Change Psychology: The Longitudinal Study on the adherence to New Year’s Resolutions

The 2-year follow-up study by Dr.Norcross1 on the New Year’s resolutions. The study added a 2-year follow-up survey of the 200 subjects from his first study on feasibility of New Year’s resolutions.

The main outcome of the original study was that the resolvers were able to adhere to their resolutions in 55%, 43% and 40% of cases at 1-, 3-, and 6-month marks respectively. This study added another time point to that investigation and showed that after 2 years only 19% of resolvers were able to adhere to their resolutions.

While this statistic is not very encouraging, I would invite you to review my comprehensive analysis and interpretation of Dr.Nocross’ team research findings on New Year’s Resolutions in my blog "New Year’s Resolutions: An Update".


1. Norcross JC, Vangarelli DJ. The resolution solution: longitudinal examination of New Year's change attempts. J Subst Abuse. 1988;1(2):127-134.

Change Psychology: The New Year’s Resolutions Study (1989)

The first study by Dr.Norcross, published in 19891. The study followed 200 subjects who made New Year’s Resolutions for 6 months and reported on their rate of adherence to their resolutions.

The main outcome of the study was that the resolvers were able to adhere to their resolutions in 55%, 43% and 40% of cases at 1-, 3-, and 6-month marks respectively. The major limitation was the absence of a control group, which was addressed by another study by Dr.Norcross and colleagues, published in 2002. They also conducted a 2-year follow-up study, published separately.

You can see my detailed interpretation of Dr.Nocross’ team research findings on New Year’s Resolutions in my blog "New Year’s Resolutions: An Update".


1. Norcross JC, Ratzin AC, Payne D. Ringing in the new year: the change processes and reported outcomes of resolutions. Addict Behav. 1989;14(2):205-212.

The Lifestyle Heart Trial

This is quite an influential study by Dr.Ornish1. They conducted a clinical trial of a comprehensive behavioral and nutritional intervention in people with severe coronary artery disease. The experimental group (n=28) received a complex intervention, which included low-fat vegetarian diet, stress management, smoking cessation and moderate exercise. The control group (n=20) received treatment as usual.

The study lasted 1 year and by the end of the study the authors reported a decrease in coronary artery stenosis diameter (from 40.0% to 38.7%) in subjects receiving comprehensive intervention whereas some increase is stenosis diameter was observed in the control group. The study was a hit of its time and it still is. What is shows that a comprehensive intervention can reverse the course of a serious heart problem.


1. Ornish D, Brown SE, Scherwitz LW, et al. Can lifestyle changes reverse coronary heart disease? The Lifestyle Heart Trial. Lancet. 1990;336(8708):129-133.

Prevalence of Low-Carbohydrate Diet Use

My colleague and a fellow YouTuber, Dr.Fox, The Lifting Dermatologist, asked me a good question – how many people use low-carbohydrate / ketogenic diets? It turned out that such a simple question was not an easy one to answer.

Here, I would like to present one of the very few studies on prevalence of low-carbohydrate use. The study of Blanck et al1 was published in 2006 and was based on a telephone survey of 9,300 Americans. The authors reported that among their respondents 12.5% reported ever used a low-carbohydrate diet (lifetime prevalence) and 3.4% reported current use (point prevalence), which I think is a good snapshot of the low-carbohydrate diet use. This study is of decent size, but it’s limited to one geographic area and somewhat outdated. That’s the best I have at the moment, but I promise to keep my eyes open and making a follow-up report is I come across something new.

NB: You would need to register at Medscape (it’s free) to access the actual report.

1. Blanck HM, Gillespie C, Serdula MK, Khan LK, Galusk DA, Ainsworth BE. Use of low-carbohydrate, high-protein diets among americans: correlates, duration, and weight loss. MedGenMed : Medscape general medicine. 2006;8(2):5.

Prevalence of Steroid Use among Athletes

We know that some athletes are using anabolic steroids to boost their athletic performance, but the numbers of actual prevalence of steroid use are hard to come by. Sepehri et al1, conducted a confidential survey of 202 athletes in Kerman city in Iran. They found that 18.8% of the athletes reported steroid use. The study obviously has some limitations as it was based on self-reported data and limited to a specific location, so their findings cannot be generalized. At the same time, it is a relatively recent study and we can use their data to gauge the prevalence of anabolic steroids in other settings.


1. Sepehri G, Mousavi Fard M, Sepehri E. Frequency of Anabolic Steroids Abuse in Bodybuilder Athletes in Kerman CityThis article has been published in the Journal of Rafsanjan University of Medical Sciences in Persian language. Addiction & Health. 2009;1(1):25-29.

Fat-Free Mass Index

There is a debate among fitness bloggers whether the Fat-Free Mass Index (FFMI) can be used as an indicator of steroid use or not (and some accusations and “analyses” of individual fitness celebrities’ physiques). Most of these talks are based on the article of Kouri et al1, 19831. I would like to present the original findings here.

The authors took two groups of subjects – those who admittedly were steroid users (n=83) and those who weren’t (n=74) and calculated their FFMI. They found that the average FFMI among users was 24.8±2.2 and among non-users – 21.8±1.8. The difference was substantial and statistically significant, which allowed the authors to suggest using FFMI as a screening instrument for steroid use. The recommended cut-off score is 25.

I have plotted the theoretical distributions of FFMI for users and non-users and conducted a more in-depth analysis of the findings as well as the method of conditional probability of steroid use given that the FFMI is 25 or higher in one of my blogs and YouTube videos.


1. Kouri EM, Pope HG, Jr., Katz DL, Oliva P. Fat-free mass index in users and nonusers of anabolic-androgenic steroids. Clinical journal of sport medicine : official journal of the Canadian Academy of Sport Medicine. 1995;5(4):223-228.

Ketosis vs. Ketoacidosis

I've dedicated a whole blog to everything related to ketosis and one of the things discussed there was whether an otherwise healthy person can get into a state of ketoacidosis while following a strict low-carbohydrate diet.

As I said there it is very unlikely that such thing would happen, but it nevertheless possible – there are some case reports where a person following a ketogenic diet enters a benign ketoacidosis. Here is one of these case reports – an article published in New England Journal of Medicine in 2006 by Drs. Shah and Isley1. Totally worth reading – a healthy woman followed a strict low-carbohydrate diet for several months and presented to the hospitals with signs and symptoms of ketoacidosis, confirmed by laboratory tests.


1. Shah P, Isley WL. Ketoacidosis during a Low-Carbohydrate Diet. 2006;354(1):97-98.

Change Psychology: The New Year’s Resolutions Study (2002)

Very nicely designed study by Dr.Norcross, a psychologist who was famous for multiple great studies, including the common factors research in psychotherapy. In this study he looked into the chances of accomplishing specific personal goals depending on the fact of making a form New Year’s resolution or not.

Researchers have randomly called 1288 telephone numbers in Scranton, PA in the last week of 1995. Out of the 434 individuals who responded to the call, 159 were making New Year’s resolutions (resolvers), and 123 have identified a behaviour they would like to change, but were not making a resolution (non-resolvers). In psychological terms, resolvers were in the action stage of change and non-resolvers were in the contemplation stage of change. Researchers interviewed these people, collected data on behaviours that they wanted to change and a number of other parameters that were necessary for statistical analyses. Majority of participants were women (72%) and almost all of them were Caucasian (99%). The three most common resolutions were weight loss (31%), exercise program (15%) and smoking cessation (12%). There was a significant difference between resolvers and non-resolvers – resolvers were more likely to list exercise program (22%) than non-resolvers (only 9%).

After this initial interview, researchers contacted their study subjects in 1, 2, 3 and 4 weeks and 3 and 6 months to see if they were successful in realization of their New Year’s resolutions. The analysis of the data showed that 71% of resolvers maintained their success in the first couple of weeks and almost half of them (46%) - up to 6 months, which was a pretty good result in my opinion. Especially, if we compare it to those who did not make their resolution – only half of them (51%) were successful in changing their behaviour in the first 1-2 weeks, and only 4% were successful at the 6-month time point.

You can see my detailed interpretation of the research findings in my blog on New Year’s resolutions as well as the analysis of the three studies (check them here and here) by Dr.Norcross’ team in the most recent blog "New Year’s Resolutions: An Update".


Norcross JC, Mrykalo MS, Blagys MD. Auld lang syne: success predictors, change processes, and self-reported outcomes of New Year's resolvers and nonresolvers. Journal of clinical psychology. 2002;58(4):397-405.

Classical Text: Stages of Change

The monumental publication by Prochaska and DiClemente, which laid a foundation for decades of research and clinical practice based on client's stage of behavior change also known as the Transtheoretical Model of Change. The article has both historical and clinical value as it outlines the shifts in perception of many clinical issues (including weight loss) and attitudes toward them. The model's stages are as follows:

  1. Precontemplation
  2. Contemplation
  3. Preparation
  4. Action
  5. Maintenance
  6. Relapse



  1. Prochaska JO, DiClemente CC. Stages and processes of self-change of smoking: toward an integrative model of change. Journal of consulting and clinical psychology. 1983;51(3):390-395.

Classical Text: S.M.A.R.T. goals

The original publication by George T.Doran, in which he outlines the S.M.A.R.T. goals - the rationale, the way they should be set, structured and completed. The article was published in 1981 and the original spelling for S.M.A.R.T. has evolved since then as I described in one of my blogs:

  1. S - Specific
  2. M - Measurable
  3. A - Assignable / Achievable
  4. R - Realistic / Relevant
  5. T - Time-related



  1. Doran GT. There's a S.M.A.R.T. Way to Write Management's Goals and Objectives. Management Review. 1981;70:35-36.

Meta-Analysis: Diet vs. Exercise for Weight Loss

An excellent meta-analysis by Dr. James E. Clark1 published in the Journal of Diabetes & Metabolic Disorders in 2015. The meta-analysis summarizes 66 population-based studies and includes 162-studywise groups.
The main take-home points are as follows:

  1. Hypocaloric balance is essential for weight loss - the total body mass changes were most pronounced in the diet only group (ES*=1.24)
  2. Endurance training alone did not produce any significant changes in body mass
  3. Resistance training alone produced minimal changes in body mass (ES=0.25)
  4. Addition of exercise to diet resulted in less intense weight loss with effect sizes of 1.19, 1.06 and 0.57 for endurance training, resistance training and both added to the diet, respectively.
  5. At the same time the addition of exercise, especially resistance training helped to spare lean body mass and had a number of other positive metabolic and hormonal benefits.

*ES stands for effect size, shown only if statistically significant


  1. Clark JE. Diet, exercise or diet with exercise: comparing the effectiveness of treatment options for weight-loss and changes in fitness for adults (18-65 years old) who are overfat, or obese; systematic review and meta-analysis. Journal of Diabetes & Metabolic Disorders. 2015;14:31.