Marta Kolbuszewska1,2
Marina Milyavskaya- 1Department of Psychology, University of British Columbia, Vancouver, BC, Canada
- 2Department of Psychology, Carleton University, Ottawa, ON, Canada
- 3Faunalytics, Olympia, WA, United States
Previous studies have consistently shown that autonomous motivation – pursuing goals because one wants to, rather than has to – is associated with greater behaviour maintenance in the context of healthy eating, exercise, and diet maintenance. The present study used a 7-wave longitudinal design to examine how autonomous motivation is related to dietary goal progress in individuals (N = 222) transitioning to a veg*n (i.e., vegetarian or vegan) diet. We hypothesized that when people reported more autonomous motivation (compared to their own average) they would be more successful in reaching their dietary goals. We also explored the role of goal-facilitating behaviours in this process. We found no directional effects of relative autonomous motivation on goal progress or goal-facilitating behaviours, although the concurrent relations were significant. There were also no within-person effects of behaviours on progress. These findings shed light onto the relationship between autonomous motivation, behaviours, and goal progress both at the same time and over time, and highlight the importance of examining within-person fluctuations over time.
Introduction
Plant-based diets (whether in the form of reduced meat consumption or complete elimination of animal products) have received increased media coverage and popular interest in recent years (Phua et al., 2020; Van Loo et al., 2020). Campaigns to reduce meat consumption like Veganuary have seen growing success; in 2022, 629,000 people participated in Veganuary, up from 3,000 in 2014 (Veganuary, 2022), and meat alternatives are now mainstream, available at fast-food chains and grocery stores (Van Loo et al., 2020). Indeed, reducing meat consumption provides significant opportunities to mitigate climate change and reduce greenhouse gas emissions (Shukla et al., 2019), protect animal welfare (Westhoek et al., 2014), and reduce the burden of chronic illness linked to cardiovascular disease (Kahleova et al., 2018; Siapco and Sabaté, 2019), colorectal cancers (Bouvard et al., 2015), and type 2 diabetes (Kahleova et al., 2011). Nevertheless, global meat consumption is increasing (Godfray et al., 2018) and despite considerable interest in vegetarian or vegan (henceforth referred to as veg*n) diets, only a small proportion of individuals who try a veg*n diet stick with it long-term (Faunalytics, 2016). In the United States, there are more than five times as many former veg*ns (i.e., people who tried a veg*n diet and then abandoned it) as current veg*ns; that is, over 80% of vegetarians/vegans abandon their diet (Faunalytics, 2016). Given the low success rate, what can help people stick to a veg*n diet?
Autonomous motivation
A large body of research has explored the environmental and psychological factors that influence individuals’ uptake and maintenance of health behaviours (Sallis et al., 2015). Motivation is a psychological factor that is especially relevant to promoting goal attainment (Sheldon et al., 2004). Although past research has examined different motives or reasons for transitioning to a veg*n diet (Fox and Ward, 2008; Faunalytics, 2014; Grassian, 2020; North et al., 2021; Ghaffari et al., 2022), it has not considered the quality of motivation. Self-Determination Theory (Deci and Ryan, 2000) suggests that motivation exists on a continuum from autonomous (because one wants to) to controlled (because one has to; Ryan and Connell, 1989). Autonomous motivation entails enacting a behaviour for the enjoyment or challenge inherent to that action, because it is integral to their identity (e.g., a person avoids meat because it aligns with their beliefs), or because they believe their goal to be important (e.g., a person reduces milk consumption because they do not support the dairy industry, even though they really like cheese). Controlled motivation, on the other hand, is characterized by external pressures and demands. Individuals might pursue a goal because of feelings of guilt, shame, or social pressure (e.g., a vegetarian gives up eggs and dairy because they fear the negative reactions of their vegan peers if they continue eating animal products), or in order to meet external incentives or to satisfy an external demand (e.g., a person eats vegetarian because they will win a gift certificate if they do so).
Past studies have found that more autonomous motivation is associated with greater goal progress (Sheldon and Elliot, 1999; Koestner et al., 2002; Sheldon et al., 2004; Werner et al., 2016), and behaviour maintenance (of multiple behaviours; Ryan and Connell, 1989; Silva et al., 2011; Hagger et al., 2014; Nurmi et al., 2016; Vancampfort et al., 2016; Voi and Sainsbury, 2019), compared to controlled motivation. Although some of this research has examined the role of autonomous and controlled motivation in diet maintenance, it has predominantly focused on dieting for weight loss, which entails caloric restriction (Wadden et al., 1994; Wing et al., 2006) and implicates physiological processes related to metabolic adaptation that may interfere with weight loss maintenance (Ohsiek and Williams, 2011; Anastasiou et al., 2015). Transitioning to, and maintaining, a veg*n diet can thus differ from pursuing diets for weight control. Additionally, autonomous as opposed to controlled motivation is associated with using more adaptive strategies (Koestner et al., 2008), experiencing fewer temptations (Milyavskaya et al., 2015) and reporting greater subject ease (Werner et al., 2016) during general goal pursuit. We thus expect that relatively more autonomous motivation will similarly relate to more successful transition to a veg*n diet, including engagement in more goal-facilitating behaviours.
Goal-facilitating behaviours
What are some ways that people can stick to their goal of eating fewer animal products? Engaging in certain activities, like planning meals in advance, or avoiding situations with tempting dietary options, can help people succeed at meeting their goals (Williamson and Wilkowski, 2020). For veg*ns, some activities may be more influential than others at helping people reach their dietary goals. Faunalytics (2014) and Grassian (2020) found that veg*ns and former veg*ns list six general factors that influence veg*n diet maintenance, including cravings, convenience, motivation, cost, health concerns, and social support.
Strategies for dealing with cravings
One way to promote goal-consistent choices is by using strategies to actively manage oneself and one’s environment and avoid temptations that may hinder goal progress (Duckworth et al., 2014; Duckworth et al., 2016). Prior research on self-control strategies finds that they are generally effective in preventing indulgence in the moment, and that using more strategies is more effective (Milyavskaya et al., 2020). In the context of transitioning to a veg*n diet, individuals may use strategies when faced with tempting situations (e.g., planning a strategy to use if a craving occurs) in order to help achieve their goals.
Convenience
Goal-consistent behaviours that increase convenience may also play an important role in supporting individuals’ transition and maintenance of veg*n diets. For example, situation selection, choosing situations that help one stick to their goals and avoiding situations where self-control will be needed, helps people stick to their various goals more broadly (Duckworth et al., 2016). Similarly, choosing in advance generally encourages more self-controlled decisions (Laibson, 1997). Consequently, behaviours that increase convenience (e.g., going to a vegetarian restaurant instead of a steakhouse) may be particularly relevant to those following a veg*n diet.
Information seeking
Veg*ns cite various reasons for eliminating animal products from their diet, with animal welfare, environmental, and health concerns often topping the list (Dyett et al., 2013; Kerschke-Risch, 2015; Radnitz et al., 2015; Izmirli and Phillips, 2011, see Janssen et al., 2016). However, some reasons are more effective than others at influencing long-term behaviour change; for example, many veg*ns cite learning about the harms of livestock agriculture as an important factor in transitioning to a veg*n diet (Faunalytics, 2014). We thus examined whether learning about the benefits of a veg*n diet (or the potential detriments of a non-veg*n diet) promotes dietary change.
Health
Another set of behaviours that are particularly relevant to the veg*n context are health-related behaviours (e.g., getting blood work done to check one’s iron or B12 levels). Monitoring nutritional needs is especially important for maintaining health and may thereby help people stick to their diet (Herrmann and Geisel, 2002). Regular monitoring of serum B12 and iron levels has been recommended for children and pregnant/lactating women (Lemale et al., 2019), as well as adults (Herrmann and Geisel, 2002; Pawlak et al., 2014) following a plant-based diet, and current veg*ns are much more likely to have had these values checked than those who abandon a veg*n diet (Faunalytics, 2014). Additionally, nutritional concerns and deficits are cited as one of the top reasons for abandoning a veg*n diet (Faunalytics, 2014). As such, proactively monitoring health and nutrition may help individuals successfully transition to a veg*n diet.
Cost
For individuals pursuing a healthy diet, food choice is influenced by personal economic conditions: Eating a healthy, and environmentally friendly, diet often incurs financial costs (Cade et al., 1999) while financial constraints lead to less healthy eating (Drewnowski and Darmon, 2005; Barosh et al., 2014). Examining the affordability of health food items, Barosh et al. (2014) found that a low-income household would need to spend 40 to 48% of their weekly income to afford a healthy food basket, whereas a high-income household would only need to spend between 8 and 9% of their salary to afford the same food. Although veg*n and reduced-meat diets do not necessarily need to be expensive (Wilson et al., 2013), many individuals transitioning to a veg*n diet find cost to be a factor when planning their diet (Faunalytics, 2014; Van Den Berg et al., 2022). Strategies to reduce costs may therefore play a role in successfully transitioning to and maintaining a veg*n diet.
Social
Social support from various sources (e.g., family, healthcare professionals, friends) can positively influence goal attainment, including health outcomes (Jakubiak and Feeney, 2016). Social support is implicated in healthier food choices (Kubik et al., 2005; Stanton et al., 2007) and adherence to dietary changes (Sorensen et al., 1998; Wilson et al., 2013). Just as diet-related social support helps individuals pursue healthy eating behaviours, social support plays an important role in maintaining a veg*n diet (Jabs et al., 1998; Hielkema and Lund, 2021), with veg*ns often seeking out veg*n social groups (Chuter, 2018; Séré de Lanauze and Sirieix, 2022) and romantic partners (Twine, 2014). Similarly, a lack of social support can present a barrier to individuals maintaining a veg*n diet (Hodson and Earle, 2018; Markowski and Roxburgh, 2019).
Fluctuations over time and the present research
There is evidence that goal intentions (Conner et al., 2000; Conroy et al., 2011) and behaviours implicated in goal pursuit (Inauen et al., 2016) naturally fluctuate over time. That is, people’s intentions (e.g., to exercise) and behaviours (e.g., snacking) vary on the short- to medium- term (i.e., on the weekly and monthly scale; Conroy et al., 2011; Reuter et al., 2009; Scholz et al., 2008). Previous research found that the greatest reported drop-off in diet adherence was within the first few months of a veg*n diet (34% within 3 months, another 19% within the first year; Asher et al., 2014); we thus chose one-month follow-ups, for 6 months, to try and strike a reasonable balance between frequency in those early months and not overburdening participants. Our research addresses a critical gap in the literature by addressing how goal progress may vary for a single individual over time, examining prospective effects of within-person deviations from trait levels. More concretely, we examine whether relative autonomous motivation will lead to engaging in more behaviours that facilitate goal pursuit, and whether this will lead to greater dietary goal progress among individuals transitioning to a veg*n diet - that is, whether more relative autonomous motivation in a given month compared to your own average will lead to greater goal progress).
The current study
In the present research, we examined whether feeling greater relative autonomous motivation and engaging in more behaviours that facilitate goal pursuit predict dietary goal progress among individuals transitioning to a veg*n diet. Specifically, we were interested in assessing whether goal-facilitating behaviours mediate the relationship between motivation and progress. We hypothesized that: (A) When individuals have higher relative autonomous motivation than usual, they will experience a subsequent increase in dietary goal progress. (B) When individuals engage in more behaviours that facilitate goal progress than usual, they will experience a subsequent increase in dietary goal progress. (C) Individuals who have higher relative autonomous motivation than usual will engage in more behaviours that facilitate goal progress than usual; this will in turn lead to an increase in dietary goal progress. (D) There will be an indirect effect of relative autonomous motivation on goal progress via behaviours that facilitate goal progress at the within-person level.1
Materials and methods
Participants and procedure
Participants were 222 individuals transitioning to a vegetarian or vegan diet (67.6% women, Mage = 31.4, 40.5% had attempted a veg*n diet before, average time since beginning the current veg*n diet = 3.52 weeks) recruited from a variety of North American online sources (e.g., Facebook groups for health, plant-based recipes). Participants were surveyed once a month for 6 months, starting with a baseline survey at sign-up. At each follow-up, participants were emailed to ask if they were still pursuing the diet. If they were not pursuing their diet anymore, they were directed to a separate survey regarding diet abandonment. If they were still pursuing the diet, they filled out a longer survey.2 Therefore, participants completed up to seven surveys in total. All survey questionnaires are available at https://osf.io/bhksj/. Sample size was determined by a-priori power analyses, with a sample of 200 participants required to detect a small-to-medium effect (f2 = 0.08) with 90% power at α = 0.05 level of significance (although we did initially plan to recruit 400 participants to account for drop-out; see https://osf.io/z5vef/ for the original recruitment plan). Our final sample consisted of 222 participants. Exclusion criteria were pre-registered, however due to an influx of scammers during initial stages of data collection, exclusion criteria were revised prior to analysis to remove fraudulent responses. Full details of the revised exclusion criteria can be found online at https://osf.io/bhksj/. The data were collected as part of a collaboration with Faunalytics (a non-profit organization), which has published two reports stemming from the full dataset (Anderson et al., 2021; Anderson and Milyavskaya, 2021).
Measures
Relative autonomous motivation
A 12-item adapted version of the Treatment Self-Regulation Questionnaire (TSRQ; Ryan and Connell, 1989) was used to measure relative autonomous motivation for maintaining a veg*n diet. This scale consists of 12 items that ask participants to rate six statements representing autonomous motivation (e.g., “Because I personally believe it is the best thing to do”) and six statements representing controlled motivation (e.g., “Because I would feel guilty or ashamed of myself if I did not follow this diet”) on a 5-point Likert Scale ranging from 1 = strongly disagree, to 5 = strongly agree. For the purposes of the present study, relative autonomous motivation was computed as a composite score of the TSRQ, by subtracting the score for controlled motivation from autonomous motivation. Reliability for both the controlled motivation (α = 0.75–0.88) and autonomous motivation (α = 0.86–0.92) subscales was high.
Behaviours that facilitate goal progress
To assess behaviours that facilitate goal progress, participants were provided a list of 44 items, divided into six subsections: social (7 items; e.g., “Tried to meet new people with diets similar to yours”), convenience (8 items; e.g., “Switched to a restaurant, dining hall, etc., with better options for your diet”), cost (4 items; e.g., “Looked for cheaper restaurants”), health (5 items; e.g., “Taken vitamins or nutritional supplements”), information (9 items; e.g., “Learned more about the environmental impact of eating meat”), and cravings (11 items, e.g., “Planned a strategy for dealing with temptation if it occurs”). The total of 44 items included one open-ended item in each subsection. All variables were binary, scored 1 = “Yes,” 0 = “No,” that participants engaged in over the past month. The open-ended item was a string entry and was recoded as “yes” if answered (and answer did not duplicate prior answers), “no” if unanswered. A total score for behaviours was obtained by summing total items checked for each month.3
Dietary goal progress
We assessed dietary goal progress using two measures: subjective dietary goal progress and objective dietary goal progress.4
Subjective dietary goal progress
Dietary goal progress was assessed using a measure of perceived (subjective) goal progress. Participants were asked to rate how much progress they had made toward their dietary goal using a scale from 0% (not at all successful) to 100% (completely successful).
Objective dietary goal progress
Objective goal progress was calculated as a difference between the goal diet at the initial time point and the actual diet at the given time point, both assessed using a Food Frequency Questionnaire, a type of structured recall instrument often used in epidemiology research (e.g., Fred Hutch Cancer Center, 2022; National Cancer Institute, 2022) and more recently in psychology (e.g., Asher and Peters, 2020; Sparkman et al., 2021). At baseline, before all participants had started working towards their goal, objective goal progress was calculated as a difference between their goal diet and their actual diet at the same time point. The instructions for reporting dietary goals were as follows: “Once you achieve your new goal, how often do you expect to eat each of the following foods (including in other dishes or baked goods)?” Participants were provided with 5 food groups (dairy, poultry, fish/seafood, red meat, eggs) and asked to rate each item on a 5-point scale ranging from 1 = daily to 5 = not at all.
The instructions for reporting actual diet were as follows: “In the past month, how often have you eaten each of the following foods (including in other dishes or baked goods)?” Participants were provided with 5 food groups (dairy, poultry, fish/seafood, red meat, eggs) and asked to rate each item on a 5-point scale ranging from 1 = daily to 5 = not at all. A composite score was calculated by taking a difference between goal and actual diet for each food category and then averaging the scores for each participant. All participants who ‘exceeded’ their dietary goals (i.e., those that ate less meat, fish, etc. than they cited as their goal) were calculated as having no difference between their goal and actual diet progress. Therefore, the range of possible scores is 0 to 4, with 4 representing the most progress.
Analyses
All hypotheses as well as the analytical plan were pre-registered after data was collected but before data cleaning or analysis took place.5 Analyses were conducted in R version 4.0.2 (R Core Team, 2020) Hypotheses A, B, C, and D were tested using the RI-CLPM model specified in Figure 1. Since both behaviours and progress were assessed with respect to the past month, we tested effects of behaviours on progress reported at the same time point (rather than cross-lagged), since it would not have made sense for behaviours in 1 month to predict progress in the following month (for example, behaviours in January should predict progress in January, not in February). Three random intercepts account for stable trait-like differences between persons in relative autonomous motivation, behaviours, and goal progress and separate out between-person variance, allowing the lagged relationships to account for within-person variance. These random intercepts, with all factor loadings constrained to 1, are represented by RI-AM, RI-Beh, and RI-GP in Figure 1. Observed measures for goal progress, behaviours, and relative autonomous motivation were regressed onto their respective latent, within-person centered variables. As such, cross-lags and autoregressive lags between latent variables indicated how changes in one construct (from an individual’s average) influenced changes in other constructs (from an individual’s average). Intervals between waves had the same length, and so cross-wave equality constraints were placed on autoregressive and cross-lagged effects (Hamaker et al., 2015; Orth et al., 2020). Hypothesis D was tested by requesting indirect effects of motivation on progress via behaviour with bootstrapped confidence intervals.
Figure 1. Random intercept cross-lagged panel model used to test hypotheses A to D.
As per the preregistration, we tested correlations between objective and subjective progress over time in order to determine whether an indicator variable would be created to measure goal progress. Shapiro–Wilk’s test was conducted to assess normality of data, and Spearman’s rho was used to calculate correlations due to the skewed nature of variable distributions. Correlations between objective and subjective progress ranged between r = 0.51 and r = 0.64 (see online supplement for correlations at each time point), under our pre-registered cut-off of r = 0.7. Consequently, we fit two models to the data, one with each measure of progress.
In both models, longitudinal associations between relative autonomous motivation, goal-consistent behaviours, and goal progress (either objective or subjective) across seven time points were modeled using lavaan in R.6 Although the original preregistration stated that all autoregressive, cross-lagged, and correlational paths would be constrained to be equal, at baseline (T0) many participants had not started working towards their goal and so instead we allowed the paths from goal progress at baseline to vary freely and constrained the paths across remaining time points. Model results with all paths constrained according to the original preregistration can be found in the online supplement.
In all analyses, full information maximum likelihood (FIML) estimates were used to deal with missing data (Enders and Bandalos, 2001). We assessed model fit using Comparative Fit Index (CFI), Root Mean Square Error of Approximation (RMSEA), Standardized Root Mean Square Residual (SRMR), and Chi square statistics. Because significance levels of the Chi-square statistic depend on sample size, model fit was evaluated using CFI, RMSEA, and SRMR. CFI values greater than 0.90 were considered to indicate acceptable fit, greater than 0.95 good fit. RMSEA values less than 0.08 indicated good fit, and SRMR values less than 0.06 indicated good fit (Hu and Bentler, 1999). For all analyses, standardized results are reported in text; unstandardized results can be found in the online supplement.7
Results
Preliminary analyses
Descriptive statistics of the variables of interests are presented in Table 1, and correlations are presented in Table 2.
Table 1. Means, standard deviations, and ICC of variables of interest at times T0-T6.
Table 2. Correlation matrix of all variables at times T0-T6.
Objective progress
The RI-CLPM model examining within-person relative autonomous motivation, behaviours, and objective goal progress showed adequate model fit (χ2 (202) = 406.76, p < 0.001, CFI = 0.91, RMSEA = 0.07, 90% CI (0.06, 0.08), although the SRMR = 0.13 was poor). Autoregressive paths for within-person relative autonomous motivation and behaviours were significant and moderate (see Table 3 for standardized parameters and online supplement for unstandardized parameters). The relationship between goal progress at baseline (before participants had started working towards their goal) and time 1 was negative (β = −0.24, p = 0.023) – unsurprisingly, participants who had already made more progress at baseline made smaller additional gains at the first follow-up. Autoregressive effects were larger than other reported effects, suggesting that relative autonomous motivation and engagement in goal-consistent behaviours over the past month are best predicted by the same constructs at the previous time point. No cross-lagged effects were significant. Indirect effects of motivation on goal progress via behaviours were not significant (β = −0.000, p = 0.996, 95%CI [−0.002, 0.002]).8 At the between-person level, the random intercept factor of relative autonomous motivation was uncorrelated with behaviours and goal progress suggesting that individuals who reported greater motivation did not necessarily report more behaviours or goal progress. The random intercept factors of behaviours and goal progress were positively correlated (β = 0.23, p = 0.008), such that those individuals who reported engaging in more behaviours overall also made more overall progress,
Table 3. Standardized RI-CLPM parameter estimates for Objective Progress Model.
Subjective progress
The RI-CLPM model examining relative autonomous motivation, goal-consistent behaviours, and subjective goal progress showed adequate model fit (χ2 (202) = 349.99, p < 0.001, CFI = 0.927, RMSEA = 0.057, 90% CI (0.047, 0.067), although SRMR was poor at 0.11). Autoregressive paths were all significant (see Table 4 for standardized parameters and online supplement for unstandardized parameters). Standardized autoregressive paths for within-person relative autonomous motivation (β = 0.16, p = 0.004), behaviours (β = 0.38, p < 0.001), and subjective goal progress (βT0 = 0.23, p = 0.016; βT1-T6 = 0.25, p < 0.001) were significant and low to moderate in size. Autoregressive effects were larger than other reported effects, suggesting that relative autonomous motivation and engagement in goal-consistent behaviours over the past month are best predicted by the same construct at the previous time point.
Table 4. Standardized RI-CLPM parameter estimates for Subjective Progress Model.
Effects for subjective goal progress on motivation were significant (β = 0.15, p = 0.006), suggesting a small positive relationship between subjective goal progress and motivation (i.e., when individuals reported that they were more successful in attaining their goal compared to their own average, they reported more relative autonomous motivation compared to their own average at the following time). Covariances between relative autonomous motivation and goal progress at the same time point were significant across waves (βT0 = 0.20, p = 0.023; βT1-T6 = 0.10, p = 0.018). At the between-person level, the random intercept factors of relative autonomous motivation, behaviours, and goal progress had no significant correlations, suggesting that individuals who reported greater motivation did not necessarily report more behaviours or goal progress. Indirect effects of motivation on goal progress via behaviours were not significant (β = 0.002, p = 0.979, 95%CI [−0.122, 0.125]).
Discussion
The primary aim of this study was to test the reciprocal associations between relative autonomous motivation, goal-facilitating behaviours, and dietary goal progress in individuals transitioning to a veg*n diet. Most of our hypotheses were not supported. At the within person level, contrary to hypothesis A, when individuals had higher relative autonomous motivation than usual, they did not report a subsequent increase in dietary goal progress (although motivation and progress were again positively correlated at the follow-ups). Contrary to hypothesis B, when individuals engaged in more behaviours that facilitate goal progress than usual, they did not report greater subjective or objective dietary goal progress. Inconsistent with hypothesis C, individuals who had higher relative autonomous motivation than usual did not report engaging in more behaviours that facilitate goal progress than usual. Lastly, contrary to hypothesis D, there was no significant indirect effect of relative autonomous motivation on goal progress via behaviours that facilitate goal progress at the within-person level.
Theoretical and practical implications
Our findings add to a growing literature on veg*n diet transition that examines the role of motivations and behaviour in increasing veg*n diet maintenance (Faunalytics, 2016; Rosenfeld and Tomiyama, 2019a,b; Grassian, 2020). Furthermore, our results offer some support for past research examining the relationship between goal-consistent behaviours, goal-pursuit, and motivation (Judge et al., 2005; Koestner et al., 2008; Milyavskaya et al., 2015). The present research also provides a novel examination of both objective and subjective veg*n goal progress. This is particularly important in the context of a veg*n diet given that people’s claimed identity (e.g., vegan/vegetarian) does not always align with what they eat (e.g., 17% of vegetarians report regularly eating fish and 51% of vegetarians report having eaten meat since becoming vegetarian; Rosenfeld and Tomiyama, 2019a,b). Specifically, our study used an objective indicator of goal progress that took into account individuals’ idiosyncratic, specific goals. By considering the difference between people’s goals and actual diets, we were able to assess how much progress individuals had made related to their own goals (i.e., if two individuals stopped eating meat and ate only eggs, but one individual had a goal of eliminating only meat while the other individual had a goal of eliminating meat and eggs, our measure of goal progress accounted for these idiosyncrasies).
Autonomous motivation
Our findings are partially inconsistent with empirical and theoretical work that identifies autonomous motivation as an important predictor of goal progress (e.g., Koestner et al., 2008; see Ryan and Deci, 2017 for an overview). As can be expected, the two constructs were positively related at each time point. This means that participants who experienced greater relative autonomy also reported more goal progress, and also in months where autonomy was higher, participants reported greater progress. However, relative autonomous motivation did not predict greater progress in the following month. This may be due to autonomous motivation being relatively stable (57% of variability was between-person) and high; perhaps it is only when motivation becomes relatively less autonomous that subsequent goal pursuit is affected. It is also likely that the goal of transitioning to a veg*n diet differs from other goals (e.g., veg*ns face social stigma for their choices; Markowski and Roxburgh, 2019), so the processes linking motivation to progress may differ, or may be moderated by factors we did not examine.
We did, however, find that goal progress was positively related to subsequent reports of relative autonomous motivation. This aligns with research by Sheldon and Houser-Marko (2001), who found that greater attainment of personal goals was linked to more self-concordance (i.e., within-person relative autonomous motivation) the following semester. It may also be that dietary goal progress might indicate competence, with individuals reporting greater goal progress feeling more competent, thus leading to more relative autonomous motivation. Indeed, goal progress has been linked to greater satisfaction of basic psychological needs, which is associated with greater autonomous motivation (Milyavskaya et al., 2014).
In the present study, autonomous and controlled motivation were combined into one index measure of relative autonomy. This is a common practice, and in line with self-determination theory’s theoretical view that these forms of motivation are opposite ends of a continuum (Ryan and Deci, 2017). Past research, however, has shown that autonomous and controlled motivation can have different effects on goal pursuit (e.g., Koestner et al., 2008; Milyavskaya et al., 2015; Leduc-Cummings et al., 2022): autonomous motivation is related to more successful goal pursuit and experiencing fewer obstacles. Controlled motivation, on the other hand, is unrelated to goal progress, and setting up and perceiving more obstacles, and greater effort to overcome them. For the present study, we had decided to combine autonomous and controlled motivation into an index of relative autonomy in order to keep model complexity manageable. Perhaps looking at autonomous and controlled motivation separately would have yielded different or more nuanced results. Current investigation examined if introverts and extraverts benefit differentially from specific positive psychology interventions.
Goal-facilitating behaviours
In examining the effects of goal-facilitating behaviours on goal progress, we found no within-person effects of behaviours on progress. That is, even in those months that individuals used goal-facilitating behaviours, they did not report more progress than their own average. This may be reflective of an inconsistent link between behaviour monitoring and goal progress and attainment more broadly (Harkin et al., 2016). In a meta-analysis examining goal interventions, Harkin et al. (2016) found that monitoring behaviours led to greater behaviour progress, but not necessarily goal progress. In the context of a veg*n diet, this could mean that as a response to engaging in goal-consistent behaviours (e.g., finding vegetarian-friendly restaurants), individuals may dine at vegetarian restaurants more often, but not necessarily maintain a vegetarian diet overall. As such, participants may have perceived themselves to be successful in following their goal diet (e.g., because they dined at a vegetarian restaurant), but may have still eaten animal products on other days and thus did not report objective progress. Additionally, the goal-facilitating behaviours measured in this study were diverse, and included activities such as getting bloodwork done, planning strategies for if a craving occurs, and seeking out veg*n social groups. It may be that engaging in more goal-facilitating behaviours than one’s usual was not necessarily better than engaging in relevant goal-facilitating behaviours might be.
Additionally, fit between behaviours and a person’s goals might be an important factor in the effectiveness of behaviours for meeting one’s goals. People respond differentially to behavioural interventions based on their personality (Schueller, 2012), and a similar pattern may hold for engaging dietary goal-facilitating behaviours. Outside the context of dietary goals, individuals have been found to favour different strategies, with idiosyncratic personal strategies being more effective than assigned expert strategies at helping people reach their goals (Peetz and Davydenko, 2021). Participants in our study were provided a set of empirically-derived goal-facilitating behaviours, rather than instructed to list personal, idiosyncratic behaviours. It may be that engaging in more goal-facilitating behaviours than one’s own usual is only helpful when these behaviours are consistent with one’s goals or relevant to the individual. Finally, it may be that some people are simply better than others at enacting goal-consistent behaviours (e.g., through implementation intentions) in order to overcome obstacles when pursuing their goal (Koestner et al., 2008).
Indeed, the within-person variance in behaviours was rather low, suggesting that some people regularly enacted more behaviours than others (overall). It may be that people simply do not change their behaviour much month to month, especially if they find something that works. Alternatively, since we assessed number of strategies, it is possible that participants used the same number of strategies month to month, but the strategies themselves differed. When we focused on between-person effects, both in the CLMP model presented in online supplements,9 and the correlation between random intercept factors in the RI-CLMP model, the hypothesized relationship between behaviours and progress emerged for the objective measure of goal progress. Together, this suggests that individuals who generally engage in more goal facilitating behaviours tend to make more progress on average compared to others who engage in fewer such behaviours (although they do not perceive this as progress, as indicated by a lack of relation between behaviours and subjective progress).
Limitations
The measure of goal-facilitating behaviours used in this study has not been previously validated and contains numerous items which measure different constructs (e.g., social support, health monitoring, cost monitoring). Theoretical and empirical research has shown that progress and behaviour monitoring are not monolithic constructs (Wilde and Garvin, 2007; Anseel et al., 2015). Rather, people can assess their behaviour in many ways. Further, behaviour monitoring is most effective at predicting and affecting matching behaviours (e.g., tracking how many times one snacks on cheese may help reduce how often one eats cheese, but may not impact the broader outcome, which is becoming vegan). Future research should better disentangle the various behaviours veg*ns engage in to support their dietary transition. Moreover, certain self-control strategies like implementation intentions are most effective when they are narrow and specific (De Vet et al., 2011). Although participants were asked if they had plans for dealing with cravings, future research would benefit by having individuals transitioning to a veg*n diet make specific, relevant plans for such scenarios.
Additionally, lack of variability with regard to relative autonomous motivation may have influenced the present findings. Participants reported high autonomous motivation and commitment (i.e., intent to continue their veg*n diet after completion of the study; see Anderson and Milyavskaya, 2021; Anderson et al., 2021). New veg*ns in the present study might not represent the general population transitioning to a veg*n diet, who might be more likely to lapse in their diets (Faunalytics, 2016).
In this study, motivation, behaviour, and goal progress were all assessed monthly, and modeled as influencing the following month’s responses. This time scale, however, may not be appropriate (for example, motivation may fluctuate more or less frequently). Using different assessment intervals, and modelling the paths differently, may thus yield different results, although there is currently no reason to expect a different assessment schedule to be more appropriate than what was selected in the current study. Motivations, behaviours, and perceptions are all incredibly fluid and changeable; there is simply not enough research on these fluctuations to properly understand how frequently they may shift and should be assessed.
A final limitation concerns the representativeness of our sample. As described in greater detail in our report on this sample, our participants could be considered representative of those who begin new veg*n diets in Canada and the United States with an initial high level of commitment (Anderson et al., 2021). This means that these findings are not likely to generalize to those who are just experimenting with a veg*n diet, or to individuals in other countries.
Conclusion
In sum, the present study provides preliminary insights on associations between autonomous motivation, goal-facilitating behaviours, and dietary goal progress in individuals transitioning to a veg*n diet. In line with self-determination theory, autonomous motivation was related with greater progress, but this occurred only when progress was assessed at the same time point; no prospective effects were found. These findings shed light onto the relationship between autonomous motivation, behaviours, and goal progress both at the same time and over time.
Data availability statement
The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found at: https://osf.io/zx4sf/.
Ethics statement
The studies involving human participants were reviewed and approved by Carleton University Research Ethics Board-B. The patients/participants provided their written informed consent to participate in this study.
Author contributions
MK and MM came up with the research questions tested in this manuscript. MM and JA designed and conducted the overall larger study. MK conducted the analyses and wrote the manuscript with feedback from MM and JA. All authors contributed to the article and approved the submitted version.
Funding
This research was supported by Social Sciences and Humanities Research Council of Canada Partnership Engage grant to MM and JA, and a grant from Animal Advocacy Research Fund to Faunalytics.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Footnotes
1. ^We had also preregistered hypotheses on between-person effects, to be tested using cross-lagged panel models (CLMP). However, given the general criticisms of these models (e.g., Lucas, 2022) and the poor fit of these models to our data, on the editor’s recommendation we decided to report the results of these models in an online supplement only: https://osf.io/ez3wx, https://osf.io/bs3qr
2. ^Only our variables of interest are reported in this paper. For a full list of variables included in the questionnaires, see https://osf.io/bhksj/
3. ^Note that all behaviour categories were combined, as examining each type of behaviour separately was outside the scope of this paper.
4. ^Data on subjective and objective progress (and their relation) are used in another manuscript focusing on the correspondence between behavioural and self-report measures of goal progress (Smyth et al., under review).
6. ^https://osf.io/zx4sf/?view_only=f96dfaabf5ca43b5bc1ec6e1c93eaf96
8. ^In the tested models, variance of goal-facilitating behaviours was much higher than the variances of the other variables due to the operationalization in which scores were measured on different scales, resulting in a warning in R. We ran additional analyses with scaled variables. Standardized results remained the same (see online supplement).
References
Anastasiou, C. A., Karfopoulou, E., and Yannakoulia, M. (2015). Weight regaining: from statistics and behaviors to physiology and metabolism. Metabolism 64, 1395–1407. doi: 10.1016/j.metabol.2015.08.006
Anderson, J., and Milyavskaya, M. (2021). Going vegan or vegetarian: Motivations & Influences - Faunalytics. Fauna
Anderson, J., Milyavskaya, M., and Kolbuszewska, M. (2021). Going vegan or vegetarian: many paths to one goal. Fauna. Available at: https://faunalytics.org/going-veg-many-paths/ (Accessed August 7, 2022).
Anseel, F., Beatty, A. S., Shen, W., Lievens, F., and Sackett, P. R. (2015). How are we doing after 30 years? A meta-analytic review of the antecedents and outcomes of feedback-seeking behavior. J. Manag. 41, 318–348. doi: 10.1177/0149206313484521
Asher, K., Green, C., Gutbrod, H., Jewell, M., Hale, G., and Bastian, B. (2014). Study of current and former vegetarians and vegans. Available at: https://faunalytics.org/wp-content/uploads/2015/06/Faunalytics_Current-Former-Vegetarians_Full-Report.pdf (Accessed October 11, 2022)
Asher, K. G., and Peters, P. (2020). Go the whole nine yards? How extent of meat restriction impacts individual dietary experience. Ecol. Food Nutr. 59, 436–458. doi: 10.1080/03670244.2020.1737043
Barosh, L., Friel, S., Engelhardt, K., and Chan, L. (2014). The cost of a healthy and sustainable diet – who can afford it? Aust. N. Z. J. Public Health 38, 7–12. doi: 10.1111/1753-6405.12158
Bouvard, V., Loomis, D., Guyton, K. Z., Grosse, Y., El Ghissassi, F., Benbrahim-Tallaa, L., et al. (2015). Carcinogenicity of consumption of red and processed meat. Lancet Oncol. 16, 1599–1600. doi: 10.1016/S1470-2045(15)00444-1
Cade, J., Upmeier, H., Calvert, C., and Greenwood, D. (1999). Costs of a healthy diet: analysis from the UK Women’s cohort study. Public Health Nutr. 2, 505–512. doi: 10.1017/S1368980099000683
Chuter, R. (2018). Finding companionship on the road less travelled: A netnography of the whole food plant-based Aussies Facebook group.
Conner, M., Sheeran, P., Norman, P., and Armitage, C. J. (2000). Temporal stability as a moderator of relationships in the theory of planned behaviour. Br. J. Soc. Psychol. 39, 469–493. doi: 10.1348/014466600164598
Conroy, D. E., Elavsky, S., Hyde, A. L., and Doerksen, S. E. (2011). The dynamic nature of physical activity intentions: a within-person perspective on intention-behavior coupling. J. Sport Exerc. Psychol. 33, 807–827. doi: 10.1123/jsep.33.6.807
De Vet, E., Oenema, A., and Brug, J. (2011). More or better: do the number and specificity of implementation intentions matter in increasing physical activity? Psychol. Sport Exerc. 12, 471–477. doi: 10.1016/j.psychsport.2011.02.008
Deci, E. L., and Ryan, R. M. (2000). The “what” and “why” of goal pursuits: human needs and the self-determination of behavior. Psychol. Inq. 11, 227–268. doi: 10.1207/S15327965PLI1104_01
Drewnowski, A., and Darmon, N. (2005). The economics of obesity: dietary energy density and energy cost. Am. J. Clin. Nutr. 82, 265S–273S. doi: 10.1093/ajcn/82.1.265S
Duckworth, A. L., Gendler, T. S., and Gross, J. J. (2014). Self-control in school-age children. Educ. Psychol. 49, 199–217. doi: 10.1080/00461520.2014.926225
Duckworth, A. L., Gendler, T. S., and Gross, J. J. (2016). Situational strategies for self-control. Perspect. Psychol. Sci. 11, 35–55. doi: 10.1177/1745691615623247
Dyett, P. A., Sabaté, J., Haddad, E., Rajaram, S., and Shavlik, D. (2013). Vegan lifestyle behaviors. An exploration of congruence with health-related beliefs and assessed health indices. Appetite 67, 119–124. doi: 10.1016/j.appet.2013.03.015
Enders, C. K., and Bandalos, D. L. (2001). The relative performance of full information maximum likelihood estimation for missing data in structural equation models. Struct. Equ. Model. 8, 430–457. doi: 10.1207/S15328007SEM0803_5
Faunalytics (2014). Study of current and former vegetarians and vegans. Faunalytics. Available at: https://faunalytics.org/wp-content/uploads/2015/06/Faunalytics_Current-Former-Vegetarians_Full-Report.pdf (Accessed October 11, 2022).
Faunalytics (2016). A summary of Faunalytics’ study of current and former vegetarians and vegans. Faunalytics. Available at: https://faunalytics.org/a-summary-of-faunalytics-study-of-current-and-former-vegetarians-and-vegans/ (Accessed December 7, 2020).
Fox, N., and Ward, K. (2008). Health, ethics and environment: a qualitative study of vegetarian motivations. Appetite 50, 422–429. doi: 10.1016/j.appet.2007.09.007
Fred Hutch Cancer Center (2022). Food Frequency Questionnaires (FFQ). Available at: https://www.fredhutch.org/en/research/divisions/public-health-sciences-division/research/nutrition-assessment.html#food-frequency (Accessed October 11, 2022).
Georgiadis, M. M., Biddle, S. J., and Stavrou, N. A. (2006). Motivation for weight-loss diets: a clustering, longitudinal field study using self-esteem and self-determination theory perspectives. Health Educ. J. 65, 53–72. doi: 10.1177/0017896906066067
Ghaffari, M., Rodrigo, P. G. K., Ekinci, Y., and Pino, G. (2022). Consumers’ motivations for adopting a vegan diet: a mixed-methods approach. Int. J. Consum. Stud. 46, 1193–1208. doi: 10.1111/ijcs.12752
Godfray, H. C. J., Aveyard, P., Garnett, T., Hall, J. W., Key, T. J., Lorimer, J., et al. (2018). Meat consumption, health, and the environment. Science 361:eaam5324. doi: 10.1126/science.aam5324
Grassian, D. (2020). The dietary behaviors of participants in UK-based meat reduction and vegan campaigns – a longitudinal, mixed-methods study. Appetite 154:104788. doi: 10.1016/j.appet.2020.104788
Hagger, M. S., Hardcastle, S. J., Chater, A., Mallett, C., Pal, S., and Chatzisarantis, N. L. D. (2014). Autonomous and controlled motivational regulations for multiple health-related behaviors: between- and within-participants analyses. Health Psychol. Behav. Med. 2, 565–601. doi: 10.1080/21642850.2014.912945
Hamaker, E. L., Kuiper, R. M., and Grasman, R. P. P. P. (2015). A critique of the cross-lagged panel model. Psychol. Methods 20, 102–116. doi: 10.1037/a0038889
Harkin, B., Webb, T. L., Chang, B. P. I., Benn, Y., Prestwich, A., Conner, M., et al. (2016). Does monitoring goal Progress promote goal attainment? A meta-analysis of the experimental evidence. Psychol. Bull. 142, 198–229. doi: 10.1037/bul0000025
Herrmann, W., and Geisel, J. (2002). Vegetarian lifestyle and monitoring of vitamin B-12 status. Clin. Chim. Acta 326, 47–59. doi: 10.1016/S0009-8981(02)00307-8
Hielkema, M. H., and Lund, T. B. (2021). Reducing meat consumption in meat-loving Denmark: exploring willingness, behavior, barriers and drivers. Food Qual. Prefer. 93:104257. doi: 10.1016/j.foodqual.2021.104257
Hodson, G., and Earle, M. (2018). Conservatism predicts lapses from vegetarian/vegan diets to meat consumption (through lower social justice concerns and social support). Appetite 120, 75–81. doi: 10.1016/j.appet.2017.08.027
Hu, L., and Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct. Equ. Model. Multidiscip. J. 6, 1–55. doi: 10.1080/10705519909540118
Inauen, J., Shrout, P. E., Bolger, N., Stadler, G., and Scholz, U. (2016). Mind the gap? An intensive longitudinal study of between-person and within-person intention-behavior relations. Ann. Behav. Med. 50, 516–522. doi: 10.1007/s12160-016-9776-x
Izmirli, S., and Phillips, C. (2011). The relationship between student consumption of animal products and attitudes to animals in Europe and Asia. Br. Food J. 113, 436–450. doi: 10.1108/00070701111116482
Jabs, J., Devine, C. M., and Sobal, J. (1998). Maintaining vegetarian diets personal factors, social networks and environmental resources. Can. J. Diet. Pract. Res. 59, 183–189.
Jakubiak, B. K., and Feeney, B. C. (2016). Daily goal progress is facilitated by spousal support and promotes psychological, physical, and relational well-being throughout adulthood. J. Pers. Soc. Psychol. 111, 317–340. doi: 10.1037/pspi0000062
Janssen, M., Busch, C., Rödiger, M., and Hamm, U. (2016). Motives of consumers following a vegan diet and their attitudes towards animal agriculture. Appetite 105, 643–651. doi: 10.1016/j.appet.2016.06.039
Judge, T. A., Bono, J. E., Erez, A., and Locke, E. A. (2005). Core self-evaluations and job and life satisfaction: the role of self-concordance and goal attainment. J. Appl. Psychol. 90, 257–268. doi: 10.1037/0021-9010.90.2.257
Kahleova, H., Levin, S., and Barnard, N. D. (2018). Vegetarian dietary patterns and cardiovascular disease. Prog. Cardiovasc. Dis. 61, 54–61. doi: 10.1016/j.pcad.2018.05.002
Kahleova, H., Matoulek, M., Malinska, H., Oliyarnik, O., Kazdova, L., Neskudla, T., et al. (2011). Vegetarian diet improves insulin resistance and oxidative stress markers more than conventional diet in subjects with type 2 diabetes. Diabet. Med. 28, 549–559. doi: 10.1111/j.1464-5491.2010.03209.x
Kerschke-Risch, P. (2015). Vegan diet: motives, approach and duration. Initial results of a quantitative sociological study. Ernaehrungs Umschau 62, 98–103. doi: 10.4455/eu.2015.016
Koestner, R., Lekes, N., Powers, T. A., and Chicoine, E. (2002). Attaining personal goals: self-concordance plus implementation intentions equals success. J. Pers. Soc. Psychol. 83, 231–244. doi: 10.1037/0022-3514.83.1.231
Koestner, R., Otis, N., Powers, T. A., Pelletier, L., and Gagnon, H. (2008). Autonomous motivation, controlled motivation, and goal Progress. J. Pers. 76, 1201–1230. doi: 10.1111/j.1467-6494.2008.00519.x
Kubik, M. Y., Lytle, L., and Fulkerson, J. A. (2005). Fruits, vegetables, and football: findings from focus groups with alternative high school students regarding eating and physical activity. J. Adolesc. Health 36, 494–500. doi: 10.1016/j.jadohealth.2004.05.010
Leduc-Cummings, I., Werner, K. M., Milyavskaya, M., Dominick, J. K., and Cole, S. (2022). Experiencing obstacles during goal pursuit: the role of goal motivation and trait self-control. J. Res. Pers. 99:104231. doi: 10.1016/j.jrp.2022.104231
Lemale, J., Mas, E., Jung, C., Bellaiche, M., and Tounian, P. (2019). Vegan diet in children and adolescents. Recommendations from the French-speaking pediatric hepatology, gastroenterology and nutrition group (GFHGNP). Arch. Pédiatrie 26, 442–450. doi: 10.1016/j.arcped.2019.09.001
Lucas, R. E. (2022). It’s time to abandon the cross-lagged panel model. PsyArXiv 1–37. doi: 10.31234/osf.io/pkec7
Markowski, K. L., and Roxburgh, S. (2019). “If I became a vegan, my family and friends would hate me:” anticipating vegan stigma as a barrier to plant-based diets. Appetite 135, 1–9. doi: 10.1016/j.appet.2018.12.040
Milyavskaya, M., Inzlicht, M., Hope, N., and Koestner, R. (2015). Saying “no” to temptation: want-to motivation improves self-regulation by reducing temptation rather than by increasing self-control. J. Pers. Soc. Psychol. 109, 677–693. doi: 10.1037/pspp0000045
Milyavskaya, M., Nadolny, D., and Koestner, R. (2014). Where do self-concordant goals come from? The role of domain-specific psychological need satisfaction. Personal. Soc. Psychol. Bull. 40, 700–711. doi: 10.1177/0146167214524445
National Cancer Institute (2022). Diet history questionnaire II (DHQ II) for U.S. & Canada. Available at: https://epi.grants.cancer.gov/dhq2/ (Accessed October 11, 2022).
North, M., Klas, A., Ling, M., and Kothe, E. (2021). A qualitative examination of the motivations behind vegan, vegetarian, and omnivore diets in an Australian population. Appetite 167:105614. doi: 10.1016/j.appet.2021.105614
Nurmi, J., Hagger, M. S., Haukkala, A., Araújo-Soares, V., and Hankonen, N. (2016). Relations between autonomous motivation and leisure-time physical activity participation: the mediating role of self-regulation techniques. J. Sport Exerc. Psychol. 38, 128–137. doi: 10.1123/jsep.2015-0222
Ohsiek, S., and Williams, M. (2011). Psychological factors influencing weight loss maintenance: an integrative literature review. J. Am. Acad. Nurse Pract. 23, 592–601. doi: 10.1111/j.1745-7599.2011.00647.x
Orth, U., Clark, D. A., Donnellan, M. B., and Robins, R. W. (2020). Testing prospective effects in longitudinal research: comparing seven competing cross-lagged models. J. Pers. Soc. Psychol. 120, 1013–1034. doi: 10.1037/pspp0000358
Pawlak, R., Lester, S. E., and Babatunde, T. (2014). The prevalence of cobalamin deficiency among vegetarians assessed by serum vitamin B12: a review of literature. Eur. J. Clin. Nutr. 68, 541–548. doi: 10.1038/ejcn.2014.46
Peetz, J., and Davydenko, M. (2021). Financial self-control strategy use: generating personal strategies reduces spending more than learning expert strategies. J. Exp. Soc. Psychol. 97:104189. doi: 10.1016/j.jesp.2021.104189
Phua, J., Jin, S., and Kim, J. (2020). The roles of celebrity endorsers’ and consumers’ vegan identity in marketing communication about veganism. J. Mark. Commun. 26, 813–835. doi: 10.1080/13527266.2019.1590854
R Core Team (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Available at: https://www.R-project.org/ (Accessed October 11, 2022).
Radnitz, C., Beezhold, B., and DiMatteo, J. (2015). Investigation of lifestyle choices of individuals following a vegan diet for health and ethical reasons. Appetite 90, 31–36. doi: 10.1016/j.appet.2015.02.026
Reuter, T., Ziegelmann, J. P., Lippke, S., and Schwarzer, R. (2009). Long-term relations between intentions, planning, and exercise: a 3-year longitudinal study after orthopedic rehabilitation. Rehabil. Psychol. 54, 363–371. doi: 10.1037/a0017830
Rosenfeld, D. L., and Tomiyama, A. J. (2019a). When vegetarians eat meat: why vegetarians violate their diets and how they feel about doing so. Appetite 143:104417. doi: 10.1016/j.appet.2019.104417
Rosenfeld, D. L., and Tomiyama, A. J. (2019b). How proximal are pescatarians to vegetarians? An investigation of dietary identity, motivation, and attitudes toward animals. J. Health Psychol. 15, 713–727. doi: 10.1177/1359105319842933
Ryan, R. M., and Connell, J. P. (1989). Perceived locus of causality and internalization: examining reasons for acting in two domains. J. Pers. Soc. Psychol. 57, 749–761. doi: 10.1037/0022-3514.57.5.749
Ryan, R. M., and Deci, E. L. (2017). Self-determination theory: Basic psychological needs in motivation, development, and wellness. New York, NY: Guilford Press.
Sallis, J. F., Owen, N., and Fisher, E. (2015). “Ecological models of health behavior”, in Health behavior: Theory, research, and practice. Jossey-Bass.eds. K. Glanz, B. K. Rimer and K. Viswanath 43–64.
Scholz, U., Nagy, G., Schüz, B., and Ziegelmann, J. P. (2008). The role of motivational and volitional factors for self-regulated running training: associations on the between- and within- person level. Br. J. Soc. Psychol. 47, 421–439. doi: 10.1348/014466607X266606
Schueller, S. M. (2012). Personality fit and positive interventions: extraverted and introverted individuals benefit from different happiness increasing strategies. Psychology 3, 1166–1173. doi: 10.4236/psych.2012.312A172
Séré de Lanauze, G., and Sirieix, L. (2022). Impact of social influences and adoptive community on behaviours: an exploratory study of young French vegetarians. Int. J. Consum. Stud. 46, 419–433. doi: 10.1111/ijcs.12689
Sheldon, K. M., and Elliot, A. J. (1999). Goal striving, need satisfaction, and longitudinal well-being: the self-concordance model. J. Pers. Soc. Psychol. 76, 482–497. doi: 10.1037/0022-3514.76.3.482
Sheldon, K. M., and Houser-Marko, L. (2001). Self-concordance, goal attainment, and the pursuit of happiness: can there be an upward spiral? J. Pers. Soc. Psychol. 80, 152–165. doi: 10.1037/0022-3514.80.1.152
Sheldon, K. M., Ryan, R. M., Deci, E. L., and Kasser, T. (2004). The independent effects of goal contents and motives on well-being: It’s both what you pursue and why you pursue it. Personal. Soc. Psychol. Bull. 30, 475–486. doi: 10.1177/0146167203261883
Shukla, P. R., Skeg, J., Buendia, E. C., Masson-Delmotte, V., Pörtner, H. O., Roberts, D., et al. (2019). Climate change and land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems. Intergovernmental Panel on Climate Change. Available at: https://www.ipcc.ch/site/assets/uploads/2019/11/SRCCL-Full-Report-Compiled-191128.pdf (Accessed October 11, 2022).
Siapco, G., and Sabaté, J. (2019). Correction: health and sustainability outcomes of vegetarian dietary patterns: a revisit of the EPIC-Oxford and the Adventist health Study-2 cohorts. Eur. J. Clin. Nutr. 73:968. doi: 10.1038/s41430-019-0427-8
Silva, M. N., Markland, D., Carraça, E. V., Vieira, P. N., Coutinho, S. R., Minderico, C. S., et al. (2011). Exercise autonomous motivation predicts 3-yr weight loss in women: med. Sci. Sports Exerc. 43, 728–737. doi: 10.1249/MSS.0b013e3181f3818f
Sorensen, G., Stoddard, A., and Macario, E. (1998). Social support and readiness to make dietary changes. Health Educ. Behav. 25, 586–598. doi: 10.1177/109019819802500506
Sparkman, G., Macdonald, B. N. J., Caldwell, K. D., Kateman, B., and Boese, G. D. (2021). Cut back or give it up? The effectiveness of reduce and eliminate appeals and dynamic norm messaging to curb meat consumption. J. Environ. Psychol. 75:101592. doi: 10.1016/j.jenvp.2021.101592
Stanton, C. A., Green, S. L., and Fries, E. A. (2007). Diet-specific social support among rural adolescents. J. Nutr. Educ. Behav. 39, 214–218. doi: 10.1016/j.jneb.2006.10.001
Teixeira, P. J., Carraça, E. V., Markland, D., Silva, M. N., and Ryan, R. M. (2012). Exercise, physical activity, and self-determination theory: a systematic review. Int. J. Behav. Nutr. Phys. Act. 9:78. doi: 10.1186/1479-5868-9-78
Twine, R. (2014). Vegan killjoys at the table—contesting happiness and negotiating relationships with food practices. Societies 4, 623–639. doi: 10.3390/soc4040623
Van Den Berg, S. W., Van Den Brink, A. C., Wagemakers, A., and Den Broeder, L. (2022). Reducing meat consumption: the influence of life course transitions, barriers and enablers, and effective strategies according to young Dutch adults. Food Qual. Prefer. 100:104623. doi: 10.1016/j.foodqual.2022.104623
Van Loo, E. J., Caputo, V., and Lusk, J. L. (2020). Consumer preferences for farm-raised meat, lab-grown meat, and plant-based meat alternatives: does information or brand matter? Food Policy 95:101931. doi: 10.1016/j.foodpol.2020.101931
Vancampfort, D., Moens, H., Madou, T., De Backer, T., Vallons, V., Bruyninx, P., et al. (2016). Autonomous motivation is associated with the maintenance stage of behaviour change in people with affective disorders. Psychiatry Res. 240, 267–271. doi: 10.1016/j.psychres.2016.04.005
Veganuary (2022). Campaign in review. Veganuary. Available at: https://veganuary.com/campaign-reports/ (Accessed October 11, 2022).
Voi, S., and Sainsbury, K. (2019). The roles of autonomous motivation and self-control lapses in concurrent adherence to a gluten-free diet and a self-chosen weight loss plan in adults with coeliac disease. Psychol. Health 34, 943–962. doi: 10.1080/08870446.2019.1579912
Wadden, T., Foster, G., and Letizia, K. (1994). One-year behavioral treatment of obesity: comparison of moderate and severe caloric restriction and the effects of weight maintenance therapy. J. Consult. Clin. Psychol. 62, 165–171. doi: 10.1037/0022-006X.62.1.165
Werner, K. M., Milyavskaya, M., Foxen-Craft, E., and Koestner, R. (2016). Some goals just feel easier: self-concordance leads to goal progress through subjective ease, not effort. Personal. Individ. Differ. 96, 237–242. doi: 10.1016/j.paid.2016.03.002
Westhoek, H., Lesschen, J. P., Rood, T., Wagner, S., De Marco, A., Murphy-Bokern, D., et al. (2014). Food choices, health and environment: effects of cutting Europe’s meat and dairy intake. Glob. Environ. Chang. 26, 196–205. doi: 10.1016/j.gloenvcha.2014.02.004
Wilde, M. H., and Garvin, S. (2007). A concept analysis of self-monitoring. J. Adv. Nurs. 57, 339–350. doi: 10.1111/j.1365-2648.2006.04089.x
Williamson, L. Z., and Wilkowski, B. M. (2020). Nipping temptation in the bud: Examining strategic self-control in daily life. Pers. Soc. Psychol. Bull. 46, 961–975. doi: 10.1177/0146167219883606
Wilson, N., Nghiem, N., Mhurchu, C. N., Eyles, H., Baker, M. G., and Blakely, T. (2013). Foods and dietary patterns that are healthy, low-cost, and environmentally sustainable: a case study of optimization modeling for New Zealand. PLoS One 8:e59648. doi: 10.1371/journal.pone.0059648
Keywords: vegan, vegetarian, self-determination, autonomy, behaviour change
Citation: Kolbuszewska M, Anderson J and Milyavskaya M (2022) Autonomous motivation, goal-facilitating behaviours, and dietary goal progress in individuals transitioning to a veg*n diet: A longitudinal study. Front. Psychol. 13:1019714. doi: 10.3389/fpsyg.2022.1019714
Edited by:
Christopher J. Hopwood, University of Zurich, SwitzerlandReviewed by:
Meike Morren, VU Amsterdam, NetherlandsDerrick Tanous, University of Innsbruck, Austria
Copyright © 2022 Kolbuszewska, Anderson and Milyavskaya. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Marina Milyavskaya, marina.milyavskaya@carleton.ca