Characteristics of Samples Used for Quantitative Analyses in the Journal Body Image

class: center, middle, inverse, title-slide

.title[
# Characteristics of Samples Used for Quantitative Analyses in the Journal Body Image
]
.author[
### Thomas Pollet, Rosie Buhaenko and Jeanne Bovet <br> Northumbria University <br><br> (<a href="mailto:thomas.pollet@northumbria.ac.uk" class="email">thomas.pollet@northumbria.ac.uk</a>)
]
.date[
### 2022-11-15 | <a href="http://tvpollet.github.io/disclaimer">disclaimer</a>
]

---

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## Today

* Work in progress.

* Largely descriptive project.

---
## Movement towards meta-science.

* Replication crisis in Psychology

* Describing the samples we use.

--> Recurrent criticism that psychology relies on student samples (e.g., [Thalmayer et al. 2020](https://doi.org/10.1037/amp0000622))

--> [W.E.I.R.D.](https://www2.psych.ubc.ca/~henrich/pdfs/WeirdPeople.pdf) : Western Educated Industrialised Rich and Democratic

--> External validity - [measurement crisis](https://doi.org/10.1177/2515245920952393)

--> ['Power failure'](https://doi.org/10.1038/nrn3475)

Previous project on samples used in [Evolution and Human Behaviour and Evolutionary Psychology](https://link.springer.com/article/10.1007/s40806-019-00192-2).

???
70% Online or student samples / >80% from 'Western' countries (Europe, USA/CAN/AUS)

---
## Sampling

A closer look at the samples being used.

Descriptive project

* Are samples different from general population in terms of age?

* Are samples different from general population in terms of BMI?

???
Why focus on age and BMI. Interesting variables: Aging population / population becoming more obese.
Separate gen. pop. and students.

---
## Methodology.

* All papers from 2021 from _Body Image_ (n = 137).

* 149 samples (5 meta-analyses or content analyses not analysed further).

---
## Methodology: Coding

* Type of paper (Quant. or not)

* Type of design (Between, Mixed, Within)

* Country (incl. multi-country)

* Type of sample: "General Population", Student, Other

* Sample characteristics (Age, Majority Ethnicity, Gender)

* BMI (Mean/SD - how measured)

???
Sample type based on majority

---
## Methodology: Statistical power

* [Cohen (1988)](https://scholar.google.com/scholar?as_q=&as_epq=Statistical%20power%20for%20the%20social%20sciences&as_occt=title&as_sauthors=J+Cohen&as_ylo=1988&as_yhi=1988&as_sdt=1.&as_sdtp=on&as_sdtf=&as_sdts=22&): 'small', 'medium' and 'large' effect sizes: 0.2 , 0.5 and 0.8 for Cohen's _d_.

* [Lovakov & Agadullina (2021)](https://doi.org/10.1002/ejsp.2752): over 6,000 Cohen's _d_ estimates and based on the 25th, 50th and 75th percentile, they suggested 0.15, 0.36 and 0.65 as small, medium and large.

* Some very broad assumptions:

* _t_-test (between-subject)
  * two-tailed _p_. 
  * 80% power is "good".

---
## Methodology: Simulations

* **Age**. Estimates from [CIA world factbook](cia.gov/the-world-factbook/) from 2020.

* **BMI**. Overall population estimate by gender from [NCD Risk Factor Collaboration (NCD-RisC)](https://linkinghub.elsevier.com/retrieve/pii/S0140673617321293) from 2016. Further checks with matched age groups.

--
* 100k simulations. One simulation: Draw a random sample (_n_) of the same size as the original study's sample size. `\(n \sim \mathcal{N}(\mu,\,\sigma^{2})\)` using the Means and SD provided. We then perform a one sample _t_-test against the reference value.

* median _p_ value of those 100k simulations.

???
Some robustness checks.

---
## Map: Inclusion.

???
Some coverage of Latin America, no coverage of Africa, China, Russia
Majority of quantitative samples are from the United States (n = 55), followed by the United Kingdom (n = 18), Australia (n = 18) and Canada (n = 11).

---
## Map: k samples.

---
## Map: Total sample sizes.

---
## Map: Median sample size.

???
Large sample from New Zealand. (AUS: 230; USA: 317; UK: 271.5; NZL: 6258)

---
## Type of samples

???
pregnant women (n = 1), mothers (n = 1) and a sample of students but who scored in the top tertile on a sub-scale of the EDI-2. Only four samples labelled as clinical. One gen. pop. sample recruited via churches.

---
## Types of samples: size.

???
341 vs. 204 - _p_ = .008. Not plotted other and clinical

---
## Power: Between-subject

* Median sample size: n = 404 (n = 393, if we restrict the analysis to one sample per paper).

* Excellent statistical power for both theoretical and empirical 'large' effect sizes: 100% and >99.99%, respectively.

* Very good power to detect 'medium' theoretical and empirical effect sizes: 99.89% and 95.05%, respectively.

* Low power to detect 'weak' effect sizes: 51.81% and 32.44%.

???
Robustness checks needed.

---
## Power: mixed designs

* Median sample size was substantially lower for designs classified as mixed (n = 142) versus between-participant (n = 404).

* Excellent statistical power for both theoretical and empirical 'large' effect sizes: 99.72% and 97.04%, respectively.

* Good power to detect 'medium' theoretical effect size of 0.5 : 84.10%, but inadequate power to document an empirical medium effect 56.76%.

* Very low power to detect 'weak' effect sizes: 21.96% and 14.40%.

???
35 mixed designs

---
## Sample size by design

<div class="figure" style="text-align: center">
<img src="raincloud.png" alt="Distribution of sample sizes of quantitative studies in Body Image. Two studies with within-participant design are not plotted" width="800px" />
<p class="caption">Distribution of sample sizes of quantitative studies in Body Image. Two studies with within-participant design are not plotted</p>
</div>

---
## Gender

* **Across all samples**: No difference in the median sample sizes of men and women (respectively: 240 and 249, Wilcoxon test _p_ = .819).

* **General population samples**: Sample sizes did not differ by gender (Wilcoxon test _p_ = .658).

* **Student samples**: female sample sizes tended to be larger than male sample sizes (respective medians: 199.5 vs. 70.5, Wilcoxon test _p_ = .008).

* Samples that collected **both** men and women (n = 60): Significantly more women than men (median difference: 17 more women than men, paired Wilcoxon test, _p_ = .003).

* Similar conclusion when we restrict to general population samples or student samples (respective _p's_ = .009 and .0005).

---
## Age

* Weighted mean age by sample size for women (_M_ = 26.83 years, _SD_ = 6.17) was significantly lower than that for men (_M_ = 30.83, _SD_ = 8.70, _t_(52552) = 73.19, _d_ = 0.554).

* The overall difference between men and women in age is largely driven by that there are more women in student samples.

---
## Age: female and male samples

<table style="text-align:center"><caption><strong>Weighed means and standard deviations for age by type of sample for female samples</strong></caption>
<tr><td colspan="4" style="border-bottom: 1px solid black"></td></tr><tr><td style="text-align:left">Type of sample</td><td>Mean Age women</td><td>SD Age women</td><td>n women</td></tr>
<tr><td colspan="4" style="border-bottom: 1px solid black"></td></tr><tr><td style="text-align:left">Clinical</td><td>23.970</td><td>7.659</td><td>362</td></tr>
<tr><td style="text-align:left">General Population</td><td>33.044</td><td>9.659</td><td>33,078</td></tr>
<tr><td style="text-align:left">Other</td><td>23.488</td><td>3.880</td><td>11,207</td></tr>
<tr><td style="text-align:left">Students</td><td>20.357</td><td>2.652</td><td>10,993</td></tr>
<tr><td colspan="4" style="border-bottom: 1px solid black"></td></tr></table>

<br>

<table style="text-align:center"><caption><strong>Weighed means and standard deviations for age by type of sample for male samples</strong></caption>
<tr><td colspan="4" style="border-bottom: 1px solid black"></td></tr><tr><td style="text-align:left">Type of sample</td><td>Mean Age men</td><td>SD Age men</td><td>n men</td></tr>
<tr><td colspan="4" style="border-bottom: 1px solid black"></td></tr><tr><td style="text-align:left">General Population</td><td>29.548</td><td>5.462</td><td>16,817</td></tr>
<tr><td style="text-align:left">Other</td><td>31.694</td><td>9.881</td><td>14,350</td></tr>
<tr><td style="text-align:left">Students</td><td>20.762</td><td>3.121</td><td>1,698</td></tr>
<tr><td colspan="4" style="border-bottom: 1px solid black"></td></tr></table>

???
Notice discrepancy in n men for students vs. n women

---
## BMI

* BMI collected for 69.44% of the quantitative samples. Vast majority of samples BMI was self-reported. 9% reporting it being measured.

* **All Samples**: The weighted mean BMI by sample size for women (_M_ = 24.41, _SD_ = 5.27) was significantly lower than that for men (_M_ = 26.27, _SD_ = 5.95, _t_(62452) = 46.73, _p_ < .0001, _d_ = 0.312).

* **General population**: The weighted mean BMI by sample size for women (_M_ = 25.36, _SD_ = 5.98) was significantly lower than that for men (_M_ = 25.51, _SD_ = 5.45, _t_(36686) = 2.84, _p_ = .005, _d_ = 0.026).

* **Students**: The weighted mean BMI by sample size for women (_M_ = 22.8, _SD_ = 4.13) was significantly lower than that for men (_M_ = 25.13, _SD_ = 5.03, _t_(2064) = 18.16, _p_ <.0001, _d_ = 0.547). (Note over 10x as large a difference)

???
Note again that female students outnumber male students 10 to 1.

---
## BMI: female and male samples

<table style="text-align:center"><caption><strong>Weighed means and standard deviations for BMI by type of sample for female samples</strong></caption>
<tr><td colspan="4" style="border-bottom: 1px solid black"></td></tr><tr><td style="text-align:left">Type of sample</td><td>Mean BMI women</td><td>SD BMI women</td><td>n women</td></tr>
<tr><td colspan="4" style="border-bottom: 1px solid black"></td></tr><tr><td style="text-align:left">Clinical</td><td>20.499</td><td>5.114</td><td>362</td></tr>
<tr><td style="text-align:left">General Population</td><td>25.357</td><td>5.980</td><td>33,078</td></tr>
<tr><td style="text-align:left">Other</td><td>27.478</td><td>6.448</td><td>11,207</td></tr>
<tr><td style="text-align:left">Students</td><td>22.800</td><td>4.125</td><td>10,993</td></tr>
<tr><td colspan="4" style="border-bottom: 1px solid black"></td></tr></table>

<br>

<table style="text-align:center"><caption><strong>Weighed means and standard deviations for BMI by type of sample for male samples</strong></caption>
<tr><td colspan="4" style="border-bottom: 1px solid black"></td></tr><tr><td style="text-align:left">Type of sample</td><td>Mean BMI men</td><td>SD BMI men</td><td>n men</td></tr>
<tr><td colspan="4" style="border-bottom: 1px solid black"></td></tr><tr><td style="text-align:left">General Population</td><td>25.508</td><td>5.454</td><td>16,817</td></tr>
<tr><td style="text-align:left">Other</td><td>26.673</td><td>6.228</td><td>14,350</td></tr>
<tr><td style="text-align:left">Students</td><td>25.131</td><td>5.034</td><td>1,698</td></tr>
<tr><td colspan="4" style="border-bottom: 1px solid black"></td></tr></table>

---
class: simulation_small
## Simulations: Age

<table style="text-align:center"><caption><strong>Summary of simulations. Note: p < .1 = ., p < .05 = *, p < .01 = **, p < .001 = ***.</strong></caption>
<tr><td colspan="7" style="border-bottom: 1px solid black"></td></tr><tr><td style="text-align:left">Country</td><td>Gender of sample</td><td>Mean Age</td><td>SD Age</td><td>Sample Size</td><td>Mean Age population</td><td>p</td></tr>
<tr><td colspan="7" style="border-bottom: 1px solid black"></td></tr><tr><td style="text-align:left">USA</td><td>Female</td><td>33</td><td>8.12</td><td>916</td><td>39.80</td><td>* * *</td></tr>
<tr><td style="text-align:left">USA</td><td>Female</td><td>21.87</td><td>2.28</td><td>350</td><td>39.80</td><td>* * *</td></tr>
<tr><td style="text-align:left">USA</td><td>Female</td><td>31.14</td><td>11.47</td><td>341</td><td>39.80</td><td>* * *</td></tr>
<tr><td style="text-align:left">USA</td><td>Female</td><td>37.51</td><td>11.07</td><td>235</td><td>39.80</td><td>* *</td></tr>
<tr><td style="text-align:left">USA</td><td>Female</td><td>35.47</td><td>13.52</td><td>425</td><td>39.80</td><td>* * *</td></tr>
<tr><td style="text-align:left">USA</td><td>Female</td><td>36.42</td><td>4.16</td><td>135</td><td>39.80</td><td>* * *</td></tr>
<tr><td style="text-align:left">USA</td><td>Female</td><td>55.95</td><td>7.11</td><td>126</td><td>39.80</td><td>* * *</td></tr>
<tr><td style="text-align:left">USA</td><td>Female</td><td>53.10</td><td>12.70</td><td>82</td><td>39.80</td><td>* * *</td></tr>
<tr><td style="text-align:left">USA</td><td>Female</td><td>36.66</td><td>11.92</td><td>115</td><td>39.80</td><td>* *</td></tr>
<tr><td style="text-align:left">USA</td><td>Female</td><td>36.83</td><td>11.46</td><td>130</td><td>39.80</td><td>* *</td></tr>
<tr><td style="text-align:left">USA</td><td>Female</td><td>38.50</td><td>11.09</td><td>132</td><td>39.80</td><td></td></tr>
<tr><td style="text-align:left">USA</td><td>Female</td><td>49.10</td><td>13.99</td><td>13</td><td>39.80</td><td>*</td></tr>
<tr><td style="text-align:left">USA</td><td>Male</td><td>24</td><td>3.60</td><td>1,011</td><td>37.20</td><td>* * *</td></tr>
<tr><td style="text-align:left">USA</td><td>Male</td><td>36.61</td><td>4.12</td><td>153</td><td>37.20</td><td>.</td></tr>
<tr><td style="text-align:left">USA</td><td>Male</td><td>55</td><td>6.59</td><td>108</td><td>37.20</td><td>* * *</td></tr>
<tr><td style="text-align:left">UK</td><td>Female</td><td>25.29</td><td>5.64</td><td>156</td><td>41.70</td><td>* * *</td></tr>
<tr><td style="text-align:left">UK</td><td>Female</td><td>29.30</td><td>10.20</td><td>369</td><td>41.70</td><td>* * *</td></tr>
<tr><td style="text-align:left">UK</td><td>Male</td><td>23.64</td><td>5.29</td><td>42</td><td>39.60</td><td>* * *</td></tr>
<tr><td style="text-align:left">UK</td><td>Male</td><td>30.67</td><td>8.80</td><td>201</td><td>39.60</td><td>* * *</td></tr>
<tr><td style="text-align:left">AUS</td><td>Female</td><td>19.79</td><td>2.07</td><td>227</td><td>38.50</td><td>* * *</td></tr>
<tr><td style="text-align:left">AUS</td><td>Female</td><td>44.70</td><td>6.97</td><td>240</td><td>38.50</td><td>* * *</td></tr>
<tr><td style="text-align:left">AUS</td><td>Female</td><td>23.39</td><td>6.49</td><td>111</td><td>38.50</td><td>* * *</td></tr>
<tr><td style="text-align:left">AUS</td><td>Female</td><td>21.68</td><td>5.50</td><td>291</td><td>38.50</td><td>* * *</td></tr>
<tr><td style="text-align:left">AUS</td><td>Female</td><td>46.75</td><td>4.54</td><td>206</td><td>38.50</td><td>* * *</td></tr>
<tr><td style="text-align:left">AUS</td><td>Female</td><td>24.43</td><td>5.25</td><td>119</td><td>38.50</td><td>* * *</td></tr>
<tr><td style="text-align:left">AUS</td><td>Female</td><td>32.33</td><td>8.48</td><td>3,039</td><td>38.50</td><td>* * *</td></tr>
<tr><td colspan="7" style="border-bottom: 1px solid black"></td></tr></table>

---
## Simulations: Age: scrollable

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---
class: simulation
## Simulations: BMI (general population)

<table style="text-align:center"><caption><strong>Summary of simulations. Note: p < .1 = ., p < .05 = *, p < .01 = **, p < .001 = ***.</strong></caption>
<tr><td colspan="7" style="border-bottom: 1px solid black"></td></tr><tr><td style="text-align:left">Country</td><td>Gender of sample</td><td>Mean BMI</td><td>SD BMI</td><td>Sample Size</td><td>Mean BMI population</td><td>p</td></tr>
<tr><td colspan="7" style="border-bottom: 1px solid black"></td></tr><tr><td style="text-align:left">USA</td><td>Female</td><td>26.71</td><td>7.69</td><td>350</td><td>29.07</td><td>* * *</td></tr>
<tr><td style="text-align:left">USA</td><td>Female</td><td>28.20</td><td>7.97</td><td>135</td><td>29.07</td><td></td></tr>
<tr><td style="text-align:left">USA</td><td>Female</td><td>28.58</td><td>7.36</td><td>126</td><td>29.07</td><td></td></tr>
<tr><td style="text-align:left">USA</td><td>Female</td><td>26.70</td><td>6.50</td><td>82</td><td>29.07</td><td>* *</td></tr>
<tr><td style="text-align:left">USA</td><td>Female</td><td>27.18</td><td>8.85</td><td>115</td><td>29.07</td><td>*</td></tr>
<tr><td style="text-align:left">USA</td><td>Female</td><td>27.82</td><td>7.31</td><td>130</td><td>29.07</td><td>.</td></tr>
<tr><td style="text-align:left">USA</td><td>Female</td><td>28.99</td><td>7.44</td><td>132</td><td>29.07</td><td></td></tr>
<tr><td style="text-align:left">USA</td><td>Female</td><td>27.01</td><td>6.41</td><td>13</td><td>29.07</td><td></td></tr>
<tr><td style="text-align:left">USA</td><td>Male</td><td>25.33</td><td>6.23</td><td>1,011</td><td>29.01</td><td>* * *</td></tr>
<tr><td style="text-align:left">USA</td><td>Male</td><td>28.47</td><td>7.83</td><td>153</td><td>29.01</td><td></td></tr>
<tr><td style="text-align:left">USA</td><td>Male</td><td>28.60</td><td>5.34</td><td>108</td><td>29.01</td><td></td></tr>
<tr><td style="text-align:left">UK</td><td>Female</td><td>26.99</td><td>8</td><td>188</td><td>27.15</td><td></td></tr>
<tr><td style="text-align:left">UK</td><td>Male</td><td>24.41</td><td>3.52</td><td>42</td><td>27.48</td><td>* * *</td></tr>
<tr><td style="text-align:left">AUS</td><td>Female</td><td>23.50</td><td>5.34</td><td>227</td><td>26.87</td><td>* * *</td></tr>
<tr><td style="text-align:left">AUS</td><td>Female</td><td>27.85</td><td>7.85</td><td>240</td><td>26.87</td><td>.</td></tr>
<tr><td style="text-align:left">AUS</td><td>Female</td><td>24.59</td><td>5.43</td><td>291</td><td>26.87</td><td>* * *</td></tr>
<tr><td style="text-align:left">AUS</td><td>Female</td><td>28.35</td><td>6.91</td><td>206</td><td>26.87</td><td>* *</td></tr>
<tr><td style="text-align:left">AUS</td><td>Female</td><td>24.71</td><td>5.60</td><td>119</td><td>26.87</td><td>* * *</td></tr>
<tr><td style="text-align:left">AUS</td><td>Female</td><td>25.90</td><td>6.42</td><td>3,039</td><td>26.87</td><td>* * *</td></tr>
<tr><td colspan="7" style="border-bottom: 1px solid black"></td></tr></table>

---
class: simulation
## Simulations: BMI (general population matched)

<table style="text-align:center"><caption><strong>Summary of simulations. Note: p < .1 = ., p < .05 = *, p < .01 = **, p < .001 = ***.</strong></caption>
<tr><td colspan="7" style="border-bottom: 1px solid black"></td></tr><tr><td style="text-align:left">Country</td><td>Gender of sample</td><td>Mean BMI</td><td>SD BMI</td><td>Sample Size</td><td>Mean BMI population</td><td>p</td></tr>
<tr><td colspan="7" style="border-bottom: 1px solid black"></td></tr><tr><td style="text-align:left">USA</td><td>Female</td><td>26.71</td><td>7.69</td><td>350</td><td>26</td><td>.</td></tr>
<tr><td style="text-align:left">USA</td><td>Female</td><td>28.20</td><td>7.97</td><td>135</td><td>29.20</td><td></td></tr>
<tr><td style="text-align:left">USA</td><td>Female</td><td>28.58</td><td>7.36</td><td>126</td><td>31.05</td><td>* * *</td></tr>
<tr><td style="text-align:left">USA</td><td>Female</td><td>26.70</td><td>6.50</td><td>82</td><td>30.88</td><td>* * *</td></tr>
<tr><td style="text-align:left">USA</td><td>Female</td><td>27.18</td><td>8.85</td><td>115</td><td>29.20</td><td>*</td></tr>
<tr><td style="text-align:left">USA</td><td>Female</td><td>27.82</td><td>7.31</td><td>130</td><td>29.20</td><td>*</td></tr>
<tr><td style="text-align:left">USA</td><td>Female</td><td>28.99</td><td>7.44</td><td>132</td><td>29.20</td><td></td></tr>
<tr><td style="text-align:left">USA</td><td>Female</td><td>27.01</td><td>6.41</td><td>13</td><td>30.50</td><td>.</td></tr>
<tr><td style="text-align:left">USA</td><td>Male</td><td>25.33</td><td>6.23</td><td>1,011</td><td>26.74</td><td>* * *</td></tr>
<tr><td style="text-align:left">USA</td><td>Male</td><td>28.47</td><td>7.83</td><td>153</td><td>29.38</td><td></td></tr>
<tr><td style="text-align:left">USA</td><td>Male</td><td>28.60</td><td>5.34</td><td>108</td><td>30.20</td><td>* *</td></tr>
<tr><td style="text-align:left">UK</td><td>Female</td><td>26.99</td><td>8</td><td>188</td><td>25.67</td><td>*</td></tr>
<tr><td style="text-align:left">UK</td><td>Male</td><td>24.41</td><td>3.52</td><td>42</td><td>24.98</td><td></td></tr>
<tr><td style="text-align:left">AUS</td><td>Female</td><td>23.50</td><td>5.34</td><td>227</td><td>24.29</td><td>*</td></tr>
<tr><td style="text-align:left">AUS</td><td>Female</td><td>27.85</td><td>7.85</td><td>240</td><td>27.98</td><td></td></tr>
<tr><td style="text-align:left">AUS</td><td>Female</td><td>24.59</td><td>5.43</td><td>291</td><td>24.29</td><td></td></tr>
<tr><td style="text-align:left">AUS</td><td>Female</td><td>28.35</td><td>6.91</td><td>206</td><td>27.98</td><td></td></tr>
<tr><td style="text-align:left">AUS</td><td>Female</td><td>24.71</td><td>5.60</td><td>119</td><td>24.29</td><td></td></tr>
<tr><td style="text-align:left">AUS</td><td>Female</td><td>25.90</td><td>6.42</td><td>3,039</td><td>25.90</td><td></td></tr>
<tr><td colspan="7" style="border-bottom: 1px solid black"></td></tr></table>
---
class: simulation
## Simulations: BMI (Students)

<table style="text-align:center"><caption><strong>Summary of simulations. Note: p < .1 = ., p < .05 = *, p < .01 = **, p < .001 = ***.</strong></caption>
<tr><td colspan="7" style="border-bottom: 1px solid black"></td></tr><tr><td style="text-align:left">Country</td><td>Gender of sample</td><td>Mean BMI</td><td>SD BMI</td><td>Sample Size</td><td>Mean BMI population (20-24)</td><td>p</td></tr>
<tr><td colspan="7" style="border-bottom: 1px solid black"></td></tr><tr><td style="text-align:left">USA</td><td>Female</td><td>25.57</td><td>7.39</td><td>371</td><td>26</td><td></td></tr>
<tr><td style="text-align:left">USA</td><td>Female</td><td>24.89</td><td>6</td><td>475</td><td>26</td><td>* * *</td></tr>
<tr><td style="text-align:left">USA</td><td>Female</td><td>23.67</td><td>4.46</td><td>151</td><td>26</td><td>* * *</td></tr>
<tr><td style="text-align:left">USA</td><td>Female</td><td>22.25</td><td>3.17</td><td>556</td><td>26</td><td>* * *</td></tr>
<tr><td style="text-align:left">USA</td><td>Female</td><td>23.11</td><td>3.54</td><td>349</td><td>26</td><td>* * *</td></tr>
<tr><td style="text-align:left">USA</td><td>Male</td><td>25.44</td><td>5.09</td><td>265</td><td>26.74</td><td>* * *</td></tr>
<tr><td style="text-align:left">UK</td><td>Female</td><td>23.61</td><td>4.97</td><td>189</td><td>24.76</td><td>* *</td></tr>
<tr><td style="text-align:left">UK</td><td>Female</td><td>24.24</td><td>3.99</td><td>51</td><td>24.76</td><td></td></tr>
<tr><td style="text-align:left">AUS</td><td>Female</td><td>22.10</td><td>3.70</td><td>373</td><td>24.29</td><td>* * *</td></tr>
<tr><td style="text-align:left">AUS</td><td>Female</td><td>21.50</td><td>3</td><td>115</td><td>24.29</td><td>* * *</td></tr>
<tr><td style="text-align:left">AUS</td><td>Female</td><td>21.74</td><td>3.71</td><td>146</td><td>24.29</td><td>* * *</td></tr>
<tr><td style="text-align:left">AUS</td><td>Female</td><td>24.82</td><td>5.67</td><td>233</td><td>24.29</td><td></td></tr>
<tr><td style="text-align:left">AUS</td><td>Male</td><td>23.89</td><td>4.81</td><td>66</td><td>25.38</td><td>*</td></tr>
<tr><td style="text-align:left">CAN</td><td>Female</td><td>21.83</td><td>4.97</td><td>142</td><td>24.10</td><td>* * *</td></tr>
<tr><td style="text-align:left">CAN</td><td>Female</td><td>22.83</td><td>3.73</td><td>24</td><td>24.10</td><td></td></tr>
<tr><td style="text-align:left">CAN</td><td>Female</td><td>22.89</td><td>4.28</td><td>28</td><td>24.10</td><td></td></tr>
<tr><td style="text-align:left">CAN</td><td>Female</td><td>23.35</td><td>4.34</td><td>340</td><td>24.10</td><td>* *</td></tr>
<tr><td style="text-align:left">CAN</td><td>Female</td><td>23.25</td><td>4.90</td><td>311</td><td>24.10</td><td>* *</td></tr>
<tr><td colspan="7" style="border-bottom: 1px solid black"></td></tr></table>

---
## Summary

* Provided an overview of the type of samples that are in _Body image_ .

* Simulations suggest that "general population" samples tend to differ from the overall population in age and sometimes also BMI.

* Simulations suggest that student samples tend to differ from age matched population samples in BMI.

???
Limitations: descriptive project. Did not code claims on inference or generality. Though some examples call for further research on other cultures or ethnicities.

---
## Moving forward...

* **Description.** Whether it is "Good or Bad" is a different question -- I am not an editor for _Body Image_ (not even an active researcher on body image.)

* Our synthesis might provide some reference data for future work.

* Introduction of [Constraints on Generality statements](https://doi.org/10.1177/1745691617708630).

---
## Any Questions?

[http://tvpollet.github.io](http://tvpollet.github.io)

Twitter: @tvpollet

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## Acknowledgments

* I am greatly indebted to my collaborators. (Any mistakes are my own!).

* You for listening!