0
We're unable to sign you in at this time. Please try again in a few minutes.
Retry
We were able to sign you in, but your subscription(s) could not be found. Please try again in a few minutes.
Retry
There may be a problem with your account. Please contact the AMA Service Center to resolve this issue.
Contact the AMA Service Center:
Telephone: 1 (800) 262-2350 or 1 (312) 670-7827  *   Email: subscriptions@jamanetwork.com
Error Message ......
Original Investigation |

A Randomized Trial Comparing Human e-Mail Counseling, Computer-Automated Tailored Counseling, and No Counseling in an Internet Weight Loss Program FREE

Deborah F. Tate, PhD; Elizabeth H. Jackvony, MPH; Rena R. Wing, PhD
[+] Author Affiliations

Author Affiliations: Schools of Public Health and Medicine, Department of Health Behavior and Health Education/Department of Nutrition, University of North Carolina, Chapel Hill (Dr Tate); and Weight Control and Diabetes Research Center, Miriam Hospital (Ms Jackvony and Dr Wing); and Brown University School of Medicine (Dr Wing), Providence, RI.


Arch Intern Med. 2006;166(15):1620-1625. doi:10.1001/archinte.166.15.1620.
Text Size: A A A
Published online

Background  Several studies have shown that e-mail counseling improves weight loss achieved in self-directed Internet programs. Computer-tailored feedback offers a population-based alternative to human e-mail counseling.

Methods  One hundred ninety-two adults, aged 49.2 ± 9.8 years, having a body mass index (calculated as weight in kilograms divided by height in meters squared) of 32.7 ± 3.5, were randomized to 1 of 3 Internet treatment groups: No counseling, computer-automated feedback, or human e-mail counseling. All participants received 1 weight loss group session, coupons for meal replacements, and access to an interactive Web site. The human e-mail counseling and computer-automated feedback groups also had access to an electronic diary and message board. The human e-mail counseling group received weekly e-mail feedback from a counselor, and the computer-automated feedback group received automated, tailored messages.

Results  Retention was 82% at 3 months and 80% at 6 months for all 3 groups. At 3 months, completers in both the computer-automated feedback (−5.3 ± 4.2 kg) and human e-mail counseling (−6.1 ± 3.9 kg) groups had significantly greater weight losses compared with the no counseling group (−2.8 ± 3.5 kg) and these groups did not differ from each other. At 6 months, weight losses were significantly greater in the human e-mail counseling group (−7.3 ± 6.2 kg) than in the computer-automated feedback (−4.9 ± 5.9 kg) or no counseling (−2.6 ± 5.7 kg) groups. Intent-to-treat analyses using single or multiple imputation techniques showed the same pattern of significance.

Conclusions  Providing automated computer-tailored feedback in an Internet weight loss program was as effective as human e-mail counseling at 3 months. Further research is needed to improve the efficacy of automated computer-tailored feedback as a population-based weight loss approach.

Trial Registration  clinicaltrials.gov Identifier: NCT00200304.

Figures in this Article

The Internet has increasingly been used to provide behavioral change interventions, and several studies13 have demonstrated its potential for delivering weight control therapy. In 2 of these studies,1,2 better weight losses were produced by programs in which a human counselor provided weekly e-mail behavioral weight loss counseling compared with Internet programs that were self-directed and involved no weekly guidance. Although providing Internet weight loss programs with e-mail counseling may offer an alternative to in-person programs, if effective counseling were provided by a computer preprogrammed with messages based on performance criteria, Internet weight management interventions could be a more widely disseminable treatment approach. The goal of this study was to determine the short-term efficacy of a self-directed Internet weight loss program compared with the same program supplemented with behavioral counseling from either a computer-automated tailored system or from a human counselor.

PARTICIPANTS

One hundred ninety-two (162 female, 30 male) overweight or obese adults with a mean ± SD age of 49.2 ± 9.8 years and having a body mass index (calculated as weight in kilograms divided by height in meters squared) of 32.7 ± 3.5 were recruited from advertisements placed in local newspapers and screened for eligibility via telephone (Figure 1). Eligibility criteria included age 20 to 65 years, body mass index of 27 to 40, willingness to use meal replacements as part of the dietary regimen, and availability of a computer with Internet access (dial-up or high-speed service). Criteria for ineligibility included a history of heart attack, stroke, or cancer in the past 5 years; diabetes, angina, or orthopedic or joint problems that would prohibit exercise; a major psychiatric disorder involving hospitalization during the past year; and current, planned, or previous (within 6 months) pregnancy. Individuals endorsing any item on the Physical Activity Readiness Questionnaire4 (n = 79 [21%]) were required to obtain physician consent to participate in this study.

Place holder to copy figure label and caption
Figure 1.

Participant flowchart. AF indicates tailored computer-automated feedback; BMI, body mass index (calculated as weight in kilograms divided by the square of height in meters); HC, human e-mail counseling; ITT, intention-to-treat; and NC, no counseling.

Graphic Jump Location
DESIGN

Written informed consent and baseline measurements were obtained in person. Participants were advised during informed consent that, despite password protection, potential breaches in confidentiality existed when using the Web site and e-mail. Simple randomization procedures with computerized random numbers were used to assign participants to 1 of 3 treatment groups: no counseling (NC; n = 67); computer-automated e-mail feedback (AF, n = 61); or human e-mail counseling (HC, n = 64). All participants were seen in the clinic at baseline and at 3 and 6 months for objective measurement of body weight and completion of questionnaires, and they were paid $25.00 and $50.00, respectively, for attending the 3- and 6-month follow-up appointments.

All participants attended 1 group face-to-face session (approximately 25 participants per group) in which they were informed of random assignment, introduced to behavioral weight loss recommendations for diet, exercise, and behavioral changes that are typical in in-person behavioral weight loss programs,5 and oriented to the Internet programs. A standard script and slide set were used to ensure comparability of weight loss recommendations; however, orientation to the Web sites differed by group.

A standard calorie-restricted diet of 1200 to 1500 kcal/d was recommended based on baseline weight. Participants were instructed about the use of structured meals6 and meal replacements7 as helpful strategies for meeting caloric goals. Two meal replacements per day consisting of a liquid weight loss beverage (Slim-Fast; Unilever, London, England) were recommended to equal about 440 kcal/d of total daily calories. The remaining calories were to be consumed from foods and beverages of the participants' choosing. All participants were provided with meal replacements for the first week and then given coupons ($2.00/wk) to offset the price of meal replacements. All participants were encouraged to increase physical activity over time to expend a minimum of 1050 kcal/wk equivalent to approximately 30 minutes of walking per day and to self-monitor diet and exercise daily.

All participants were instructed on how to use the Slim-Fast Web site, which is free to the public. This interactive Web site included the following features: weekly reporting and graphs of weight, weekly e-mail prompts to report weight, weekly weight loss tips via e-mail, recipes, and a weight loss e-buddy network system that enabled users to match themselves with other persons in the United States with similar characteristics and act as peer support for weight loss via e-mail.

ADDITIONAL PROCEDURES FOR e-COUNSELING GROUPS

Participants randomized to the 2 e-counseling groups (AF and HC) also had access to a separate Web site that offered additional features specific to the research study, including an electronic diary (to report weight, daily caloric intake, use of meal replacements, and exercise) and a message board on which they could post messages to other study participants randomized to the same study group. In addition, these participants received a second weekly e-mail that reminded them to complete the online diary and included a weekly behavioral lesson on topics similar to those used in the Diabetes Prevention Program.8

The difference between the two e-counseling groups was the feedback participants received in response to their self-monitoring diaries. Weekly feedback was either from a preprogrammed computer that instantaneously returned tailored feedback on a Web page when the weight loss diary was submitted (AF) or via e-mail from a human weight loss counselor whom they had not met with in person (HC).

In the AF condition, feedback algorithms were predetermined based on cognitive-behavioral theory, focused specifically on behavioral changes from week to week, and suggested behavioral strategies to improve adherence and weight loss. A computer-tailored message was compiled instantaneously based on the weekly diary information. Weekly and average weight losses were compared with expected weight losses corresponding to the week in the program. Praise or feedback to build motivation for self-monitoring was included depending on the frequency of monitoring. Reported calories were compared with individualized goals. If calories were above the recommended level, suggestions for reducing calories were provided. Use of meal replacements was encouraged as one strategy to control caloric intake. A variety of portion-controlled meals were recommended when adherence was low, such as liquid shakes (eg, Slim-Fast), prepackaged frozen entrees (eg, Lean Cuisine [Stouffers, a division of Nestlé] or Weight Watchers' Smart Ones [H. J. Heinz Co]), a variety of meal bars, or other prepackaged foods that met caloric requirements of a low-calorie meal (eg, canned soup). The number of calories expended in physical activity was compared with the weekly goal. When exercise was less than prescribed, strategies for overcoming a variety of barriers were suggested. Finally, a summary compared reported behaviors with weight loss progress; provided ongoing support, praise, or motivation; and suggested next steps. In the HC condition, participants were randomized to 1 of 5 human e-counselors with behavioral weight loss experience and degrees in nutrition, exercise physiology, psychology, or health education. All human e-counselors were blinded to the algorithms used to program the AF counselor and were trained and supervised using procedures from other behavioral e-counseling weight loss trials.1,2 Although messages were individualized, e-counselors generally considered weekly weight loss compared with overall progress, progress toward behavioral goals, overcoming specific weight loss barriers, motivation, and answers to participants' questions. There was no predefined structure or content for HC e-mails, and counselors prioritized and selected the focus of the communication based on their clinical judgment.

DEPENDENT MEASURES

The primary dependent measure was change in body weight. Weight was measured in the clinic at baseline and at 3 and 6 months with the participant in lightweight street clothing, without shoes, on a calibrated scale, by nonintervention research staff. Height was measured using a wall-mounted stadiometer at baseline. Physical activity was measured using the activity questionnaire of Paffenbarger et al.9 Dietary intake was measured using the Block Food Frequency questionnaire.10 These questionnaires have shown sensitivity to behavioral changes in other weight loss intervention trials.11,12 Login frequency and use of various site components were assessed using objective recordings of Web site use.

STATISTICAL ANALYSIS

This study was powered based on previous Internet weight loss studies1,2 and designed to detect differences in weight loss of 2.5 kg with an SD of 5 kg (an effect size of 0.5) with 80% power. Primary and secondary outcomes were examined separately using repeated-measures analysis of variance. Nonparametric tests or transformations were used when data were abnormal. Bonferroni adjustments were used for all multiple comparisons. Unless noted, all data are reported as mean ± SD. For intention-to-treat analyses, a range of possible imputation methods were used, including single imputation (baseline carried forward and last observation carried forward) and multiple imputation (expectation maximization and regression). All analyses were performed using Statistical Package for the Social Sciences software (version 13 for Windows; SPSS, Chicago, Ill).

At baseline, there were no differences between randomized groups on measures of age, weight, body mass index, calorie and fat intake, exercise, or years of Web or Internet experience (Table 1). Eighty-two percent of participants randomized (n =158) attended the 3-month assessment; attendance did not vary by treatment assignment (χ2 = 2.3; P = .31). Eighty percent of those randomized (n = 155) attended the 6-month assessment; there was a trend for fewer participants in the AF group to attend the follow-up assessments (χ2 = 5.2, P = .07). Six-month attendees and nonattendees did not differ at baseline for age, body mass index, years of Internet experience, or hours of weekly Internet use. There were no significant adverse events in any intervention group.

CLINICAL OUTCOMES: BODY WEIGHT

The pattern of weight change was examined with observed data (completers) and several intent-to-treat analysis strategies, including both single imputation strategies common to weight loss (baseline carried forward considered a conservative approach assuming return to baseline weight for missing data and last observation carried forward) and 2 multiple imputation strategies (expectation maximization and regression). The pattern of statistical significance using repeated-measures analysis of variance of observed or imputed weights at baseline and at 3 and 6 months was identical. Mean weight losses using various imputation strategies are given in Table 2. Weight losses for participants with observed data were −2.8 ± 3.5 kg (NC), −5.3 ± 4.2 kg (AF), and −6.1 ± 3.9 kg (HC). Weight lost between baseline and 3 months differed significantly by group (F = 9.4; P<.001). Both the AF and HC groups lost significantly more weight than did the NC group (P = .005 and P = .001, respectively), but they did not differ from each other (P = .95). Weight loss at 6 months was −2.6 ± 5.7 kg, −4.9 ± 5.9 kg, and −7.2 ± 6.2 kg, respectively, for the NC, AF, and HC groups (P = .001). Weight loss was significantly different in the NC and HC groups (P<.001). The AF condition did not differ significantly from the NC or HC conditions (AF vs NC, P = .16; AF vs HC, P = .15; Figure 2).

Place holder to copy figure label and caption
Figure 2.

Changes in body weight (observed data). Error bars indicate the 95% confidence interval of the mean; AF, tailored computer-automated feedback; HC, human e-mail counseling; and NC, no counseling.

Graphic Jump Location
Table Graphic Jump LocationTable 2. Mean Weight Loss With Observed Data and Various Intent-to-Treat Imputation Techniques*

The mean percent of initial body weight lost at 3 months was −3.2% ± 3.7%, −5.8% ± 4.4%, and −6.8% ± 3.9%, and at 6 months was −2.8% ± 5.9%, −5.3% ± 6.5%, and −8.1% ± 6.3%, in the NC, AF, and HC groups, respectively. At 6 months (assuming participants with missing data did not achieve significant weight loss), the percent of randomized participants who lost 5% or more of initial body weight was 27% in the NC group, 34% in the AF group, and 52% in the HC group (χ2 = 8.9; P = .01). Post hoc comparisons showed that significantly more participants in the HC group compared with the NC group lost 5% or more of their initial body weight (P<.05).

SECONDARY OUTCOMES: DIETARY INTAKE AND EXERCISE

Mean (±SD) scores on behavioral variables are given in Table 3. The treatment-×-time interaction for calorie intake was not significant. All groups reported significant reductions in caloric intake between baseline and 6 months (F = 35.5; P<.001). Percent of calories from dietary fat differed by treatment group (F = 5.8; P = .004), with greater reductions in the HC group compared with the NC group. Repeated-measures analysis of variance of log-transformed energy expenditure data showed no treatment-×-time interaction; however, all groups showed increased physical activity during the first 3 months, which subsequently declined between 3 and 6 months (F = 6.7; P = .001).

Table Graphic Jump LocationTable 3. Mean Energy Intake and Physical Activity*
WEB SITE LOGIN FREQUENCY

Web site use consisted primarily of 2 parts: a public site available to all groups and diary submissions available to only the AC and HC groups. Login data were abnormal; therefore, median analyses were used. The groups differed in the frequency of logins to both sites (total logins) over the 6-month period (Kruskal-Wallis χ2, 11.9; P = .003). Post hoc comparisons showed that the NC and HC groups logged in significantly more often than the AF group did. The median number of total logins to the Web sites was 34, 20, and 32.5 times, respectively, for the NC, AF, and HC groups. The pattern of logins for each month during the 6 months of treatment is shown by treatment group in Figure 3. Total login frequency was associated with weight loss at 6 months in both the completers (Spearman ρ, −0.38; P = .000) and baseline carried forward (Spearman ρ, −0.15; P = .04) analyses.

Place holder to copy figure label and caption
Figure 3.

Participant monthly login frequency. Reference line indicates 4 logins per month. This frequency is equivalent to the expected frequency of online diary submissions in the e-counseling groups (once per week). Error bars indicate the 95% confidence interval of the mean; AF, tailored computer-automated feedback; HC, human e-mail counseling; and NC, no counseling.

Graphic Jump Location

The median number of logins to the public Web site during the 6 months was 20, 2, and 9, respectively, for the NC, AF, and HC groups (Kruskal-Wallis χ2, 13.8; P = .001). Greater use of the public Web site was correlated with weight loss in the NC group (Spearman ρ, −0.27; P = .03) but not in the AF (Spearman ρ, −0.14; P = .29) or HC (Spearman ρ, −0.16; P = .22) groups.

Online diary submissions were examined for the 2 e-counseling groups—AF and HC. Participants in the HC group submitted diaries for more weeks (17.2 ± 8.7 vs 11.4 ± 9.2; P = .000). Diary submission was significantly associated with weight loss in the AF (r = −0.69) and HC (r = −0.56) groups (P<.001).

Finding population-based methods for providing behavioral weight loss interventions is urgently needed. This study shows that an Internet behavioral weight loss program providing weekly feedback about weight, diet, and activity from either a computer-automated program or a human e-mail counselor produced significant weight loss and that both were significantly more effective during the first 3 months than was a weight loss Web site that provided no feedback on behavioral change. At 6 months, the group receiving feedback from the human e-counselor had greater overall weight loss compared with the NC group; the AF group did not differ significantly from either of the other groups.

Few studies have examined the use of fully automated computer or Internet programs for weight loss involving no human contact.13 The present study tested the efficacy of an Internet program that included fully computer-automated feedback to participants about weight loss behaviors and their change over time. For the first 3 months, weight loss was comparable in the AF and HC groups, which suggests that computer feedback was sufficient to promote short-term adherence to the diet and activity goals. From a public health perspective, this is a promising direction to explore. The weight loss in this group averaged 4 to 5 kg (approximately 5% of initial body weight), and 34% of those randomized achieved a weight loss of 5% or more: a clinically meaningful weight loss. Weight loss in the group receiving 1 weekly e-mail from a human counselor is also encouraging, inasmuch as average weight loss of 6 to 7 kg (approximately 7%-8% of initial body weight) was achieved and more than 50% of participants randomized were able to lose at least 5% of their initial body weight. Behavioral programs with in-person intervention have historically produced a mean weight loss in 6 months of 9 kg among completers14; however, several large randomized trials of weight loss with intensive group or individual in-person interventions have shown significant health benefits with weight loss of 5 to 6 kg.8,15

Since both the AF and HC groups received behavioral lessons via e-mail and also accessed the additional Web site with diary, feedback, and a peer support board, it is impossible to determine which of these components produced better weight loss in these conditions. However, in a previous study,2 we controlled all procedures including behavioral lessons and peer support boards and varied only the weekly behavioral e-mail counseling from a human being and showed significantly better weight losses with the weekly human feedback. Therefore, it is likely that the behavioral feedback provided by either the computer or the human being was responsible for greater weight losses in those groups at 3 months.

Several aspects of this first-generation automated system may have limited its efficacy over time and could be easily improved in future iterations. The automated system used a message library that repeated every 6 weeks. Although the likelihood of having the exact same behavior pattern on all variables was low, repetition in messages was possible and message structure did not vary over time. The pattern of logins in the AF group suggests that each month fewer participants interacted with the automated system. Weekly lessons and reminders to submit the diary were sent to both groups, but feedback about behavior was provided only in the AF group in response to a diary submission. In contrast, if a participant in the HC group did not submit a dairy, the counselor sent an e-mail inquiring how the participant was doing and encouraging that person to communicate even during periods of nonadherence.

The login data suggest that the resources available on the public site were helpful only for the group receiving no counseling. Since the two e-counseling groups received behavioral lessons via e-mail, they may have gained little additional information from logging onto the public site.

This study has several strengths, including a randomized design, objective follow-up measures, feedback on weight loss and behavior over time, multiple e-mail counselors who had not met with participants face to face and who were blinded to the programming of the computer-tailored system, and ability to track objective use of both Web sites. Limitations of the study include the fairly homogeneous and educated sample, lack of cost-effectiveness data, and short duration of treatment.

The results of this study replicate our previous studies showing that human e-mail counseling improves weight loss compared with educational sites1 or more interactive sites that include behavioral tools but provide no feedback on behavior change over time.2 Computer-tailored feedback also produces significantly greater initial weight losses than interactive sites without weekly behavioral feedback and for the first 3 months helped participants to achieve weight loss equivalent to that lost by participants who received human e-counseling. Further research is needed to improve the computer-tailored approach. Specifically, strategies to promote continued adherence to computer-tailored systems and ways to combine such systems with other more intensive approaches (via Internet or periodic face-to-face meetings) should be examined. Population-based intervention approaches are a necessary part of combating the obesity epidemic.

Correspondence: Deborah F. Tate, PhD, Schools of Public Health and Medicine, 313 Rosenau Hall, University of North Carolina, Chapel Hill, NC 27599 (dtate@unc.edu).

Accepted for Publication: May 11, 2006.

Author Contributions: Drs Tate and Wing had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Financial Disclosure: None reported.

Funding/Support: This study was supported by the Slim-Fast Nutrition Institute.

Role of the Sponsor: The funder provided the researchers with login data from their Web site. They had no role in the design or conduct of the study; in data collection, analysis, or interpretation; or in preparation or approval of the manuscript.

Tate  DFWing  RRWinett  RA Using Internet technology to deliver a behavioral weight loss program. JAMA 2001;2851172- 1177
PubMed Link to Article
Tate  DFJackvony  EHWing  RR Effects of Internet behavioral counseling on weight loss in adults at risk for type 2 diabetes: a randomized trial. JAMA 2003;2891833- 1836
PubMed Link to Article
Harvey-Berino  JPintauro  SBuzzell  PGold  EC Effect of Internet support on the long-term maintenance of weight loss. Obes Res 2004;12320- 329
PubMed Link to Article
Thomas  SReading  JShephard  R Revision of the Physical Activity Readiness Questionnaire (PAR-Q). Can J Sport Sci 1992;17338- 345
Wing  RR Behavioral approaches to the treatment of obesity. Bray  GBouchard  CJames  Peds.Handbook of Obesity. New York, NY Marcel Dekker Inc1998;855- 873
Wing  RRJeffery  RWBurton  LRThorson  CNissinoff  KSBaxter  JE Food provision vs. structured meal plans in the behavioral treatment of obesity. Int J Obes Relat Metab Disord 1996;2056- 62
PubMed
Ditschuneit  HHFlechtner-Mors  M Value of structured meals for weight management: risk factors and long-term weight maintenance. Obes Res 2001;9 ((suppl 4)) 284S- 289S
PubMed Link to Article
Diabetes Prevention Program Research Group, Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med 2002;346393- 403
PubMed Link to Article
Paffenbarger  RSWing  ALHyde  RT Physical activity as an index of heart attack risk in college alumni. Am J Epidemiol 1978;108161- 175
PubMed
Block  GHartman  AMDresser  CMCarroll  MDGannon  JGardner  L A data-based approach to diet questionnaire design and testing. Am J Epidemiol 1986;124453- 469
PubMed
Jeffery  RWWing  RRSherwood  NETate  DF Physical activity and weight loss: does prescribing higher physical activity goals improve outcome? Am J Clin Nutr 2003;78684- 689
PubMed
Jakicic  JMWinters  CLang  WWing  RR Effects of intermittent exercise and use of home exercise equipment on adherence, weight loss, and fitness in overweight women: a randomized trial. JAMA 1999;2821554- 1560
PubMed Link to Article
Goulis  DGGiaglis  GDBoren  SA  et al.  Effectiveness of home-centered care through telemedicine applications for overweight and obese patients: a randomized controlled trial. Int J Obes Relat Metab Disord 2004;281391- 1398
PubMed Link to Article
Wing  RR Behavioral weight control. Wadden  TAStunkard  AJeds.Handbook of Obesity Treatment. New York, NY The Guilford Press2002;301- 316
Writing Group of the PREMIER Collaborative Research Group, Effects of comprehensive lifestyle modification on blood pressure control: main results of the PREMIER clinical trial. JAMA 2003;2892083- 2093
PubMed

Figures

Place holder to copy figure label and caption
Figure 1.

Participant flowchart. AF indicates tailored computer-automated feedback; BMI, body mass index (calculated as weight in kilograms divided by the square of height in meters); HC, human e-mail counseling; ITT, intention-to-treat; and NC, no counseling.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.

Changes in body weight (observed data). Error bars indicate the 95% confidence interval of the mean; AF, tailored computer-automated feedback; HC, human e-mail counseling; and NC, no counseling.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 3.

Participant monthly login frequency. Reference line indicates 4 logins per month. This frequency is equivalent to the expected frequency of online diary submissions in the e-counseling groups (once per week). Error bars indicate the 95% confidence interval of the mean; AF, tailored computer-automated feedback; HC, human e-mail counseling; and NC, no counseling.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 2. Mean Weight Loss With Observed Data and Various Intent-to-Treat Imputation Techniques*
Table Graphic Jump LocationTable 3. Mean Energy Intake and Physical Activity*

References

Tate  DFWing  RRWinett  RA Using Internet technology to deliver a behavioral weight loss program. JAMA 2001;2851172- 1177
PubMed Link to Article
Tate  DFJackvony  EHWing  RR Effects of Internet behavioral counseling on weight loss in adults at risk for type 2 diabetes: a randomized trial. JAMA 2003;2891833- 1836
PubMed Link to Article
Harvey-Berino  JPintauro  SBuzzell  PGold  EC Effect of Internet support on the long-term maintenance of weight loss. Obes Res 2004;12320- 329
PubMed Link to Article
Thomas  SReading  JShephard  R Revision of the Physical Activity Readiness Questionnaire (PAR-Q). Can J Sport Sci 1992;17338- 345
Wing  RR Behavioral approaches to the treatment of obesity. Bray  GBouchard  CJames  Peds.Handbook of Obesity. New York, NY Marcel Dekker Inc1998;855- 873
Wing  RRJeffery  RWBurton  LRThorson  CNissinoff  KSBaxter  JE Food provision vs. structured meal plans in the behavioral treatment of obesity. Int J Obes Relat Metab Disord 1996;2056- 62
PubMed
Ditschuneit  HHFlechtner-Mors  M Value of structured meals for weight management: risk factors and long-term weight maintenance. Obes Res 2001;9 ((suppl 4)) 284S- 289S
PubMed Link to Article
Diabetes Prevention Program Research Group, Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med 2002;346393- 403
PubMed Link to Article
Paffenbarger  RSWing  ALHyde  RT Physical activity as an index of heart attack risk in college alumni. Am J Epidemiol 1978;108161- 175
PubMed
Block  GHartman  AMDresser  CMCarroll  MDGannon  JGardner  L A data-based approach to diet questionnaire design and testing. Am J Epidemiol 1986;124453- 469
PubMed
Jeffery  RWWing  RRSherwood  NETate  DF Physical activity and weight loss: does prescribing higher physical activity goals improve outcome? Am J Clin Nutr 2003;78684- 689
PubMed
Jakicic  JMWinters  CLang  WWing  RR Effects of intermittent exercise and use of home exercise equipment on adherence, weight loss, and fitness in overweight women: a randomized trial. JAMA 1999;2821554- 1560
PubMed Link to Article
Goulis  DGGiaglis  GDBoren  SA  et al.  Effectiveness of home-centered care through telemedicine applications for overweight and obese patients: a randomized controlled trial. Int J Obes Relat Metab Disord 2004;281391- 1398
PubMed Link to Article
Wing  RR Behavioral weight control. Wadden  TAStunkard  AJeds.Handbook of Obesity Treatment. New York, NY The Guilford Press2002;301- 316
Writing Group of the PREMIER Collaborative Research Group, Effects of comprehensive lifestyle modification on blood pressure control: main results of the PREMIER clinical trial. JAMA 2003;2892083- 2093
PubMed

Correspondence

CME
Meets CME requirements for:
Browse CME for all U.S. States
Accreditation Information
The American Medical Association is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians. The AMA designates this journal-based CME activity for a maximum of 1 AMA PRA Category 1 CreditTM per course. Physicians should claim only the credit commensurate with the extent of their participation in the activity. Physicians who complete the CME course and score at least 80% correct on the quiz are eligible for AMA PRA Category 1 CreditTM.
Note: You must get at least of the answers correct to pass this quiz.
You have not filled in all the answers to complete this quiz
The following questions were not answered:
Sorry, you have unsuccessfully completed this CME quiz with a score of
The following questions were not answered correctly:
Commitment to Change (optional):
Indicate what change(s) you will implement in your practice, if any, based on this CME course.
Your quiz results:
The filled radio buttons indicate your responses. The preferred responses are highlighted
For CME Course: A Proposed Model for Initial Assessment and Management of Acute Heart Failure Syndromes
Indicate what changes(s) you will implement in your practice, if any, based on this CME course.
Submit a Comment

Multimedia

Some tools below are only available to our subscribers or users with an online account.

Web of Science® Times Cited: 148

Related Content

Customize your page view by dragging & repositioning the boxes below.

Articles Related By Topic
Related Collections
PubMed Articles