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How intensive longitudinal data can stimulate advances in health behavior maintenance theories and interventions.

Abstract：

:Interventions that promote long-term maintenance of behaviors such as exercise, healthy eating, and avoidance of tobacco and excessive alcohol are critical to reduce noncommunicable disease burden. Theories of health behavior maintenance tend to address reactive (i.e., automatic) or reflective (i.e., deliberative) decision-making processes, but rarely both. Progress in this area has been stalled by theories that say little about when, why, where, and how reactive and reflective systems interact to promote or derail a positive health behavior change. In this commentary, we discuss factors influencing the timing and circumstances under which an individual may shift between the two systems such as (a) limited availability of psychological assets, (b) interruption in exposure to established contextual cues, and (c) lack of intrinsic or appetitive motives. To understand the putative factors that regulate the interface between these systems, research methods are needed that are able to capture properties such as (a) fluctuation over short periods of time, (b) change as a function of time, (c) context dependency, (d) implicit and physiological channels, and (e) idiographic phenomenology. These properties are difficult to assess with static, cross-sectional, laboratory-based, or retrospective research methods. We contend that intensive longitudinal data (ILD) collection and analytic strategies such as smartphone and sensor-based real-time activity and location monitoring, ecological momentary assessment (EMA), machine learning, and systems modeling are well-positioned to capture and interpret within-person shifts between reactive and reflective systems underlying behavior maintenance. We conclude with examples of how ILD can accelerate the development of theories and interventions to sustain health behavior over the long term.

journal_name

Transl Behav Med

journal_title

Translational behavioral medicine

authors

Dunton GF,Rothman AJ,Leventhal AM,Intille SS

doi

10.1093/tbm/ibz165

subject

Has Abstract

pub_date

2019-11-15 00:00:00

eissn

1869-6716

issn

1613-9860

pii

5626448

pub_type

杂志文章

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How intensive longitudinal data can stimulate advances in health behavior maintenance theories and interventions.