OSF

I imagine there are some other folks on here who keep a file of papers to convince skeptical colleagues that, yes, you really can use ecological momentary assessment, even in that sample?

Here's another example: Folks waiting for spinal surgery

https://journals.lww.com/neurosurgery/Fulltext/9900/Feasibility_and_Acceptability_of_a_Preoperative.481.aspx

These folks are often in a lot of pain and having a lot of trouble, but they liked EMA just fine.

#EcologicalMomentaryAssessment #EMA #Pain #SpineSurgery

Feasibility and Acceptability of a Preoperative Multimodal... : Neurosurgery

arge-scale study has examined the feasibility and acceptability of these methods in spine surgery patients. OBJECTIVE: To evaluate the feasibility and acceptability of a multimodal preoperative mHealth assessment in patients with degenerative spine disease. METHODS: Adults undergoing elective spine surgery were provided with Fitbit trackers and sent preoperative ecological momentary assessments (EMAs) assessing pain, disability, mood, and catastrophizing 5 times daily for 3 weeks. Objective adherence rates and a subjective acceptability survey were used to evaluate feasibility of these methods. RESULTS: The 77 included participants completed an average of 82 EMAs each, with an average completion rate of 86%. Younger age and chronic pulmonary disease were significantly associated with lower EMA adherence. Seventy-two (93%) participants completed Fitbit monitoring and wore the Fitbits for an average of 247 hours each. On average, participants wore the Fitbits for at least 12 hours per day for 15 days. Only worse mood scores were independently associated with lower Fitbit adherence. Most participants endorsed positive experiences with the study protocol, including 91% who said they would be willing to complete EMAs to improve their preoperative surgical guidance. CONCLUSION: Spine fusion candidates successfully completed a preoperative multimodal mHealth assessment with high acceptability. The intensive longitudinal data collected may provide new insights that improve patient selection and treatment guidance....

LWW

A while back I started writing blog posts on how to analyze #IntensiveLongitudinalData using #STAN.

The idea was sharing code for some of the most used models like (hierarchical) AR and VAR models as well as explaining the #STAN syntax a bit 😊.

I want to pick it up again, but for now, here is an example discussing the hierarchical AR(1) model. Curious what you all think 😊.

https://experienced-sampler.netlify.app/post/stan-hierarchical-ar/

#Bayes #rstats #ESM #ILD #EMA #ExperienceSampling #EcologicalMomentaryAssessment

STAN Code for Analyzing Intensive Longitudinal Data: Part IIa - Hierarchical Autoregressive Models | Experienced Sampler

Table of Contents Introduction The Complete Model But What Does it all Mean? 1.The Data Block and Data-generation 2.The Transformed Data Block 3.The Parameters Block 4.The Model Block

Experienced Sampler