Annoyance

About: Annoyance is a research topic. Over the lifetime, 2015 publications have been published within this topic receiving 38300 citations. The topic is also known as: annoy.

Association between Noise Annoyance and Mental Health Outcomes: A Systematic Review and Meta-Analysis

Abstract: To date, most studies of noise and mental health have focused on noise exposure rather than noise annoyance. The purpose of this systematic review and meta-analysis was to evaluate whether the available evidence supports an adverse association between noise annoyance and mental health problems in people. We carried out a literature search of Web of Science, PubMed, Scopus, PsycINFO, and conference proceedings published between 2000 and 2022. Thirteen papers met the inclusion criteria. We conducted meta-analyses of noise annoyance in relation to depression, anxiety, and general mental health. In the meta-analyses, we found that depression was approximately 1.23 times greater in those who were highly noise-annoyed (N = 8 studies). We found an approximately 55% higher risk of anxiety (N = 6) in highly noise-annoyed people. For general mental health (N = 5), highly annoyed participants had an almost 119% increased risk of mental health problems as assessed by Short Form (SF) or General Household Questionnaires (GHQ), but with high heterogeneity and risk of publication bias. In conclusion, findings are suggestive of a potential link between noise annoyance and poorer mental health based on a small number of studies. More evidence is needed to confirm these findings.

Fuzzy modeling of traffic noise annoyance

Abstract: This paper presents a fuzzy rule-based model for the prediction of traffic noise annoyance. Several inference schemes are compared for their performance in prediction capabilities as well as in speed. It is shown that the fastest implementation does an equally good job, after optimization of certainty degrees attached to the rules. For this optimization, a genetic algorithm is applied.

H.264 coding artifacts and their relation to perceived annoyance

Abstract: In this study we investigate coding artifacts in H.264 baseline profile. A psychophysical experiment was conducted that collected data about the subjectively perceived annoyance of short video sequences as well as the perceived strength of three coding artifacts. The data provided by 52 subjects is analyzed with respect to bitrate and intra period of the encoded sequences. A new data analysis method is presented which is based on a granular data representation and enables the detection of multidimensional functional dependencies in data sets. This method is employed to establish a model for the perceived annoyance as a function of artifact strength.

Low Frequency Noise from Transportation Sources

Abstract: Low frequency noise (LFN) is common as background noise in urban environments and as an emission from many artificial sources: road vehicles, aircraft, industrial machinery, artillery and mining explosions, and air movement machinery including wind turbines, compressors, and indoor ventilation and air conditioning units (Tempest, 1976; Leventhall, 1988 from St Pierre and Maguire [1]). LFN may also produce vibrations and rattles as secondary effects. The effects of LFN are of particular concern because of its pervasiveness due to numerous sources, efficient propagation and reduced efficacy of many structures (dwellings, walls, and hearing protection) in attenuating LFN compared with other noise. Current transportation noise impact assessments are usually based on broadband A-weighted noise indicators. Over the past 50 years, the A-weighted sound pressure level (dB(A)) has become the major measurement descriptor used in noise assessment. This is despite the fact that many studies have shown that the use of the A-weighting curve underestimates the role that LFN plays in loudness perception, annoyance, and speech intelligibility. The de-emphasizing of LFN content by A-weighting can also lead to an underestimation of the exposure risk of some physical and psychological effects that have been associated with low frequency noise. As a result of this reliance on dB(A) measurements, there is a lack of importance placed on minimizing LFN impacts. A more complete picture and better correlation with annoyance and health effects may result from indicators that include temporal aspects and frequency character. This paper presents an overview of some examples of low frequency indicators applied to transportation sources.

The annoyance and unacceptability of lower level low frequency noise

Abstract: In a continuing study of the annoyance due to low frequency noise, 75 subjects (21 actual complainants and 54 controls) carried out a magnitude estimation task and rated the annoyance due to lower-...