社交圈反映健康状况

你的朋友会比你的健身追踪器透露更多关于健康的信息

If you wear a fitness tracker, no doubt you check it throughout the day, tallying your steps or checking your heart rate and patting yourself on the back as you get closer to your goals. But a new study finds that your faithful Fitbit really isn't as much of an indicator of your health and fitness as the people you hang out with.

如果你戴着健身追踪器，毫无疑问你一整天都在查看它，记录你的步数或检查你的心率，当你接近目标时拍拍自己的后背。但一项新的研究发现，你忠实的Fitbit运动追踪器并不能像和你一起出去玩的人一样，显示你的健康状况。

(Photo: Monkey Business Images/Shutterstock)

Researchers (and, heck, our parents) have long known that our peers influence whether we drink or smoke or engage in other not-so-healthy habits. Now scientists wanted to take a closer look to see if friends also influence health, as well as happiness and stress.

研究人员(见鬼，还有我们的父母)早就知道，我们的同龄人会影响我们喝酒、抽烟或其他不太健康的习惯。现在，科学家们想要近距离观察朋友是否也会影响健康、幸福和压力。

"We were interested in the topology of the social network — what does my position within my social network predict about my health and well-being?" said study lead author Nitesh V. Chawla, professor of computer science and engineering at Notre Dame, in a statement. "What we found was the social network structure provides a significant improvement in predictability of wellness states of an individual over just using the data derived from wearables, like the number of steps or heart rate."

“我们对社交网络的拓扑结构很感兴趣——我在社交网络中的位置如何预测我的健康和幸福?”“我们发现，社交网络结构大大提高了个人健康状况的可预测性，而不仅仅是使用来自可穿戴设备的数据，比如步数或心率。”

Participants in the study wore Fitbits so researchers could gather information about steps, heart rate, sleep data and activity level. They also completed surveys about their feelings of happiness, positivity and stress. Researchers captured data about the participants' social networks using a phone app that gathered information about calls and texts.

这项研究的参与者佩戴fitbit，这样研究人员就可以收集有关步数、心率、睡眠数据和活动水平的信息。他们还完成了关于幸福感、积极性和压力的调查。研究人员使用一款手机应用程序捕捉了参与者社交网络的数据，该应用程序收集了有关通话和短信的信息。

(Photo: Syda Productions/Shutterstock)

The team then analyzed the data, comparing the tracker information to the social network characteristics. The results, which were published in the journal PLOS ONE, showed a strong correlation between the structure of the participants' social network and their heart rate, the number of steps they took and their daily level of activity.

然后，研究小组分析了这些数据，并将跟踪器信息与社交网络特征进行了比较。研究结果发表在《公共科学图书馆•综合》杂志上，结果显示，参与者的社交网络结构与他们的心率、步数和日常活动水平之间存在很强的相关性。

Adding information from a social network made for a much better predictor of an individual's health and well-being versus just looking at Fitbit health data alone, the study found. When researchers combined friend group info with data from fitness trackers, they had a 65% improvement in predicting a person's happiness, 54% improvement in predicting a person's self-assessed health, 55% improvement in predicting positive attitude and 38% improvement in predicting feelings of success.

研究发现，与只看Fitbit上的健康数据相比，在社交网络上添加信息能更好地预测一个人的健康状况。当研究人员将朋友圈信息与健身追踪器的数据结合起来时，他们预测一个人的快乐程度的准确率提高了65%，预测一个人自我评估的健康状况的准确率提高了54%，预测积极态度的准确率提高了55%，预测成功感觉的准确率提高了38%。

"This study asserts that without social network information, we only have an incomplete view of an individual's wellness state, and to be fully predictive or to be able to derive interventions, it is critical to be aware of the social network structural features as well," Chawla said.

舒拉说:“这项研究表明，如果没有社交网络的信息，我们对一个人的健康状况只有一个不完整的看法，要想完全预测或得出干预措施，了解社交网络的结构特征也至关重要。”

The researchers suggest that one way these research results might be used is in the workplace. Employers who give workers fitness trackers in order to improve their health could suggest they share their progress on a social media platform in order to build an encouraging network.

研究人员表示，这些研究结果可能被用于工作场所。为员工提供健身追踪器以改善他们健康状况的雇主，可以建议他们在社交媒体平台上分享自己的进步，以建立一个令人鼓舞的网络。

"I do believe these incentives that we institute at work are meaningful, but I also believe we're not seeing the effect because we may not be capitalizing on them the way we should," Chawla said.

舒拉说:“我确实认为，我们在工作中制定的这些激励措施是有意义的，但是我也认为，我们没有看到效果，因为我们可能没有以最适当的方式利用这些措施。”