes of saturated fat, although findings were not explicitly stated as such. A similar limitation exists with reports of FV intake. Studies reporting a significant intervention effect for FV intake typically saw only modest increases, and only 1 study reported FV intake meeting the recommended levels of 3 servings of vegetables and 2 servings of fruit per day.34 Another limitation is found in the diversity of measurement procedures used for assessing diet outcomes, making it difficult in some cases to ascertain if recommended levels were achieved. Many studies had multiple follow-up time points and, in most cases, reported detailed descriptions of within-group and between-group differences at each time point. However, in some cases when treatment effects (based on intervention) were reported, we were unable to assess if there were also significant within-group differences.

Practical Recommendations

This review elucidated constructs that have been related to long-term maintenance and therefore might be successful if used by practitioners or those attempting to counsel on maintenance of dietary improvements. The specific theoretical components of interventions directly measured and explicitly linked to maintenance of diet change (increase in FV or decrease in fat) included self-efficacy or self-efficacy-related constructs such as motivation and competence.9,14,21 Thus, integrating behavior change techniques that address self-efficacy may be useful when the goal is to maintain long-term changes in FV and/or fat. Additionally, many of the theory-based interventions reviewed utilized tailored feedback, including individualized reports of dietary intake and messages relevant to the population of interest, with most TTM interventions including messages tailored to the stage of change. More detailed evaluations of theory’s role in long-term adherence to dietary improvements is needed, specifically direct measures of theory in relation to long-term maintenance of diet quality.

Footnotes

*

References 9, 11, 14, 15, 17-19, 21, 26, 32.

References

  • 1. Craig P, Dieppe P, Macintyre S, Michie S, Nazareth I, Petticrew M. Developing and evaluating complex interventions: the new Medical Research Council guidance. Int J Nurs Stud. 2013;50:587-592. [DOI] [PubMed] [Google Scholar]
  • 2. Avery KN, Donovan JL, Horwood J, Lane JA. Behavior theory for dietary interventions for cancer prevention: a systematic review of utilization and effectiveness in creating behavior change. Cancer Causes Control. 2013;24:409-420. [DOI] [PubMed] [Google Scholar]
  • 3. Joseph RP, Daniel CL, Thind H, Benitez TJ, Pekmezi D. Applying psychological theories to promote long-term maintenance of health behaviors [published online October 14, 2016]. Am J Lifestyle Med. doi: 10.1177/1559827614554594. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4. Prestwich A, Sniehotta FF, Whittington C, Dombrowski SU, Rogers L, Michie S. Does theory influence the effectiveness of health behavior interventions? Meta-analysis. Health Psychol. 2014;33:465-474. [DOI] [PubMed] [Google Scholar]
  • 5. Ammerman AS, Lindquist CH, Lohr KN, Hersey J. The efficacy of behavioral interventions to modify dietary fat and fruit and vegetable intake: a review of the evidence. Prev Med. 2002;35:25-41. [DOI] [PubMed] [Google Scholar]
  • 6. Michie S, Abraham C, Whittington C, McAteer J, Gupta S. Effective techniques in healthy eating and physical activity interventions: a meta-regression. Health Psychol. 2009;28:690-701. [DOI] [PubMed] [Google Scholar]
  • 7. Rehm CD, Penalvo JL, Afshin A, Mozaffarian D. Dietary intake among US adults, 1999-2012. JAMA. 2016;315:2542-2553. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8. Chapman K. Can people make healthy changes to their diet and maintain them in the long term? A review of the evidence. Appetite. 2010;54:433-441. [DOI] [PubMed] [Google Scholar]
  • 9. Riebe D, Blissmer B, Greene G, et al. Long-term maintenance of exercise and healthy eating behaviors in overweight adults. Prev Med. 2005;40:769-778. [DOI] [PubMed] [Google Scholar]
  • 10. Racette SB, Deusinger SS, Inman CL, et al. Worksite Opportunities for Wellness (WOW): effects on cardiovascular disease risk factors after 1 year. Prev Med. 2009;49:108-114. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11. Peters NC, Contento IR, Kronenberg F, Coleton M. Adherence in a 1-year whole foods eating pattern intervention with healthy postmenopausal women. Public Health Nutr. 2014;17:2806-2815. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12. Kattelmann KK, Bredbenner CB, White AA, et al. The effects of Young Adults Eating and Active for Health (YEAH): a theory-based web-delivered intervention. J Nutr Educ Behav. 2014;46:S27-S41. [DOI] [PubMed] [Google Scholar]
  • 13. Griffin SJ, Simmons RK, Prevost AT, et al. Multiple behaviour change intervention and outcomes in recently diagnosed type 2 diabetes: The ADDITION-Plus randomised controlled trial. Diabetologia. 2014;57:1308-1319. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14. Brown DL, Conley KM, Sánchez BN, et al. A multicomponent behavioral intervention to reduce stroke risk factor behaviors: the Stroke Health And Risk Education cluster-randomized controlled trial. Stroke. 2015;46:2861-2867. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15. Campbell MK, Tessaro I, DeVellis B, et al. Effects of a tailored health promotion program for female blue-collar workers: health works for women. Prev Med. 2002;34:313-323. [DOI] [PubMed] [Google Scholar]
  • 16. Hageman PA, Pullen CH, Hertzog M, Boeckner LS. Effectiveness of tailored lifestyle interventions, using web-based and print-mail, for reducing blood pressure among rural women with prehypertension: main results of the Wellness for Women: DASHing towards Health clinical trial. Int J Behav Nutr Phys Act. 2014;11:148. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17. Johnson SS, Paiva AL, Cummins CO, et al. Transtheoretical model-based multiple behavior intervention for weight management: effectiveness on a population basis. Prev Med. 2008;46:238-246. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18. Kristal AR, Curry SJ, Shattuck AL, Feng Z, Li S. A randomized trial of a tailored, self-help dietary intervention: The Puget Sound Eating Patterns study. Prev Med. 2000;31:380-389. [DOI] [PubMed] [Google Scholar]
  • 19. Lin PH, Appel LJ, Funk K, et al. The PREMIER intervention helps participants follow the dietary approaches to stop hypertension dietary pattern and the current dietary reference intakes recommendations. J Am Diet Assoc. 2007;107:1541-1551. [DOI] [PubMed] [Google Scholar]
  • 20. McCarthy WJ, Yancey AK, Harrison GG, Leslie J, Siegel JM. Fighting cancer with fitness: dietary outcomes of a randomized, controlled lifestyle change intervention in healthy African American women. Prev Med. 2007;44:246-253. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21. Mosher CE, Fuemmeler BF, Sloane R, et al. Change in self-efficacy partially mediates the effects of the FRESH START intervention on cancer survivors’ dietary outcomes. Psychooncology. 2008;17:1014-1023. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22. Pakiz B, Flatt S, Mills KC, Jordan LJ, Carethers JM, Rock CL. Quality of life and diet intervention in individuals at risk for recurrence of colorectal adenomas. Psychooncology. 2005;14:85-93. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23. Pierce JP, Natarajan L, Caan BJ, et al. Influence of a diet very high in vegetables, fruit, and fiber and low in fat on prognosis following treatment for breast cancer: the Women’s Healthy Eating and Living (WHEL) randomized trial. JAMA. 2007;298:289-298. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24. Steptoe A, Perkins-Porras L, McKay C, Rink E, Hilton S, Cappuccio FP. Behavioural counselling to increase consumption of fruit and vegetables in low income adults: randomised trial. BMJ. 2003;326:855. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25. Stevens VJ, Glasgow RE, Toobert DJ, Karanja N, Smith KS. One-year results from a brief, computer-assisted intervention to decrease consumption of fat and increase consumption of fruits and vegetables. Prev Med. 2003;36:594-600. [DOI] [PubMed] [Google Scholar]
  • 26. Toft U, Kristoffersen L, Ladelund S, et al. The impact of a population-based multi-factorial lifestyle intervention on changes in long-term dietary habits: the Inter99 study. Prev Med. 2008;47:378-383. [DOI] [PubMed] [Google Scholar]
  • 27. Winett RA, Anderson ES, Wojcik JR, Winett SG, Bowden T. Guide to health: nutrition and physical activity outcomes of a group-randomized trial of an Internet-based intervention in churches. Ann Behav Med. 2007;33:251-261. [DOI] [PubMed] [Google Scholar]
  • 28. Bandura A. Social Foundations of Thought and Action: A Social Cognitive Framework. Englewood Cliffs, NJ: Prentice Hall; 1986. [Google Scholar]
  • 29. Prochaska JO, DiClemente CC. The Transtheoretical Approach: Crossing Traditional Boundaries of Therapy. Homewood, IL: Dow Jones Irwin; 1984. [Google Scholar]
  • 30. Ryan RM, Deci EL. Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. Am Psychol. 2000;55:68-78. [DOI] [PubMed] [Google Scholar]
  • 31. Ajzen I. From intentions to actions: A theory of planned behavior. In: Kuhl J, Beckmann J. eds. Action Control: From Cognition to Behavior. Heidelberg, Germany: Springer; 1985:1-39. [Google Scholar]
  • 32. Prochaska JO, Velicer WF, Redding C, et al. Stage-based expert systems to guide a population of primary care patients to quit smoking, eat healthier, prevent skin cancer, and receive regular mammograms. Prev Med. 2005;41:406-416. [DOI] [PubMed] [Google Scholar]
  • 33. Bandura A. Self-efficacy: toward a unifying theory of behavioral change. Psychol Rev. 1977;84:191-215. [DOI] [PubMed] [Google Scholar]
  • 34. US Department of Health and Human Services and US Department of Agriculture. 2015-2020 Dietary Guidelines for Americans. 8th ed. Washington, DC: US Department of Health and Human Services; 2015. http://health.gov/dietaryguidelines/2015/guidelines/. Accessed July 12, 2016. [Google Scholar]

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