scholarly journals Testing Self-Report Time-Use Diaries against Objective Instruments in Real Time

2019 ◽  
Vol 50 (1) ◽  
pp. 318-349 ◽  
Author(s):  
Jonathan Gershuny ◽  
Teresa Harms ◽  
Aiden Doherty ◽  
Emma Thomas ◽  
Karen Milton ◽  
...  
Keyword(s):  
Physical Activity ◽  
Time Use ◽  
Large Scale ◽  
Population Level ◽  
Self Report ◽  
Objective Criterion ◽  
Diary Studies ◽  
Aggregate Sample ◽  
Metabolic Equivalent Of Task ◽  
Activity Questionnaires

This study provides a new test of time-use diary methodology, comparing diaries with a pair of objective criterion measures: wearable cameras and accelerometers. A volunteer sample of respondents ( n = 148) completed conventional self-report paper time-use diaries using the standard UK Harmonised European Time Use Study (HETUS) instrument. On the diary day, respondents wore a camera that continuously recorded images of their activities during waking hours (approximately 1,500–2,000 images/day) and also an accelerometer that tracked their physical activity continuously throughout the 24-hour period covered by the diary. Of the initial 148 participants recruited, 131 returned usable diary and camera records, of whom 124 also provided a usable whole-day accelerometer record. The comparison of the diary data with the camera and accelerometer records strongly supports the use of diary methodology at both the aggregate (sample) and individual levels. It provides evidence that time-use data could be used to complement physical activity questionnaires for providing population-level estimates of physical activity. It also implies new opportunities for investigating techniques for calibrating metabolic equivalent of task (MET) attributions to daily activities using large-scale, population-representative time-use diary studies.

scholarly journals Screens, Teens, and Psychological Well-Being: Evidence From Three Time-Use-Diary Studies

2019 ◽  
Vol 30 (5) ◽  
pp. 682-696 ◽  
Author(s):  
Amy Orben ◽  
Andrew K. Przybylski
Keyword(s):  
Time Use ◽  
Large Scale ◽  
Well Being ◽  
The United States ◽  
Psychological Research ◽  
Research Area ◽  
Self Report ◽  
Clear Cut ◽  
Diary Studies ◽  
Psychological Evidence

The notion that digital-screen engagement decreases adolescent well-being has become a recurring feature in public, political, and scientific conversation. The current level of psychological evidence, however, is far removed from the certainty voiced by many commentators. There is little clear-cut evidence that screen time decreases adolescent well-being, and most psychological results are based on single-country, exploratory studies that rely on inaccurate but popular self-report measures of digital-screen engagement. In this study, which encompassed three nationally representative large-scale data sets from Ireland, the United States, and the United Kingdom ( N = 17,247 after data exclusions) and included time-use-diary measures of digital-screen engagement, we used both exploratory and confirmatory study designs to introduce methodological and analytical improvements to a growing psychological research area. We found little evidence for substantial negative associations between digital-screen engagement—measured throughout the day or particularly before bedtime—and adolescent well-being.

scholarly journals Public health surveillance of habitual physical activity in adolescents and adults in Namibia: a cross-sectional validation of activity questionnaires against accelerometry

2020 ◽  
Author(s):  
Hilde L Nashandi ◽  
John J Reilly ◽  
Xanne Janssen
Keyword(s):  
Physical Activity ◽  
Adolescent Girls ◽  
Rank Order ◽  
Vigorous Physical Activity ◽  
Population Level ◽  
Self Report ◽  
Adult Women ◽  
Cross Sectional ◽  
Individual Level ◽  
Activity Questionnaires

Abstract Background Monitoring population-level physical activity is crucial for examining adherence to global guidelines and addressing obesity. This study validated self-reported moderate-to-vigorous physical activity (MVPA) against an accurate device-based method in Namibia. Methods Adolescent girls (n = 52, mean age 16.2 years [SD 1.6]) and adult women (n = 51, mean age 31.3 years [SD 4.7]) completed the PACE+/GPAQ self-report questionnaires and were asked to wear an Actigraph accelerometer for 7 days. Validity of self-reported MVPA was assessed using rank-order correlations between self-report and accelerometry, and classification ability of the questionnaires with Mann–Whitney tests, kappa’s, sensitivity and specificity. Results In the adolescents, Spearman’s rank coefficients between self-reported MVPA (days/week) and accelerometry measured MVPA were positive but not significant (r = 0.240; P = 0.104). In the adults, self-reported MVPA (minutes/day) was moderately and significantly correlated with accelerometer-measured MVPA (r = 0.396; P = 0.008). In both groups, there was fair agreement between accelerometry and questionnaire-defined tertiles of MVPA (adolescents κ = 0.267; P = 0.010; adults κ = 0.284; P = 0.008), and measured MVPA was significantly higher in the individuals self-reporting higher MVPA than those reporting lower MVPA. Conclusions The PACE+ and GPAQ questionnaires have a degree of validity in adolescent girls and adult females in Namibia, though more suitable for population than individual level measurement.

scholarly journals Concurrent comparison of energy intake and expenditure among adults in Butajira District, Ethiopia

2008 ◽  
Vol 11 (7) ◽  
pp. 675-683 ◽  
Author(s):  
Fikru Tesfaye ◽  
Peter Byass ◽  
Stig Wall
Keyword(s):  
Physical Activity ◽  
Energy Intake ◽  
Population Level ◽  
Cross Sectional Study ◽  
Activity Level ◽  
Metabolic Energy ◽  
Sampling Frame ◽  
Cross Sectional ◽  
Dietary History ◽  
Activity Questionnaires

AbstractObjectiveTo estimate and compare dietary energy intake (DEI) and total energy expenditure (TEE) among adults, using questionnaires.DesignComparative, cross-sectional study.SettingCommunity-based, at the demographic surveillance site (DSS) in Butajira District of Ethiopia.SubjectsA total of 619 adults, 18–64 years of age, were randomly selected from among the urban and rural population of Butajira using the DSS sampling frame. Habitual dietary intake and physical activity were assessed using questionnaires. BMR was estimated using a regression equation, and TEE was calculated from BMR and the metabolic energy equivalent task (MET) and duration of reported activities. Physical activity level (PAL) was calculated as TEE/BMR, while food intake level (FIL) was calculated as DEI/BMR. The mean DEI:TEE ratio was used to evaluate reported DEI at the population level, while individual misreporters were identified by applying the Goldberg cut-off points at three levels of PAL.ResultsBased on the Goldberg method, 57 % of the study participants were identified as acceptable reporters of DEI, among whom mean TEE was 8·21 (95 % CI 8·01, 8·42) MJ (1963 (95 % CI 1914, 2012) kcal), mean DEI was 8·13 (95 % CI 7·93, 8·34) MJ (1944 (95 % CI 1895, 1993) kcal) and mean DEI:TEE was 1·01 (95 % CI 0·99, 1·04).ConclusionThe dietary history and physical activity questionnaires provide comparable estimates of mean energy intake and expenditure at a population level. Acceptable reporters have to be identified in order to obtain better estimates. Questionnaire-based estimates of energy intake should not be interpreted without an inherent system of comparison or validation.

scholarly journals The development and evaluation of a novel computer program to assess previous-day dietary and physical activity behaviours in school children: The Synchronised Nutrition and Activity ProgramTM (SNAPTM)

2008 ◽  
Vol 99 (6) ◽  
pp. 1266-1274 ◽  
Author(s):  
Helen J. Moore ◽  
Louisa J. Ells ◽  
Sally A. McLure ◽  
Sean Crooks ◽  
David Cumbor ◽  
...  
Keyword(s):  
Physical Activity ◽  
Energy Balance ◽  
Dietary Intake ◽  
Vigorous Physical Activity ◽  
Population Level ◽  
Mean Difference ◽  
Self Report ◽  
Substantial Contribution ◽  
Activity Levels ◽  
Food Groups

Self-report recall questionnaires used to measure physical activity and dietary intake in children can be labour intensive and monotonous and tend to focus on either dietary intake or physical activity. The web-based software, Synchronised Nutrition and Activity ProgramTM (SNAPTM), was developed to produce a novel, simple, quick and engaging method of assessing energy balance-related behaviours at a population level, combining principles from new and existing 24 h recall methodologies, set within a user-friendly interface. Dietary intake was measured using counts for twenty-one food groups and physical activity levels were measured in min of moderate to vigorous physical activity (MVPA). A combination of the mean difference between methods, type II regression and non-parametric limits of agreement techniques were used to examine the accuracy and precision of SNAPTM. Method comparison analyses demonstrated a good agreement for both dietary intake and physical activity behaviours. For dietary variables, accuracy of SNAPTM (mean difference) was within ± 1 count for the majority of food groups. The proportion of the sample with between-method agreement within ± 1 count ranged from 0·40 to 0·99. For min of MVPA, there was no substantial fixed or proportional bias, and a mean difference between methods (SNAPTM – accelerometry) of − 9 min. SNAPTM provides a quick, accurate, low-burden, cost-effective and engaging method of assessing energy balance behaviours at a population level. Tools such as SNAPTM, which exploit the popularity, privacy and engagement of the computer interface, and linkages with other datasets, could make a substantial contribution to future public health monitoring and research.

How Sedentary Are Older People? A Systematic Review of the Amount of Sedentary Behavior

2015 ◽  
Vol 23 (3) ◽  
pp. 471-487 ◽  
Author(s):  
Juliet A. Harvey ◽  
Sebastien F.M. Chastin ◽  
Dawn A. Skelton
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Sedentary Behavior ◽  
Successful Aging ◽  
Large Scale ◽  
Well Being ◽  
Self Report ◽  
Sitting Time ◽  
Scale Population ◽  
Data Source

Background/objectives:Sedentary behavior (SB), defined as sitting (nonexercising), reclining, and lying down (posture), or by low energy expenditure, is a public health risk independent to physical activity. The objective of this systematic literature review was to synthesize the available evidence on amount of SB reported by and measured in older adults.Data source:Studies published between 1981 and 2014 were identified from electronic databases and manual searching. Large-scale population studies/surveys reporting the amount of SB (objective/subjective) in older adults aged ≥ 60 years of age were included. Appraisal and synthesis was completed using MOOSE guidelines.Results:349,698 adults aged ≥ 60 within 22 studies (10 countries and 1 EU-wide) were included. Objective measurement of SB shows that older adults spend an average of 9.4 hr a day sedentary, equating to 65–80% of their waking day. Self-report of SB is lower, with average weighted self-reports being 5.3 hr daily. Within specific domains of SB, older adults report 3.3 hr in leisure sitting time and 3.3 hr watching TV. There is an association with more time spent in SB as age advances and a trend for older men to spend more time in SB than women.Conclusion/implications:Time spent sedentary ranges from 5.3–9.4 hr per waking day in older adults. With recent studies suggesting a link between SB, health, and well-being, independent of physical activity, this is an area important for successful aging.Limitations:Different methodologies of measurement and different reporting methods of SB made synthesis difficult. Estimated SB time from self-report is half of that measured objectively; suggesting that most self-report surveys of SB will vastly underestimate the actual time spent in SB.

scholarly journals Exploring the Association Between Electronic Wearable Device Use and Levels of Physical Activity Among Individuals With Depression and Anxiety: A Population Level Study

2021 ◽  
Vol 3 ◽  
Author(s):  
Henry Onyeaka ◽  
Joe Firth ◽  
Valentine Enemuo ◽  
Chioma Muoghalu ◽  
John Naslund ◽  
...  
Keyword(s):  
Physical Activity ◽  
United States ◽  
Large Scale ◽  
Population Level ◽  
The United States ◽  
Individual Characteristics ◽  
Activity Levels ◽  
Depression And Anxiety ◽  
Related Factors ◽  
Cross Sectional

Aim: The present study aimed to investigate the cross-sectional association between self-reported use of electronic wearable devices (EWDs) and the levels of physical activity among a representative sample of adults with depression and anxiety in the United States.Methods: For this cross-sectional study, data were pooled from the Health Information National Trends Survey 2019. A sample of 1,139 adults with self-reported depression and anxiety (60.9% women; mean age of 52.5 years) was analyzed. The levels of physical activity and prevalence of EWD utilization were self-reported. The chi-square tests were used to compare individual characteristics through the use of EWDs. Multivariable logistic regression was employed to investigate the association between EWDs and physical activity levels while adjusting for sociodemographic and health-related factors.Results: From the 1,139 adults with self-reported depression and anxiety, 261 (weighted percentage 28.1%) endorsed using EWD in the last year. After adjusting for covariates, the use of EWDs was only significantly associated with a higher odds of reporting intention to lose weight (OR 2.12; 95% CI 1.04, 4.35; p = 0.04). We found no association between the use of EWDs and meeting the national weekly recommendation for physical activity or resistance/strength exercise training.Conclusion: About three in 10 adults suffering from depression and anxiety in the United States reported using EWDs in the last year. The current study findings indicate that among people living with mental illness, EWD use is associated with higher odds of weight loss intent suggesting that EWDs may serve as an opening for the clinical interactions around physical health through identifying patients primed for behavior change. Further large-scale studies using randomized trial designs are needed to examine the causal relationships between EWDs and the physical activity of people with mental health conditions.

Dose–Response Association Between Physical Activity and Cognitive Function in a National Sample of Older Adults

2017 ◽  
Vol 32 (3) ◽  
pp. 554-560 ◽  
Author(s):  
Paul D. Loprinzi ◽  
Meghan K. Edwards ◽  
Elizabeth Crush ◽  
Toshikazu Ikuta ◽  
Alberto Del Arco
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Cognitive Function ◽  
Dose Response ◽  
Vigorous Physical Activity ◽  
National Sample ◽  
Self Report ◽  
Favorable Effect ◽  
Digit Symbol Substitution Test ◽  
Metabolic Equivalent Of Task

Purpose: Previous research demonstrates a favorable effect of physical activity on cognitive function among older adults. The potential dose–response relationship between physical activity and cognitive function in this population is less understood, which was the purpose of this study. Setting: Data from the 1999 to 2002 National Health and Nutrition Examination Survey were employed. Participants: A total of 2157 older adults aged 60 to 85 years. Measures: Cognitive function was assessed from the Digit Symbol Substitution Test. Moderate-to-vigorous physical activity (MVPA), expressed as metabolic equivalent of task (MET)-min-month (MET-min-month = days × duration × MET level), was assessed via self-report, with 5 MVPA categories evaluated: (1) <2000 MVPA MET-min-month, (2) 2000 to 3999 MVPA MET-min-month, (3) 4000 to 5999 MVPA MET-min-month, (4) 6000 to 7999 MVPA MET-min-month, and (5) 8000+ MVPA MET-min-month. Analysis: Weighted multivariable linear regression. Results: An inverted U-shaped relationship was observed. Consistent across several adjusted models, those who engaged in 6000 to 7999 MVPA MET-min-month had the highest cognitive function score. Conclusion: The results suggest an optimal amount of physical activity to prevent the cognitive decline associated with aging.

Surveillance of Physical Activity, Sedentary Behavior and Sleep (SurPASS): A study protocol of the development and feasibility evaluation of a novel measurement system (Preprint)

2021 ◽  
Author(s):  
Patrick Crowley ◽  
Sheikh Mohammed Shariful Islam ◽  
Rasmus Kildedal ◽  
Sandra Schade Jacobsen ◽  
Jon Roslyng Larsen ◽  
...  
Keyword(s):  
Physical Activity ◽  
Sedentary Behavior ◽  
Data Privacy ◽  
Large Scale ◽  
Phase 1 ◽  
Self Report ◽  
Surveillance Systems ◽  
Phase 2 ◽  
Evaluation Phase ◽  
Feasibility Evaluation

BACKGROUND There is increasing recognition of the need for more comprehensive surveillance data, including information on physical activity of all intensities, sedentary behavior, and sleep. However, meeting this need poses significant challenges for current surveillance systems, which are mainly reliant on self-report. OBJECTIVE The primary objective of the SurPASS (Surveillance of Physical Activity Sedentary behavior and Sleep) project is to develop and evaluate the feasibility of a sensor-based system for use in the surveillance of physical activity of all intensities, sedentary behavior, and sleep. METHODS The SurPASS project involves an international, multidisciplinary team of researchers collaborating with an industrial partner. The SurPASS system consists of 1) a thigh-worn accelerometer with Bluetooth connectivity, 2) a smartphone app, 3) an integrated back-end, facilitating the automated upload, analysis, storage, and provision of personalized feedback in a manner compliant with European Union regulations on data privacy, and 4) an administrator web-interface (web-app) to monitor progress. The system development and evaluation will be performed in three phases. These phases will include gathering user input and specifications (Phase 1), the iterative development, evaluation and refinement of the system (Phase 2), and the feasibility evaluation (Phase 3). RESULTS The project started in September 2020, is currently in Phase 2, and will be completed in 2023. CONCLUSIONS If feasible, the SurPASS system could be a catalyst towards large-scale sensor-based surveillance of physical activity, sedentary behavior and sleep. It could also be adapted for cohort and interventional research, thus contributing to the generation of evidence for both interventions and public health policies and recommendations.

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