| Title |
Just-in-Time Adaptive Interventions (JITAIs) in Mobile Health: Key Components and Design Principles for Ongoing Health Behavior Support
|
|---|---|
| Published in |
Annals of Behavioral Medicine, December 2017
|
| DOI | 10.1007/s12160-016-9830-8 |
| Pubmed ID | |
| Authors |
Inbal Nahum-Shani, Shawna N Smith, Bonnie J Spring, Linda M Collins, Katie Witkiewitz, Ambuj Tewari, Susan A Murphy |
X Demographics
The data shown below were collected from the profiles of 44 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 15 | 34% |
| United Kingdom | 8 | 18% |
| Australia | 2 | 5% |
| Sri Lanka | 1 | 2% |
| Italy | 1 | 2% |
| Argentina | 1 | 2% |
| Canada | 1 | 2% |
| Colombia | 1 | 2% |
| Singapore | 1 | 2% |
| Other | 0 | 0% |
| Unknown | 13 | 30% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 18 | 41% |
| Members of the public | 14 | 32% |
| Practitioners (doctors, other healthcare professionals) | 10 | 23% |
| Science communicators (journalists, bloggers, editors) | 2 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 1,021 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | <1% |
| United Arab Emirates | 1 | <1% |
| Unknown | 1019 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 202 | 20% |
| Researcher | 144 | 14% |
| Student > Master | 104 | 10% |
| Student > Bachelor | 80 | 8% |
| Student > Doctoral Student | 69 | 7% |
| Other | 168 | 16% |
| Unknown | 254 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 237 | 23% |
| Computer Science | 101 | 10% |
| Medicine and Dentistry | 66 | 6% |
| Social Sciences | 59 | 6% |
| Engineering | 48 | 5% |
| Other | 170 | 17% |
| Unknown | 340 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 60. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 October 2022.
All research outputs
#719,905
of 25,759,158 outputs
Outputs from Annals of Behavioral Medicine
#90
of 1,496 outputs
Outputs of similar age
#15,951
of 446,239 outputs
Outputs of similar age from Annals of Behavioral Medicine
#6
of 42 outputs
Altmetric has tracked 25,759,158 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,496 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.6. This one has done particularly well, scoring higher than 93% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 446,239 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 42 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.