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Feasibility of a Digital Health Intervention to Improve Diet Quality Among Women With High Blood Pressure: Randomized Controlled Feasibility Trial

Feasibility of a Digital Health Intervention to Improve Diet Quality Among Women With High Blood Pressure: Randomized Controlled Feasibility Trial

The mean days tracked per week overall was slightly higher, although not statistically significant, in the active comparator arm compared with the intervention arm (mean 4.6, SD 2.7 days vs 4.2, SD 2.1 days; P=.54). Likewise, a higher proportion of active comparator participants tracked 5 days or more per week, on average, compared with intervention participants (18/29, 63% vs 14/30, 47%; P=.24).

Dori M M Steinberg, Melissa C Kay, Laura P Svetkey, Sandy Askew, Jacob Christy, Jasmine Burroughs, Hira Ahmed, Gary G Bennett

JMIR Mhealth Uhealth 2020;8(12):e17536

The Association Between Engagement and Weight Loss Through Personal Coaching and Cell Phone Interventions in Young Adults: Randomized Controlled Trial

The Association Between Engagement and Weight Loss Through Personal Coaching and Cell Phone Interventions in Young Adults: Randomized Controlled Trial

Even though neither arm lost a significantly different amount of weight compared with the control arm at 24 months, the PC arm lost the greatest amount of weight at 6 months (P The CITY study was 1 of the 7 trials in the Early Adult Reduction of weight through Lifest Yle Intervention consortium, sponsored by National Heart Lung and Blood Institute (NHLBI, 5 U01 HL096720) [9].

Pao-Hwa Lin, Steven Grambow, Stephen Intille, John A Gallis, Tony Lazenka, Hayden Bosworth, Corrine L. Voils, Gary G Bennett, Bryan Batch, Jenifer Allen, Leonor Corsino, Crystal Tyson, Laura Svetkey

JMIR Mhealth Uhealth 2018;6(10):e10471

Associations of Internet Website Use With Weight Change in a Long-term Weight Loss Maintenance Program

Associations of Internet Website Use With Weight Change in a Long-term Weight Loss Maintenance Program

Tests at P < .05 were considered significant. Multiple imputation techniques to account for missing data are described elsewhere [15]. We used logistic and multiple linear regression analyses, as appropriate, to adjust selected weight outcomes for race, sex, education, income, age, and initial BMI. Suitably weighted point estimates, standard deviations, and P values were calculated using the MIANALYZE procedure in SAS.

Kristine L L Funk, Victor J Stevens, Lawrence J Appel, Alan Bauck, Phillip J Brantley, Catherine M Champagne, Janelle Coughlin, Arlene T Dalcin, Jean Harvey-Berino, Jack F Hollis, Gerald J Jerome, Betty M Kennedy, Lillian F Lien, Valerie H Myers, Carmen Samuel-Hodge, Laura P Svetkey, William M Vollmer

J Med Internet Res 2010;12(3):e29