Diminished Anticipatory and Consummatory Pleasure in Dysphoria: Evidence From an Experience Sampling Study

Li, Xu; Zhang, Yuting; Zhi-jing, Huang; Chen, Xuelei; Yuan, Feng-Hui; Sun, Xin

doi:10.3389/fpsyg.2019.02124

Cited by 17 publications

(15 citation statements)

References 66 publications

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“…Sufferers may exhibit several symptoms, including (but not limited to) reduced cognitive performance, insomnia, low mood/self-esteem, non-interactiveness/motor retardation, and reduced appetite [ 24 , 185 ]. Previous research has employed digital technology to identify distinct associations between depressed participants and patterns of behavior [ 116 , 118 , 140 , 169 , 200 ]. For example, depression has been assessed via patterned psychomotor activity based on accelerometer oscillations and text/call behavior on mobile phones [ 93 ].…”

Section: Introductionmentioning

confidence: 99%

Exploring the digital footprint of depression: a PRISMA systematic literature review of the empirical evidence

et al. 2022

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Background This PRISMA systematic literature review examined the use of digital data collection methods (including ecological momentary assessment [EMA], experience sampling method [ESM], digital biomarkers, passive sensing, mobile sensing, ambulatory assessment, and time-series analysis), emphasizing on digital phenotyping (DP) to study depression. DP is defined as the use of digital data to profile health information objectively. Aims Four distinct yet interrelated goals underpin this study: (a) to identify empirical research examining the use of DP to study depression; (b) to describe the different methods and technology employed; (c) to integrate the evidence regarding the efficacy of digital data in the examination, diagnosis, and monitoring of depression and (d) to clarify DP definitions and digital mental health records terminology. Results Overall, 118 studies were assessed as eligible. Considering the terms employed, “EMA”, “ESM”, and “DP” were the most predominant. A variety of DP data sources were reported, including voice, language, keyboard typing kinematics, mobile phone calls and texts, geocoded activity, actigraphy sensor-related recordings (i.e., steps, sleep, circadian rhythm), and self-reported apps’ information. Reviewed studies employed subjectively and objectively recorded digital data in combination with interviews and psychometric scales. Conclusions Findings suggest links between a person’s digital records and depression. Future research recommendations include (a) deriving consensus regarding the DP definition and (b) expanding the literature to consider a person’s broader contextual and developmental circumstances in relation to their digital data/records.

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Section: Introductionmentioning

confidence: 99%

Exploring the digital footprint of depression: a PRISMA systematic literature review of the empirical evidence

et al. 2022

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“…For example, low PA in anhedonia is associated with lower levels of motivation six hours later [45], and the results suggest that individuals with anhedonia are at risk for a negative spiral of low PA and low motivation. Furthermore, depressive symptoms are also linked to diminished anticipatory pleasure experiences [46 ], and a weaker link between anticipatory pleasure and active behavior [37]. Together, these EMA advances suggest that, in addition to a lower mean level of PA, individuals with depressive symptoms are less able or less motivated to modify their daily behaviors as a function of reward anticipation.…”

Section: Anhedonia In Daily Lifementioning

confidence: 99%

Psychopathology and positive emotions in daily life

Heininga¹,

Kuppens²

2020

Preprint

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In this short review, we describe recent trends from research investigating positive affect (PA) in daily life in relation to mood disorders. Aside from notable exceptions (e.g., mania), most mood disorders involve relatively lower levels of PA in daily life, often combined with a larger level of variability in PA. In reaction to positive events, studies show a puzzling “mood brightening” effect in individuals with mood disorder symptoms that suggests hyper responsiveness to real-life rewards. Studies into anhedonia (i.e., lack of, or lower levels of PA) suggest that high-arousal PA and anticipatory PA are potential targets for intervention. Despite PA-focused interventions bear promises of greater therapeutic effectiveness, so far, these promises have not materialized yet.

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“…Sufferers may exhibit several symptoms, including (but not limited to) reduced cognitive performance, insomnia, low mood/self-esteem, non-interactiveness/ motor retardation, and reduced appetite [24,185]. Previous research has employed digital technology to identify distinct associations between depressed participants and patterns of behavior [116,118,140,169,200]. For example, depression has been assessed via patterned psychomotor activity based on accelerometer oscillations and text/call behavior on mobile phones [93].…”

Section: The Digital Footprint Of Depressionmentioning

confidence: 99%

Exploring the Digital Footprint of Depression: A PRISMA Systematic Literature Review of the Empirical Evidence.

Zarate¹,

Stavropoulos²,

Ball³

et al. 2022

Preprint

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Background: This PRISMA systematic literature review examined the use of digital data collection methods (including ecological momentary assessment [EMA], experience sampling method [ESM], digital biomarkers, passive sensing, mobile sensing, ambulatory assessment, and time-series analysis), emphasizing on digital phenotyping (DP) to study depression. DP is defined as the use of digital data to profile health information objectively. Aims: Four distinct yet interrelated goals underpin this study: (a) to identify empirical research examining the use of DP to study depression; (b) to describe the different methods and technology employed; (c) to integrate the evidence regarding the efficacy of digital data in the examination, diagnosis, and monitoring of depression and (d) to clarify DP definitions and digital mental health records terminology. Results: Overall, 118 studies were assessed as eligible. Considering the terms employed, “EMA”, “ESM”, and “DP” were the most predominant. A variety of DP data sources were reported, including voice, language, keyboard typing kinematics, mobile phone calls and texts, geocoded activity, actigraphy sensor-related recordings (i.e., steps, sleep, circadian rhythm), and self-reported apps’ information. Reviewed studies employed subjectively and objectively recorded digital data in combination with interviews and psychometric scales. Conclusions: Findings suggest links between a person’s digital records and depression. Future research recommendations include (a) deriving consensus regarding the DP definition and (b) expanding the literature to consider a person’s broader contextual and developmental circumstances in relation to their digital data/records.

show abstract

Diminished Anticipatory and Consummatory Pleasure in Dysphoria: Evidence From an Experience Sampling Study

Cited by 17 publications

References 66 publications

Exploring the digital footprint of depression: a PRISMA systematic literature review of the empirical evidence

Exploring the digital footprint of depression: a PRISMA systematic literature review of the empirical evidence

Psychopathology and positive emotions in daily life

Exploring the Digital Footprint of Depression: A PRISMA Systematic Literature Review of the Empirical Evidence.

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