KEY WORDS: Health, affective states, exercise, emotion, and fitness.

Participants
Thirty-four regular male golfers from an ageing population (Age: M = 68.68, SD = 5.41 years) completed a mood measure immediately before and after an 18-hole round of golf. All participants were regular golfers (> 1 day per week) and members of the seniors section of a private golf club. An acknowledged limitation of the present samples was that participation motives to playing golf were not explored.

Measures Mood
Mood was measured using a 32-item scale that used subscales from two previously validated scales (Matthews et al., 1990; Terry et al., 1999; 2003). The Brunel Mood Scale (Terry et al., 1999; 2003) is based on the Profile of Mood States (McNair et al., 1971) and assesses the mood states of anger, confusion, depression, fatigue, tension, and vigour. The subscales of happiness and calmness were taken from the UWIST (Matthews et al., 1990). Recent research has questioned the use of the POMS model of mood in an exercise setting (Ekkekakis and Petruzzello, 2002). Ekkekakis and Petruzzello, (2002) suggested the use of the circumplex model as a conceptual and measurement model for studying affect in the context of exercise. A limitation of the POMS model of mood is that it does not address the full range of positive mood states with recent research suggesting that positive mood dimensions, such as happiness and calmness, may also influence sports performance (Hanin, 2000). It is suggested that the eight mood dimensions assessed provide a more balanced assessment of positive mood and negative mood.

Anger items include "Bad-tempered" and "Angry", Confusion items include "Mixed-up" and "Uncertain", Depression items include "Depressed" and "Downhearted", Fatigue items include "Worn out" and "Tired", Tension items include "Anxious" and "Panicky", and Vigor items include "Alert" and "Energetic". Calmness items include "Calm" and "Relaxed" and Happiness items include "Cheerful" and "Happy". Items are rated on a 5-point scale anchored by "not at all" (0) to "extremely" (4).

Terry et al. (1999; 2003) provided comprehensive evidence of factorial, concurrent and predictive validity of the BRUMS. Matthews et al. (1990) provided evidence of factorial validity. Internal consistency coefficients for subscales were:

Anger, alpha = .88; Calmness, alpha = .84; Confusion, alpha, = .72; Depression, alpha, = .74; Fatigue, alpha, = .88; Happiness, alpha, = .89; Tension, alpha, = .74; and Vigour, alpha, = .87.Distance walked

Distance walked per game was measured using a pedometer.

Procedure
Data were collected during the day of the 'monthly medal', an in-house and light-hearted social competition between golf club members. Participants competed against their friends and other players in the club. All participants were seated in the lounge area of the golf club and issued with the BRUMS during the 5-minute period immediately prior to starting play. Each participant then played 18 holes of golf at their regular pace with their normal playing partners. The weather was clear and pleasant with no precipitation. Following the round of golf, participants were allowed 5 minutes to put away their golf clubs and change footwear before returning to the lounge where a second BRUMS questionnaire was administered.

Repeated measures multivariate analysis of variance compared mood scores over time and indicated a multivariate effect (Wilks lambda _8,26 = 0.59, P < 0.05, Eta² = 0.41, see Table 1). Univariate results indicated that post-game mood scores were higher for Anger (F_1,33 = 12.17, p < 0.01, Eta² = 0.27), Depression (F_1,33 = 6.54, p < 0.05, Eta² = 0.17) and Fatigue (F_1,33 = 8.57, p < 0.001, Eta² = 0.21), with lower scores on Vigor (F_1,33 = 9.10, p < 0.01, Eta² = 0.22). Pedometer results indicated golfers walked a mean distance of 10.21 km (± 1.11). Results showed that participants of this age-group engaged in a meaningful exercise session and that mood scores deteriorated following play. Although results showed mood deteriorated, after-game variability as indicated by the standard deviation of mood scores was larger than pre-game mood (p < 0.05).

The aim of the present study was to explore mood state responses to playing a round of golf. Results of the present study indicate that playing golf is associated with increased unpleasant mood states, a mood profile more associated losing or poor performance (see Biddle and Hill, 1991; Lane et al., 2002; Lowther and Lane, 2002) than exercise. These results show that elderly golfers experienced mood profiles following golf similar to younger athletes following competition. Although the walking element of golf resulted in players engaging in a meaningful exercise session for their age, the psychological response seems to suggest that positive feelings that should accompany exercise are not so consistent.

Although results show an increase in unpleasant mood states following playing golf, it should be noted that participants reported much larger scores for pleasant mood states than unpleasant mood states. Therefore, it could be argued that although there was an increase in unpleasant mood states, this should be seen in the context of the overall mood profile, which was positive. Research has emphasised the importance of exploring the interplay between mood states (Lane and Terry, 2000). In the present study, increased anger showed the largest effect size, and previous research has shown anger can be facilitative of performance under certain conditions (see Beedie et al., 2000; Lane and Terry, 2000). It is suggested that increased arousal associated with anger might be helpful for performance if it enables players to increase concentration. Research has found that individuals are aware of mood states associated with performance (Hanin, 2000) and make attempts to regulate mood to optimal states. Thus, among some individuals, anger might be perceived as helpful, and when a player feels increases in anger, attempts to reduce anger are not attempted. Lane and Terry (2000) indicated that anger experienced with depression is qualitatively different to anger experienced with positive mood states such as vigor.In the present study, results suggest individuals reported feelings of anger, calmness and happiness simultaneously. It is suggested that some individuals use feelings associated with anger as a strategy to aid performance.

Findings of the present study lend support to previous research that has investigated psychological state responses to playing golf (Cohn, 1990; Beauchamp et al., 1996; Thomas and Fogarty, 1997; Kirschenbaum et al., 1998; Giacobbi et al., 2004). Consistent with suggestions of Giacobbi et al. (2004, intervention strategies designed to teach golfers emotional control techniques should be considered. Following Giacobbi et al. (2004) suggestions, the Rational Emotive Behavioral Therapy program that teaches individuals how to document negative, self-demeaning dialogs, emotional reactions, and the circumstances that give rise to these reactions should be considered. Encouraging golfers simulate stressful situations on the golf course (e.g., hitting a difficult shot, performing in front of others, or playing with good golfers) could assist in developing of strategies for regulating negative mood states. Therefore, golfers of all skill levels should be encouraged to regularly practice behavioral simulations in the presence of other people with the driving range offering a possible place for such practice to occur.

We suggest that future research investigates mood changes following performance on an intra-individual basis. Individuals who consistently experience unpleasant mood states following performance are likely to develop negative expectations toward playing, which in turn can become de-motivational. For golf to be recommended as an activity for promoting physical activity among an aging population, players should be taught strategies to regulate unpleasant mood states. A strategy for regulating negative mood among elderly players should be to encourage social interaction. The benefits of social support gained from interacting with peers whilst playing golf should be considered as a potential strategy for mood-regulation. Thayer et al. (1994) found that social support was a commonly used and effective self-regulation strategy to counter negative mood states, a finding that was supported on a sample of athletes by Stevens and Lane et al (2001).

There are several limitations to the results of the present study. First, the stability of mood changes during competition and following competition were not known. Mood has been found to be an ephemeral construct and thus it was possible that mood states changed from hole to hole. Second, the sample size was relatively small even for this specific population. Third, measures of goal attainment and goal expectancy were not assessed. Understanding the link between goal outcome and mood states might offer a clearer rationale for mood responses in golf.

• Findings show ageing male golfers engaged in a meaningful exercise session and that mood scores deteriorated following play.
• Mood profiles before and after playing golf for elderly golfers were similar to younger athletes following competition.
• For golf to be recommended as an activity for promoting physical activity among an aging population, the player's ability to regulate unpleasant mood states should be considered.