Thinking Quantitatively about New Year’s Resolutions

It’s that time again for New Year’s resolutions.

“At the start of the new year, millions of Americans will resolve to lose weight,” according to medical doctors writing in The New England Journal of Medicine (Jan. 1, 1998; 338), “but by tomorrow, or next week, or maybe next month, most of them will have given up trying” (p. 52).

Is this true? Do most people make New Year’s resolutions to lose weight? Do most people fail? And do most people give up by February?

That’s where those of us in the social sciences come in. For academic researchers who ponder phenomena, it’s an opportunity to explore human behavior by thinking quantitatively.

In a study of New Year’s Resolutions, published in Psychological Reports in 1972 (Marlatt & Kaplan), researchers at the University of Wisconsin asked: What factors determine the success or failure in keeping a given resolution?
(Click here for the full article.)

They distributed questionnaires to college students. They found that, of those making resolutions, more than one-third (38.5 percent) resolve to lose weight. However, most of those weight-loss resolutions failed. “Resolving to lose weight or monitoring weights over the 12-week period did not produce significant weight loss,” the authors concluded (p. 126). Of the non-weight-loss-related resolutions, most involved health habits, like smoking, or relationships, like sexual behavior, or academic performance (p. 127). Twenty-five percent of the total resolutions were broken, before the first 15 weeks of the year had elapsed (p. 128). “The average duration a resolution was kept prior to abandonment was 41 days for men and 44 days for women” (p. 128). But 75 percent of respondents succeeded in maintaining their resolution, at least for the first several months of the year. “The ‘success rate’ appeared quite good,” the authors concluded (p. 129).

A study in the Journal of Clinical Psychology found that those who make New Years resolutions are more likely to accomplish the goal than those who commit to a goal without making it officially a New Year’s resolution (2002, Norcross, Mrykalo & Blagys). “Resolvers reported higher rates of success than nonresolvers; at six months, 46% of the resolvers were continuously successful compared to 4% of the nonresolvers” (p. 397). (Click here for the full article.)

This was corroborated in American Psychologist when Professor Peter Gollwitzer studied how people translate their goals into action and found that “implementation intentions” – i.e. making New Year’s resolutions — “further the attainment of goals” (1999, p. 493). (citation) And a study in the Journal of Personality and Social Psychology found that “goal self-concordance and implementation intentions combined synergistically to facilitate goal progress” (Koestner, Lekes, Powers & Chicoine, 2002, p. 231). (citation)

In a recent issue of Journal of Applied Social Psychology, the researchers found there’s a correlation between “the increase or high level of enjoyableness and positiveness of the behaviors themselves” and a higher likelihood of someone keeping his or her resolution (Phillips & Chapman, 2011, pp. 16-17). So when tackling “long-term, goal-related behaviors” (p. 1), make your New Year’s resolution fun and you’ll have an even better chance of accomplishing it.

Therefore, don’t lose hope! If you make a New Year’s resolution, the statistics are on your side for achieving success!


1 Comment

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One response to “Thinking Quantitatively about New Year’s Resolutions

  1. For those of you making new years resolutions to exercise more: Deborah Kendzierski, of the Dept of Psychology at Villanova Univ, wrote “approximately 50% of those who start an exercise program drop
    out within a year”. Her paper stated empirically:

    “The three groups did not differ significantly in terms of whether they
    made New Year’s resolutions to exercise regularly (overall, 90% made such
    a resolution), x^(2) = 2.635, ns, but they did differ significantly in whether
    they intended to exercise regularly during the current semester, x^(2) =
    10.759, p < .005. Further analyses revealed that exerciser schematics were
    more likely to intend to exercise (lOO% did so) than were nonexerciser
    schematics (57.1<^o did so), corrected x^(l) = 7.668, p < .006, although
    they were not significantly more likely to do so than aschematics (89.2^o did
    so), corrected x^(l) = 1.559, ns, and the latter two groups also did not
    differ, corrected x^(l) = 1-769, ns.

    source: "Self-Schemata and Exercise", BASIC AND APPLIED SOCIAL PSYCHOLOGY, 1988, 9(1), 45-59

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