Dataset Viewer
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string | target_doi
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PMC10001724
|
1. Introduction
|
A preliminary, multinational survey reporting step counts provided by smartphones showed that social distancing measures to contain the spread of SARS-CoV-2 have induced physical inactivity (i.e., not meeting the physical activity guidelines) [1].
|
10.7326/M20-2665
|
PMC7384265
|
PMC10001724
|
1. Introduction
|
The onset of the coronavirus disease 2019 (COVID-19) pandemic has placed further spotlight on participation in sedentary behavior (i.e., time spent in a sitting or reclining posture with a low energy expenditure [≤1.5 METs]), with reported increases in daily sitting time from pre-pandemic levels ranging from 30 min up to 3 h in different populations [2,3].
|
10.1016/j.pcad.2020.04.005
|
PMC7194897
|
PMC10001724
|
1. Introduction
|
The onset of the coronavirus disease 2019 (COVID-19) pandemic has placed further spotlight on participation in sedentary behavior (i.e., time spent in a sitting or reclining posture with a low energy expenditure [≤1.5 METs]), with reported increases in daily sitting time from pre-pandemic levels ranging from 30 min up to 3 h in different populations [2,3].
|
10.3390/nu12061583
|
PMC7352706
|
PMC10001724
|
1. Introduction
|
Extensive epidemiological evidence has indicated that physical inactivity is a major risk factor for early mortality and chronic diseases, including obesity, type 2 diabetes, cardiovascular diseases, metabolic syndrome, certain type of cancers, and others [4].
|
10.1016/S0140-6736(12)61031-9
|
PMC3645500
|
PMC10001724
|
1. Introduction
|
Even though time spent in moderate-to-vigorous intensity physical activity has the strongest detrimental associations with health outcomes [5,6,7], similar (albeit, detrimental) relationships have been broadly observed for excessive time in sedentary behaviors [7,8,9,10,11,12,13,14,15,16].
|
10.1136/bjsports-2020-102345
|
PMC8543228
|
PMC10001724
|
1. Introduction
|
Even though time spent in moderate-to-vigorous intensity physical activity has the strongest detrimental associations with health outcomes [5,6,7], similar (albeit, detrimental) relationships have been broadly observed for excessive time in sedentary behaviors [7,8,9,10,11,12,13,14,15,16].
|
10.1136/bjsports-2020-103270
|
PMC7719907
|
PMC10001724
|
1. Introduction
|
Even though time spent in moderate-to-vigorous intensity physical activity has the strongest detrimental associations with health outcomes [5,6,7], similar (albeit, detrimental) relationships have been broadly observed for excessive time in sedentary behaviors [7,8,9,10,11,12,13,14,15,16].
|
10.1136/bmj.l4570
|
PMC6699591
|
PMC10001724
|
1. Introduction
|
Even though time spent in moderate-to-vigorous intensity physical activity has the strongest detrimental associations with health outcomes [5,6,7], similar (albeit, detrimental) relationships have been broadly observed for excessive time in sedentary behaviors [7,8,9,10,11,12,13,14,15,16].
|
10.7326/M17-0212
|
PMC5961729
|
PMC10001724
|
1. Introduction
|
Even though time spent in moderate-to-vigorous intensity physical activity has the strongest detrimental associations with health outcomes [5,6,7], similar (albeit, detrimental) relationships have been broadly observed for excessive time in sedentary behaviors [7,8,9,10,11,12,13,14,15,16].
|
10.1007/s00125-015-3861-8
|
PMC4779127
|
PMC10001724
|
1. Introduction
|
Even though time spent in moderate-to-vigorous intensity physical activity has the strongest detrimental associations with health outcomes [5,6,7], similar (albeit, detrimental) relationships have been broadly observed for excessive time in sedentary behaviors [7,8,9,10,11,12,13,14,15,16].
|
10.1007/s10654-018-0380-1
|
PMC6133005
|
PMC10001724
|
1. Introduction
|
Even though time spent in moderate-to-vigorous intensity physical activity has the strongest detrimental associations with health outcomes [5,6,7], similar (albeit, detrimental) relationships have been broadly observed for excessive time in sedentary behaviors [7,8,9,10,11,12,13,14,15,16].
|
10.3945/ajcn.111.019620
|
PMC3260070
|
PMC10001724
|
1. Introduction
|
Importantly, both total sitting time and prolonged, uninterrupted sitting time are associated with increased risk of all-cause mortality even after consideration of the influence of participation in moderate-to-vigorous intensity physical activity [7,8,17].
|
10.1136/bmj.l4570
|
PMC6699591
|
PMC10001724
|
1. Introduction
|
Importantly, both total sitting time and prolonged, uninterrupted sitting time are associated with increased risk of all-cause mortality even after consideration of the influence of participation in moderate-to-vigorous intensity physical activity [7,8,17].
|
10.7326/M17-0212
|
PMC5961729
|
PMC10001724
|
1. Introduction
|
Importantly, both total sitting time and prolonged, uninterrupted sitting time are associated with increased risk of all-cause mortality even after consideration of the influence of participation in moderate-to-vigorous intensity physical activity [7,8,17].
|
10.1161/JAHA.121.023845
|
PMC9238579
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PMC10001724
|
1. Introduction
|
Moreover, the deleterious associations of sedentary behavior with cardiometabolic risk and all-cause mortality are most pronounced in those who are physically inactive [6,11,18,19,20].
|
10.1136/bjsports-2020-103270
|
PMC7719907
|
PMC10001724
|
1. Introduction
|
Moreover, the deleterious associations of sedentary behavior with cardiometabolic risk and all-cause mortality are most pronounced in those who are physically inactive [6,11,18,19,20].
|
10.1249/MSS.0000000000001935
|
PMC6527341
|
PMC10001724
|
1. Introduction
|
Patients with rheumatoid arthritis have a higher risk of morbidity and mortality from cardiovascular diseases [24].
|
10.1016/j.amjmed.2008.06.011
|
PMC2858687
|
PMC10001724
|
1. Introduction
|
Physical inactivity and sedentary behavior are modifiable risk factors considered to be potential targets to prevent morbimortality in autoimmune rheumatic diseases [28,29].
|
10.1038/s41584-020-0427-z
|
PMC7191971
|
PMC10001724
|
1. Introduction
|
Among patients with rheumatoid arthritis, sedentary behavior is associated with higher disease scores, increased pain, fatigue [30] and number of comorbidities, reduced aerobic capacity [31] and physical function [30], and poor self-efficacy [32].
|
10.1186/s13075-015-0584-7
|
PMC4384324
|
PMC10001724
|
1. Introduction
|
Among patients with rheumatoid arthritis, sedentary behavior is associated with higher disease scores, increased pain, fatigue [30] and number of comorbidities, reduced aerobic capacity [31] and physical function [30], and poor self-efficacy [32].
|
10.3109/03009742.2014.931456
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PMC4356639
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PMC10001724
|
1. Introduction
|
Patients with rheumatoid arthritis have been shown to be more susceptible to COVID-19 infection [33] and, therefore, may be subjected to more restrictive measures of social distancing, potentially with significant impacts on their activity options, and, hence, on their burden of cardiovascular disease risk, the main cause of mortality in this population [26].
|
10.1016/S2665-9913(20)30227-7
|
PMC7333992
|
PMC10001724
|
2. Materials and Methods
|
Fatigue was assessed by the Fatigue Severity Scale [40], in which scores range from 9 to 63; lower scores indicate lower fatigue.
|
10.1016/j.jclinepi.2007.08.016
|
PMC2486378
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PMC10001724
|
4. Discussion
|
As those confined at home are less prone to perform physical activity, it has been speculated that inactivity and sedentary behavior could peak during the COVID-19 pandemic [29].
|
10.1038/s41584-020-0427-z
|
PMC7191971
|
PMC10001724
|
4. Discussion
|
In fact, a rapid review has shown a substantial decrease in physical activity with a concomitant increase in sedentary behavior across all age groups during COVID-19 lockdown [42].
|
10.3390/ijerph18168567
|
PMC8393482
|
PMC10001724
|
4. Discussion
|
As for the Brazilian population, a national retrospective survey comprising 39,693 adults and older adults has shown a significant increase on self-reported physical inactivity and screen-based sedentary behaviors during the COVID-19 pandemic [43,44], which corroborates the objectively measured data presented herein.
|
10.1016/j.annepidem.2021.05.001
|
PMC8451973
|
PMC10001724
|
4. Discussion
|
Observational and experimental evidence demonstrates that inactivity can predispose to pathological states and poor outcomes [45].
|
10.1152/physrev.00019.2016
|
PMC6347102
|
PMC10001724
|
4. Discussion
|
Sedentary behavior can add to the adverse impacts of physical inactivity in impairing cardiovascular health [46].
|
10.1371/journal.pone.0180119
|
PMC5491133
|
PMC10001724
|
4. Discussion
|
Consequently, individuals who are both physically inactive and highly sedentary are at the highest risk for poor outcomes [6,20], which might be the case for patients with autoimmune rheumatic diseases, as they commonly spent most of their daily hours engaged in sedentary behavior and did not achieve minimum levels of moderate-to-vigorous physical activity [28].
|
10.1136/bjsports-2020-103270
|
PMC7719907
|
PMC10001724
|
4. Discussion
|
Namely in rheumatoid arthritis, the estimates of physical inactivity and sedentary behavior are comparable to those of other chronic diseases (e.g., type 2 diabetes and cardiovascular diseases), groups in which both physical inactivity and sedentary behaviors are associated with poor disease prognosis and mortality [9,10,11,13,47], as well as poor health-related outcomes (i.e., higher disease activity score, disease symptoms and number of comorbidities, and lower physical capacity and functioning) [28].
|
10.1007/s00125-015-3861-8
|
PMC4779127
|
PMC10001724
|
4. Discussion
|
Namely in rheumatoid arthritis, the estimates of physical inactivity and sedentary behavior are comparable to those of other chronic diseases (e.g., type 2 diabetes and cardiovascular diseases), groups in which both physical inactivity and sedentary behaviors are associated with poor disease prognosis and mortality [9,10,11,13,47], as well as poor health-related outcomes (i.e., higher disease activity score, disease symptoms and number of comorbidities, and lower physical capacity and functioning) [28].
|
10.1007/s12471-011-0237-7
|
PMC3346869
|
PMC10001724
|
4. Discussion
|
Prolonged, uninterrupted bouts of sedentary behavior are associated with all-cause mortality [8], whereas well-controlled studies show that very-light to light-intensity active interruptions in prolonged sedentary time (e.g., 2 min of walking for every 30 min of sitting) can elicit immediate improvements in cardiometabolic risk factors [50].
|
10.7326/M17-0212
|
PMC5961729
|
PMC10001724
|
4. Discussion
|
Recent evidence has shown that light-intensity physical activity is associated with lower disability, disease activity and cardiovascular risk in rheumatoid arthritis, in contrast to excessive sitting [28,51].
|
10.1186/s12891-017-1473-9
|
PMC5404687
|
PMC10001724
|
4. Discussion
|
This raises the need for widespread recommendation of breaking-up prolonged sitting whenever possible (e.g., 3 min breaks of light-intensity walking every 30 min of sitting) to avoid poor health outcomes during the pandemic, which tend to be more restrictive for high-risk groups for COVID-19, such as those with autoimmune rheumatic diseases [33], a condition associated with lower vaccine responses, which may enforce more vulnerable patients to maintain some degree of physical distance and home isolation for as long as the pandemic endures.
|
10.1016/S2665-9913(20)30227-7
|
PMC7333992
|
PMC10001724
|
4. Discussion
|
Conversely, they noted social distancing resulted in worsened mental health-related symptoms [53].
|
10.1136/bmjopen-2021-056555
|
PMC9330330
|
PMC10004034
|
1. Introduction
|
Spinal muscular atrophy (SMA) is an autosomal recessive neuromuscular disorder caused by mutations in the survival motor neuron 1 (SMN1) gene located on chromosome 5q leading to SMN protein deficiency [1,2,3,4].
|
10.1007/s00415-017-8549-1
|
PMC5502065
|
PMC10004034
|
1. Introduction
|
Spinal muscular atrophy (SMA) is an autosomal recessive neuromuscular disorder caused by mutations in the survival motor neuron 1 (SMN1) gene located on chromosome 5q leading to SMN protein deficiency [1,2,3,4].
|
10.1001/archneurol.2010.373
|
PMC3839315
|
PMC10004034
|
1. Introduction
|
It induces proximal muscle atrophy and weakness, leading to secondary complications including scoliosis, joint contractures, and progressive respiratory decline [4,5].
|
10.1001/archneurol.2010.373
|
PMC3839315
|
PMC10004034
|
1. Introduction
|
It induces proximal muscle atrophy and weakness, leading to secondary complications including scoliosis, joint contractures, and progressive respiratory decline [4,5].
|
10.1016/j.ncl.2015.07.004
|
PMC4628728
|
PMC10004034
|
1. Introduction
|
Type 1 children do not achieve the ability to sit independently, type 2 children can sit but cannot walk independently, and type 3 children achieve independent walking, but lose motor function over time and many become wheelchair dependant [4,5].
|
10.1001/archneurol.2010.373
|
PMC3839315
|
PMC10004034
|
1. Introduction
|
Type 1 children do not achieve the ability to sit independently, type 2 children can sit but cannot walk independently, and type 3 children achieve independent walking, but lose motor function over time and many become wheelchair dependant [4,5].
|
10.1016/j.ncl.2015.07.004
|
PMC4628728
|
PMC10004034
|
1. Introduction
|
Both nusinersen [6,7,8] and risdiplam [9,10] have been studied in symptomatic type 1 and pre-symptomatic cohorts, as well as in type 2 and 3 SMA, and significant benefits have been demonstrated, with transformative changes especially when administered close to disease onset or pre-symptomatically [3,6,7,8,10,11].
|
10.1212/WNL.0000000000007527
|
PMC6541434
|
PMC10004034
|
1. Introduction
|
Both nusinersen [6,7,8] and risdiplam [9,10] have been studied in symptomatic type 1 and pre-symptomatic cohorts, as well as in type 2 and 3 SMA, and significant benefits have been demonstrated, with transformative changes especially when administered close to disease onset or pre-symptomatically [3,6,7,8,10,11].
|
10.1007/s40263-019-00656-w
|
PMC6776494
|
PMC10004034
|
1. Introduction
|
The Revised Hammersmith Scale (RHS) was developed to address discontinuity in the HFMSE [13], and several items were adapted and added from the North Star Ambulatory Assessment (NSAA) [14] and the Children’s Hospital of Philadelphia Infant Test of Neuromuscular Disorders (CHOP-INTEND) [15] to increase the sensitivity of the scale in the strongest and weakest patients, respectively.
|
10.1371/journal.pone.0172346
|
PMC5319655
|
PMC10004034
|
2. Materials and Methods
|
Change scores were stratified by type and age as follows: < 5, 5–7, 8–13, and 14–18 years, in order to align with previous research on the HFMSE which used similar age groups [22,23].
|
10.1016/j.nmd.2015.10.006
|
PMC4762230
|
PMC10004034
|
2. Materials and Methods
|
Change scores were stratified by type and age as follows: < 5, 5–7, 8–13, and 14–18 years, in order to align with previous research on the HFMSE which used similar age groups [22,23].
|
10.1002/acn3.51514
|
PMC8935309
|
PMC10004034
|
4. Discussion
|
Indeed, we found that the RHS is highly correlated with the RULM, similarly to the HFMSE [24].
|
10.1002/mus.27384
|
PMC9291175
|
PMC10004034
|
4. Discussion
|
The groups here are nevertheless similar to groups used in papers analysing the HFMSE and reflect the peak in motor function observed at 5 years in the SMA 2s, and at 7 years in the SMA 3s [24].
|
10.1002/mus.27384
|
PMC9291175
|
PMC10004034
|
4. Discussion
|
In order to allow analysis of the change scores by motor function category and baseline RHS, the groups that have previously been used (i.e., <5, 5–13, >13 for SMA 2s age [20,23,26,27]; and <5, 5–7, 8–14, >14 for SMA 3s [23,28]) were merged to create the following groups: <5, 5–7, 7–13, 14–18.
|
10.1002/acn3.51514
|
PMC8935309
|
PMC10004034
|
4. Discussion
|
In order to allow analysis of the change scores by motor function category and baseline RHS, the groups that have previously been used (i.e., <5, 5–13, >13 for SMA 2s age [20,23,26,27]; and <5, 5–7, 8–14, >14 for SMA 3s [23,28]) were merged to create the following groups: <5, 5–7, 7–13, 14–18.
|
10.1002/acn3.51411
|
PMC8351459
|
PMC10004034
|
4. Discussion
|
In this analysis, only children were included, but it will be important to separately analyse the natural history of the RHS in adult SMA in the future [23].
|
10.1002/acn3.51514
|
PMC8935309
|
PMC10004519
|
Introduction
|
Intraoperative organ hypoperfusion is a cause of poor outcomes and may lead to high postoperative mortality [2].
|
10.1016/j.bja.2019.03.027
|
PMC6676242
|
PMC10004519
|
Introduction
|
The International Standards for a Safe Practice of Anesthesia recommend monitoring end-tidal carbon dioxide (EtCO2) using a capnograph during general anesthesia [3].
|
10.1007/s12630-010-9381-6
|
PMC2957572
|
PMC10004519
|
Introduction
|
In fact, several studies have shown that EtCO2 is useful in predicting the effectiveness of resuscitation [6] and outcomes in patients with cardiopulmonary arrest (CPA) [7, 8] and in predicting cardiac output when the patient is weaned from cardiopulmonary bypass (CPB) [9, 10].
|
10.1016/j.heliyon.2019.e01871
|
PMC6581839
|
PMC10004519
|
Introduction
|
Similarly, EtCO2 in noncardiac surgery was associated with increased postoperative mortality [11] and prolonged postoperative length of hospital stay [11–13].
|
10.1007/s00268-021-05984-x
|
PMC7885757
|
PMC10004519
|
Methods
|
Dose effects were assessed using the mean EtCO2; patients were divided into two groups based on the cutoff level of 35 mmHg, widely used lower limit of normal PaCO2 [16, 17].
|
10.1016/j.bjane.2020.11.010
|
PMC9373272
|
PMC10004519
|
Methods
|
Dose effects were assessed using the mean EtCO2; patients were divided into two groups based on the cutoff level of 35 mmHg, widely used lower limit of normal PaCO2 [16, 17].
|
10.1155/2011/271539
|
PMC3202118
|
PMC10004519
|
Methods
|
Referring to a previous study [18], the primary outcome was a composite of at least one organ dysfunction among AKI (postoperative serum creatinine [SCr] levels increased more than 0.3 mg.dl-1 or 1.5 times more than preoperative SCr levels, defined by the Kidney Disease: Improving Global Outcome Acute Kidney Injury Work Group) [19], circulatory dysfunction (use of norepinephrine, epinephrine, and vasopressin and the administration of dopamine ≥5 μg.kg-1.min-1 and phenylephrine ≥50 μg.min-1), respiratory dysfunction (the need for invasive ventilation by endotracheal intubation or tracheostomy beyond 24 h postoperatively; does not include continuous positive airway pressure or noninvasive ventilation or scheduled reintubation, such as extubation within 24 h after reoperation), coagulation dysfunction (platelet count of < 100 × 103 cells.μl-1, i.e., a Sequential Organ Failure Assessment [SOFA] score of ≥2 points in the coagulation component) [20], and liver dysfunction (total bilirubin of ≥ 2.0 mg.dl-1, i.e., a SOFA score of ≥2 points in the liver component) 7 days after surgery [20].
|
10.1001/jama.2017.14172
|
PMC5710560
|
PMC10004519
|
Methods
|
In model 4, the covariates included in the postoperative respiratory failure risk index (RFRI) were adjusted for age, emergency surgery, albumin level of less than 30 g.l-1, blood urea nitrogen level of more than or equal to 30 mg.dl-1, and chronic obstructive pulmonary disease (COPD) [24], except for partially or fully dependent status because of missing data.
|
10.1097/00000658-200008000-00015
|
PMC1421137
|
PMC10004519
|
Methods
|
To determine the statistical power, we predicted 4,500 eligible surgeries in our database in the 9 years, a risk ratio of 1.5 with postoperative organ dysfunction of 30% [18] and low EtCO2 proportion of 50% [25], resulting in an estimated power of 100%.
|
10.1001/jama.2017.14172
|
PMC5710560
|
PMC10004519
|
Methods
|
To determine the statistical power, we predicted 4,500 eligible surgeries in our database in the 9 years, a risk ratio of 1.5 with postoperative organ dysfunction of 30% [18] and low EtCO2 proportion of 50% [25], resulting in an estimated power of 100%.
|
10.1007/s12630-018-1249-1
|
PMC6331507
|
PMC10004519
|
Discussion
|
Studies on EtCO2 have focused primarily on patients with CPA and assessed the usefulness of EtCO2 as a valuable tool that can assess the effectiveness of cardiopulmonary resuscitation (CPR) [6–9] and predict the outcome.
|
10.1016/j.heliyon.2019.e01871
|
PMC6581839
|
PMC10004519
|
Discussion
|
Some studies have reported that EtCO2 is associated with increased postoperative mortality [11] and prolonged postoperative length of hospital stay [12, 13], but the cause of death has not been evaluated, and the mechanism is unknown.
|
10.1007/s00268-021-05984-x
|
PMC7885757
|
PMC10004542
|
Introduction
|
Some are inventories, such as the Patient Health Questionnaire-9 (PHQ-9) [1], the Remission Evaluation and Mood Inventory Tool (REMIT) [2], and the Ecological Momentary Assessment (EMA) [3], while others are symptom scales, including the Hamilton Rating Scale for Depression (HAM-D) [4], the Montgomery-Asburg Depression Rating Scale (MADRS) [5], and the Young Mania Rating Scale (YMRS) [6].
|
10.1136/jnnp.23.1.56
|
PMC495331
|
PMC10004542
|
Introduction
|
Some measures have targeted physiological markers of the stress response and emotional distress such as changes in facial skin temperature or color [11–13].
|
10.1073/pnas.1716084115
|
PMC5889636
|
PMC10004542
|
Introduction
|
Other studies have used facial EMG to detect purposeful changes in facial expression [25], as well as involuntary movements in response to affective touch [26].
|
10.1186/1475-925X-12-73
|
PMC3724582
|
PMC10004567
|
Introduction
|
Lung cancer has progressed to be one of the most frequent and deadly variations of cancer worldwide, even in low-middle-income countries (LMICs) [1].
|
10.21037/tlcr.2018.05.06
|
PMC6037963
|
PMC10004567
|
Introduction
|
Health outcomes are worse in Latin American countries than in other regions because of their fragmented and underbudgeted health systems [5].
|
10.1200/JGO.17.00040
|
PMC6223408
|
PMC10004567
|
Introduction
|
However, health systems in LMICs are precarious, and most people with this condition are diagnosed in late stages if their cancer occurs, thus causing higher mortality rates [6].
|
10.1186/s12992-020-00553-8
|
PMC7081618
|
PMC10004567
|
Introduction
|
It has also been described that lung cancer risk increases over time, especially in elderly people over 65-years-old [9, 10].
|
10.21037/jtd.2016.05.20
|
PMC5124601
|
PMC10004567
|
Introduction
|
It has also been described that lung cancer risk increases over time, especially in elderly people over 65-years-old [9, 10].
|
10.1038/s41598-020-58345-4
|
PMC6985117
|
PMC10004567
|
Introduction
|
All of these combined factors can cause an increase in prevalence rates in some regions of the country due to the high prevalence of smokers or mining activities [11, 12].
|
10.5334/aogh.2419
|
PMC6724220
|
PMC10004567
|
Discussion
|
Using prevalence estimates is a useful strategy to design public policy and calculate attributable cost [21].
|
10.1158/1055-9965.EPI-19-1534
|
PMC9514601
|
PMC10004567
|
Discussion
|
Furthermore, prevalence rates reported by Cuenta de Alto Costo were based on data provided by insurers using clinical reports as data source; although it included information from 98% of the total population affiliated with the health system, these reported data could have underestimated the real prevalence, as it depended on passive reporting [24, 25].
|
10.1200/JGO.17.00008
|
PMC6180751
|
PMC10004567
|
Discussion
|
Furthermore, prevalence rates reported by Cuenta de Alto Costo were based on data provided by insurers using clinical reports as data source; although it included information from 98% of the total population affiliated with the health system, these reported data could have underestimated the real prevalence, as it depended on passive reporting [24, 25].
|
10.1186/s12885-020-07611-9
|
PMC7661250
|
PMC10004567
|
Discussion
|
As LMIC countries enact changes to the population aging pattern, there is also a change in the burden of disease patterns from communicable to noncommunicable diseases (such as lung cancer), and efficient estimations are required to follow up on trends in public health [28, 30–32].
|
10.1186/s12913-020-05435-8
|
PMC7310020
|
PMC10004567
|
Discussion
|
It has been observed that developed countries have increased prevalence rates in comparison to developing countries [35].
|
10.1136/bmjgh-2020-002788
|
PMC7542628
|
PMC10004567
|
Discussion
|
This situation can be explained by differences in smoking rates or other exposure factors, such as chemical exposure, mining activities or higher exposure to air pollution that usually affects lower income population groups or states within the country [36–39].
|
10.1289/ehp.1104660
|
PMC3404667
|
PMC10007007
|
Introduction
|
Artificial intelligence (AI)–driven chatbots (AI chatbots) are conversational agents that mimic human interaction through written, oral, and visual forms of communication with a user [1,2].
|
10.1093/jamia/ocy072
|
PMC6118869
|
PMC10007007
|
Introduction
|
Artificial intelligence (AI)–driven chatbots (AI chatbots) are conversational agents that mimic human interaction through written, oral, and visual forms of communication with a user [1,2].
|
10.1186/s12966-021-01224-6
|
PMC8665320
|
PMC10007007
|
Introduction
|
The overall conversational flexibility offered by AI chatbots in terms of communicating at anytime from anywhere offers a safe space to facilitate interactions with patients who feel or experience stigmatization while seeking health care services [5].
|
10.2196/jmir.7737
|
PMC5958282
|
PMC10007007
|
Introduction
|
First, AI chatbots can collect data sets from diverse sources: electronic health records, unstructured clinical notes, real-time physiological data points using additional sensors (eye-movement tracking, facial recognition, movement tracking, and heartbeat), and user interactions [5,6].
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10.2196/jmir.7737
|
PMC5958282
|
PMC10007007
|
Introduction
|
Second, the AI algorithm uses machine learning (ML) and natural language processing (NLP) techniques to identify clinically meaningful patterns and understand user needs [7].
|
10.2196/20346
|
PMC7644372
|
PMC10007007
|
Introduction
|
AI chatbots can also be integrated into embodied functions (eg, virtual reality) that offer additional benefits, such as an immersive experience, which can catalyze the process of health behavior change [8].
|
10.2196/14166
|
PMC6914342
|
PMC10007007
|
Introduction
|
Of the extant systematic reviews on AI chatbots, 6 articles targeted at assessing efficacy of AI-chatbots in enhancing mental health outcomes [1,7,9-12], 2 examined the feasibility of AI-chatbots in health care settings [8,13], and 1 described the technical architectures and characteristics of the AI chatbots used in chronic conditions [14].
|
10.1093/jamia/ocy072
|
PMC6118869
|
PMC10007007
|
Introduction
|
Of the extant systematic reviews on AI chatbots, 6 articles targeted at assessing efficacy of AI-chatbots in enhancing mental health outcomes [1,7,9-12], 2 examined the feasibility of AI-chatbots in health care settings [8,13], and 1 described the technical architectures and characteristics of the AI chatbots used in chronic conditions [14].
|
10.2196/20346
|
PMC7644372
|
PMC10007007
|
Introduction
|
Of the extant systematic reviews on AI chatbots, 6 articles targeted at assessing efficacy of AI-chatbots in enhancing mental health outcomes [1,7,9-12], 2 examined the feasibility of AI-chatbots in health care settings [8,13], and 1 described the technical architectures and characteristics of the AI chatbots used in chronic conditions [14].
|
10.2196/16021
|
PMC7385637
|
PMC10007007
|
Introduction
|
Of the extant systematic reviews on AI chatbots, 6 articles targeted at assessing efficacy of AI-chatbots in enhancing mental health outcomes [1,7,9-12], 2 examined the feasibility of AI-chatbots in health care settings [8,13], and 1 described the technical architectures and characteristics of the AI chatbots used in chronic conditions [14].
|
10.2196/jmir.6553
|
PMC5442350
|
PMC10007007
|
Introduction
|
Of the extant systematic reviews on AI chatbots, 6 articles targeted at assessing efficacy of AI-chatbots in enhancing mental health outcomes [1,7,9-12], 2 examined the feasibility of AI-chatbots in health care settings [8,13], and 1 described the technical architectures and characteristics of the AI chatbots used in chronic conditions [14].
|
10.2196/14166
|
PMC6914342
|
PMC10007007
|
Introduction
|
Of the extant systematic reviews on AI chatbots, 6 articles targeted at assessing efficacy of AI-chatbots in enhancing mental health outcomes [1,7,9-12], 2 examined the feasibility of AI-chatbots in health care settings [8,13], and 1 described the technical architectures and characteristics of the AI chatbots used in chronic conditions [14].
|
10.2196/jmir.7351
|
PMC5709656
|
PMC10007007
|
Introduction
|
Of the extant systematic reviews on AI chatbots, 6 articles targeted at assessing efficacy of AI-chatbots in enhancing mental health outcomes [1,7,9-12], 2 examined the feasibility of AI-chatbots in health care settings [8,13], and 1 described the technical architectures and characteristics of the AI chatbots used in chronic conditions [14].
|
10.2196/20701
|
PMC7522733
|
PMC10007007
|
Introduction
|
Oh et al [2] conducted a systematic review that assessed the efficacy of AI chatbots for lifestyle modification (eg, physical activity, diet, and weight management).
|
10.1186/s12966-021-01224-6
|
PMC8665320
|
PMC10007007
|
Methods
|
The study protocol of this systematic literature review followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines [15] in each step.
|
10.1186/2046-4053-4-1
|
PMC4320440
|
PMC10007007
|
Methods
|
Feasibility was defined as the demand of the intervention, that is, the actual use of the intervention and whether the intervention is doable in a certain setting [16].
|
10.1016/j.amepre.2009.02.002
|
PMC2859314
|
PMC10007007
|
Methods
|
Acceptability was defined as the quality of user experience with the AI chatbot [17], for example, the satisfaction score or number of likes to the interaction with the AI chatbot.
|
10.1037/amp0000983
|
PMC9481750
|
PMC10007007
|
Methods
|
Usability was defined as the level of contribution by the intervention to achieve the prespecified goals by users [18], such as the usability of the content provided by the AI chatbot in achieving health behavior goals.
|
10.1177/2633489520987828
|
PMC9122125
|
PMC10007007
|
Methods
|
AI techniques specific to AI chatbot interventions were also appraised using the CONSORT-AI (Consolidated Standards of Reporting Trials–Artificial Intelligence) extension guidance for AI studies [20].
|
10.1136/bmj.m3164
|
PMC7490784
|
PMC10007007
|
Results
|
The results of the quality assessment are presented in Multimedia Appendix 2 [5,6,21-33].
|
10.2196/jmir.7737
|
PMC5958282
|
PMC10007007
|
Results
|
The results of the quality assessment are presented in Multimedia Appendix 2 [5,6,21-33].
|
10.2196/15085
|
PMC7267999
|
PMC10007007
|
Results
|
The results of the quality assessment are presented in Multimedia Appendix 2 [5,6,21-33].
|
10.1016/j.pec.2013.05.011
|
PMC3727973
|
PMC10007007
|
Results
|
Among the 4 RCT studies, the study by Carrasco-Hernandez et al [23] reported the highest compliance relatively (8/12, 67%), followed closely by the study by Piao et al [21] (7/12, 58%).
|
10.2196/17530
|
PMC7215523
|
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